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  1. Ethics and epistemology of accurate prediction in clinical research.

    Science.gov (United States)

    Hey, Spencer Phillips

    2015-07-01

    All major research ethics policies assert that the ethical review of clinical trial protocols should include a systematic assessment of risks and benefits. But despite this policy, protocols do not typically contain explicit probability statements about the likely risks or benefits involved in the proposed research. In this essay, I articulate a range of ethical and epistemic advantages that explicit forecasting would offer to the health research enterprise. I then consider how some particular confidence levels may come into conflict with the principles of ethical research.

  2. High IFIT1 expression predicts improved clinical outcome, and IFIT1 along with MGMT more accurately predicts prognosis in newly diagnosed glioblastoma.

    Science.gov (United States)

    Zhang, Jin-Feng; Chen, Yao; Lin, Guo-Shi; Zhang, Jian-Dong; Tang, Wen-Long; Huang, Jian-Huang; Chen, Jin-Shou; Wang, Xing-Fu; Lin, Zhi-Xiong

    2016-06-01

    Interferon-induced protein with tetratricopeptide repeat 1 (IFIT1) plays a key role in growth suppression and apoptosis promotion in cancer cells. Interferon was reported to induce the expression of IFIT1 and inhibit the expression of O-6-methylguanine-DNA methyltransferase (MGMT).This study aimed to investigate the expression of IFIT1, the correlation between IFIT1 and MGMT, and their impact on the clinical outcome in newly diagnosed glioblastoma. The expression of IFIT1 and MGMT and their correlation were investigated in the tumor tissues from 70 patients with newly diagnosed glioblastoma. The effects on progression-free survival and overall survival were evaluated. Of 70 cases, 57 (81.4%) tissue samples showed high expression of IFIT1 by immunostaining. The χ(2) test indicated that the expression of IFIT1 and MGMT was negatively correlated (r = -0.288, P = .016). Univariate and multivariate analyses confirmed high IFIT1 expression as a favorable prognostic indicator for progression-free survival (P = .005 and .017) and overall survival (P = .001 and .001), respectively. Patients with 2 favorable factors (high IFIT1 and low MGMT) had an improved prognosis as compared with others. The results demonstrated significantly increased expression of IFIT1 in newly diagnosed glioblastoma tissue. The negative correlation between IFIT1 and MGMT expression may be triggered by interferon. High IFIT1 can be a predictive biomarker of favorable clinical outcome, and IFIT1 along with MGMT more accurately predicts prognosis in newly diagnosed glioblastoma. PMID:26980050

  3. Prognostic breast cancer signature identified from 3D culture model accurately predicts clinical outcome across independent datasets

    Energy Technology Data Exchange (ETDEWEB)

    Martin, Katherine J.; Patrick, Denis R.; Bissell, Mina J.; Fournier, Marcia V.

    2008-10-20

    One of the major tenets in breast cancer research is that early detection is vital for patient survival by increasing treatment options. To that end, we have previously used a novel unsupervised approach to identify a set of genes whose expression predicts prognosis of breast cancer patients. The predictive genes were selected in a well-defined three dimensional (3D) cell culture model of non-malignant human mammary epithelial cell morphogenesis as down-regulated during breast epithelial cell acinar formation and cell cycle arrest. Here we examine the ability of this gene signature (3D-signature) to predict prognosis in three independent breast cancer microarray datasets having 295, 286, and 118 samples, respectively. Our results show that the 3D-signature accurately predicts prognosis in three unrelated patient datasets. At 10 years, the probability of positive outcome was 52, 51, and 47 percent in the group with a poor-prognosis signature and 91, 75, and 71 percent in the group with a good-prognosis signature for the three datasets, respectively (Kaplan-Meier survival analysis, p<0.05). Hazard ratios for poor outcome were 5.5 (95% CI 3.0 to 12.2, p<0.0001), 2.4 (95% CI 1.6 to 3.6, p<0.0001) and 1.9 (95% CI 1.1 to 3.2, p = 0.016) and remained significant for the two larger datasets when corrected for estrogen receptor (ER) status. Hence the 3D-signature accurately predicts breast cancer outcome in both ER-positive and ER-negative tumors, though individual genes differed in their prognostic ability in the two subtypes. Genes that were prognostic in ER+ patients are AURKA, CEP55, RRM2, EPHA2, FGFBP1, and VRK1, while genes prognostic in ER patients include ACTB, FOXM1 and SERPINE2 (Kaplan-Meier p<0.05). Multivariable Cox regression analysis in the largest dataset showed that the 3D-signature was a strong independent factor in predicting breast cancer outcome. The 3D-signature accurately predicts breast cancer outcome across multiple datasets and holds prognostic

  4. A new, accurate predictive model for incident hypertension

    DEFF Research Database (Denmark)

    Völzke, Henry; Fung, Glenn; Ittermann, Till;

    2013-01-01

    Data mining represents an alternative approach to identify new predictors of multifactorial diseases. This work aimed at building an accurate predictive model for incident hypertension using data mining procedures....

  5. Accurate Multisteps Traffic Flow Prediction Based on SVM

    OpenAIRE

    Zhang Mingheng; Zhen Yaobao; Hui Ganglong; Chen Gang

    2013-01-01

    Accurate traffic flow prediction is prerequisite and important for realizing intelligent traffic control and guidance, and it is also the objective requirement for intelligent traffic management. Due to the strong nonlinear, stochastic, time-varying characteristics of urban transport system, artificial intelligence methods such as support vector machine (SVM) are now receiving more and more attentions in this research field. Compared with the traditional single-step prediction method, the mul...

  6. Accurate Multisteps Traffic Flow Prediction Based on SVM

    Directory of Open Access Journals (Sweden)

    Zhang Mingheng

    2013-01-01

    Full Text Available Accurate traffic flow prediction is prerequisite and important for realizing intelligent traffic control and guidance, and it is also the objective requirement for intelligent traffic management. Due to the strong nonlinear, stochastic, time-varying characteristics of urban transport system, artificial intelligence methods such as support vector machine (SVM are now receiving more and more attentions in this research field. Compared with the traditional single-step prediction method, the multisteps prediction has the ability that can predict the traffic state trends over a certain period in the future. From the perspective of dynamic decision, it is far important than the current traffic condition obtained. Thus, in this paper, an accurate multi-steps traffic flow prediction model based on SVM was proposed. In which, the input vectors were comprised of actual traffic volume and four different types of input vectors were compared to verify their prediction performance with each other. Finally, the model was verified with actual data in the empirical analysis phase and the test results showed that the proposed SVM model had a good ability for traffic flow prediction and the SVM-HPT model outperformed the other three models for prediction.

  7. Accurate prediction of secondary metabolite gene clusters in filamentous fungi

    DEFF Research Database (Denmark)

    Andersen, Mikael Rørdam; Nielsen, Jakob Blæsbjerg; Klitgaard, Andreas;

    2013-01-01

    Biosynthetic pathways of secondary metabolites from fungi are currently subject to an intense effort to elucidate the genetic basis for these compounds due to their large potential within pharmaceutics and synthetic biochemistry. The preferred method is methodical gene deletions to identify...... supporting enzymes for key synthases one cluster at a time. In this study, we design and apply a DNA expression array for Aspergillus nidulans in combination with legacy data to form a comprehensive gene expression compendium. We apply a guilt-by-association-based analysis to predict the extent...... of the biosynthetic clusters for the 58 synthases active in our set of experimental conditions. A comparison with legacy data shows the method to be accurate in 13 of 16 known clusters and nearly accurate for the remaining 3 clusters. Furthermore, we apply a data clustering approach, which identifies cross...

  8. Plant diversity accurately predicts insect diversity in two tropical landscapes.

    Science.gov (United States)

    Zhang, Kai; Lin, Siliang; Ji, Yinqiu; Yang, Chenxue; Wang, Xiaoyang; Yang, Chunyan; Wang, Hesheng; Jiang, Haisheng; Harrison, Rhett D; Yu, Douglas W

    2016-09-01

    Plant diversity surely determines arthropod diversity, but only moderate correlations between arthropod and plant species richness had been observed until Basset et al. (Science, 338, 2012 and 1481) finally undertook an unprecedentedly comprehensive sampling of a tropical forest and demonstrated that plant species richness could indeed accurately predict arthropod species richness. We now require a high-throughput pipeline to operationalize this result so that we can (i) test competing explanations for tropical arthropod megadiversity, (ii) improve estimates of global eukaryotic species diversity, and (iii) use plant and arthropod communities as efficient proxies for each other, thus improving the efficiency of conservation planning and of detecting forest degradation and recovery. We therefore applied metabarcoding to Malaise-trap samples across two tropical landscapes in China. We demonstrate that plant species richness can accurately predict arthropod (mostly insect) species richness and that plant and insect community compositions are highly correlated, even in landscapes that are large, heterogeneous and anthropogenically modified. Finally, we review how metabarcoding makes feasible highly replicated tests of the major competing explanations for tropical megadiversity. PMID:27474399

  9. Bayesian calibration of power plant models for accurate performance prediction

    International Nuclear Information System (INIS)

    Highlights: • Bayesian calibration is applied to power plant performance prediction. • Measurements from a plant in operation are used for model calibration. • A gas turbine performance model and steam cycle model are calibrated. • An integrated plant model is derived. • Part load efficiency is accurately predicted as a function of ambient conditions. - Abstract: Gas turbine combined cycles are expected to play an increasingly important role in the balancing of supply and demand in future energy markets. Thermodynamic modeling of these energy systems is frequently applied to assist in decision making processes related to the management of plant operation and maintenance. In most cases, model inputs, parameters and outputs are treated as deterministic quantities and plant operators make decisions with limited or no regard of uncertainties. As the steady integration of wind and solar energy into the energy market induces extra uncertainties, part load operation and reliability are becoming increasingly important. In the current study, methods are proposed to not only quantify various types of uncertainties in measurements and plant model parameters using measured data, but to also assess their effect on various aspects of performance prediction. The authors aim to account for model parameter and measurement uncertainty, and for systematic discrepancy of models with respect to reality. For this purpose, the Bayesian calibration framework of Kennedy and O’Hagan is used, which is especially suitable for high-dimensional industrial problems. The article derives a calibrated model of the plant efficiency as a function of ambient conditions and operational parameters, which is also accurate in part load. The article shows that complete statistical modeling of power plants not only enhances process models, but can also increases confidence in operational decisions

  10. Standardized EEG interpretation accurately predicts prognosis after cardiac arrest

    Science.gov (United States)

    Rossetti, Andrea O.; van Rootselaar, Anne-Fleur; Wesenberg Kjaer, Troels; Horn, Janneke; Ullén, Susann; Friberg, Hans; Nielsen, Niklas; Rosén, Ingmar; Åneman, Anders; Erlinge, David; Gasche, Yvan; Hassager, Christian; Hovdenes, Jan; Kjaergaard, Jesper; Kuiper, Michael; Pellis, Tommaso; Stammet, Pascal; Wanscher, Michael; Wetterslev, Jørn; Wise, Matt P.; Cronberg, Tobias

    2016-01-01

    Objective: To identify reliable predictors of outcome in comatose patients after cardiac arrest using a single routine EEG and standardized interpretation according to the terminology proposed by the American Clinical Neurophysiology Society. Methods: In this cohort study, 4 EEG specialists, blinded to outcome, evaluated prospectively recorded EEGs in the Target Temperature Management trial (TTM trial) that randomized patients to 33°C vs 36°C. Routine EEG was performed in patients still comatose after rewarming. EEGs were classified into highly malignant (suppression, suppression with periodic discharges, burst-suppression), malignant (periodic or rhythmic patterns, pathological or nonreactive background), and benign EEG (absence of malignant features). Poor outcome was defined as best Cerebral Performance Category score 3–5 until 180 days. Results: Eight TTM sites randomized 202 patients. EEGs were recorded in 103 patients at a median 77 hours after cardiac arrest; 37% had a highly malignant EEG and all had a poor outcome (specificity 100%, sensitivity 50%). Any malignant EEG feature had a low specificity to predict poor prognosis (48%) but if 2 malignant EEG features were present specificity increased to 96% (p EEG was found in 1% of the patients with a poor outcome. Conclusions: Highly malignant EEG after rewarming reliably predicted poor outcome in half of patients without false predictions. An isolated finding of a single malignant feature did not predict poor outcome whereas a benign EEG was highly predictive of a good outcome. PMID:26865516

  11. Standardized EEG interpretation accurately predicts prognosis after cardiac arrest

    DEFF Research Database (Denmark)

    Westhall, Erik; Rossetti, Andrea O; van Rootselaar, Anne-Fleur;

    2016-01-01

    OBJECTIVE: To identify reliable predictors of outcome in comatose patients after cardiac arrest using a single routine EEG and standardized interpretation according to the terminology proposed by the American Clinical Neurophysiology Society. METHODS: In this cohort study, 4 EEG specialists...... patients. EEGs were recorded in 103 patients at a median 77 hours after cardiac arrest; 37% had a highly malignant EEG and all had a poor outcome (specificity 100%, sensitivity 50%). Any malignant EEG feature had a low specificity to predict poor prognosis (48%) but if 2 malignant EEG features were present...

  12. Simple Mathematical Models Do Not Accurately Predict Early SIV Dynamics

    Directory of Open Access Journals (Sweden)

    Cecilia Noecker

    2015-03-01

    Full Text Available Upon infection of a new host, human immunodeficiency virus (HIV replicates in the mucosal tissues and is generally undetectable in circulation for 1–2 weeks post-infection. Several interventions against HIV including vaccines and antiretroviral prophylaxis target virus replication at this earliest stage of infection. Mathematical models have been used to understand how HIV spreads from mucosal tissues systemically and what impact vaccination and/or antiretroviral prophylaxis has on viral eradication. Because predictions of such models have been rarely compared to experimental data, it remains unclear which processes included in these models are critical for predicting early HIV dynamics. Here we modified the “standard” mathematical model of HIV infection to include two populations of infected cells: cells that are actively producing the virus and cells that are transitioning into virus production mode. We evaluated the effects of several poorly known parameters on infection outcomes in this model and compared model predictions to experimental data on infection of non-human primates with variable doses of simian immunodifficiency virus (SIV. First, we found that the mode of virus production by infected cells (budding vs. bursting has a minimal impact on the early virus dynamics for a wide range of model parameters, as long as the parameters are constrained to provide the observed rate of SIV load increase in the blood of infected animals. Interestingly and in contrast with previous results, we found that the bursting mode of virus production generally results in a higher probability of viral extinction than the budding mode of virus production. Second, this mathematical model was not able to accurately describe the change in experimentally determined probability of host infection with increasing viral doses. Third and finally, the model was also unable to accurately explain the decline in the time to virus detection with increasing viral

  13. Standardized EEG interpretation accurately predicts prognosis after cardiac arrest

    Science.gov (United States)

    Rossetti, Andrea O.; van Rootselaar, Anne-Fleur; Wesenberg Kjaer, Troels; Horn, Janneke; Ullén, Susann; Friberg, Hans; Nielsen, Niklas; Rosén, Ingmar; Åneman, Anders; Erlinge, David; Gasche, Yvan; Hassager, Christian; Hovdenes, Jan; Kjaergaard, Jesper; Kuiper, Michael; Pellis, Tommaso; Stammet, Pascal; Wanscher, Michael; Wetterslev, Jørn; Wise, Matt P.; Cronberg, Tobias

    2016-01-01

    Objective: To identify reliable predictors of outcome in comatose patients after cardiac arrest using a single routine EEG and standardized interpretation according to the terminology proposed by the American Clinical Neurophysiology Society. Methods: In this cohort study, 4 EEG specialists, blinded to outcome, evaluated prospectively recorded EEGs in the Target Temperature Management trial (TTM trial) that randomized patients to 33°C vs 36°C. Routine EEG was performed in patients still comatose after rewarming. EEGs were classified into highly malignant (suppression, suppression with periodic discharges, burst-suppression), malignant (periodic or rhythmic patterns, pathological or nonreactive background), and benign EEG (absence of malignant features). Poor outcome was defined as best Cerebral Performance Category score 3–5 until 180 days. Results: Eight TTM sites randomized 202 patients. EEGs were recorded in 103 patients at a median 77 hours after cardiac arrest; 37% had a highly malignant EEG and all had a poor outcome (specificity 100%, sensitivity 50%). Any malignant EEG feature had a low specificity to predict poor prognosis (48%) but if 2 malignant EEG features were present specificity increased to 96% (p < 0.001). Specificity and sensitivity were not significantly affected by targeted temperature or sedation. A benign EEG was found in 1% of the patients with a poor outcome. Conclusions: Highly malignant EEG after rewarming reliably predicted poor outcome in half of patients without false predictions. An isolated finding of a single malignant feature did not predict poor outcome whereas a benign EEG was highly predictive of a good outcome. PMID:26865516

  14. Artificial neural network accurately predicts hepatitis B surface antigen seroclearance.

    Directory of Open Access Journals (Sweden)

    Ming-Hua Zheng

    Full Text Available BACKGROUND & AIMS: Hepatitis B surface antigen (HBsAg seroclearance and seroconversion are regarded as favorable outcomes of chronic hepatitis B (CHB. This study aimed to develop artificial neural networks (ANNs that could accurately predict HBsAg seroclearance or seroconversion on the basis of available serum variables. METHODS: Data from 203 untreated, HBeAg-negative CHB patients with spontaneous HBsAg seroclearance (63 with HBsAg seroconversion, and 203 age- and sex-matched HBeAg-negative controls were analyzed. ANNs and logistic regression models (LRMs were built and tested according to HBsAg seroclearance and seroconversion. Predictive accuracy was assessed with area under the receiver operating characteristic curve (AUROC. RESULTS: Serum quantitative HBsAg (qHBsAg and HBV DNA levels, qHBsAg and HBV DNA reduction were related to HBsAg seroclearance (P<0.001 and were used for ANN/LRM-HBsAg seroclearance building, whereas, qHBsAg reduction was not associated with ANN-HBsAg seroconversion (P = 0.197 and LRM-HBsAg seroconversion was solely based on qHBsAg (P = 0.01. For HBsAg seroclearance, AUROCs of ANN were 0.96, 0.93 and 0.95 for the training, testing and genotype B subgroups respectively. They were significantly higher than those of LRM, qHBsAg and HBV DNA (all P<0.05. Although the performance of ANN-HBsAg seroconversion (AUROC 0.757 was inferior to that for HBsAg seroclearance, it tended to be better than those of LRM, qHBsAg and HBV DNA. CONCLUSIONS: ANN identifies spontaneous HBsAg seroclearance in HBeAg-negative CHB patients with better accuracy, on the basis of easily available serum data. More useful predictors for HBsAg seroconversion are still needed to be explored in the future.

  15. Fast and accurate predictions of covalent bonds in chemical space

    Science.gov (United States)

    Chang, K. Y. Samuel; Fias, Stijn; Ramakrishnan, Raghunathan; von Lilienfeld, O. Anatole

    2016-05-01

    We assess the predictive accuracy of perturbation theory based estimates of changes in covalent bonding due to linear alchemical interpolations among molecules. We have investigated σ bonding to hydrogen, as well as σ and π bonding between main-group elements, occurring in small sets of iso-valence-electronic molecules with elements drawn from second to fourth rows in the p-block of the periodic table. Numerical evidence suggests that first order Taylor expansions of covalent bonding potentials can achieve high accuracy if (i) the alchemical interpolation is vertical (fixed geometry), (ii) it involves elements from the third and fourth rows of the periodic table, and (iii) an optimal reference geometry is used. This leads to near linear changes in the bonding potential, resulting in analytical predictions with chemical accuracy (˜1 kcal/mol). Second order estimates deteriorate the prediction. If initial and final molecules differ not only in composition but also in geometry, all estimates become substantially worse, with second order being slightly more accurate than first order. The independent particle approximation based second order perturbation theory performs poorly when compared to the coupled perturbed or finite difference approach. Taylor series expansions up to fourth order of the potential energy curve of highly symmetric systems indicate a finite radius of convergence, as illustrated for the alchemical stretching of H 2+ . Results are presented for (i) covalent bonds to hydrogen in 12 molecules with 8 valence electrons (CH4, NH3, H2O, HF, SiH4, PH3, H2S, HCl, GeH4, AsH3, H2Se, HBr); (ii) main-group single bonds in 9 molecules with 14 valence electrons (CH3F, CH3Cl, CH3Br, SiH3F, SiH3Cl, SiH3Br, GeH3F, GeH3Cl, GeH3Br); (iii) main-group double bonds in 9 molecules with 12 valence electrons (CH2O, CH2S, CH2Se, SiH2O, SiH2S, SiH2Se, GeH2O, GeH2S, GeH2Se); (iv) main-group triple bonds in 9 molecules with 10 valence electrons (HCN, HCP, HCAs, HSiN, HSi

  16. Fast and accurate predictions of covalent bonds in chemical space.

    Science.gov (United States)

    Chang, K Y Samuel; Fias, Stijn; Ramakrishnan, Raghunathan; von Lilienfeld, O Anatole

    2016-05-01

    We assess the predictive accuracy of perturbation theory based estimates of changes in covalent bonding due to linear alchemical interpolations among molecules. We have investigated σ bonding to hydrogen, as well as σ and π bonding between main-group elements, occurring in small sets of iso-valence-electronic molecules with elements drawn from second to fourth rows in the p-block of the periodic table. Numerical evidence suggests that first order Taylor expansions of covalent bonding potentials can achieve high accuracy if (i) the alchemical interpolation is vertical (fixed geometry), (ii) it involves elements from the third and fourth rows of the periodic table, and (iii) an optimal reference geometry is used. This leads to near linear changes in the bonding potential, resulting in analytical predictions with chemical accuracy (∼1 kcal/mol). Second order estimates deteriorate the prediction. If initial and final molecules differ not only in composition but also in geometry, all estimates become substantially worse, with second order being slightly more accurate than first order. The independent particle approximation based second order perturbation theory performs poorly when compared to the coupled perturbed or finite difference approach. Taylor series expansions up to fourth order of the potential energy curve of highly symmetric systems indicate a finite radius of convergence, as illustrated for the alchemical stretching of H2 (+). Results are presented for (i) covalent bonds to hydrogen in 12 molecules with 8 valence electrons (CH4, NH3, H2O, HF, SiH4, PH3, H2S, HCl, GeH4, AsH3, H2Se, HBr); (ii) main-group single bonds in 9 molecules with 14 valence electrons (CH3F, CH3Cl, CH3Br, SiH3F, SiH3Cl, SiH3Br, GeH3F, GeH3Cl, GeH3Br); (iii) main-group double bonds in 9 molecules with 12 valence electrons (CH2O, CH2S, CH2Se, SiH2O, SiH2S, SiH2Se, GeH2O, GeH2S, GeH2Se); (iv) main-group triple bonds in 9 molecules with 10 valence electrons (HCN, HCP, HCAs, HSiN, HSi

  17. Copeptin does not accurately predict disease severity in imported malaria

    Directory of Open Access Journals (Sweden)

    van Wolfswinkel Marlies E

    2012-01-01

    Full Text Available Abstract Background Copeptin has recently been identified to be a stable surrogate marker for the unstable hormone arginine vasopressin (AVP. Copeptin has been shown to correlate with disease severity in leptospirosis and bacterial sepsis. Hyponatraemia is common in severe imported malaria and dysregulation of AVP release has been hypothesized as an underlying pathophysiological mechanism. The aim of the present study was to evaluate the performance of copeptin as a predictor of disease severity in imported malaria. Methods Copeptin was measured in stored serum samples of 204 patients with imported malaria that were admitted to our Institute for Tropical Diseases in Rotterdam in the period 1999-2010. The occurrence of WHO defined severe malaria was the primary end-point. The diagnostic performance of copeptin was compared to that of previously evaluated biomarkers C-reactive protein, procalcitonin, lactate and sodium. Results Of the 204 patients (141 Plasmodium falciparum, 63 non-falciparum infection, 25 had severe malaria. The Area Under the ROC curve of copeptin for severe disease (0.66 [95% confidence interval 0.59-0.72] was comparable to that of lactate, sodium and procalcitonin. C-reactive protein (0.84 [95% CI 0.79-0.89] had a significantly better performance as a biomarker for severe malaria than the other biomarkers. Conclusions C-reactive protein but not copeptin was found to be an accurate predictor for disease severity in imported malaria. The applicability of copeptin as a marker for severe malaria in clinical practice is limited to exclusion of severe malaria.

  18. Modeling methodology for the accurate and prompt prediction of symptomatic events in chronic diseases.

    Science.gov (United States)

    Pagán, Josué; Risco-Martín, José L; Moya, José M; Ayala, José L

    2016-08-01

    Prediction of symptomatic crises in chronic diseases allows to take decisions before the symptoms occur, such as the intake of drugs to avoid the symptoms or the activation of medical alarms. The prediction horizon is in this case an important parameter in order to fulfill the pharmacokinetics of medications, or the time response of medical services. This paper presents a study about the prediction limits of a chronic disease with symptomatic crises: the migraine. For that purpose, this work develops a methodology to build predictive migraine models and to improve these predictions beyond the limits of the initial models. The maximum prediction horizon is analyzed, and its dependency on the selected features is studied. A strategy for model selection is proposed to tackle the trade off between conservative but robust predictive models, with respect to less accurate predictions with higher horizons. The obtained results show a prediction horizon close to 40min, which is in the time range of the drug pharmacokinetics. Experiments have been performed in a realistic scenario where input data have been acquired in an ambulatory clinical study by the deployment of a non-intrusive Wireless Body Sensor Network. Our results provide an effective methodology for the selection of the future horizon in the development of prediction algorithms for diseases experiencing symptomatic crises. PMID:27260782

  19. An Overview of Practical Applications of Protein Disorder Prediction and Drive for Faster, More Accurate Predictions

    Directory of Open Access Journals (Sweden)

    Xin Deng

    2015-07-01

    Full Text Available Protein disordered regions are segments of a protein chain that do not adopt a stable structure. Thus far, a variety of protein disorder prediction methods have been developed and have been widely used, not only in traditional bioinformatics domains, including protein structure prediction, protein structure determination and function annotation, but also in many other biomedical fields. The relationship between intrinsically-disordered proteins and some human diseases has played a significant role in disorder prediction in disease identification and epidemiological investigations. Disordered proteins can also serve as potential targets for drug discovery with an emphasis on the disordered-to-ordered transition in the disordered binding regions, and this has led to substantial research in drug discovery or design based on protein disordered region prediction. Furthermore, protein disorder prediction has also been applied to healthcare by predicting the disease risk of mutations in patients and studying the mechanistic basis of diseases. As the applications of disorder prediction increase, so too does the need to make quick and accurate predictions. To fill this need, we also present a new approach to predict protein residue disorder using wide sequence windows that is applicable on the genomic scale.

  20. Is Three-Dimensional Soft Tissue Prediction by Software Accurate?

    Science.gov (United States)

    Nam, Ki-Uk; Hong, Jongrak

    2015-11-01

    The authors assessed whether virtual surgery, performed with a soft tissue prediction program, could correctly simulate the actual surgical outcome, focusing on soft tissue movement. Preoperative and postoperative computed tomography (CT) data for 29 patients, who had undergone orthognathic surgery, were obtained and analyzed using the Simplant Pro software. The program made a predicted soft tissue image (A) based on presurgical CT data. After the operation, we obtained actual postoperative CT data and an actual soft tissue image (B) was generated. Finally, the 2 images (A and B) were superimposed and analyzed differences between the A and B. Results were grouped in 2 classes: absolute values and vector values. In the absolute values, the left mouth corner was the most significant error point (2.36 mm). The right mouth corner (2.28 mm), labrale inferius (2.08 mm), and the pogonion (2.03 mm) also had significant errors. In vector values, prediction of the right-left side had a left-sided tendency, the superior-inferior had a superior tendency, and the anterior-posterior showed an anterior tendency. As a result, with this program, the position of points tended to be located more left, anterior, and superior than the "real" situation. There is a need to improve the prediction accuracy for soft tissue images. Such software is particularly valuable in predicting craniofacial soft tissues landmarks, such as the pronasale. With this software, landmark positions were most inaccurate in terms of anterior-posterior predictions.

  1. Highly Accurate Structure-Based Prediction of HIV-1 Coreceptor Usage Suggests Intermolecular Interactions Driving Tropism.

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    Chris A Kieslich

    Full Text Available HIV-1 entry into host cells is mediated by interactions between the V3-loop of viral glycoprotein gp120 and chemokine receptor CCR5 or CXCR4, collectively known as HIV-1 coreceptors. Accurate genotypic prediction of coreceptor usage is of significant clinical interest and determination of the factors driving tropism has been the focus of extensive study. We have developed a method based on nonlinear support vector machines to elucidate the interacting residue pairs driving coreceptor usage and provide highly accurate coreceptor usage predictions. Our models utilize centroid-centroid interaction energies from computationally derived structures of the V3-loop:coreceptor complexes as primary features, while additional features based on established rules regarding V3-loop sequences are also investigated. We tested our method on 2455 V3-loop sequences of various lengths and subtypes, and produce a median area under the receiver operator curve of 0.977 based on 500 runs of 10-fold cross validation. Our study is the first to elucidate a small set of specific interacting residue pairs between the V3-loop and coreceptors capable of predicting coreceptor usage with high accuracy across major HIV-1 subtypes. The developed method has been implemented as a web tool named CRUSH, CoReceptor USage prediction for HIV-1, which is available at http://ares.tamu.edu/CRUSH/.

  2. Highly Accurate Structure-Based Prediction of HIV-1 Coreceptor Usage Suggests Intermolecular Interactions Driving Tropism

    Science.gov (United States)

    Kieslich, Chris A.; Tamamis, Phanourios; Guzman, Yannis A.; Onel, Melis; Floudas, Christodoulos A.

    2016-01-01

    HIV-1 entry into host cells is mediated by interactions between the V3-loop of viral glycoprotein gp120 and chemokine receptor CCR5 or CXCR4, collectively known as HIV-1 coreceptors. Accurate genotypic prediction of coreceptor usage is of significant clinical interest and determination of the factors driving tropism has been the focus of extensive study. We have developed a method based on nonlinear support vector machines to elucidate the interacting residue pairs driving coreceptor usage and provide highly accurate coreceptor usage predictions. Our models utilize centroid-centroid interaction energies from computationally derived structures of the V3-loop:coreceptor complexes as primary features, while additional features based on established rules regarding V3-loop sequences are also investigated. We tested our method on 2455 V3-loop sequences of various lengths and subtypes, and produce a median area under the receiver operator curve of 0.977 based on 500 runs of 10-fold cross validation. Our study is the first to elucidate a small set of specific interacting residue pairs between the V3-loop and coreceptors capable of predicting coreceptor usage with high accuracy across major HIV-1 subtypes. The developed method has been implemented as a web tool named CRUSH, CoReceptor USage prediction for HIV-1, which is available at http://ares.tamu.edu/CRUSH/. PMID:26859389

  3. Analytical method to accurately predict LMFBR core flow distribution

    International Nuclear Information System (INIS)

    An accurate and detailed representation of the flow distribution in LMFBR cores is very important as the starting point and basis of the thermal and structural core design. Previous experience indicated that the steady state and transient core design is as good as the core orificing; thus, a new orificing philosophy satisfying a priori all design constraints was developd. However, optimized orificing is a necessary, but not sufficient condition for achieving the optimum core flow distribution, which is affected by the hydraulic characteristics of the remainder of the primary system. Consequently, an analytical model of the overall primary system was developed, resulting in the CATFISH computer code, which, even though specifically written for LMFBRs, can be used for any reactor employing ducted assemblies

  4. An Innovative Imputation and Classification Approach for Accurate Disease Prediction

    OpenAIRE

    UshaRani, Yelipe; Sammulal, P.

    2016-01-01

    Imputation of missing attribute values in medical datasets for extracting hidden knowledge from medical datasets is an interesting research topic of interest which is very challenging. One cannot eliminate missing values in medical records. The reason may be because some tests may not been conducted as they are cost effective, values missed when conducting clinical trials, values may not have been recorded to name some of the reasons. Data mining researchers have been proposing various approa...

  5. Predicting accurate absolute binding energies in aqueous solution

    DEFF Research Database (Denmark)

    Jensen, Jan Halborg

    2015-01-01

    Recent predictions of absolute binding free energies of host-guest complexes in aqueous solution using electronic structure theory have been encouraging for some systems, while other systems remain problematic. In this paper I summarize some of the many factors that could easily contribute 1-3 kcal......-represented by continuum models. While I focus on binding free energies in aqueous solution the approach also applies (with minor adjustments) to any free energy difference such as conformational or reaction free energy differences or activation free energies in any solvent....

  6. Accurate theoretical prediction on positron lifetime of bulk materials

    CERN Document Server

    Zhang, Wenshuai; Liu, Jiandang; Ye, Bangjiao

    2015-01-01

    Based on the first-principles calculations, we perform an initiatory statistical assessment on the reliability level of theoretical positron lifetime of bulk material. We found the original generalized gradient approximation (GGA) form of the enhancement factor and correlation potentials overestimates the effect of the gradient factor. Furthermore, an excellent agreement between model and data with the difference being the noise level of the data is found in this work. In addition, we suggest a new GGA form of the correlation scheme which gives the best performance. This work demonstrates that a brand-new reliability level is achieved for the theoretical prediction on positron lifetime of bulk material and the accuracy of the best theoretical scheme can be independent on the type of materials.

  7. Change in BMI accurately predicted by social exposure to acquaintances.

    Directory of Open Access Journals (Sweden)

    Rahman O Oloritun

    Full Text Available Research has mostly focused on obesity and not on processes of BMI change more generally, although these may be key factors that lead to obesity. Studies have suggested that obesity is affected by social ties. However these studies used survey based data collection techniques that may be biased toward select only close friends and relatives. In this study, mobile phone sensing techniques were used to routinely capture social interaction data in an undergraduate dorm. By automating the capture of social interaction data, the limitations of self-reported social exposure data are avoided. This study attempts to understand and develop a model that best describes the change in BMI using social interaction data. We evaluated a cohort of 42 college students in a co-located university dorm, automatically captured via mobile phones and survey based health-related information. We determined the most predictive variables for change in BMI using the least absolute shrinkage and selection operator (LASSO method. The selected variables, with gender, healthy diet category, and ability to manage stress, were used to build multiple linear regression models that estimate the effect of exposure and individual factors on change in BMI. We identified the best model using Akaike Information Criterion (AIC and R(2. This study found a model that explains 68% (p<0.0001 of the variation in change in BMI. The model combined social interaction data, especially from acquaintances, and personal health-related information to explain change in BMI. This is the first study taking into account both interactions with different levels of social interaction and personal health-related information. Social interactions with acquaintances accounted for more than half the variation in change in BMI. This suggests the importance of not only individual health information but also the significance of social interactions with people we are exposed to, even people we may not consider as

  8. Combining clinical variables to optimize prediction of antidepressant treatment outcomes.

    Science.gov (United States)

    Iniesta, Raquel; Malki, Karim; Maier, Wolfgang; Rietschel, Marcella; Mors, Ole; Hauser, Joanna; Henigsberg, Neven; Dernovsek, Mojca Zvezdana; Souery, Daniel; Stahl, Daniel; Dobson, Richard; Aitchison, Katherine J; Farmer, Anne; Lewis, Cathryn M; McGuffin, Peter; Uher, Rudolf

    2016-07-01

    The outcome of treatment with antidepressants varies markedly across people with the same diagnosis. A clinically significant prediction of outcomes could spare the frustration of trial and error approach and improve the outcomes of major depressive disorder through individualized treatment selection. It is likely that a combination of multiple predictors is needed to achieve such prediction. We used elastic net regularized regression to optimize prediction of symptom improvement and remission during treatment with escitalopram or nortriptyline and to identify contributing predictors from a range of demographic and clinical variables in 793 adults with major depressive disorder. A combination of demographic and clinical variables, with strong contributions from symptoms of depressed mood, reduced interest, decreased activity, indecisiveness, pessimism and anxiety significantly predicted treatment outcomes, explaining 5-10% of variance in symptom improvement with escitalopram. Similar combinations of variables predicted remission with area under the curve 0.72, explaining approximately 15% of variance (pseudo R(2)) in who achieves remission, with strong contributions from body mass index, appetite, interest-activity symptom dimension and anxious-somatizing depression subtype. Escitalopram-specific outcome prediction was more accurate than generic outcome prediction, and reached effect sizes that were near or above a previously established benchmark for clinical significance. Outcome prediction on the nortriptyline arm did not significantly differ from chance. These results suggest that easily obtained demographic and clinical variables can predict therapeutic response to escitalopram with clinically meaningful accuracy, suggesting a potential for individualized prescription of this antidepressant drug. PMID:27089522

  9. Mind-set and close relationships: when bias leads to (In)accurate predictions.

    Science.gov (United States)

    Gagné, F M; Lydon, J E

    2001-07-01

    The authors investigated whether mind-set influences the accuracy of relationship predictions. Because people are more biased in their information processing when thinking about implementing an important goal, relationship predictions made in an implemental mind-set were expected to be less accurate than those made in a more impartial deliberative mind-set. In Study 1, open-ended thoughts of students about to leave for university were coded for mind-set. In Study 2, mind-set about a major life goal was assessed using a self-report measure. In Study 3, mind-set was experimentally manipulated. Overall, mind-set interacted with forecasts to predict relationship survival. Forecasts were more accurate in a deliberative mind-set than in an implemental mind-set. This effect was more pronounced for long-term than for short-term relationship survival. Finally, deliberatives were not pessimistic; implementals were unduly optimistic.

  10. Clinical studies of biomarkers in suicide prediction

    OpenAIRE

    Jokinen, Jussi

    2007-01-01

    Suicide is a major clinical problem in psychiatry and suicidal behaviours can be seen as a nosological entity per se. Predicting suicide is difficult due to its low base-rate and the limited specificity of clinical predictors. Prospective biological studies suggest that dysfunctions in the hypothalamo pituitary adrenal (HPA) axis and the serotonergic system have predictive power for suicide in mood disorders. Suicide attempt is the most robust clinical predictor making suici...

  11. Seizure semiology inferred from clinical descriptions and from video recordings. How accurate are they?

    DEFF Research Database (Denmark)

    Beniczky, Simona Alexandra; Fogarasi, András; Neufeld, Miri;

    2012-01-01

    To assess how accurate the interpretation of seizure semiology is when inferred from witnessed seizure descriptions and from video recordings, five epileptologists analyzed 41 seizures from 30 consecutive patients who had clinical episodes in the epilepsy monitoring unit. For each clinical episod...

  12. A highly accurate predictive-adaptive method for lithium-ion battery remaining discharge energy prediction in electric vehicle applications

    International Nuclear Information System (INIS)

    Highlights: • An energy prediction (EP) method is introduced for battery ERDE determination. • EP determines ERDE through coupled prediction of future states, parameters, and output. • The PAEP combines parameter adaptation and prediction to update model parameters. • The PAEP provides improved ERDE accuracy compared with DC and other EP methods. - Abstract: In order to estimate the remaining driving range (RDR) in electric vehicles, the remaining discharge energy (ERDE) of the applied battery system needs to be precisely predicted. Strongly affected by the load profiles, the available ERDE varies largely in real-world applications and requires specific determination. However, the commonly-used direct calculation (DC) method might result in certain energy prediction errors by relating the ERDE directly to the current state of charge (SOC). To enhance the ERDE accuracy, this paper presents a battery energy prediction (EP) method based on the predictive control theory, in which a coupled prediction of future battery state variation, battery model parameter change, and voltage response, is implemented on the ERDE prediction horizon, and the ERDE is subsequently accumulated and real-timely optimized. Three EP approaches with different model parameter updating routes are introduced, and the predictive-adaptive energy prediction (PAEP) method combining the real-time parameter identification and the future parameter prediction offers the best potential. Based on a large-format lithium-ion battery, the performance of different ERDE calculation methods is compared under various dynamic profiles. Results imply that the EP methods provide much better accuracy than the traditional DC method, and the PAEP could reduce the ERDE error by more than 90% and guarantee the relative energy prediction error under 2%, proving as a proper choice in online ERDE prediction. The correlation of SOC estimation and ERDE calculation is then discussed to illustrate the importance of an

  13. Hash: a program to accurately predict protein H{sup {alpha}} shifts from neighboring backbone shifts

    Energy Technology Data Exchange (ETDEWEB)

    Zeng Jianyang, E-mail: zengjy@gmail.com [Tsinghua University, Institute for Interdisciplinary Information Sciences (China); Zhou Pei [Duke University Medical Center, Department of Biochemistry (United States); Donald, Bruce Randall [Duke University, Department of Computer Science (United States)

    2013-01-15

    Chemical shifts provide not only peak identities for analyzing nuclear magnetic resonance (NMR) data, but also an important source of conformational information for studying protein structures. Current structural studies requiring H{sup {alpha}} chemical shifts suffer from the following limitations. (1) For large proteins, the H{sup {alpha}} chemical shifts can be difficult to assign using conventional NMR triple-resonance experiments, mainly due to the fast transverse relaxation rate of C{sup {alpha}} that restricts the signal sensitivity. (2) Previous chemical shift prediction approaches either require homologous models with high sequence similarity or rely heavily on accurate backbone and side-chain structural coordinates. When neither sequence homologues nor structural coordinates are available, we must resort to other information to predict H{sup {alpha}} chemical shifts. Predicting accurate H{sup {alpha}} chemical shifts using other obtainable information, such as the chemical shifts of nearby backbone atoms (i.e., adjacent atoms in the sequence), can remedy the above dilemmas, and hence advance NMR-based structural studies of proteins. By specifically exploiting the dependencies on chemical shifts of nearby backbone atoms, we propose a novel machine learning algorithm, called Hash, to predict H{sup {alpha}} chemical shifts. Hash combines a new fragment-based chemical shift search approach with a non-parametric regression model, called the generalized additive model, to effectively solve the prediction problem. We demonstrate that the chemical shifts of nearby backbone atoms provide a reliable source of information for predicting accurate H{sup {alpha}} chemical shifts. Our testing results on different possible combinations of input data indicate that Hash has a wide rage of potential NMR applications in structural and biological studies of proteins.

  14. A Single Linear Prediction Filter that Accurately Predicts the AL Index

    Science.gov (United States)

    McPherron, R. L.; Chu, X.

    2015-12-01

    The AL index is a measure of the strength of the westward electrojet flowing along the auroral oval. It has two components: one from the global DP-2 current system and a second from the DP-1 current that is more localized near midnight. It is generally believed that the index a very poor measure of these currents because of its dependence on the distance of stations from the source of the two currents. In fact over season and solar cycle the coupling strength defined as the steady state ratio of the output AL to the input coupling function varies by a factor of four. There are four factors that lead to this variation. First is the equinoctial effect that modulates coupling strength with peaks (strongest coupling) at the equinoxes. Second is the saturation of the polar cap potential which decreases coupling strength as the strength of the driver increases. Since saturation occurs more frequently at solar maximum we obtain the result that maximum coupling strength occurs at equinox at solar minimum. A third factor is ionospheric conductivity with stronger coupling at summer solstice as compared to winter. The fourth factor is the definition of a solar wind coupling function appropriate to a given index. We have developed an optimum coupling function depending on solar wind speed, density, transverse magnetic field, and IMF clock angle which is better than previous functions. Using this we have determined the seasonal variation of coupling strength and developed an inverse function that modulates the optimum coupling function so that all seasonal variation is removed. In a similar manner we have determined the dependence of coupling strength on solar wind driver strength. The inverse of this function is used to scale a linear prediction filter thus eliminating the dependence on driver strength. Our result is a single linear filter that is adjusted in a nonlinear manner by driver strength and an optimum coupling function that is seasonal modulated. Together this

  15. Rapid yet accurate first principle based predictions of alkali halide crystal phases using alchemical perturbation

    CERN Document Server

    Solovyeva, Alisa

    2016-01-01

    We assess the predictive power of alchemical perturbations for estimating fundamental properties in ionic crystals. Using density functional theory we have calculated formation energies, lattice constants, and bulk moduli for all sixteen iso-valence-electronic combinations of pure pristine alkali halides involving elements $A \\in \\{$Na, K, Rb, Cs$\\}$ and $X \\in \\{$F, Cl, Br, I$\\}$. For rock salt, zincblende and cesium chloride symmetry, alchemical Hellmann-Feynman derivatives, evaluated along lattice scans of sixteen reference crystals, have been obtained for all respective 16$\\times$15 combinations of reference and predicted target crystals. Mean absolute errors (MAE) are on par with density functional theory level of accuracy for energies and bulk modulus. Predicted lattice constants are less accurate. NaCl is the best reference salt for alchemical estimates of relative energies (MAE $<$ 40 meV/atom) while alkali fluorides are the worst. By contrast, lattice constants are predicted best using NaF as a re...

  16. Rapid and accurate prediction and scoring of water molecules in protein binding sites.

    Directory of Open Access Journals (Sweden)

    Gregory A Ross

    Full Text Available Water plays a critical role in ligand-protein interactions. However, it is still challenging to predict accurately not only where water molecules prefer to bind, but also which of those water molecules might be displaceable. The latter is often seen as a route to optimizing affinity of potential drug candidates. Using a protocol we call WaterDock, we show that the freely available AutoDock Vina tool can be used to predict accurately the binding sites of water molecules. WaterDock was validated using data from X-ray crystallography, neutron diffraction and molecular dynamics simulations and correctly predicted 97% of the water molecules in the test set. In addition, we combined data-mining, heuristic and machine learning techniques to develop probabilistic water molecule classifiers. When applied to WaterDock predictions in the Astex Diverse Set of protein ligand complexes, we could identify whether a water molecule was conserved or displaced to an accuracy of 75%. A second model predicted whether water molecules were displaced by polar groups or by non-polar groups to an accuracy of 80%. These results should prove useful for anyone wishing to undertake rational design of new compounds where the displacement of water molecules is being considered as a route to improved affinity.

  17. Accurately Estimating the State of a Geophysical System with Sparse Observations: Predicting the Weather

    CERN Document Server

    An, Zhe; Abarbanel, Henry D I

    2014-01-01

    Utilizing the information in observations of a complex system to make accurate predictions through a quantitative model when observations are completed at time $T$, requires an accurate estimate of the full state of the model at time $T$. When the number of measurements $L$ at each observation time within the observation window is larger than a sufficient minimum value $L_s$, the impediments in the estimation procedure are removed. As the number of available observations is typically such that $L \\ll L_s$, additional information from the observations must be presented to the model. We show how, using the time delays of the measurements at each observation time, one can augment the information transferred from the data to the model, removing the impediments to accurate estimation and permitting dependable prediction. We do this in a core geophysical fluid dynamics model, the shallow water equations, at the heart of numerical weather prediction. The method is quite general, however, and can be utilized in the a...

  18. The Compensatory Reserve For Early and Accurate Prediction Of Hemodynamic Compromise: A Review of the Underlying Physiology.

    Science.gov (United States)

    Convertino, Victor A; Wirt, Michael D; Glenn, John F; Lein, Brian C

    2016-06-01

    Shock is deadly and unpredictable if it is not recognized and treated in early stages of hemorrhage. Unfortunately, measurements of standard vital signs that are displayed on current medical monitors fail to provide accurate or early indicators of shock because of physiological mechanisms that effectively compensate for blood loss. As a result of new insights provided by the latest research on the physiology of shock using human experimental models of controlled hemorrhage, it is now recognized that measurement of the body's reserve to compensate for reduced circulating blood volume is the single most important indicator for early and accurate assessment of shock. We have called this function the "compensatory reserve," which can be accurately assessed by real-time measurements of changes in the features of the arterial waveform. In this paper, the physiology underlying the development and evaluation of a new noninvasive technology that allows for real-time measurement of the compensatory reserve will be reviewed, with its clinical implications for earlier and more accurate prediction of shock. PMID:26950588

  19. Meta-analysis of clinical prediction models

    NARCIS (Netherlands)

    Debray, T.P.A.

    2013-01-01

    The past decades there has been a clear shift from implicit to explicit diagnosis and prognosis. This includes appreciation of clinical -diagnostic and prognostic- prediction models, which is likely to increase with the introduction of fully computerized patient records. Prediction models aim to pro

  20. More accurate recombination prediction in HIV-1 using a robust decoding algorithm for HMMs

    Directory of Open Access Journals (Sweden)

    Brown Daniel G

    2011-05-01

    Full Text Available Abstract Background Identifying recombinations in HIV is important for studying the epidemiology of the virus and aids in the design of potential vaccines and treatments. The previous widely-used tool for this task uses the Viterbi algorithm in a hidden Markov model to model recombinant sequences. Results We apply a new decoding algorithm for this HMM that improves prediction accuracy. Exactly locating breakpoints is usually impossible, since different subtypes are highly conserved in some sequence regions. Our algorithm identifies these sites up to a certain error tolerance. Our new algorithm is more accurate in predicting the location of recombination breakpoints. Our implementation of the algorithm is available at http://www.cs.uwaterloo.ca/~jmtruszk/jphmm_balls.tar.gz. Conclusions By explicitly accounting for uncertainty in breakpoint positions, our algorithm offers more reliable predictions of recombination breakpoints in HIV-1. We also document a new domain of use for our new decoding approach in HMMs.

  1. Accurate approximation method for prediction of class I MHC affinities for peptides of length 8, 10 and 11 using prediction tools trained on 9mers

    DEFF Research Database (Denmark)

    Lundegaard, Claus; Lund, Ole; Nielsen, Morten

    2008-01-01

    Several accurate prediction systems have been developed for prediction of class I major histocompatibility complex (MHC):peptide binding. Most of these are trained on binding affinity data of primarily 9mer peptides. Here, we show how prediction methods trained on 9mer data can be used for accurate...

  2. DYNAMICALLY EVOLVING CLINICAL PRACTICES AND IMPLICATIONS FOR PREDICTING MEDICAL DECISIONS

    Science.gov (United States)

    CHEN, JONATHAN H; GOLDSTEIN, MARY K; ASCH, STEVEN M; ALTMAN, RUSS B

    2015-01-01

    Automatically data-mining clinical practice patterns from electronic health records (EHR) can enable prediction of future practices as a form of clinical decision support (CDS). Our objective is to determine the stability of learned clinical practice patterns over time and what implication this has when using varying longitudinal historical data sources towards predicting future decisions. We trained an association rule engine for clinical orders (e.g., labs, imaging, medications) using structured inpatient data from a tertiary academic hospital. Comparing top order associations per admission diagnosis from training data in 2009 vs. 2012, we find practice variability from unstable diagnoses with rank biased overlap (RBO)0.6. Predicting admission orders for future (2013) patients with associations trained on recent (2012) vs. older (2009) data improved accuracy evaluated by area under the receiver operating characteristic curve (ROC-AUC) 0.89 to 0.92, precision at ten (positive predictive value of the top ten predictions against actual orders) 30% to 37%, and weighted recall (sensitivity) at ten 2.4% to 13%, (P<10−10). Training with more longitudinal data (2009-2012) was no better than only using recent (2012) data. Secular trends in practice patterns likely explain why smaller but more recent training data is more accurate at predicting future practices. PMID:26776186

  3. Machine learning predictions of molecular properties: Accurate many-body potentials and nonlocality in chemical space

    International Nuclear Information System (INIS)

    Simultaneously accurate and efficient prediction of molecular properties throughout chemical compound space is a critical ingredient toward rational compound design in chemical and pharmaceutical industries. Aiming toward this goal, we develop and apply a systematic hierarchy of efficient empirical methods to estimate atomization and total energies of molecules. These methods range from a simple sum over atoms, to addition of bond energies, to pairwise interatomic force fields, reaching to the more sophisticated machine learning approaches that are capable of describing collective interactions between many atoms or bonds. In the case of equilibrium molecular geometries, even simple pairwise force fields demonstrate prediction accuracy comparable to benchmark energies calculated using density functional theory with hybrid exchange-correlation functionals; however, accounting for the collective many-body interactions proves to be essential for approaching the 'holy grail' of chemical accuracy of 1 kcal/mol for both equilibrium and out-of-equilibrium geometries. This remarkable accuracy is achieved by a vectorized representation of molecules (so-called Bag of Bonds model) that exhibits strong nonlocality in chemical space. The same representation allows us to predict accurate electronic properties of molecules, such as their polarizability and molecular frontier orbital energies

  4. A Novel Method for Accurate Operon Predictions in All SequencedProkaryotes

    Energy Technology Data Exchange (ETDEWEB)

    Price, Morgan N.; Huang, Katherine H.; Alm, Eric J.; Arkin, Adam P.

    2004-12-01

    We combine comparative genomic measures and the distance separating adjacent genes to predict operons in 124 completely sequenced prokaryotic genomes. Our method automatically tailors itself to each genome using sequence information alone, and thus can be applied to any prokaryote. For Escherichia coli K12 and Bacillus subtilis, our method is 85 and 83% accurate, respectively, which is similar to the accuracy of methods that use the same features but are trained on experimentally characterized transcripts. In Halobacterium NRC-1 and in Helicobacterpylori, our method correctly infers that genes in operons are separated by shorter distances than they are in E.coli, and its predictions using distance alone are more accurate than distance-only predictions trained on a database of E.coli transcripts. We use microarray data from sixphylogenetically diverse prokaryotes to show that combining intergenic distance with comparative genomic measures further improves accuracy and that our method is broadly effective. Finally, we survey operon structure across 124 genomes, and find several surprises: H.pylori has many operons, contrary to previous reports; Bacillus anthracis has an unusual number of pseudogenes within conserved operons; and Synechocystis PCC6803 has many operons even though it has unusually wide spacings between conserved adjacent genes.

  5. LogGPO: An accurate communication model for performance prediction of MPI programs

    Institute of Scientific and Technical Information of China (English)

    CHEN WenGuang; ZHAI JiDong; ZHANG Jin; ZHENG WeiMin

    2009-01-01

    Message passing interface (MPI) is the de facto standard in writing parallel scientific applications on distributed memory systems. Performance prediction of MPI programs on current or future parallel sys-terns can help to find system bottleneck or optimize programs. To effectively analyze and predict per-formance of a large and complex MPI program, an efficient and accurate communication model is highly needed. A series of communication models have been proposed, such as the LogP model family, which assume that the sending overhead, message transmission, and receiving overhead of a communication is not overlapped and there is a maximum overlap degree between computation and communication. However, this assumption does not always hold for MPI programs because either sending or receiving overhead introduced by MPI implementations can decrease potential overlap for large messages. In this paper, we present a new communication model, named LogGPO, which captures the potential overlap between computation with communication of MPI programs. We design and implement a trace-driven simulator to verify the LogGPO model by predicting performance of point-to-point communication and two real applications CG and Sweep3D. The average prediction errors of LogGPO model are 2.4% and 2.0% for these two applications respectively, while the average prediction errors of LogGP model are 38.3% and 9.1% respectively.

  6. Microstructure-Dependent Gas Adsorption: Accurate Predictions of Methane Uptake in Nanoporous Carbons

    Energy Technology Data Exchange (ETDEWEB)

    Ihm, Yungok [University of Tennessee (UTK) and Oak Ridge National Laboratory (ORNL); Cooper, Valentino R [ORNL; Gallego, Nidia C [ORNL; Contescu, Cristian I [ORNL; Morris, James R [ORNL

    2014-01-01

    We demonstrate a successful, efficient framework for predicting gas adsorption properties in real materials based on first-principles calculations, with a specific comparison of experiment and theory for methane adsorption in activated carbons. These carbon materials have different pore size distributions, leading to a variety of uptake characteristics. Utilizing these distributions, we accurately predict experimental uptakes and heats of adsorption without empirical potentials or lengthy simulations. We demonstrate that materials with smaller pores have higher heats of adsorption, leading to a higher gas density in these pores. This pore-size dependence must be accounted for, in order to predict and understand the adsorption behavior. The theoretical approach combines: (1) ab initio calculations with a van der Waals density functional to determine adsorbent-adsorbate interactions, and (2) a thermodynamic method that predicts equilibrium adsorption densities by directly incorporating the calculated potential energy surface in a slit pore model. The predicted uptake at P=20 bar and T=298 K is in excellent agreement for all five activated carbon materials used. This approach uses only the pore-size distribution as an input, with no fitting parameters or empirical adsorbent-adsorbate interactions, and thus can be easily applied to other adsorbent-adsorbate combinations.

  7. The MIDAS touch for Accurately Predicting the Stress-Strain Behavior of Tantalum

    Energy Technology Data Exchange (ETDEWEB)

    Jorgensen, S. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2016-03-02

    Testing the behavior of metals in extreme environments is not always feasible, so material scientists use models to try and predict the behavior. To achieve accurate results it is necessary to use the appropriate model and material-specific parameters. This research evaluated the performance of six material models available in the MIDAS database [1] to determine at which temperatures and strain-rates they perform best, and to determine to which experimental data their parameters were optimized. Additionally, parameters were optimized for the Johnson-Cook model using experimental data from Lassila et al [2].

  8. Physical modeling of real-world slingshots for accurate speed predictions

    CERN Document Server

    Yeats, Bob

    2016-01-01

    We discuss the physics and modeling of latex-rubber slingshots. The goal is to get accurate speed predictions inspite of the significant real world difficulties of force drift, force hysteresis, rubber ageing, and the very non- linear, non-ideal, force vs. pull distance curves of slingshot rubber bands. Slingshots are known to shoot faster under some circumstances when the bands are tapered rather than having constant width and stiffness. We give both qualitative understanding and numerical predictions of this effect. We consider two models. The first is based on conservation of energy and is easier to implement, but cannot determine the speeds along the rubber bands without making assumptions. The second, treats the bands as a series of mass points subject to being pulled by immediately adjacent mass points according to how much the rubber has been stretched on the two adjacent sides. This is a classic many-body F=ma problem but convergence requires using a particular numerical technique. It gives accurate p...

  9. Accurate Prediction of Radiation Exposures of Workers Involved in the Transport of NORM

    International Nuclear Information System (INIS)

    A study of the radiation exposures encountered by workers involved in the transport of minerals and mineral concentrates containing radionuclides of natural origin was undertaken during 2008–2012. Hundreds of measurements were made during road, rail and marine transport of NORM between mining and processing sites in Australia and within and between ports in Australia, China and Japan. The investigation was focused on minerals and mineral concentrates containing thorium and uranium (including ilmenite, rutile, zircon and monazite). It was found that the use of the ‘exclusion’ factor of 10 for the concentrations of radionuclides in natural materials in the IAEA Transport Regulations is appropriate and is to be maintained. The dose rates from all potential pathways of exposure of workers could be accurately predicted, based on the concentrations of thorium and uranium in the transported material. These dose rates remain the same, irrespective of whether the transport is by road, rail or sea. The information presented in the paper allows, by the use of simple charts, the accurate prediction of doses to workers involved in the transport of NORM. It is suggested that it can be used in any assessments of exposures of workers that may be required prior to the start of the NORM transport process, by both regulatory bodies and by the mining and mineral processing industry. (author)

  10. ILT based defect simulation of inspection images accurately predicts mask defect printability on wafer

    Science.gov (United States)

    Deep, Prakash; Paninjath, Sankaranarayanan; Pereira, Mark; Buck, Peter

    2016-05-01

    At advanced technology nodes mask complexity has been increased because of large-scale use of resolution enhancement technologies (RET) which includes Optical Proximity Correction (OPC), Inverse Lithography Technology (ILT) and Source Mask Optimization (SMO). The number of defects detected during inspection of such mask increased drastically and differentiation of critical and non-critical defects are more challenging, complex and time consuming. Because of significant defectivity of EUVL masks and non-availability of actinic inspection, it is important and also challenging to predict the criticality of defects for printability on wafer. This is one of the significant barriers for the adoption of EUVL for semiconductor manufacturing. Techniques to decide criticality of defects from images captured using non actinic inspection images is desired till actinic inspection is not available. High resolution inspection of photomask images detects many defects which are used for process and mask qualification. Repairing all defects is not practical and probably not required, however it's imperative to know which defects are severe enough to impact wafer before repair. Additionally, wafer printability check is always desired after repairing a defect. AIMSTM review is the industry standard for this, however doing AIMSTM review for all defects is expensive and very time consuming. Fast, accurate and an economical mechanism is desired which can predict defect printability on wafer accurately and quickly from images captured using high resolution inspection machine. Predicting defect printability from such images is challenging due to the fact that the high resolution images do not correlate with actual mask contours. The challenge is increased due to use of different optical condition during inspection other than actual scanner condition, and defects found in such images do not have correlation with actual impact on wafer. Our automated defect simulation tool predicts

  11. ACE-I Angioedema: Accurate Clinical Diagnosis May Prevent Epinephrine-Induced Harm

    OpenAIRE

    R. Mason Curtis; Sarah Felder; Rozita Borici-Mazi; Ian Ball

    2016-01-01

    Introduction: Upper airway angioedema is a life-threatening emergency department (ED) presentation with increasing incidence. Angiotensin-converting enzyme inhibitor induced angioedema (AAE) is a non-mast cell mediated etiology of angioedema. Accurate diagnosis by clinical examination can optimize patient management and reduce morbidity from inappropriate treatment with epinephrine. The aim of this study is to describe the incidence of angioedema subtypes and the management of AAE. We evaluat...

  12. Genetic crossovers are predicted accurately by the computed human recombination map.

    Directory of Open Access Journals (Sweden)

    Pavel P Khil

    2010-01-01

    Full Text Available Hotspots of meiotic recombination can change rapidly over time. This instability and the reported high level of inter-individual variation in meiotic recombination puts in question the accuracy of the calculated hotspot map, which is based on the summation of past genetic crossovers. To estimate the accuracy of the computed recombination rate map, we have mapped genetic crossovers to a median resolution of 70 Kb in 10 CEPH pedigrees. We then compared the positions of crossovers with the hotspots computed from HapMap data and performed extensive computer simulations to compare the observed distributions of crossovers with the distributions expected from the calculated recombination rate maps. Here we show that a population-averaged hotspot map computed from linkage disequilibrium data predicts well present-day genetic crossovers. We find that computed hotspot maps accurately estimate both the strength and the position of meiotic hotspots. An in-depth examination of not-predicted crossovers shows that they are preferentially located in regions where hotspots are found in other populations. In summary, we find that by combining several computed population-specific maps we can capture the variation in individual hotspots to generate a hotspot map that can predict almost all present-day genetic crossovers.

  13. Intermolecular potentials and the accurate prediction of the thermodynamic properties of water

    Energy Technology Data Exchange (ETDEWEB)

    Shvab, I.; Sadus, Richard J., E-mail: rsadus@swin.edu.au [Centre for Molecular Simulation, Swinburne University of Technology, PO Box 218, Hawthorn, Victoria 3122 (Australia)

    2013-11-21

    The ability of intermolecular potentials to correctly predict the thermodynamic properties of liquid water at a density of 0.998 g/cm{sup 3} for a wide range of temperatures (298–650 K) and pressures (0.1–700 MPa) is investigated. Molecular dynamics simulations are reported for the pressure, thermal pressure coefficient, thermal expansion coefficient, isothermal and adiabatic compressibilities, isobaric and isochoric heat capacities, and Joule-Thomson coefficient of liquid water using the non-polarizable SPC/E and TIP4P/2005 potentials. The results are compared with both experiment data and results obtained from the ab initio-based Matsuoka-Clementi-Yoshimine non-additive (MCYna) [J. Li, Z. Zhou, and R. J. Sadus, J. Chem. Phys. 127, 154509 (2007)] potential, which includes polarization contributions. The data clearly indicate that both the SPC/E and TIP4P/2005 potentials are only in qualitative agreement with experiment, whereas the polarizable MCYna potential predicts some properties within experimental uncertainty. This highlights the importance of polarizability for the accurate prediction of the thermodynamic properties of water, particularly at temperatures beyond 298 K.

  14. Radiogenomics: predicting clinical normal tissue radiosensitivity

    DEFF Research Database (Denmark)

    Alsner, Jan

    2006-01-01

    of subcutaneous fibrosis in breast cancer patients will be presented and discussed in relation to possible future studies in radiogenomics. One important and necessary basis for future studies is the collection of carefully designed clinical studies with the accrual of very large numbers of patients (the ESTRO......Studies on the genetic basis of normal tissue radiosensitivity, or  'radiogenomics', aims at predicting clinical radiosensitivity and optimize treatment from individual genetic profiles. Several studies have now reported links between variations in certain genes related to the biological response...... to radiation injury and risk of normal tissue morbidity in cancer patients treated with radiotherapy. However, after these initial association studies including few genes, we are still far from being able to predict clinical radiosensitivity on an individual level. Recent data from our own studies on risk...

  15. Clinical prediction rule for nonmelanoma skin cancer

    Directory of Open Access Journals (Sweden)

    John Alexander Nova

    2015-01-01

    Full Text Available Background: Skin cancer is the most frequent neoplasia in the world. Even though ultraviolet radiation is the main cause, established prevention campaigns have not proved to be effective for controlling the incidence of this disease. Objective: To develop clinical prediction rules based on medical consultation and a questionnaire to estimate the risk of developing nonmelanoma skin cancer. Methods: This study was developed in several steps. They were: Identifying risk factors that could be possible predictors of nonmelanoma skin cancer; their clinical validation; developing a prediction rule using logistic regression; and collecting information from 962 patients in a case and control design (481 cases and 481 controls. We developed independent prediction rules for basal cell and squamous cell carcinomas. Finally, we evaluated reliability for each of the variables. Results: The variables that made up the final prediction rule were: Family history of skin cancer, history of outdoor work, age, phototypes 1-3 and the presence of poikiloderma of civatte, actinic keratosis and conjunctivitis in band. Prediction rules specificity was 87% for basal cell carcinomas and 92% for squamous cell carcinomas. Inter- and intra-observer reliability was good except for the conjunctivitis in band variable. Conclusions: The prediction rules let us calculate the individual risk of developing basal cell carcinoma and squamous cell carcinoma. This is an economic easy-to-apply tool that could be useful in primary and secondary prevention of skin cancer.

  16. Fast and accurate prediction of numerical relativity waveforms from binary black hole mergers using surrogate models

    CERN Document Server

    Blackman, Jonathan; Galley, Chad R; Szilagyi, Bela; Scheel, Mark A; Tiglio, Manuel; Hemberger, Daniel A

    2015-01-01

    Simulating a binary black hole coalescence by solving Einstein's equations is computationally expensive, requiring days to months of supercomputing time. In this paper, we construct an accurate and fast-to-evaluate surrogate model for numerical relativity (NR) waveforms from non-spinning binary black hole coalescences with mass ratios from $1$ to $10$ and durations corresponding to about $15$ orbits before merger. Our surrogate, which is built using reduced order modeling techniques, is distinct from traditional modeling efforts. We find that the full multi-mode surrogate model agrees with waveforms generated by NR to within the numerical error of the NR code. In particular, we show that our modeling strategy produces surrogates which can correctly predict NR waveforms that were {\\em not} used for the surrogate's training. For all practical purposes, then, the surrogate waveform model is equivalent to the high-accuracy, large-scale simulation waveform but can be evaluated in a millisecond to a second dependin...

  17. A fast and accurate method to predict 2D and 3D aerodynamic boundary layer flows

    International Nuclear Information System (INIS)

    A quasi-simultaneous interaction method is applied to predict 2D and 3D aerodynamic flows. This method is suitable for offshore wind turbine design software as it is a very accurate and computationally reasonably cheap method. This study shows the results for a NACA 0012 airfoil. The two applied solvers converge to the experimental values when the grid is refined. We also show that in separation the eigenvalues remain positive thus avoiding the Goldstein singularity at separation. In 3D we show a flow over a dent in which separation occurs. A rotating flat plat is used to show the applicability of the method for rotating flows. The shown capabilities of the method indicate that the quasi-simultaneous interaction method is suitable for design methods for offshore wind turbine blades

  18. A fast and accurate method to predict 2D and 3D aerodynamic boundary layer flows

    Science.gov (United States)

    Bijleveld, H. A.; Veldman, A. E. P.

    2014-12-01

    A quasi-simultaneous interaction method is applied to predict 2D and 3D aerodynamic flows. This method is suitable for offshore wind turbine design software as it is a very accurate and computationally reasonably cheap method. This study shows the results for a NACA 0012 airfoil. The two applied solvers converge to the experimental values when the grid is refined. We also show that in separation the eigenvalues remain positive thus avoiding the Goldstein singularity at separation. In 3D we show a flow over a dent in which separation occurs. A rotating flat plat is used to show the applicability of the method for rotating flows. The shown capabilities of the method indicate that the quasi-simultaneous interaction method is suitable for design methods for offshore wind turbine blades.

  19. Differential contribution of visual and auditory information to accurately predict the direction and rotational motion of a visual stimulus.

    Science.gov (United States)

    Park, Seoung Hoon; Kim, Seonjin; Kwon, MinHyuk; Christou, Evangelos A

    2016-03-01

    Vision and auditory information are critical for perception and to enhance the ability of an individual to respond accurately to a stimulus. However, it is unknown whether visual and auditory information contribute differentially to identify the direction and rotational motion of the stimulus. The purpose of this study was to determine the ability of an individual to accurately predict the direction and rotational motion of the stimulus based on visual and auditory information. In this study, we recruited 9 expert table-tennis players and used table-tennis service as our experimental model. Participants watched recorded services with different levels of visual and auditory information. The goal was to anticipate the direction of the service (left or right) and the rotational motion of service (topspin, sidespin, or cut). We recorded their responses and quantified the following outcomes: (i) directional accuracy and (ii) rotational motion accuracy. The response accuracy was the accurate predictions relative to the total number of trials. The ability of the participants to predict the direction of the service accurately increased with additional visual information but not with auditory information. In contrast, the ability of the participants to predict the rotational motion of the service accurately increased with the addition of auditory information to visual information but not with additional visual information alone. In conclusion, this finding demonstrates that visual information enhances the ability of an individual to accurately predict the direction of the stimulus, whereas additional auditory information enhances the ability of an individual to accurately predict the rotational motion of stimulus.

  20. In vitro transcription accurately predicts lac repressor phenotype in vivo in Escherichia coli

    Directory of Open Access Journals (Sweden)

    Matthew Almond Sochor

    2014-07-01

    Full Text Available A multitude of studies have looked at the in vivo and in vitro behavior of the lac repressor binding to DNA and effector molecules in order to study transcriptional repression, however these studies are not always reconcilable. Here we use in vitro transcription to directly mimic the in vivo system in order to build a self consistent set of experiments to directly compare in vivo and in vitro genetic repression. A thermodynamic model of the lac repressor binding to operator DNA and effector is used to link DNA occupancy to either normalized in vitro mRNA product or normalized in vivo fluorescence of a regulated gene, YFP. An accurate measurement of repressor, DNA and effector concentrations were made both in vivo and in vitro allowing for direct modeling of the entire thermodynamic equilibrium. In vivo repression profiles are accurately predicted from the given in vitro parameters when molecular crowding is considered. Interestingly, our measured repressor–operator DNA affinity differs significantly from previous in vitro measurements. The literature values are unable to replicate in vivo binding data. We therefore conclude that the repressor-DNA affinity is much weaker than previously thought. This finding would suggest that in vitro techniques that are specifically designed to mimic the in vivo process may be necessary to replicate the native system.

  1. Measuring solar reflectance Part I: Defining a metric that accurately predicts solar heat gain

    Energy Technology Data Exchange (ETDEWEB)

    Levinson, Ronnen; Akbari, Hashem; Berdahl, Paul

    2010-05-14

    Solar reflectance can vary with the spectral and angular distributions of incident sunlight, which in turn depend on surface orientation, solar position and atmospheric conditions. A widely used solar reflectance metric based on the ASTM Standard E891 beam-normal solar spectral irradiance underestimates the solar heat gain of a spectrally selective 'cool colored' surface because this irradiance contains a greater fraction of near-infrared light than typically found in ordinary (unconcentrated) global sunlight. At mainland U.S. latitudes, this metric RE891BN can underestimate the annual peak solar heat gain of a typical roof or pavement (slope {le} 5:12 [23{sup o}]) by as much as 89 W m{sup -2}, and underestimate its peak surface temperature by up to 5 K. Using R{sub E891BN} to characterize roofs in a building energy simulation can exaggerate the economic value N of annual cool-roof net energy savings by as much as 23%. We define clear-sky air mass one global horizontal ('AM1GH') solar reflectance R{sub g,0}, a simple and easily measured property that more accurately predicts solar heat gain. R{sub g,0} predicts the annual peak solar heat gain of a roof or pavement to within 2 W m{sup -2}, and overestimates N by no more than 3%. R{sub g,0} is well suited to rating the solar reflectances of roofs, pavements and walls. We show in Part II that R{sub g,0} can be easily and accurately measured with a pyranometer, a solar spectrophotometer or version 6 of the Solar Spectrum Reflectometer.

  2. Highly Accurate Prediction of Protein-Protein Interactions via Incorporating Evolutionary Information and Physicochemical Characteristics

    Science.gov (United States)

    Li, Zheng-Wei; You, Zhu-Hong; Chen, Xing; Gui, Jie; Nie, Ru

    2016-01-01

    Protein-protein interactions (PPIs) occur at almost all levels of cell functions and play crucial roles in various cellular processes. Thus, identification of PPIs is critical for deciphering the molecular mechanisms and further providing insight into biological processes. Although a variety of high-throughput experimental techniques have been developed to identify PPIs, existing PPI pairs by experimental approaches only cover a small fraction of the whole PPI networks, and further, those approaches hold inherent disadvantages, such as being time-consuming, expensive, and having high false positive rate. Therefore, it is urgent and imperative to develop automatic in silico approaches to predict PPIs efficiently and accurately. In this article, we propose a novel mixture of physicochemical and evolutionary-based feature extraction method for predicting PPIs using our newly developed discriminative vector machine (DVM) classifier. The improvements of the proposed method mainly consist in introducing an effective feature extraction method that can capture discriminative features from the evolutionary-based information and physicochemical characteristics, and then a powerful and robust DVM classifier is employed. To the best of our knowledge, it is the first time that DVM model is applied to the field of bioinformatics. When applying the proposed method to the Yeast and Helicobacter pylori (H. pylori) datasets, we obtain excellent prediction accuracies of 94.35% and 90.61%, respectively. The computational results indicate that our method is effective and robust for predicting PPIs, and can be taken as a useful supplementary tool to the traditional experimental methods for future proteomics research. PMID:27571061

  3. Highly Accurate Prediction of Protein-Protein Interactions via Incorporating Evolutionary Information and Physicochemical Characteristics.

    Science.gov (United States)

    Li, Zheng-Wei; You, Zhu-Hong; Chen, Xing; Gui, Jie; Nie, Ru

    2016-01-01

    Protein-protein interactions (PPIs) occur at almost all levels of cell functions and play crucial roles in various cellular processes. Thus, identification of PPIs is critical for deciphering the molecular mechanisms and further providing insight into biological processes. Although a variety of high-throughput experimental techniques have been developed to identify PPIs, existing PPI pairs by experimental approaches only cover a small fraction of the whole PPI networks, and further, those approaches hold inherent disadvantages, such as being time-consuming, expensive, and having high false positive rate. Therefore, it is urgent and imperative to develop automatic in silico approaches to predict PPIs efficiently and accurately. In this article, we propose a novel mixture of physicochemical and evolutionary-based feature extraction method for predicting PPIs using our newly developed discriminative vector machine (DVM) classifier. The improvements of the proposed method mainly consist in introducing an effective feature extraction method that can capture discriminative features from the evolutionary-based information and physicochemical characteristics, and then a powerful and robust DVM classifier is employed. To the best of our knowledge, it is the first time that DVM model is applied to the field of bioinformatics. When applying the proposed method to the Yeast and Helicobacter pylori (H. pylori) datasets, we obtain excellent prediction accuracies of 94.35% and 90.61%, respectively. The computational results indicate that our method is effective and robust for predicting PPIs, and can be taken as a useful supplementary tool to the traditional experimental methods for future proteomics research. PMID:27571061

  4. Highly Accurate Prediction of Protein-Protein Interactions via Incorporating Evolutionary Information and Physicochemical Characteristics

    Directory of Open Access Journals (Sweden)

    Zheng-Wei Li

    2016-08-01

    Full Text Available Protein-protein interactions (PPIs occur at almost all levels of cell functions and play crucial roles in various cellular processes. Thus, identification of PPIs is critical for deciphering the molecular mechanisms and further providing insight into biological processes. Although a variety of high-throughput experimental techniques have been developed to identify PPIs, existing PPI pairs by experimental approaches only cover a small fraction of the whole PPI networks, and further, those approaches hold inherent disadvantages, such as being time-consuming, expensive, and having high false positive rate. Therefore, it is urgent and imperative to develop automatic in silico approaches to predict PPIs efficiently and accurately. In this article, we propose a novel mixture of physicochemical and evolutionary-based feature extraction method for predicting PPIs using our newly developed discriminative vector machine (DVM classifier. The improvements of the proposed method mainly consist in introducing an effective feature extraction method that can capture discriminative features from the evolutionary-based information and physicochemical characteristics, and then a powerful and robust DVM classifier is employed. To the best of our knowledge, it is the first time that DVM model is applied to the field of bioinformatics. When applying the proposed method to the Yeast and Helicobacter pylori (H. pylori datasets, we obtain excellent prediction accuracies of 94.35% and 90.61%, respectively. The computational results indicate that our method is effective and robust for predicting PPIs, and can be taken as a useful supplementary tool to the traditional experimental methods for future proteomics research.

  5. Highly Accurate Prediction of Protein-Protein Interactions via Incorporating Evolutionary Information and Physicochemical Characteristics.

    Science.gov (United States)

    Li, Zheng-Wei; You, Zhu-Hong; Chen, Xing; Gui, Jie; Nie, Ru

    2016-01-01

    Protein-protein interactions (PPIs) occur at almost all levels of cell functions and play crucial roles in various cellular processes. Thus, identification of PPIs is critical for deciphering the molecular mechanisms and further providing insight into biological processes. Although a variety of high-throughput experimental techniques have been developed to identify PPIs, existing PPI pairs by experimental approaches only cover a small fraction of the whole PPI networks, and further, those approaches hold inherent disadvantages, such as being time-consuming, expensive, and having high false positive rate. Therefore, it is urgent and imperative to develop automatic in silico approaches to predict PPIs efficiently and accurately. In this article, we propose a novel mixture of physicochemical and evolutionary-based feature extraction method for predicting PPIs using our newly developed discriminative vector machine (DVM) classifier. The improvements of the proposed method mainly consist in introducing an effective feature extraction method that can capture discriminative features from the evolutionary-based information and physicochemical characteristics, and then a powerful and robust DVM classifier is employed. To the best of our knowledge, it is the first time that DVM model is applied to the field of bioinformatics. When applying the proposed method to the Yeast and Helicobacter pylori (H. pylori) datasets, we obtain excellent prediction accuracies of 94.35% and 90.61%, respectively. The computational results indicate that our method is effective and robust for predicting PPIs, and can be taken as a useful supplementary tool to the traditional experimental methods for future proteomics research.

  6. An Accurate Calculation of the Big-Bang Prediction for the Abundance of Primordial Helium

    CERN Document Server

    López, R E; Lopez, Robert E.; Turner, Michael S.

    1999-01-01

    Within the standard model of particle physics and cosmology we have calculated the big-bang prediction for the primordial abundance of Helium to a theoretical uncertainty of $0.1 \\pct$ $(\\delta Y_P = \\pm 0.0002)$. At this accuracy the uncertainty in the abundance is dominated by the experimental uncertainty in the neutron mean lifetime, $\\tau_n = 885.3 \\pm 2.0 \\rm{sec}$. The following physical effects were included in the calculation: the zero and finite-temperature radiative, Coulomb and finite-nucleon mass corrections to the weak rates; order-$\\alpha$ quantum-electrodynamic correction to the plasma density, electron mass, and neutrino temperature; and incomplete neutrino decoupling. New results for the finite-temperature radiative correction and the QED plasma correction were used. In addition, we wrote a new and independent nucleosynthesis code to control numerical errors to less than 0.1\\pct. Our predictions for the \\EL[4]{He} abundance are summarized with an accurate fitting formula. Summarizing our work...

  7. ChIP-seq Accurately Predicts Tissue-Specific Activity of Enhancers

    Energy Technology Data Exchange (ETDEWEB)

    Visel, Axel; Blow, Matthew J.; Li, Zirong; Zhang, Tao; Akiyama, Jennifer A.; Holt, Amy; Plajzer-Frick, Ingrid; Shoukry, Malak; Wright, Crystal; Chen, Feng; Afzal, Veena; Ren, Bing; Rubin, Edward M.; Pennacchio, Len A.

    2009-02-01

    A major yet unresolved quest in decoding the human genome is the identification of the regulatory sequences that control the spatial and temporal expression of genes. Distant-acting transcriptional enhancers are particularly challenging to uncover since they are scattered amongst the vast non-coding portion of the genome. Evolutionary sequence constraint can facilitate the discovery of enhancers, but fails to predict when and where they are active in vivo. Here, we performed chromatin immunoprecipitation with the enhancer-associated protein p300, followed by massively-parallel sequencing, to map several thousand in vivo binding sites of p300 in mouse embryonic forebrain, midbrain, and limb tissue. We tested 86 of these sequences in a transgenic mouse assay, which in nearly all cases revealed reproducible enhancer activity in those tissues predicted by p300 binding. Our results indicate that in vivo mapping of p300 binding is a highly accurate means for identifying enhancers and their associated activities and suggest that such datasets will be useful to study the role of tissue-specific enhancers in human biology and disease on a genome-wide scale.

  8. A Simple and Accurate Model to Predict Responses to Multi-electrode Stimulation in the Retina.

    Directory of Open Access Journals (Sweden)

    Matias I Maturana

    2016-04-01

    Full Text Available Implantable electrode arrays are widely used in therapeutic stimulation of the nervous system (e.g. cochlear, retinal, and cortical implants. Currently, most neural prostheses use serial stimulation (i.e. one electrode at a time despite this severely limiting the repertoire of stimuli that can be applied. Methods to reliably predict the outcome of multi-electrode stimulation have not been available. Here, we demonstrate that a linear-nonlinear model accurately predicts neural responses to arbitrary patterns of stimulation using in vitro recordings from single retinal ganglion cells (RGCs stimulated with a subretinal multi-electrode array. In the model, the stimulus is projected onto a low-dimensional subspace and then undergoes a nonlinear transformation to produce an estimate of spiking probability. The low-dimensional subspace is estimated using principal components analysis, which gives the neuron's electrical receptive field (ERF, i.e. the electrodes to which the neuron is most sensitive. Our model suggests that stimulation proportional to the ERF yields a higher efficacy given a fixed amount of power when compared to equal amplitude stimulation on up to three electrodes. We find that the model captures the responses of all the cells recorded in the study, suggesting that it will generalize to most cell types in the retina. The model is computationally efficient to evaluate and, therefore, appropriate for future real-time applications including stimulation strategies that make use of recorded neural activity to improve the stimulation strategy.

  9. A Simple and Accurate Model to Predict Responses to Multi-electrode Stimulation in the Retina.

    Science.gov (United States)

    Maturana, Matias I; Apollo, Nicholas V; Hadjinicolaou, Alex E; Garrett, David J; Cloherty, Shaun L; Kameneva, Tatiana; Grayden, David B; Ibbotson, Michael R; Meffin, Hamish

    2016-04-01

    Implantable electrode arrays are widely used in therapeutic stimulation of the nervous system (e.g. cochlear, retinal, and cortical implants). Currently, most neural prostheses use serial stimulation (i.e. one electrode at a time) despite this severely limiting the repertoire of stimuli that can be applied. Methods to reliably predict the outcome of multi-electrode stimulation have not been available. Here, we demonstrate that a linear-nonlinear model accurately predicts neural responses to arbitrary patterns of stimulation using in vitro recordings from single retinal ganglion cells (RGCs) stimulated with a subretinal multi-electrode array. In the model, the stimulus is projected onto a low-dimensional subspace and then undergoes a nonlinear transformation to produce an estimate of spiking probability. The low-dimensional subspace is estimated using principal components analysis, which gives the neuron's electrical receptive field (ERF), i.e. the electrodes to which the neuron is most sensitive. Our model suggests that stimulation proportional to the ERF yields a higher efficacy given a fixed amount of power when compared to equal amplitude stimulation on up to three electrodes. We find that the model captures the responses of all the cells recorded in the study, suggesting that it will generalize to most cell types in the retina. The model is computationally efficient to evaluate and, therefore, appropriate for future real-time applications including stimulation strategies that make use of recorded neural activity to improve the stimulation strategy. PMID:27035143

  10. Can CO2 assimilation in maize leaves be predicted accurately from chlorophyll fluorescence analysis?

    Science.gov (United States)

    Edwards, G E; Baker, N R

    1993-08-01

    Analysis is made of the energetics of CO2 fixation, the photochemical quantum requirement per CO2 fixed, and sinks for utilising reductive power in the C4 plant maize. CO2 assimilation is the primary sink for energy derived from photochemistry, whereas photorespiration and nitrogen assimilation are relatively small sinks, particularly in developed leaves. Measurement of O2 exchange by mass spectrometry and CO2 exchange by infrared gas analysis under varying levels of CO2 indicate that there is a very close relationship between the true rate of O2 evolution from PS II and the net rate of CO2 fixation. Consideration is given to measurements of the quantum yields of PS II (φ PS II) from fluorescence analysis and of CO2 assimilation ([Formula: see text]) in maize over a wide range of conditions. The[Formula: see text] ratio was found to remain reasonably constant (ca. 12) over a range of physiological conditions in developed leaves, with varying temperature, CO2 concentrations, light intensities (from 5% to 100% of full sunlight), and following photoinhibition under high light and low temperature. A simple model for predicting CO2 assimilation from fluorescence parameters is presented and evaluated. It is concluded that under a wide range of conditions fluorescence parameters can be used to predict accurately and rapidly CO2 assimilation rates in maize. PMID:24317706

  11. Accurate First-Principles Spectra Predictions for Planetological and Astrophysical Applications at Various T-Conditions

    Science.gov (United States)

    Rey, M.; Nikitin, A. V.; Tyuterev, V.

    2014-06-01

    Knowledge of near infrared intensities of rovibrational transitions of polyatomic molecules is essential for the modeling of various planetary atmospheres, brown dwarfs and for other astrophysical applications 1,2,3. For example, to analyze exoplanets, atmospheric models have been developed, thus making the need to provide accurate spectroscopic data. Consequently, the spectral characterization of such planetary objects relies on the necessity of having adequate and reliable molecular data in extreme conditions (temperature, optical path length, pressure). On the other hand, in the modeling of astrophysical opacities, millions of lines are generally involved and the line-by-line extraction is clearly not feasible in laboratory measurements. It is thus suggested that this large amount of data could be interpreted only by reliable theoretical predictions. There exists essentially two theoretical approaches for the computation and prediction of spectra. The first one is based on empirically-fitted effective spectroscopic models. Another way for computing energies, line positions and intensities is based on global variational calculations using ab initio surfaces. They do not yet reach the spectroscopic accuracy stricto sensu but implicitly account for all intramolecular interactions including resonance couplings in a wide spectral range. The final aim of this work is to provide reliable predictions which could be quantitatively accurate with respect to the precision of available observations and as complete as possible. All this thus requires extensive first-principles quantum mechanical calculations essentially based on three necessary ingredients which are (i) accurate intramolecular potential energy surface and dipole moment surface components well-defined in a large range of vibrational displacements and (ii) efficient computational methods combined with suitable choices of coordinates to account for molecular symmetry properties and to achieve a good numerical

  12. Simplified versus geometrically accurate models of forefoot anatomy to predict plantar pressures: A finite element study.

    Science.gov (United States)

    Telfer, Scott; Erdemir, Ahmet; Woodburn, James; Cavanagh, Peter R

    2016-01-25

    Integration of patient-specific biomechanical measurements into the design of therapeutic footwear has been shown to improve clinical outcomes in patients with diabetic foot disease. The addition of numerical simulations intended to optimise intervention design may help to build on these advances, however at present the time and labour required to generate and run personalised models of foot anatomy restrict their routine clinical utility. In this study we developed second-generation personalised simple finite element (FE) models of the forefoot with varying geometric fidelities. Plantar pressure predictions from barefoot, shod, and shod with insole simulations using simplified models were compared to those obtained from CT-based FE models incorporating more detailed representations of bone and tissue geometry. A simplified model including representations of metatarsals based on simple geometric shapes, embedded within a contoured soft tissue block with outer geometry acquired from a 3D surface scan was found to provide pressure predictions closest to the more complex model, with mean differences of 13.3kPa (SD 13.4), 12.52kPa (SD 11.9) and 9.6kPa (SD 9.3) for barefoot, shod, and insole conditions respectively. The simplified model design could be produced in 3h in the case of the more detailed model, and solved on average 24% faster. FE models of the forefoot based on simplified geometric representations of the metatarsal bones and soft tissue surface geometry from 3D surface scans may potentially provide a simulation approach with improved clinical utility, however further validity testing around a range of therapeutic footwear types is required.

  13. Predicting accurate fluorescent spectra for high molecular weight polycyclic aromatic hydrocarbons using density functional theory

    Science.gov (United States)

    Powell, Jacob; Heider, Emily C.; Campiglia, Andres; Harper, James K.

    2016-10-01

    The ability of density functional theory (DFT) methods to predict accurate fluorescence spectra for polycyclic aromatic hydrocarbons (PAHs) is explored. Two methods, PBE0 and CAM-B3LYP, are evaluated both in the gas phase and in solution. Spectra for several of the most toxic PAHs are predicted and compared to experiment, including three isomers of C24H14 and a PAH containing heteroatoms. Unusually high-resolution experimental spectra are obtained for comparison by analyzing each PAH at 4.2 K in an n-alkane matrix. All theoretical spectra visually conform to the profiles of the experimental data but are systematically offset by a small amount. Specifically, when solvent is included the PBE0 functional overestimates peaks by 16.1 ± 6.6 nm while CAM-B3LYP underestimates the same transitions by 14.5 ± 7.6 nm. These calculated spectra can be empirically corrected to decrease the uncertainties to 6.5 ± 5.1 and 5.7 ± 5.1 nm for the PBE0 and CAM-B3LYP methods, respectively. A comparison of computed spectra in the gas phase indicates that the inclusion of n-octane shifts peaks by +11 nm on average and this change is roughly equivalent for PBE0 and CAM-B3LYP. An automated approach for comparing spectra is also described that minimizes residuals between a given theoretical spectrum and all available experimental spectra. This approach identifies the correct spectrum in all cases and excludes approximately 80% of the incorrect spectra, demonstrating that an automated search of theoretical libraries of spectra may eventually become feasible.

  14. Towards accurate cosmological predictions for rapidly oscillating scalar fields as dark matter

    CERN Document Server

    Ureña-López, L Arturo

    2015-01-01

    As we are entering the era of precision cosmology, it is necessary to count on accurate cosmological predictions from any proposed model of dark matter. In this paper we present a novel approach to the cosmological evolution of scalar fields that eases their analytic and numerical analysis at the background and at the linear order of perturbations. We apply the method to a scalar field endowed with a quadratic potential and revisit its properties as dark matter. Some of the results known in the literature are recovered, and a better understanding of the physical properties of the model is provided. It is shown that the Jeans wavenumber defined as $k_J = a \\sqrt{mH}$ is directly related to the suppression of linear perturbations at wavenumbers $k>k_J$. We also discuss some semi-analytical results that are well satisfied by the full numerical solutions obtained from an amended version of the CMB code CLASS. Finally we draw some of the implications that this new treatment of the equations of motion may have in t...

  15. Cluster abundance in chameleon $f(R)$ gravity I: toward an accurate halo mass function prediction

    CERN Document Server

    Cataneo, Matteo; Lombriser, Lucas; Li, Baojiu

    2016-01-01

    We refine the mass and environment dependent spherical collapse model of chameleon $f(R)$ gravity by calibrating a phenomenological correction inspired by the parameterized post-Friedmann framework against high-resolution $N$-body simulations. We employ our method to predict the corresponding modified halo mass function, and provide fitting formulas to calculate the fractional enhancement of the $f(R)$ halo abundance with respect to that of General Relativity (GR) within a precision of $\\lesssim 5\\%$ from the results obtained in the simulations. Similar accuracy can be achieved for the full $f(R)$ mass function on the condition that the modeling of the reference GR abundance of halos is accurate at the percent level. We use our fits to forecast constraints on the additional scalar degree of freedom of the theory, finding that upper bounds competitive with current Solar System tests are within reach of cluster number count analyses from ongoing and upcoming surveys at much larger scales. Importantly, the flexi...

  16. Accurate prediction of band gaps and optical properties of HfO2

    Science.gov (United States)

    Ondračka, Pavel; Holec, David; Nečas, David; Zajíčková, Lenka

    2016-10-01

    We report on optical properties of various polymorphs of hafnia predicted within the framework of density functional theory. The full potential linearised augmented plane wave method was employed together with the Tran-Blaha modified Becke-Johnson potential (TB-mBJ) for exchange and local density approximation for correlation. Unit cells of monoclinic, cubic and tetragonal crystalline, and a simulated annealing-based model of amorphous hafnia were fully relaxed with respect to internal positions and lattice parameters. Electronic structures and band gaps for monoclinic, cubic, tetragonal and amorphous hafnia were calculated using three different TB-mBJ parametrisations and the results were critically compared with the available experimental and theoretical reports. Conceptual differences between a straightforward comparison of experimental measurements to a calculated band gap on the one hand and to a whole electronic structure (density of electronic states) on the other hand, were pointed out, suggesting the latter should be used whenever possible. Finally, dielectric functions were calculated at two levels, using the random phase approximation without local field effects and with a more accurate Bethe-Salpether equation (BSE) to account for excitonic effects. We conclude that a satisfactory agreement with experimental data for HfO2 was obtained only in the latter case.

  17. Accurate and Simplified Prediction of AVF for Delay and Energy Efficient Cache Design

    Institute of Scientific and Technical Information of China (English)

    An-Guo Ma; Yu Cheng; Zuo-Cheng Xing

    2011-01-01

    With continuous technology scaling, on-chip structures are becoming more and more susceptible to soft errors. Architectural vulnerability factor (AVF) has been introduced to quantify the architectural vulnerability of on-chip structures to soft errors. Recent studies have found that designing soft error protection techniques with the awareness of AVF is greatly helpful to achieve a tradeoff between performance and reliability for several structures (i.e., issue queue, reorder buffer). Cache is one of the most susceptible components to soft errors and is commonly protected with error correcting codes (ECC). However, protecting caches closer to the processor (i.e., L1 data cache (L1D)) using ECC could result in high overhead. Protecting caches without accurate knowledge of the vulnerability characteristics may lead to over-protection. Therefore, designing AVF-aware ECC is attractive for designers to balance among performance, power and reliability for cache, especially at early design stage. In this paper, we improve the methodology of cache AVF computation and develop a new AVF estimation framework, soft error reliability analysis based on SimpleScalar. Then we characterize dynamic vulnerability behavior of L1D and detect the correlations between LID AVF and various performance metrics. We propose to employ Bayesian additive regression trees to accurately model the variation of L1D AVF and to quantitatively explain the important effects of several key performance metrics on L1D AVF. Then, we employ bump hunting technique to reduce the complexity of L1D AVF prediction and extract some simple selecting rules based on several key performance metrics, thus enabling a simplified and fast estimation of L1D AVF. Based on the simplified and fast estimation of L1D AVF, intervals of high L1D AVF can be identified online, enabling us to develop the AVF-aware ECC technique to reduce the overhead of ECC. Experimental results show that compared with traditional ECC technique

  18. Cytokines and signaling molecules predict clinical outcomes in sepsis.

    Directory of Open Access Journals (Sweden)

    Christopher D Fjell

    Full Text Available INTRODUCTION: Inflammatory response during sepsis is incompletely understood due to small sample sizes and variable timing of measurements following the onset of symptoms. The vasopressin in septic shock trial (VASST compared the addition of vasopressin to norepinephrine alone in patients with septic shock. During this study plasma was collected and 39 cytokines measured in a 363 patients at both baseline (before treatment and 24 hours. Clinical features relating to both underlying health and the acute organ dysfunction induced by the severe infection were collected during the first 28 days of admission. HYPOTHESIS: Cluster analysis of cytokines identifies subgroups of patients at differing risk of death and organ failure. METHODS: Circulating cytokines and other signaling molecules were measured using a Luminex multi-bead analyte detection system. Hierarchical clustering was performed on plasma values to create patient subgroups. Enrichment analysis identified clinical outcomes significantly different according to these chemically defined patient subgroups. Logistic regression was performed to assess the importance of cytokines for predicting patient subgroups. RESULTS: Plasma levels at baseline produced three subgroups of patients, while 24 hour levels produced two subgroups. Using baseline cytokine data, one subgroup of 47 patients showed a high level of enrichment for severe septic shock, coagulopathy, renal failure, and risk of death. Using data at 24 hours, a larger subgroup of 81 patients that largely encompassed the 47 baseline subgroup patients had a similar enrichment profile. Measurement of two cytokines, IL2 and CSF2 and their product were sufficient to classify patients into these subgroups that defined clinical risks. CONCLUSIONS: A distinct pattern of cytokine levels measured early in the course of sepsis predicts disease outcome. Subpopulations of patients have differing clinical outcomes that can be predicted accurately from

  19. ACE-I Angioedema: Accurate Clinical Diagnosis May Prevent Epinephrine-Induced Harm

    Directory of Open Access Journals (Sweden)

    R. Mason Curtis

    2016-06-01

    Full Text Available Introduction: Upper airway angioedema is a life-threatening emergency department (ED presentation with increasing incidence. Angiotensin-converting enzyme inhibitor induced angioedema (AAE is a non-mast cell mediated etiology of angioedema. Accurate diagnosis by clinical examination can optimize patient management and reduce morbidity from inappropriate treatment with epinephrine. The aim of this study is to describe the incidence of angioedema subtypes and the management of AAE. We evaluate the appropriateness of treatments and highlight preventable iatrogenic morbidity. Methods: We conducted a retrospective chart review of consecutive angioedema patients presenting to two tertiary care EDs between July 2007 and March 2012. Results: Of 1,702 medical records screened, 527 were included. The cause of angioedema was identified in 48.8% (n=257 of cases. The most common identifiable etiology was AAE (33.1%, n=85, with a 60.0% male predominance. The most common AAE management strategies included diphenhydramine (63.5%, n=54, corticosteroids (50.6%, n=43 and ranitidine (31.8%, n=27. Epinephrine was administered in 21.2% (n=18 of AAE patients, five of whom received repeated doses. Four AAE patients required admission (4.7% and one required endotracheal intubation. Epinephrine induced morbidity in two patients, causing myocardial ischemia or dysrhythmia shortly after administration. Conclusion: AAE is the most common identifiable etiology of angioedema and can be accurately diagnosed by physical examination. It is easily confused with anaphylaxis and mismanaged with antihistamines, corticosteroids and epinephrine. There is little physiologic rationale for epinephrine use in AAE and much risk. Improved clinical differentiation of mast cell and non-mast cell mediated angioedema can optimize patient management.

  20. How accurately can subject-specific finite element models predict strains and strength of human femora? Investigation using full-field measurements.

    Science.gov (United States)

    Grassi, Lorenzo; Väänänen, Sami P; Ristinmaa, Matti; Jurvelin, Jukka S; Isaksson, Hanna

    2016-03-21

    Subject-specific finite element models have been proposed as a tool to improve fracture risk assessment in individuals. A thorough laboratory validation against experimental data is required before introducing such models in clinical practice. Results from digital image correlation can provide full-field strain distribution over the specimen surface during in vitro test, instead of at a few pre-defined locations as with strain gauges. The aim of this study was to validate finite element models of human femora against experimental data from three cadaver femora, both in terms of femoral strength and of the full-field strain distribution collected with digital image correlation. The results showed a high accuracy between predicted and measured principal strains (R(2)=0.93, RMSE=10%, 1600 validated data points per specimen). Femoral strength was predicted using a rate dependent material model with specific strain limit values for yield and failure. This provided an accurate prediction (strain accuracy was comparable to that obtained in state-of-the-art studies which validated their prediction accuracy against 10-16 strain gauge measurements. Fracture force was accurately predicted, with the predicted failure location being very close to the experimental fracture rim. Despite the low sample size and the single loading condition tested, the present combined numerical-experimental method showed that finite element models can predict femoral strength by providing a thorough description of the local bone mechanical response. PMID:26944687

  1. Clinical predictive factors of pathologic tumor response

    Energy Technology Data Exchange (ETDEWEB)

    Choi, Chi Hwan; Kim, Won Dong; Lee, Sang Jeon; Park, Woo Yoon [Chungbuk National University College of Medicine, Cheongju (Korea, Republic of)

    2012-09-15

    The aim of this study was to identify clinical predictive factors for tumor response after preoperative chemoradiotherapy (CRT) in rectal cancer. The study involved 51 patients who underwent preoperative CRT followed by surgery between January 2005 and February 2012. Radiotherapy was delivered to the whole pelvis at a dose of 45 Gy in 25 fractions, followed by a boost of 5.4 Gy in 3 fractions to the primary tumor with 5 fractions per week. Three different chemotherapy regimens were used. Tumor responses to preoperative CRT were assessed in terms of tumor downstaging and pathologic complete response (ypCR). Statistical analyses were performed to identify clinical factors associated with pathologic tumor response. Tumor downstaging was observed in 28 patients (54.9%), whereas ypCR was observed in 6 patients (11.8%). Multivariate analysis found that predictors of downstaging was pretreatment relative lymphocyte count (p = 0.023) and that none of clinical factors was significantly associated with ypCR. Pretreatment relative lymphocyte count (%) has a significant impact on the pathologic tumor response (tumor downstaging) after preoperative CRT for locally advanced rectal cancer. Enhancement of lymphocyte-mediated immune reactions may improve the effect of preoperative CRT for rectal cancer.

  2. Comparison of statistical and clinical predictions of functional outcome after ischemic stroke.

    Directory of Open Access Journals (Sweden)

    Douglas D Thompson

    Full Text Available To determine whether the predictions of functional outcome after ischemic stroke made at the bedside using a doctor's clinical experience were more or less accurate than the predictions made by clinical prediction models (CPMs.A prospective cohort study of nine hundred and thirty one ischemic stroke patients recruited consecutively at the outpatient, inpatient and emergency departments of the Western General Hospital, Edinburgh between 2002 and 2005. Doctors made informal predictions of six month functional outcome on the Oxford Handicap Scale (OHS. Patients were followed up at six months with a validated postal questionnaire. For each patient we calculated the absolute predicted risk of death or dependence (OHS≥3 using five previously described CPMs. The specificity of a doctor's informal predictions of OHS≥3 at six months was good 0.96 (95% CI: 0.94 to 0.97 and similar to CPMs (range 0.94 to 0.96; however the sensitivity of both informal clinical predictions 0.44 (95% CI: 0.39 to 0.49 and clinical prediction models (range 0.38 to 0.45 was poor. The prediction of the level of disability after stroke was similar for informal clinical predictions (ordinal c-statistic 0.74 with 95% CI 0.72 to 0.76 and CPMs (range 0.69 to 0.75. No patient or clinician characteristic affected the accuracy of informal predictions, though predictions were more accurate in outpatients.CPMs are at least as good as informal clinical predictions in discriminating between good and bad functional outcome after ischemic stroke. The place of these models in clinical practice has yet to be determined.

  3. Clinical and MRI models predicting amyloid deposition in progressive aphasia and apraxia of speech

    Directory of Open Access Journals (Sweden)

    Jennifer L. Whitwell

    2016-01-01

    Full Text Available Beta-amyloid (Aβ deposition can be observed in primary progressive aphasia (PPA and progressive apraxia of speech (PAOS. While it is typically associated with logopenic PPA, there are exceptions that make predicting Aβ status challenging based on clinical diagnosis alone. We aimed to determine whether MRI regional volumes or clinical data could help predict Aβ deposition. One hundred and thirty-nine PPA (n = 97; 15 agrammatic, 53 logopenic, 13 semantic and 16 unclassified and PAOS (n = 42 subjects were prospectively recruited into a cross-sectional study and underwent speech/language assessments, 3.0 T MRI and C11-Pittsburgh Compound B PET. The presence of Aβ was determined using a 1.5 SUVR cut-point. Atlas-based parcellation was used to calculate gray matter volumes of 42 regions-of-interest across the brain. Penalized binary logistic regression was utilized to determine what combination of MRI regions, and what combination of speech and language tests, best predicts Aβ (+ status. The optimal MRI model and optimal clinical model both performed comparably in their ability to accurately classify subjects according to Aβ status. MRI accurately classified 81% of subjects using 14 regions. Small left superior temporal and inferior parietal volumes and large left Broca's area volumes were particularly predictive of Aβ (+ status. Clinical scores accurately classified 83% of subjects using 12 tests. Phonological errors and repetition deficits, and absence of agrammatism and motor speech deficits were particularly predictive of Aβ (+ status. In comparison, clinical diagnosis was able to accurately classify 89% of subjects. However, the MRI model performed well in predicting Aβ deposition in unclassified PPA. Clinical diagnosis provides optimum prediction of Aβ status at the group level, although regional MRI measurements and speech and language testing also performed well and could have advantages in predicting Aβ status in unclassified

  4. Clinical and MRI models predicting amyloid deposition in progressive aphasia and apraxia of speech.

    Science.gov (United States)

    Whitwell, Jennifer L; Weigand, Stephen D; Duffy, Joseph R; Strand, Edythe A; Machulda, Mary M; Senjem, Matthew L; Gunter, Jeffrey L; Lowe, Val J; Jack, Clifford R; Josephs, Keith A

    2016-01-01

    Beta-amyloid (Aβ) deposition can be observed in primary progressive aphasia (PPA) and progressive apraxia of speech (PAOS). While it is typically associated with logopenic PPA, there are exceptions that make predicting Aβ status challenging based on clinical diagnosis alone. We aimed to determine whether MRI regional volumes or clinical data could help predict Aβ deposition. One hundred and thirty-nine PPA (n = 97; 15 agrammatic, 53 logopenic, 13 semantic and 16 unclassified) and PAOS (n = 42) subjects were prospectively recruited into a cross-sectional study and underwent speech/language assessments, 3.0 T MRI and C11-Pittsburgh Compound B PET. The presence of Aβ was determined using a 1.5 SUVR cut-point. Atlas-based parcellation was used to calculate gray matter volumes of 42 regions-of-interest across the brain. Penalized binary logistic regression was utilized to determine what combination of MRI regions, and what combination of speech and language tests, best predicts Aβ (+) status. The optimal MRI model and optimal clinical model both performed comparably in their ability to accurately classify subjects according to Aβ status. MRI accurately classified 81% of subjects using 14 regions. Small left superior temporal and inferior parietal volumes and large left Broca's area volumes were particularly predictive of Aβ (+) status. Clinical scores accurately classified 83% of subjects using 12 tests. Phonological errors and repetition deficits, and absence of agrammatism and motor speech deficits were particularly predictive of Aβ (+) status. In comparison, clinical diagnosis was able to accurately classify 89% of subjects. However, the MRI model performed well in predicting Aβ deposition in unclassified PPA. Clinical diagnosis provides optimum prediction of Aβ status at the group level, although regional MRI measurements and speech and language testing also performed well and could have advantages in predicting Aβ status in unclassified PPA subjects

  5. Accurate wavelength prediction of photonic crystal resonant reflection and applications in refractive index measurement

    DEFF Research Database (Denmark)

    Hermannsson, Pétur Gordon; Vannahme, Christoph; Smith, Cameron L. C.;

    2014-01-01

    In the past decade, photonic crystal resonant reflectors have been increasingly used as the basis for label-free biochemical assays in lab-on-a-chip applications. In both designing and interpreting experimental results, an accurate model describing the optical behavior of such structures is essen......In the past decade, photonic crystal resonant reflectors have been increasingly used as the basis for label-free biochemical assays in lab-on-a-chip applications. In both designing and interpreting experimental results, an accurate model describing the optical behavior of such structures...

  6. Towards more accurate wind and solar power prediction by improving NWP model physics

    Science.gov (United States)

    Steiner, Andrea; Köhler, Carmen; von Schumann, Jonas; Ritter, Bodo

    2014-05-01

    The growing importance and successive expansion of renewable energies raise new challenges for decision makers, economists, transmission system operators, scientists and many more. In this interdisciplinary field, the role of Numerical Weather Prediction (NWP) is to reduce the errors and provide an a priori estimate of remaining uncertainties associated with the large share of weather-dependent power sources. For this purpose it is essential to optimize NWP model forecasts with respect to those prognostic variables which are relevant for wind and solar power plants. An improved weather forecast serves as the basis for a sophisticated power forecasts. Consequently, a well-timed energy trading on the stock market, and electrical grid stability can be maintained. The German Weather Service (DWD) currently is involved with two projects concerning research in the field of renewable energy, namely ORKA*) and EWeLiNE**). Whereas the latter is in collaboration with the Fraunhofer Institute (IWES), the project ORKA is led by energy & meteo systems (emsys). Both cooperate with German transmission system operators. The goal of the projects is to improve wind and photovoltaic (PV) power forecasts by combining optimized NWP and enhanced power forecast models. In this context, the German Weather Service aims to improve its model system, including the ensemble forecasting system, by working on data assimilation, model physics and statistical post processing. This presentation is focused on the identification of critical weather situations and the associated errors in the German regional NWP model COSMO-DE. First steps leading to improved physical parameterization schemes within the NWP-model are presented. Wind mast measurements reaching up to 200 m height above ground are used for the estimation of the (NWP) wind forecast error at heights relevant for wind energy plants. One particular problem is the daily cycle in wind speed. The transition from stable stratification during

  7. The development and verification of a highly accurate collision prediction model for automated noncoplanar plan delivery

    Energy Technology Data Exchange (ETDEWEB)

    Yu, Victoria Y.; Tran, Angelia; Nguyen, Dan; Cao, Minsong; Ruan, Dan; Low, Daniel A.; Sheng, Ke, E-mail: ksheng@mednet.ucla.edu [Department of Radiation Oncology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California 90024 (United States)

    2015-11-15

    attributed to phantom setup errors due to the slightly deformable and flexible phantom extremities. The estimated site-specific safety buffer distance with 0.001% probability of collision for (gantry-to-couch, gantry-to-phantom) was (1.23 cm, 3.35 cm), (1.01 cm, 3.99 cm), and (2.19 cm, 5.73 cm) for treatment to the head, lung, and prostate, respectively. Automated delivery to all three treatment sites was completed in 15 min and collision free using a digital Linac. Conclusions: An individualized collision prediction model for the purpose of noncoplanar beam delivery was developed and verified. With the model, the study has demonstrated the feasibility of predicting deliverable beams for an individual patient and then guiding fully automated noncoplanar treatment delivery. This work motivates development of clinical workflows and quality assurance procedures to allow more extensive use and automation of noncoplanar beam geometries.

  8. A simple accurate method to predict time of ponding under variable intensity rainfall

    Science.gov (United States)

    Assouline, S.; Selker, J. S.; Parlange, J.-Y.

    2007-03-01

    The prediction of the time to ponding following commencement of rainfall is fundamental to hydrologic prediction of flood, erosion, and infiltration. Most of the studies to date have focused on prediction of ponding resulting from simple rainfall patterns. This approach was suitable to rainfall reported as average values over intervals of up to a day but does not take advantage of knowledge of the complex patterns of actual rainfall now commonly recorded electronically. A straightforward approach to include the instantaneous rainfall record in the prediction of ponding time and excess rainfall using only the infiltration capacity curve is presented. This method is tested against a numerical solution of the Richards equation on the basis of an actual rainfall record. The predicted time to ponding showed mean error ≤7% for a broad range of soils, with and without surface sealing. In contrast, the standard predictions had average errors of 87%, and worst-case errors exceeding a factor of 10. In addition to errors intrinsic in the modeling framework itself, errors that arise from averaging actual rainfall records over reporting intervals were evaluated. Averaging actual rainfall records observed in Israel over periods of as little as 5 min significantly reduced predicted runoff (75% for the sealed sandy loam and 46% for the silty clay loam), while hourly averaging gave complete lack of prediction of ponding in some of the cases.

  9. Combining Evolutionary Information and an Iterative Sampling Strategy for Accurate Protein Structure Prediction.

    Directory of Open Access Journals (Sweden)

    Tatjana Braun

    2015-12-01

    Full Text Available Recent work has shown that the accuracy of ab initio structure prediction can be significantly improved by integrating evolutionary information in form of intra-protein residue-residue contacts. Following this seminal result, much effort is put into the improvement of contact predictions. However, there is also a substantial need to develop structure prediction protocols tailored to the type of restraints gained by contact predictions. Here, we present a structure prediction protocol that combines evolutionary information with the resolution-adapted structural recombination approach of Rosetta, called RASREC. Compared to the classic Rosetta ab initio protocol, RASREC achieves improved sampling, better convergence and higher robustness against incorrect distance restraints, making it the ideal sampling strategy for the stated problem. To demonstrate the accuracy of our protocol, we tested the approach on a diverse set of 28 globular proteins. Our method is able to converge for 26 out of the 28 targets and improves the average TM-score of the entire benchmark set from 0.55 to 0.72 when compared to the top ranked models obtained by the EVFold web server using identical contact predictions. Using a smaller benchmark, we furthermore show that the prediction accuracy of our method is only slightly reduced when the contact prediction accuracy is comparatively low. This observation is of special interest for protein sequences that only have a limited number of homologs.

  10. The admixed population structure in Danish Jersey dairy cattle challenges accurate genomic predictions

    DEFF Research Database (Denmark)

    Thomasen, Jørn Rind; Sørensen, Anders Christian; Su, Guosheng;

    2013-01-01

    of Danish or US origin. Furthermore, it is investigated whether a model explicitly incorporating breed origin of animals, inferred either through the known pedigree or from SNP marker data, leads to improved genomic predictions compared to a model ignoring breed origin. The study of the population structure...... incorporated 1,730 genotyped Jersey animals. In total 39,542 SNP markers were included in the analysis. The 1,079 genotyped bulls with de-regressed proof for udder health were used in the analysis for the predictions of the genomic breeding values. A range of random regressions models that included the breed...... prediction models showed that including population structure in a random regression prediction model, did not clearly improve the reliabilities of the genomic predictions compared to a basic genomic model...

  11. A machine learning approach to the accurate prediction of multi-leaf collimator positional errors

    Science.gov (United States)

    Carlson, Joel N. K.; Park, Jong Min; Park, So-Yeon; In Park, Jong; Choi, Yunseok; Ye, Sung-Joon

    2016-03-01

    Discrepancies between planned and delivered movements of multi-leaf collimators (MLCs) are an important source of errors in dose distributions during radiotherapy. In this work we used machine learning techniques to train models to predict these discrepancies, assessed the accuracy of the model predictions, and examined the impact these errors have on quality assurance (QA) procedures and dosimetry. Predictive leaf motion parameters for the models were calculated from the plan files, such as leaf position and velocity, whether the leaf was moving towards or away from the isocenter of the MLC, and many others. Differences in positions between synchronized DICOM-RT planning files and DynaLog files reported during QA delivery were used as a target response for training of the models. The final model is capable of predicting MLC positions during delivery to a high degree of accuracy. For moving MLC leaves, predicted positions were shown to be significantly closer to delivered positions than were planned positions. By incorporating predicted positions into dose calculations in the TPS, increases were shown in gamma passing rates against measured dose distributions recorded during QA delivery. For instance, head and neck plans with 1%/2 mm gamma criteria had an average increase in passing rate of 4.17% (SD  =  1.54%). This indicates that the inclusion of predictions during dose calculation leads to a more realistic representation of plan delivery. To assess impact on the patient, dose volumetric histograms (DVH) using delivered positions were calculated for comparison with planned and predicted DVHs. In all cases, predicted dose volumetric parameters were in closer agreement to the delivered parameters than were the planned parameters, particularly for organs at risk on the periphery of the treatment area. By incorporating the predicted positions into the TPS, the treatment planner is given a more realistic view of the dose distribution as it will truly be

  12. An Integrative Pathway-based Clinical-genomic Model for Cancer Survival Prediction.

    Science.gov (United States)

    Chen, Xi; Wang, Lily; Ishwaran, Hemant

    2010-09-01

    Prediction models that use gene expression levels are now being proposed for personalized treatment of cancer, but building accurate models that are easy to interpret remains a challenge. In this paper, we describe an integrative clinical-genomic approach that combines both genomic pathway and clinical information. First, we summarize information from genes in each pathway using Supervised Principal Components (SPCA) to obtain pathway-based genomic predictors. Next, we build a prediction model based on clinical variables and pathway-based genomic predictors using Random Survival Forests (RSF). Our rationale for this two-stage procedure is that the underlying disease process may be influenced by environmental exposure (measured by clinical variables) and perturbations in different pathways (measured by pathway-based genomic variables), as well as their interactions. Using two cancer microarray datasets, we show that the pathway-based clinical-genomic model outperforms gene-based clinical-genomic models, with improved prediction accuracy and interpretability.

  13. How accurate do markets predict the outcome of an event? The Euro 2000 soccer championships experiment

    OpenAIRE

    Schmidt, Carsten; Werwatz, Axel

    2002-01-01

    For the Euro 2000 Soccer Championships an experimental asset market was condueted, with traders buying and selling contracts on the winners of individual matches. Market-generated probabilities are compared to professional bet quotas, and factors that are responsible for the quality of the market prognosis are identified. The comparison shows, that the market is more accurate than the random predictor and slightly better than professional bet quotas, in the sense of mean square error. Moreove...

  14. Accurate Prediction of the Ammonia Probes of a Variable Proton-to-Electron Mass Ratio

    CERN Document Server

    Owens, Alec; Thiel, Walter; Špirko, Vladimir

    2015-01-01

    A comprehensive study of the mass sensitivity of the vibration-rotation-inversion transitions of $^{14}$NH$_3$, $^{15}$NH$_3$, $^{14}$ND$_3$, and $^{15}$ND$_3$ is carried out variationally using the TROVE approach. Variational calculations are robust and accurate, offering a new way to compute sensitivity coefficients. Particular attention is paid to the $\\Delta k=\\pm 3$ transitions between the accidentally coinciding rotation-inversion energy levels of the $\

  15. Prognostic models and risk scores: can we accurately predict postoperative nausea and vomiting in children after craniotomy?

    Science.gov (United States)

    Neufeld, Susan M; Newburn-Cook, Christine V; Drummond, Jane E

    2008-10-01

    Postoperative nausea and vomiting (PONV) is a problem for many children after craniotomy. Prognostic models and risk scores help identify who is at risk for an adverse event such as PONV to help guide clinical care. The purpose of this article is to assess whether an existing prognostic model or risk score can predict PONV in children after craniotomy. The concepts of transportability, calibration, and discrimination are presented to identify what is required to have a valid tool for clinical use. Although previous work may inform clinical practice and guide future research, existing prognostic models and risk scores do not appear to be options for predicting PONV in children undergoing craniotomy. However, until risk factors are further delineated, followed by the development and validation of prognostic models and risk scores that include children after craniotomy, clinical judgment in the context of current research may serve as a guide for clinical care in this population. PMID:18939320

  16. Selective, accurate, and timely self-invalidation using last-touch prediction

    OpenAIRE

    Lai, An-Chow; Falsafi, Babak

    2000-01-01

    Communication in cache-coherent distributed shared memory (DSM) often requires invalidating (or writing back) cached copies of a memory block, incurring high overheads. This paper proposes Last-Touch Predictors (LTPs) that learn and predict the “last touch” to a memory block by one processor before the block is accessed and subsequently invalidated by another. By predicting a last-touch and (self-)invalidating the block in advance, an LTP hides the invalidation time, significantly reduc...

  17. Accurate microRNA target prediction correlates with protein repression levels

    Directory of Open Access Journals (Sweden)

    Simossis Victor A

    2009-09-01

    Full Text Available Abstract Background MicroRNAs are small endogenously expressed non-coding RNA molecules that regulate target gene expression through translation repression or messenger RNA degradation. MicroRNA regulation is performed through pairing of the microRNA to sites in the messenger RNA of protein coding genes. Since experimental identification of miRNA target genes poses difficulties, computational microRNA target prediction is one of the key means in deciphering the role of microRNAs in development and disease. Results DIANA-microT 3.0 is an algorithm for microRNA target prediction which is based on several parameters calculated individually for each microRNA and combines conserved and non-conserved microRNA recognition elements into a final prediction score, which correlates with protein production fold change. Specifically, for each predicted interaction the program reports a signal to noise ratio and a precision score which can be used as an indication of the false positive rate of the prediction. Conclusion Recently, several computational target prediction programs were benchmarked based on a set of microRNA target genes identified by the pSILAC method. In this assessment DIANA-microT 3.0 was found to achieve the highest precision among the most widely used microRNA target prediction programs reaching approximately 66%. The DIANA-microT 3.0 prediction results are available online in a user friendly web server at http://www.microrna.gr/microT

  18. Sensor Data Fusion for Accurate Cloud Presence Prediction Using Dempster-Shafer Evidence Theory

    Directory of Open Access Journals (Sweden)

    Jesse S. Jin

    2010-10-01

    Full Text Available Sensor data fusion technology can be used to best extract useful information from multiple sensor observations. It has been widely applied in various applications such as target tracking, surveillance, robot navigation, signal and image processing. This paper introduces a novel data fusion approach in a multiple radiation sensor environment using Dempster-Shafer evidence theory. The methodology is used to predict cloud presence based on the inputs of radiation sensors. Different radiation data have been used for the cloud prediction. The potential application areas of the algorithm include renewable power for virtual power station where the prediction of cloud presence is the most challenging issue for its photovoltaic output. The algorithm is validated by comparing the predicted cloud presence with the corresponding sunshine occurrence data that were recorded as the benchmark. Our experiments have indicated that comparing to the approaches using individual sensors, the proposed data fusion approach can increase correct rate of cloud prediction by ten percent, and decrease unknown rate of cloud prediction by twenty three percent.

  19. Using Monte Carlo transport to accurately predict isotope production and activation analysis rates at the University of Missouri research reactor

    International Nuclear Information System (INIS)

    A detailed Monte Carlo N-Particle Transport Code (MCNP5) model of the University of Missouri research reactor (MURR) has been developed. The ability of the model to accurately predict isotope production rates was verified by comparing measured and calculated neutron- capture reaction rates for numerous isotopes. In addition to thermal (1/v) monitors, the benchmarking included a number of isotopes whose (n, γ) reaction rates are very sensitive to the epithermal portion of the neutron spectrum. Using the most recent neutron libraries (ENDF/ B-VII.0), the model was able to accurately predict the measured reaction rates in all cases. The model was then combined with ORIGEN 2.2, via MONTEBURNS 2.0, to calculate production of 99Mo from fission of low-enriched uranium foils. The model was used to investigate both annular and plate LEU foil targets in a variety of arrangements in a graphite irradiation wedge to optimize the production of 99Mo. (author)

  20. Empirical approaches to more accurately predict benthic-pelagic coupling in biogeochemical ocean models

    Science.gov (United States)

    Dale, Andy; Stolpovsky, Konstantin; Wallmann, Klaus

    2016-04-01

    The recycling and burial of biogenic material in the sea floor plays a key role in the regulation of ocean chemistry. Proper consideration of these processes in ocean biogeochemical models is becoming increasingly recognized as an important step in model validation and prediction. However, the rate of organic matter remineralization in sediments and the benthic flux of redox-sensitive elements are difficult to predict a priori. In this communication, examples of empirical benthic flux models that can be coupled to earth system models to predict sediment-water exchange in the open ocean are presented. Large uncertainties hindering further progress in this field include knowledge of the reactivity of organic carbon reaching the sediment, the importance of episodic variability in bottom water chemistry and particle rain rates (for both the deep-sea and margins) and the role of benthic fauna. How do we meet the challenge?

  1. An endometrial gene expression signature accurately predicts recurrent implantation failure after IVF

    Science.gov (United States)

    Koot, Yvonne E. M.; van Hooff, Sander R.; Boomsma, Carolien M.; van Leenen, Dik; Groot Koerkamp, Marian J. A.; Goddijn, Mariëtte; Eijkemans, Marinus J. C.; Fauser, Bart C. J. M.; Holstege, Frank C. P.; Macklon, Nick S.

    2016-01-01

    The primary limiting factor for effective IVF treatment is successful embryo implantation. Recurrent implantation failure (RIF) is a condition whereby couples fail to achieve pregnancy despite consecutive embryo transfers. Here we describe the collection of gene expression profiles from mid-luteal phase endometrial biopsies (n = 115) from women experiencing RIF and healthy controls. Using a signature discovery set (n = 81) we identify a signature containing 303 genes predictive of RIF. Independent validation in 34 samples shows that the gene signature predicts RIF with 100% positive predictive value (PPV). The strength of the RIF associated expression signature also stratifies RIF patients into distinct groups with different subsequent implantation success rates. Exploration of the expression changes suggests that RIF is primarily associated with reduced cellular proliferation. The gene signature will be of value in counselling and guiding further treatment of women who fail to conceive upon IVF and suggests new avenues for developing intervention. PMID:26797113

  2. LocARNA-P: Accurate boundary prediction and improved detection of structural RNAs

    DEFF Research Database (Denmark)

    Will, Sebastian; Joshi, Tejal; Hofacker, Ivo L.;

    2012-01-01

    from AUC 0.71 to AUC 0.87, significantly reduces the cost of successive analysis steps. The ready-to-use software tool LocARNA-P produces structure-based multiple RNA alignments with associated columnwise STARs and predicts ncRNA boundaries. We provide additional results, a web server for Loc...... on sequence and structure similarity; we refer to these structure-based alignment reliabilities as STARs. The columnwise STARs of alignments, or STAR profiles, provide a versatile tool for the manual and automatic analysis of ncRNAs. In particular, we improve the boundary prediction of the widely...

  3. Use of Feedback in Clinical Prediction

    Science.gov (United States)

    Schroeder, Harold E.

    1972-01-01

    Results indicated that predictive accuracy is greater when feedback is applied to the basis for the prediction than when applied to gut" impressions. Judges forming hypotheses were also able to learn from experience. (Author)

  4. Predicting live birth chances for women with multiple consecutive failing IVF cycles: a simple and accurate prediction for routine medical practice

    Directory of Open Access Journals (Sweden)

    Porcu Géraldine

    2013-01-01

    Full Text Available Abstract Background Women having experienced several consecutive failing IVF cycles constitute a critical and particular subset of patients, for which growing perception of irremediable failure, increasing costs and IVF treatment related risks necessitate appropriate decision making when starting or not a new cycle. Predicting chances of LB might constitute a useful tool for discussion between the patient and the clinician. Our essential objective was to dispose of a simple and accurate prediction model for use in routine medical practice. The currently available predictive models applicable to general populations cannot be considered as accurate enough for this purpose. Methods Patients with at least four consecutive Failing cycles (CFCs were selected. We constructed a predictive model of LB occurrence during the last cycle, by using a stepwise logistic regression, using all the baseline patient characteristics and intermediate stage variables during the four first cycles. Results On as set of 151 patients, we identified five determinant predictors: the number of previous cycles with at least one gestational sac (NGS, the mean number of good-quality embryos, age, male infertility (MI aetiology and basal FSH. Our model was characterized by a much higher discrimination as the existing models (C-statistics=0.76, and an excellent calibration. Conclusions Couples having experienced multiple IVF failures need precise and appropriate information to decide to resume or interrupt their fertility project. Our essential objective was to dispose of a simple and accurate prediction model to allow a routine practice use. Our model is adapted to this purpose: It is very simple, combines five easily collected variables in a short calculation; it is more accurate than existing models, with a fair discrimination and a well calibrated prediction.

  5. Safe surgery: how accurate are we at predicting intra-operative blood loss?

    LENUS (Irish Health Repository)

    2012-02-01

    Introduction Preoperative estimation of intra-operative blood loss by both anaesthetist and operating surgeon is a criterion of the World Health Organization\\'s surgical safety checklist. The checklist requires specific preoperative planning when anticipated blood loss is greater than 500 mL. The aim of this study was to assess the accuracy of surgeons and anaesthetists at predicting intra-operative blood loss. Methods A 6-week prospective study of intermediate and major operations in an academic medical centre was performed. An independent observer interviewed surgical and anaesthetic consultants and registrars, preoperatively asking each to predict expected blood loss in millilitre. Intra-operative blood loss was measured and compared with these predictions. Parameters including the use of anticoagulation and anti-platelet therapy as well as intra-operative hypothermia and hypotension were recorded. Results One hundred sixty-eight operations were included in the study, including 142 elective and 26 emergency operations. Blood loss was predicted to within 500 mL of measured blood loss in 89% of cases. Consultant surgeons tended to underestimate blood loss, doing so in 43% of all cases, while consultant anaesthetists were more likely to overestimate (60% of all operations). Twelve patients (7%) had underestimation of blood loss of more than 500 mL by both surgeon and anaesthetist. Thirty per cent (n = 6\\/20) of patients requiring transfusion of a blood product within 24 hours of surgery had blood loss underestimated by more than 500 mL by both surgeon and anaesthetist. There was no significant difference in prediction between patients on anti-platelet or anticoagulation therapy preoperatively and those not on the said therapies. Conclusion Predicted intra-operative blood loss was within 500 mL of measured blood loss in 89% of operations. In 30% of patients who ultimately receive a blood transfusion, both the surgeon and anaesthetist significantly underestimate

  6. Accurate Prediction of Phase Transitions in Compressed Sensing via a Connection to Minimax Denoising

    CERN Document Server

    Donoho, David; Montanari, Andrea

    2011-01-01

    Compressed sensing posits that, within limits, one can undersample a sparse signal and yet reconstruct it accurately. Knowing the precise limits to such undersampling is important both for theory and practice. We present a formula precisely delineating the allowable degree of of undersampling of generalized sparse objects. The formula applies to Approximate Message Passing (AMP) algorithms for compressed sensing, which are here generalized to employ denoising operators besides the traditional scalar shrinkers (soft thresholding, positive soft thresholding and capping). This paper gives several examples including scalar shrinkers not derivable from convex optimization -- the firm shrinkage nonlinearity and the minimax} nonlinearity -- and also nonscalar denoisers -- block thresholding (both block soft and block James-Stein), monotone regression, and total variation minimization. Let the variables \\epsilon = k/N and \\delta = n/N denote the generalized sparsity and undersampling fractions for sampling the k-gene...

  7. FastRNABindR: Fast and Accurate Prediction of Protein-RNA Interface Residues.

    Science.gov (United States)

    El-Manzalawy, Yasser; Abbas, Mostafa; Malluhi, Qutaibah; Honavar, Vasant

    2016-01-01

    A wide range of biological processes, including regulation of gene expression, protein synthesis, and replication and assembly of many viruses are mediated by RNA-protein interactions. However, experimental determination of the structures of protein-RNA complexes is expensive and technically challenging. Hence, a number of computational tools have been developed for predicting protein-RNA interfaces. Some of the state-of-the-art protein-RNA interface predictors rely on position-specific scoring matrix (PSSM)-based encoding of the protein sequences. The computational efforts needed for generating PSSMs severely limits the practical utility of protein-RNA interface prediction servers. In this work, we experiment with two approaches, random sampling and sequence similarity reduction, for extracting a representative reference database of protein sequences from more than 50 million protein sequences in UniRef100. Our results suggest that random sampled databases produce better PSSM profiles (in terms of the number of hits used to generate the profile and the distance of the generated profile to the corresponding profile generated using the entire UniRef100 data as well as the accuracy of the machine learning classifier trained using these profiles). Based on our results, we developed FastRNABindR, an improved version of RNABindR for predicting protein-RNA interface residues using PSSM profiles generated using 1% of the UniRef100 sequences sampled uniformly at random. To the best of our knowledge, FastRNABindR is the only protein-RNA interface residue prediction online server that requires generation of PSSM profiles for query sequences and accepts hundreds of protein sequences per submission. Our approach for determining the optimal BLAST database for a protein-RNA interface residue classification task has the potential of substantially speeding up, and hence increasing the practical utility of, other amino acid sequence based predictors of protein-protein and protein

  8. Revisiting the blind tests in crystal structure prediction: accurate energy ranking of molecular crystals.

    Science.gov (United States)

    Asmadi, Aldi; Neumann, Marcus A; Kendrick, John; Girard, Pascale; Perrin, Marc-Antoine; Leusen, Frank J J

    2009-12-24

    In the 2007 blind test of crystal structure prediction hosted by the Cambridge Crystallographic Data Centre (CCDC), a hybrid DFT/MM method correctly ranked each of the four experimental structures as having the lowest lattice energy of all the crystal structures predicted for each molecule. The work presented here further validates this hybrid method by optimizing the crystal structures (experimental and submitted) of the first three CCDC blind tests held in 1999, 2001, and 2004. Except for the crystal structures of compound IX, all structures were reminimized and ranked according to their lattice energies. The hybrid method computes the lattice energy of a crystal structure as the sum of the DFT total energy and a van der Waals (dispersion) energy correction. Considering all four blind tests, the crystal structure with the lowest lattice energy corresponds to the experimentally observed structure for 12 out of 14 molecules. Moreover, good geometrical agreement is observed between the structures determined by the hybrid method and those measured experimentally. In comparison with the correct submissions made by the blind test participants, all hybrid optimized crystal structures (apart from compound II) have the smallest calculated root mean squared deviations from the experimentally observed structures. It is predicted that a new polymorph of compound V exists under pressure.

  9. Accurate single-sequence prediction of solvent accessible surface area using local and global features.

    Science.gov (United States)

    Faraggi, Eshel; Zhou, Yaoqi; Kloczkowski, Andrzej

    2014-11-01

    We present a new approach for predicting the Accessible Surface Area (ASA) using a General Neural Network (GENN). The novelty of the new approach lies in not using residue mutation profiles generated by multiple sequence alignments as descriptive inputs. Instead we use solely sequential window information and global features such as single-residue and two-residue compositions of the chain. The resulting predictor is both highly more efficient than sequence alignment-based predictors and of comparable accuracy to them. Introduction of the global inputs significantly helps achieve this comparable accuracy. The predictor, termed ASAquick, is tested on predicting the ASA of globular proteins and found to perform similarly well for so-called easy and hard cases indicating generalizability and possible usability for de-novo protein structure prediction. The source code and a Linux executables for GENN and ASAquick are available from Research and Information Systems at http://mamiris.com, from the SPARKS Lab at http://sparks-lab.org, and from the Battelle Center for Mathematical Medicine at http://mathmed.org. PMID:25204636

  10. Accurate structure prediction of peptide–MHC complexes for identifying highly immunogenic antigens

    Energy Technology Data Exchange (ETDEWEB)

    Park, Min-Sun; Park, Sung Yong; Miller, Keith R.; Collins, Edward J.; Lee, Ha Youn

    2013-11-01

    Designing an optimal HIV-1 vaccine faces the challenge of identifying antigens that induce a broad immune capacity. One factor to control the breadth of T cell responses is the surface morphology of a peptide–MHC complex. Here, we present an in silico protocol for predicting peptide–MHC structure. A robust signature of a conformational transition was identified during all-atom molecular dynamics, which results in a model with high accuracy. A large test set was used in constructing our protocol and we went another step further using a blind test with a wild-type peptide and two highly immunogenic mutants, which predicted substantial conformational changes in both mutants. The center residues at position five of the analogs were configured to be accessible to solvent, forming a prominent surface, while the residue of the wild-type peptide was to point laterally toward the side of the binding cleft. We then experimentally determined the structures of the blind test set, using high resolution of X-ray crystallography, which verified predicted conformational changes. Our observation strongly supports a positive association of the surface morphology of a peptide–MHC complex to its immunogenicity. Our study offers the prospect of enhancing immunogenicity of vaccines by identifying MHC binding immunogens.

  11. Revisiting the blind tests in crystal structure prediction: accurate energy ranking of molecular crystals.

    Science.gov (United States)

    Asmadi, Aldi; Neumann, Marcus A; Kendrick, John; Girard, Pascale; Perrin, Marc-Antoine; Leusen, Frank J J

    2009-12-24

    In the 2007 blind test of crystal structure prediction hosted by the Cambridge Crystallographic Data Centre (CCDC), a hybrid DFT/MM method correctly ranked each of the four experimental structures as having the lowest lattice energy of all the crystal structures predicted for each molecule. The work presented here further validates this hybrid method by optimizing the crystal structures (experimental and submitted) of the first three CCDC blind tests held in 1999, 2001, and 2004. Except for the crystal structures of compound IX, all structures were reminimized and ranked according to their lattice energies. The hybrid method computes the lattice energy of a crystal structure as the sum of the DFT total energy and a van der Waals (dispersion) energy correction. Considering all four blind tests, the crystal structure with the lowest lattice energy corresponds to the experimentally observed structure for 12 out of 14 molecules. Moreover, good geometrical agreement is observed between the structures determined by the hybrid method and those measured experimentally. In comparison with the correct submissions made by the blind test participants, all hybrid optimized crystal structures (apart from compound II) have the smallest calculated root mean squared deviations from the experimentally observed structures. It is predicted that a new polymorph of compound V exists under pressure. PMID:19950907

  12. Accurate prediction of interfacial residues in two-domain proteins using evolutionary information: implications for three-dimensional modeling.

    Science.gov (United States)

    Bhaskara, Ramachandra M; Padhi, Amrita; Srinivasan, Narayanaswamy

    2014-07-01

    With the preponderance of multidomain proteins in eukaryotic genomes, it is essential to recognize the constituent domains and their functions. Often function involves communications across the domain interfaces, and the knowledge of the interacting sites is essential to our understanding of the structure-function relationship. Using evolutionary information extracted from homologous domains in at least two diverse domain architectures (single and multidomain), we predict the interface residues corresponding to domains from the two-domain proteins. We also use information from the three-dimensional structures of individual domains of two-domain proteins to train naïve Bayes classifier model to predict the interfacial residues. Our predictions are highly accurate (∼85%) and specific (∼95%) to the domain-domain interfaces. This method is specific to multidomain proteins which contain domains in at least more than one protein architectural context. Using predicted residues to constrain domain-domain interaction, rigid-body docking was able to provide us with accurate full-length protein structures with correct orientation of domains. We believe that these results can be of considerable interest toward rational protein and interaction design, apart from providing us with valuable information on the nature of interactions.

  13. Accurate prediction of interfacial residues in two-domain proteins using evolutionary information: implications for three-dimensional modeling.

    Science.gov (United States)

    Bhaskara, Ramachandra M; Padhi, Amrita; Srinivasan, Narayanaswamy

    2014-07-01

    With the preponderance of multidomain proteins in eukaryotic genomes, it is essential to recognize the constituent domains and their functions. Often function involves communications across the domain interfaces, and the knowledge of the interacting sites is essential to our understanding of the structure-function relationship. Using evolutionary information extracted from homologous domains in at least two diverse domain architectures (single and multidomain), we predict the interface residues corresponding to domains from the two-domain proteins. We also use information from the three-dimensional structures of individual domains of two-domain proteins to train naïve Bayes classifier model to predict the interfacial residues. Our predictions are highly accurate (∼85%) and specific (∼95%) to the domain-domain interfaces. This method is specific to multidomain proteins which contain domains in at least more than one protein architectural context. Using predicted residues to constrain domain-domain interaction, rigid-body docking was able to provide us with accurate full-length protein structures with correct orientation of domains. We believe that these results can be of considerable interest toward rational protein and interaction design, apart from providing us with valuable information on the nature of interactions. PMID:24375512

  14. Meta-analytic approach to the accurate prediction of secreted virulence effectors in gram-negative bacteria

    Directory of Open Access Journals (Sweden)

    Sato Yoshiharu

    2011-11-01

    Full Text Available Abstract Background Many pathogens use a type III secretion system to translocate virulence proteins (called effectors in order to adapt to the host environment. To date, many prediction tools for effector identification have been developed. However, these tools are insufficiently accurate for producing a list of putative effectors that can be applied directly for labor-intensive experimental verification. This also suggests that important features of effectors have yet to be fully characterized. Results In this study, we have constructed an accurate approach to predicting secreted virulence effectors from Gram-negative bacteria. This consists of a support vector machine-based discriminant analysis followed by a simple criteria-based filtering. The accuracy was assessed by estimating the average number of true positives in the top-20 ranking in the genome-wide screening. In the validation, 10 sets of 20 training and 20 testing examples were randomly selected from 40 known effectors of Salmonella enterica serovar Typhimurium LT2. On average, the SVM portion of our system predicted 9.7 true positives from 20 testing examples in the top-20 of the prediction. Removal of the N-terminal instability, codon adaptation index and ProtParam indices decreased the score to 7.6, 8.9 and 7.9, respectively. These discrimination features suggested that the following characteristics of effectors had been uncovered: unstable N-terminus, non-optimal codon usage, hydrophilic, and less aliphathic. The secondary filtering process represented by coexpression analysis and domain distribution analysis further refined the average true positive counts to 12.3. We further confirmed that our system can correctly predict known effectors of P. syringae DC3000, strongly indicating its feasibility. Conclusions We have successfully developed an accurate prediction system for screening effectors on a genome-wide scale. We confirmed the accuracy of our system by external validation

  15. Genomic Copy Number Variations in the Genomes of Leukocytes Predict Prostate Cancer Clinical Outcomes.

    Directory of Open Access Journals (Sweden)

    Yan P Yu

    Full Text Available Accurate prediction of prostate cancer clinical courses remains elusive. In this study, we performed whole genome copy number analysis on leukocytes of 273 prostate cancer patients using Affymetrix SNP6.0 chip. Copy number variations (CNV were found across all chromosomes of the human genome. An average of 152 CNV fragments per genome was identified in the leukocytes from prostate cancer patients. The size distributions of CNV in the genome of leukocytes were highly correlative with prostate cancer aggressiveness. A prostate cancer outcome prediction model was developed based on large size ratio of CNV from the leukocyte genomes. This prediction model generated an average prediction rate of 75.2%, with sensitivity of 77.3% and specificity of 69.0% for prostate cancer recurrence. When combined with Nomogram and the status of fusion transcripts, the average prediction rate was improved to 82.5% with sensitivity of 84.8% and specificity of 78.2%. In addition, the leukocyte prediction model was 62.6% accurate in predicting short prostate specific antigen doubling time. When combined with Gleason's grade, Nomogram and the status of fusion transcripts, the prediction model generated a correct prediction rate of 77.5% with 73.7% sensitivity and 80.1% specificity. To our knowledge, this is the first study showing that CNVs in leukocyte genomes are predictive of clinical outcomes of a human malignancy.

  16. Can magnetic resonance imaging accurately predict concordant pain provocation during provocative disc injection?

    International Nuclear Information System (INIS)

    To correlate magnetic resonance (MR) image findings with pain response by provocation discography in patients with discogenic low back pain, with an emphasis on the combination analysis of a high intensity zone (HIZ) and disc contour abnormalities. Sixty-two patients (aged 17-68 years) with axial low back pain that was likely to be disc related underwent lumbar discography (178 discs tested). The MR images were evaluated for disc degeneration, disc contour abnormalities, HIZ, and endplate abnormalities. Based on the combination of an HIZ and disc contour abnormalities, four classes were determined: (1) normal or bulging disc without HIZ; (2) normal or bulging disc with HIZ; (3) disc protrusion without HIZ; (4) disc protrusion with HIZ. These MR image findings and a new combined MR classification were analyzed in the base of concordant pain determined by discography. Disc protrusion with HIZ [sensitivity 45.5%; specificity 97.8%; positive predictive value (PPV), 87.0%] correlated significantly with concordant pain provocation (P < 0.01). A normal or bulging disc with HIZ was not associated with reproduction of pain. Disc degeneration (sensitivity 95.4%; specificity 38.8%; PPV 33.9%), disc protrusion (sensitivity 68.2%; specificity 80.6%; PPV 53.6%), and HIZ (sensitivity 56.8%; specificity 83.6%; PPV 53.2%) were not helpful in the identification of a disc with concordant pain. The proposed MR classification is useful to predict a disc with concordant pain. Disc protrusion with HIZ on MR imaging predicted positive discography in patients with discogenic low back pain. (orig.)

  17. Can magnetic resonance imaging accurately predict concordant pain provocation during provocative disc injection?

    Energy Technology Data Exchange (ETDEWEB)

    Kang, Chang Ho; Kim, Yun Hwan; Kim, Jung Hyuk; Chung, Kyoo Byung; Sung, Deuk Jae [Korea University Anam Hospital, Korea University College of Medicine, Department of Radiology, Seoul (Korea); Lee, Sang-Heon [Korea University Anam Hospital, Korea University College of Medicine, Department of Physical Medicine and Rehabilitation, Seoul (Korea); Derby, Richard [Spinal Diagnostics and Treatment Center, Daly City, CA (United States); Stanford University Medical Center, Division of Physical Medicine and Rehabilitation, Stanford, CA (United States)

    2009-09-15

    To correlate magnetic resonance (MR) image findings with pain response by provocation discography in patients with discogenic low back pain, with an emphasis on the combination analysis of a high intensity zone (HIZ) and disc contour abnormalities. Sixty-two patients (aged 17-68 years) with axial low back pain that was likely to be disc related underwent lumbar discography (178 discs tested). The MR images were evaluated for disc degeneration, disc contour abnormalities, HIZ, and endplate abnormalities. Based on the combination of an HIZ and disc contour abnormalities, four classes were determined: (1) normal or bulging disc without HIZ; (2) normal or bulging disc with HIZ; (3) disc protrusion without HIZ; (4) disc protrusion with HIZ. These MR image findings and a new combined MR classification were analyzed in the base of concordant pain determined by discography. Disc protrusion with HIZ [sensitivity 45.5%; specificity 97.8%; positive predictive value (PPV), 87.0%] correlated significantly with concordant pain provocation (P < 0.01). A normal or bulging disc with HIZ was not associated with reproduction of pain. Disc degeneration (sensitivity 95.4%; specificity 38.8%; PPV 33.9%), disc protrusion (sensitivity 68.2%; specificity 80.6%; PPV 53.6%), and HIZ (sensitivity 56.8%; specificity 83.6%; PPV 53.2%) were not helpful in the identification of a disc with concordant pain. The proposed MR classification is useful to predict a disc with concordant pain. Disc protrusion with HIZ on MR imaging predicted positive discography in patients with discogenic low back pain. (orig.)

  18. Can tritiated water-dilution space accurately predict total body water in chukar partridges

    International Nuclear Information System (INIS)

    Total body water (TBW) volumes determined from the dilution space of injected tritiated water have consistently overestimated actual water volumes (determined by desiccation to constant mass) in reptiles and mammals, but results for birds are controversial. We investigated potential errors in both the dilution method and the desiccation method in an attempt to resolve this controversy. Tritiated water dilution yielded an accurate measurement of water mass in vitro. However, in vivo, this method yielded a 4.6% overestimate of the amount of water (3.1% of live body mass) in chukar partridges, apparently largely because of loss of tritium from body water to sites of dissociable hydrogens on body solids. An additional source of overestimation (approximately 2% of body mass) was loss of tritium to the solids in blood samples during distillation of blood to obtain pure water for tritium analysis. Measuring tritium activity in plasma samples avoided this problem but required measurement of, and correction for, the dry matter content in plasma. Desiccation to constant mass by lyophilization or oven-drying also overestimated the amount of water actually in the bodies of chukar partridges by 1.4% of body mass, because these values included water adsorbed onto the outside of feathers. When desiccating defeathered carcasses, oven-drying at 70 degrees C yielded TBW values identical to those obtained from lyophilization, but TBW was overestimated (0.5% of body mass) by drying at 100 degrees C due to loss of organic substances as well as water

  19. Accurate prediction of hot spot residues through physicochemical characteristics of amino acid sequences

    KAUST Repository

    Chen, Peng

    2013-07-23

    Hot spot residues of proteins are fundamental interface residues that help proteins perform their functions. Detecting hot spots by experimental methods is costly and time-consuming. Sequential and structural information has been widely used in the computational prediction of hot spots. However, structural information is not always available. In this article, we investigated the problem of identifying hot spots using only physicochemical characteristics extracted from amino acid sequences. We first extracted 132 relatively independent physicochemical features from a set of the 544 properties in AAindex1, an amino acid index database. Each feature was utilized to train a classification model with a novel encoding schema for hot spot prediction by the IBk algorithm, an extension of the K-nearest neighbor algorithm. The combinations of the individual classifiers were explored and the classifiers that appeared frequently in the top performing combinations were selected. The hot spot predictor was built based on an ensemble of these classifiers and to work in a voting manner. Experimental results demonstrated that our method effectively exploited the feature space and allowed flexible weights of features for different queries. On the commonly used hot spot benchmark sets, our method significantly outperformed other machine learning algorithms and state-of-the-art hot spot predictors. The program is available at http://sfb.kaust.edu.sa/pages/software.aspx. © 2013 Wiley Periodicals, Inc.

  20. How Five Student Characteristics Accurately Predict For-Profit University Graduation Odds

    Directory of Open Access Journals (Sweden)

    Tim Gramling

    2013-07-01

    Full Text Available President Obama’s goal is for America to lead the world in college graduates by 2020. Although for-profit institutions have increased their output of graduates at ten times the rate of nonprofits over the past decade, Congress and the U.S. Department of Education have argued that these institutions exploit the ambitions of lower-performing students. In response, this study examined how student characteristics predicted graduation odds at a large, regionally accredited for-profit institution campus. A logistic regression predicted graduation for the full population of 2,548 undergraduate students enrolled from 2005 to 2009 with scheduled graduation by June 30, 2011. Sixteen independent predictors were identified from school records and organized in the Bean and Metzner framework. The regression model was more robust than any in the literature, with a Nagelkerke R2 of .663. Only five factors had a significant impact on log odds: (a grade point average (GPA, where higher values increased odds; (b half time enrollment, which had lower odds than full time; (c Blacks, who had higher odds than Whites; (d credits required, where fewer credits increased odds; and (e primary expected family contribution, where higher values increased odds. These findings imply that public policy will not increase college graduates by focusing on institution characteristics.

  1. Clinical prediction of 5-year survival in systemic sclerosis

    DEFF Research Database (Denmark)

    Fransen, Julie Munk; Popa-Diaconu, D; Hesselstrand, R;

    2011-01-01

    Systemic sclerosis (SSc) is associated with a significant reduction in life expectancy. A simple prognostic model to predict 5-year survival in SSc was developed in 1999 in 280 patients, but it has not been validated in other patients. The predictions of a prognostic model are usually less accurate...... in other patients, especially from other centres or countries. A study was undertaken to validate the prognostic model to predict 5-year survival in SSc in other centres throughout Europe....

  2. A novel method to predict visual field progression more accurately, using intraocular pressure measurements in glaucoma patients

    Science.gov (United States)

    Asaoka, Ryo; Fujino, Yuri; Murata, Hiroshi; Miki, Atsuya; Tanito, Masaki; Mizoue, Shiro; Mori, Kazuhiko; Suzuki, Katsuyoshi; Yamashita, Takehiro; Kashiwagi, Kenji; Shoji, Nobuyuki

    2016-01-01

    Visual field (VF) data were retrospectively obtained from 491 eyes in 317 patients with open angle glaucoma who had undergone ten VF tests (Humphrey Field Analyzer, 24-2, SITA standard). First, mean of total deviation values (mTD) in the tenth VF was predicted using standard linear regression of the first five VFs (VF1-5) through to using all nine preceding VFs (VF1-9). Then an ‘intraocular pressure (IOP)-integrated VF trend analysis’ was carried out by simply using time multiplied by IOP as the independent term in the linear regression model. Prediction errors (absolute prediction error or root mean squared error: RMSE) for predicting mTD and also point wise TD values of the tenth VF were obtained from both approaches. The mTD absolute prediction errors associated with the IOP-integrated VF trend analysis were significantly smaller than those from the standard trend analysis when VF1-6 through to VF1-8 were used (p < 0.05). The point wise RMSEs from the IOP-integrated trend analysis were significantly smaller than those from the standard trend analysis when VF1-5 through to VF1-9 were used (p < 0.05). This was especially the case when IOP was measured more frequently. Thus a significantly more accurate prediction of VF progression is possible using a simple trend analysis that incorporates IOP measurements. PMID:27562553

  3. Combining multiple regression and principal component analysis for accurate predictions for column ozone in Peninsular Malaysia

    Science.gov (United States)

    Rajab, Jasim M.; MatJafri, M. Z.; Lim, H. S.

    2013-06-01

    This study encompasses columnar ozone modelling in the peninsular Malaysia. Data of eight atmospheric parameters [air surface temperature (AST), carbon monoxide (CO), methane (CH4), water vapour (H2Ovapour), skin surface temperature (SSKT), atmosphere temperature (AT), relative humidity (RH), and mean surface pressure (MSP)] data set, retrieved from NASA's Atmospheric Infrared Sounder (AIRS), for the entire period (2003-2008) was employed to develop models to predict the value of columnar ozone (O3) in study area. The combined method, which is based on using both multiple regressions combined with principal component analysis (PCA) modelling, was used to predict columnar ozone. This combined approach was utilized to improve the prediction accuracy of columnar ozone. Separate analysis was carried out for north east monsoon (NEM) and south west monsoon (SWM) seasons. The O3 was negatively correlated with CH4, H2Ovapour, RH, and MSP, whereas it was positively correlated with CO, AST, SSKT, and AT during both the NEM and SWM season periods. Multiple regression analysis was used to fit the columnar ozone data using the atmospheric parameter's variables as predictors. A variable selection method based on high loading of varimax rotated principal components was used to acquire subsets of the predictor variables to be comprised in the linear regression model of the atmospheric parameter's variables. It was found that the increase in columnar O3 value is associated with an increase in the values of AST, SSKT, AT, and CO and with a drop in the levels of CH4, H2Ovapour, RH, and MSP. The result of fitting the best models for the columnar O3 value using eight of the independent variables gave about the same values of the R (≈0.93) and R2 (≈0.86) for both the NEM and SWM seasons. The common variables that appeared in both regression equations were SSKT, CH4 and RH, and the principal precursor of the columnar O3 value in both the NEM and SWM seasons was SSKT.

  4. nuMap:A Web Platform for Accurate Prediction of Nucleosome Positioning

    Institute of Scientific and Technical Information of China (English)

    Bader A Alharbi; Thamir H Alshammari; Nathan L Felton; Victor B Zhurkin; Feng Cui

    2014-01-01

    Nucleosome positioning is critical for gene expression and of major biological interest. The high cost of experimentally mapping nucleosomal arrangement signifies the need for computational approaches to predict nucleosome positions at high resolution. Here, we present a web-based application to fulfill this need by implementing two models, YR and W/S schemes, for the translational and rotational positioning of nucleosomes, respectively. Our methods are based on sequence-dependent anisotropic bending that dictates how DNA is wrapped around a histone octamer. This application allows users to specify a number of options such as schemes and param-eters for threading calculation and provides multiple layout formats. The nuMap is implemented in Java/Perl/MySQL and is freely available for public use at http://numap.rit.edu. The user manual, implementation notes, description of the methodology and examples are available at the site.

  5. The human skin/chick chorioallantoic membrane model accurately predicts the potency of cosmetic allergens.

    Science.gov (United States)

    Slodownik, Dan; Grinberg, Igor; Spira, Ram M; Skornik, Yehuda; Goldstein, Ronald S

    2009-04-01

    The current standard method for predicting contact allergenicity is the murine local lymph node assay (LLNA). Public objection to the use of animals in testing of cosmetics makes the development of a system that does not use sentient animals highly desirable. The chorioallantoic membrane (CAM) of the chick egg has been extensively used for the growth of normal and transformed mammalian tissues. The CAM is not innervated, and embryos are sacrificed before the development of pain perception. The aim of this study was to determine whether the sensitization phase of contact dermatitis to known cosmetic allergens can be quantified using CAM-engrafted human skin and how these results compare with published EC3 data obtained with the LLNA. We studied six common molecules used in allergen testing and quantified migration of epidermal Langerhans cells (LC) as a measure of their allergic potency. All agents with known allergic potential induced statistically significant migration of LC. The data obtained correlated well with published data for these allergens generated using the LLNA test. The human-skin CAM model therefore has great potential as an inexpensive, non-radioactive, in vivo alternative to the LLNA, which does not require the use of sentient animals. In addition, this system has the advantage of testing the allergic response of human, rather than animal skin. PMID:19054059

  6. Protein corona composition does not accurately predict hematocompatibility of colloidal gold nanoparticles.

    Science.gov (United States)

    Dobrovolskaia, Marina A; Neun, Barry W; Man, Sonny; Ye, Xiaoying; Hansen, Matthew; Patri, Anil K; Crist, Rachael M; McNeil, Scott E

    2014-10-01

    Proteins bound to nanoparticle surfaces are known to affect particle clearance by influencing immune cell uptake and distribution to the organs of the mononuclear phagocytic system. The composition of the protein corona has been described for several types of nanomaterials, but the role of the corona in nanoparticle biocompatibility is not well established. In this study we investigate the role of nanoparticle surface properties (PEGylation) and incubation times on the protein coronas of colloidal gold nanoparticles. While neither incubation time nor PEG molecular weight affected the specific proteins in the protein corona, the total amount of protein binding was governed by the molecular weight of PEG coating. Furthermore, the composition of the protein corona did not correlate with nanoparticle hematocompatibility. Specialized hematological tests should be used to deduce nanoparticle hematotoxicity. From the clinical editor: It is overall unclear how the protein corona associated with colloidal gold nanoparticles may influence hematotoxicity. This study warns that PEGylation itself may be insufficient, because composition of the protein corona does not directly correlate with nanoparticle hematocompatibility. The authors suggest that specialized hematological tests must be used to deduce nanoparticle hematotoxicity.

  7. Industrial Compositional Streamline Simulation for Efficient and Accurate Prediction of Gas Injection and WAG Processes

    Energy Technology Data Exchange (ETDEWEB)

    Margot Gerritsen

    2008-10-31

    Gas-injection processes are widely and increasingly used for enhanced oil recovery (EOR). In the United States, for example, EOR production by gas injection accounts for approximately 45% of total EOR production and has tripled since 1986. The understanding of the multiphase, multicomponent flow taking place in any displacement process is essential for successful design of gas-injection projects. Due to complex reservoir geometry, reservoir fluid properties and phase behavior, the design of accurate and efficient numerical simulations for the multiphase, multicomponent flow governing these processes is nontrivial. In this work, we developed, implemented and tested a streamline based solver for gas injection processes that is computationally very attractive: as compared to traditional Eulerian solvers in use by industry it computes solutions with a computational speed orders of magnitude higher and a comparable accuracy provided that cross-flow effects do not dominate. We contributed to the development of compositional streamline solvers in three significant ways: improvement of the overall framework allowing improved streamline coverage and partial streamline tracing, amongst others; parallelization of the streamline code, which significantly improves wall clock time; and development of new compositional solvers that can be implemented along streamlines as well as in existing Eulerian codes used by industry. We designed several novel ideas in the streamline framework. First, we developed an adaptive streamline coverage algorithm. Adding streamlines locally can reduce computational costs by concentrating computational efforts where needed, and reduce mapping errors. Adapting streamline coverage effectively controls mass balance errors that mostly result from the mapping from streamlines to pressure grid. We also introduced the concept of partial streamlines: streamlines that do not necessarily start and/or end at wells. This allows more efficient coverage and avoids

  8. High-throughput screening using patient-derived tumor xenografts to predict clinical trial drug response.

    Science.gov (United States)

    Gao, Hui; Korn, Joshua M; Ferretti, Stéphane; Monahan, John E; Wang, Youzhen; Singh, Mallika; Zhang, Chao; Schnell, Christian; Yang, Guizhi; Zhang, Yun; Balbin, O Alejandro; Barbe, Stéphanie; Cai, Hongbo; Casey, Fergal; Chatterjee, Susmita; Chiang, Derek Y; Chuai, Shannon; Cogan, Shawn M; Collins, Scott D; Dammassa, Ernesta; Ebel, Nicolas; Embry, Millicent; Green, John; Kauffmann, Audrey; Kowal, Colleen; Leary, Rebecca J; Lehar, Joseph; Liang, Ying; Loo, Alice; Lorenzana, Edward; Robert McDonald, E; McLaughlin, Margaret E; Merkin, Jason; Meyer, Ronald; Naylor, Tara L; Patawaran, Montesa; Reddy, Anupama; Röelli, Claudia; Ruddy, David A; Salangsang, Fernando; Santacroce, Francesca; Singh, Angad P; Tang, Yan; Tinetto, Walter; Tobler, Sonja; Velazquez, Roberto; Venkatesan, Kavitha; Von Arx, Fabian; Wang, Hui Qin; Wang, Zongyao; Wiesmann, Marion; Wyss, Daniel; Xu, Fiona; Bitter, Hans; Atadja, Peter; Lees, Emma; Hofmann, Francesco; Li, En; Keen, Nicholas; Cozens, Robert; Jensen, Michael Rugaard; Pryer, Nancy K; Williams, Juliet A; Sellers, William R

    2015-11-01

    Profiling candidate therapeutics with limited cancer models during preclinical development hinders predictions of clinical efficacy and identifying factors that underlie heterogeneous patient responses for patient-selection strategies. We established ∼1,000 patient-derived tumor xenograft models (PDXs) with a diverse set of driver mutations. With these PDXs, we performed in vivo compound screens using a 1 × 1 × 1 experimental design (PDX clinical trial or PCT) to assess the population responses to 62 treatments across six indications. We demonstrate both the reproducibility and the clinical translatability of this approach by identifying associations between a genotype and drug response, and established mechanisms of resistance. In addition, our results suggest that PCTs may represent a more accurate approach than cell line models for assessing the clinical potential of some therapeutic modalities. We therefore propose that this experimental paradigm could potentially improve preclinical evaluation of treatment modalities and enhance our ability to predict clinical trial responses.

  9. A Novel Fibrosis Index Comprising a Non-Cholesterol Sterol Accurately Predicts HCV-Related Liver Cirrhosis

    DEFF Research Database (Denmark)

    Ydreborg, Magdalena; Lisovskaja, Vera; Lagging, Martin;

    2014-01-01

    Diagnosis of liver cirrhosis is essential in the management of chronic hepatitis C virus (HCV) infection. Liver biopsy is invasive and thus entails a risk of complications as well as a potential risk of sampling error. Therefore, non-invasive diagnostic tools are preferential. The aim...... of the present study was to create a model for accurate prediction of liver cirrhosis based on patient characteristics and biomarkers of liver fibrosis, including a panel of non-cholesterol sterols reflecting cholesterol synthesis and absorption and secretion. We evaluated variables with potential predictive...... significance for liver fibrosis in 278 patients originally included in a multicenter phase III treatment trial for chronic HCV infection. A stepwise multivariate logistic model selection was performed with liver cirrhosis, defined as Ishak fibrosis stage 5-6, as the outcome variable. A new index, referred...

  10. A clinical prediction rule for histological chorioamnionitis in preterm newborns.

    Directory of Open Access Journals (Sweden)

    Jasper V Been

    Full Text Available BACKGROUND: Histological chorioamnionitis (HC is an intrauterine inflammatory process highly associated with preterm birth and adverse neonatal outcome. HC is often clinically silent and diagnosed postnatally by placental histology. Earlier identification could facilitate treatment individualisation to improve outcome in preterm newborns. AIM: Develop a clinical prediction rule at birth for HC and HC with fetal involvement (HCF in preterm newborns. METHODS: Clinical data and placental pathology were obtained from singleton preterm newborns (gestational age ≤ 32.0 weeks born at Erasmus UMC Rotterdam from 2001 to 2003 (derivation cohort; n = 216 or Máxima MC Veldhoven from 2009 to 2010 (validation cohort; n = 206. HC and HCF prediction rules were developed with preference for high sensitivity using clinical variables available at birth. RESULTS: HC and HCF were present in 39% and 24% in the derivation cohort and in 44% and 22% in the validation cohort, respectively. HC was predicted with 87% accuracy, yielding an area under ROC curve of 0.95 (95%CI = 0.92-0.98, a positive predictive value of 80% (95%CI = 74-84%, and a negative predictive value of 93% (95%CI = 88-96%. Corresponding figures for HCF were: accuracy 83%, area under ROC curve 0.92 (95%CI = 0.88-0.96, positive predictive value 59% (95%CI = 52-62%, and negative predictive value 97% (95%CI = 93-99%. External validation expectedly resulted in some loss of test performance, preferentially affecting positive predictive rather than negative predictive values. CONCLUSION: Using a clinical prediction rule composed of clinical variables available at birth, HC and HCF could be predicted with good test characteristics in preterm newborns. Further studies should evaluate the clinical value of these rules to guide early treatment individualisation.

  11. A cross-race effect in metamemory: Predictions of face recognition are more accurate for members of our own race.

    Science.gov (United States)

    Hourihan, Kathleen L; Benjamin, Aaron S; Liu, Xiping

    2012-09-01

    The Cross-Race Effect (CRE) in face recognition is the well-replicated finding that people are better at recognizing faces from their own race, relative to other races. The CRE reveals systematic limitations on eyewitness identification accuracy and suggests that some caution is warranted in evaluating cross-race identification. The CRE is a problem because jurors value eyewitness identification highly in verdict decisions. In the present paper, we explore how accurate people are in predicting their ability to recognize own-race and other-race faces. Caucasian and Asian participants viewed photographs of Caucasian and Asian faces, and made immediate judgments of learning during study. An old/new recognition test replicated the CRE: both groups displayed superior discriminability of own-race faces, relative to other-race faces. Importantly, relative metamnemonic accuracy was also greater for own-race faces, indicating that the accuracy of predictions about face recognition is influenced by race. This result indicates another source of concern when eliciting or evaluating eyewitness identification: people are less accurate in judging whether they will or will not recognize a face when that face is of a different race than they are. This new result suggests that a witness's claim of being likely to recognize a suspect from a lineup should be interpreted with caution when the suspect is of a different race than the witness.

  12. Accurate prediction of sour gas hydrate equilibrium dissociation conditions by using an adaptive neuro fuzzy inference system

    International Nuclear Information System (INIS)

    Highlights: ► An ANFIS model is developed for predicting sour gas hydrate dissociation conditions. ► It can be used over wide ranges of operating conditions. ► At all H2S concentrations, the developed model outperforms the thermodynamic models. ► The presented model is useful for design of industrial sour gas handling systems. - Abstract: An adaptive neuro fuzzy inference system (ANFIS) has been proposed for predicting the sour gas hydrate equilibrium dissociation conditions. The proposed model predictions have been compared with those of the available thermodynamic models at different operating conditions. It is found that at all H2S concentrations especially at the concentrations higher than 10 mol%, the developed ANFIS model outperforms the existing thermodynamic models with the average absolute deviation of 2.18%. The proposed ANFIS model can be used for accurate and reliable predictions of sour gas hydrate equilibrium conditions over wide ranges of temperatures and acid gas concentrations and is a useful tool for proper design of sour natural gas flow assurance systems and gas hydrate energy storage processes in oil and gas industries.

  13. Accurate predictions for charged Higgs production: closing the $m_{H^{\\pm}}\\sim m_t$ window

    CERN Document Server

    Degrande, Celine; Hirschi, Valentin; Ubiali, Maria; Wiesemann, Marius; Zaro, Marco

    2016-01-01

    We present predictions for the total cross section for the production of a charged Higgs boson in a generic type-II two-Higgs-doublet model in the intermediate-mass range ($m_{H^{\\pm}}\\sim m_t$) at the LHC. Results are obtained at next-to-leading order (NLO) accuracy in QCD perturbation theory, by studying the full process $pp\\to H^\\pm W^\\mp b \\bar b$ in the complex-(top)-mass scheme with massive bottom quarks. Compared to lowest-order predictions, NLO corrections have a sizable impact: they increase the cross section by roughly 50% and reduce uncertainties due to scale variations by more than a factor of two. Our computation reliably interpolates between the low- and high-mass regime. Our results provide the first NLO prediction for charged Higgs production in the intermediate-mass range and therefore allow to have NLO accurate predictions in the full $m_{H^{\\pm}}$ range.

  14. Pharmacogenetics : the science of predictive clinical pharmacology

    OpenAIRE

    Fenech, Anthony G; Grech, Godfrey

    2014-01-01

    The study of pharmacogenetics has expanded from what were initially casual family-based clinical drug response observations, to a fully-fledged science with direct therapeutic applications, all within a time-span of less than 60 years. A wide spectrum of polymorphisms, located within several genes, are now recognised to influence the pharmacokinetics and pharmacodynamics of the majority of drugs within our therapeutic armamentarium. This information forms the basis for the new development of ...

  15. Accurate prediction of unsteady and time-averaged pressure loads using a hybrid Reynolds-Averaged/large-eddy simulation technique

    Science.gov (United States)

    Bozinoski, Radoslav

    Significant research has been performed over the last several years on understanding the unsteady aerodynamics of various fluid flows. Much of this work has focused on quantifying the unsteady, three-dimensional flow field effects which have proven vital to the accurate prediction of many fluid and aerodynamic problems. Up until recently, engineers have predominantly relied on steady-state simulations to analyze the inherently three-dimensional ow structures that are prevalent in many of today's "real-world" problems. Increases in computational capacity and the development of efficient numerical methods can change this and allow for the solution of the unsteady Reynolds-Averaged Navier-Stokes (RANS) equations for practical three-dimensional aerodynamic applications. An integral part of this capability has been the performance and accuracy of the turbulence models coupled with advanced parallel computing techniques. This report begins with a brief literature survey of the role fully three-dimensional, unsteady, Navier-Stokes solvers have on the current state of numerical analysis. Next, the process of creating a baseline three-dimensional Multi-Block FLOw procedure called MBFLO3 is presented. Solutions for an inviscid circular arc bump, laminar at plate, laminar cylinder, and turbulent at plate are then presented. Results show good agreement with available experimental, numerical, and theoretical data. Scalability data for the parallel version of MBFLO3 is presented and shows efficiencies of 90% and higher for processes of no less than 100,000 computational grid points. Next, the description and implementation techniques used for several turbulence models are presented. Following the successful implementation of the URANS and DES procedures, the validation data for separated, non-reattaching flows over a NACA 0012 airfoil, wall-mounted hump, and a wing-body junction geometry are presented. Results for the NACA 0012 showed significant improvement in flow predictions

  16. Bacteremia with Streptococcus bovis and Streptococcus salivarius: clinical correlates of more accurate identification of isolates.

    Science.gov (United States)

    Ruoff, K L; Miller, S I; Garner, C V; Ferraro, M J; Calderwood, S B

    1989-01-01

    Two biotypes of Streptococcus bovis can be identified by laboratory testing and can be distinguished from the phenotypically similar organism Streptococcus salivarius. We assessed the clinical relevance of careful identification of these organisms in 68 patients with streptococcal bacteremia caused by these similar species. S. bovis was more likely to be clinically significant when isolated from blood (89%) than was S. salivarius (23%). There was a striking association between S. bovis I bacteremia and underlying endocarditis (94%) compared with that of S. bovis II bacteremia (18%). Bacteremia with S. bovis I was also highly correlated with an underlying colonic neoplasm (71% of patients overall, 100% of those with thorough colonic examinations) compared with bacteremia due to S. bovis II or S. salivarius (17% overall, 25% of patients with thorough colonic examinations). We conclude that careful identification of streptococcal bacteremic isolates as S. bovis biotype I provides clinically important information and should be more widely applied. PMID:2915024

  17. Reporting and Methods in Clinical Prediction Research: A Systematic Review

    OpenAIRE

    Bouwmeester, W; Zuithoff, NP; Mallett, S.; Geerlings, MI; Vergouwe, Y.; Steyerberg, EW; Altman, DG; Moons, KG

    2012-01-01

    Editors' Summary Background There are often times in our lives when we would like to be able to predict the future. Is the stock market going to go up, for example, or will it rain tomorrow? Being able predict future health is also important, both to patients and to physicians, and there is an increasing body of published clinicalprediction research.” Diagnostic prediction research investigates the ability of variables or test results to predict the presence or absence of a specific diagnos...

  18. Clinical Prediction Rules for Physical Therapy Interventions: A Systematic Review

    OpenAIRE

    Beneciuk, Jason M.; Bishop, Mark D; George, Steven Z.

    2009-01-01

    Background and Purpose: Clinical prediction rules (CPRs) involving physical therapy interventions have been published recently. The quality of the studies used to develop the CPRs was not previously considered, a fact that has potential implications for clinical applications and future research. The purpose of this systematic review was to determine the quality of published CPRs developed for physical therapy interventions.

  19. An approach to estimating and extrapolating model error based on inverse problem methods: towards accurate numerical weather prediction

    International Nuclear Information System (INIS)

    Model error is one of the key factors restricting the accuracy of numerical weather prediction (NWP). Considering the continuous evolution of the atmosphere, the observed data (ignoring the measurement error) can be viewed as a series of solutions of an accurate model governing the actual atmosphere. Model error is represented as an unknown term in the accurate model, thus NWP can be considered as an inverse problem to uncover the unknown error term. The inverse problem models can absorb long periods of observed data to generate model error correction procedures. They thus resolve the deficiency and faultiness of the NWP schemes employing only the initial-time data. In this study we construct two inverse problem models to estimate and extrapolate the time-varying and spatial-varying model errors in both the historical and forecast periods by using recent observations and analogue phenomena of the atmosphere. Numerical experiment on Burgers' equation has illustrated the substantial forecast improvement using inverse problem algorithms. The proposed inverse problem methods of suppressing NWP errors will be useful in future high accuracy applications of NWP. (geophysics, astronomy, and astrophysics)

  20. Predictive data mining in clinical medicine: Current issues and guidelines

    OpenAIRE

    Bellazzi, Riccado; Zupan, Blaz

    2008-01-01

    BACKGROUND: The widespread availability of new computational methods and tools for data analysis and predictive modeling requires medical informatics researchers and practitioners to systematically select the most appropriate strategy to cope with clinical prediction problems. In particular, the collection of methods known as 'data mining' offers methodological and technical solutions to deal with the analysis of medical data and construction of prediction models. A large variety of these met...

  1. A novel fibrosis index comprising a non-cholesterol sterol accurately predicts HCV-related liver cirrhosis.

    Directory of Open Access Journals (Sweden)

    Magdalena Ydreborg

    Full Text Available Diagnosis of liver cirrhosis is essential in the management of chronic hepatitis C virus (HCV infection. Liver biopsy is invasive and thus entails a risk of complications as well as a potential risk of sampling error. Therefore, non-invasive diagnostic tools are preferential. The aim of the present study was to create a model for accurate prediction of liver cirrhosis based on patient characteristics and biomarkers of liver fibrosis, including a panel of non-cholesterol sterols reflecting cholesterol synthesis and absorption and secretion. We evaluated variables with potential predictive significance for liver fibrosis in 278 patients originally included in a multicenter phase III treatment trial for chronic HCV infection. A stepwise multivariate logistic model selection was performed with liver cirrhosis, defined as Ishak fibrosis stage 5-6, as the outcome variable. A new index, referred to as Nordic Liver Index (NoLI in the paper, was based on the model: Log-odds (predicting cirrhosis = -12.17+ (age × 0.11 + (BMI (kg/m(2 × 0.23 + (D7-lathosterol (μg/100 mg cholesterol×(-0.013 + (Platelet count (x10(9/L × (-0.018 + (Prothrombin-INR × 3.69. The area under the ROC curve (AUROC for prediction of cirrhosis was 0.91 (95% CI 0.86-0.96. The index was validated in a separate cohort of 83 patients and the AUROC for this cohort was similar (0.90; 95% CI: 0.82-0.98. In conclusion, the new index may complement other methods in diagnosing cirrhosis in patients with chronic HCV infection.

  2. Survival outcomes scores (SOFT, BAR, and Pedi-SOFT) are accurate in predicting post-liver transplant survival in adolescents.

    Science.gov (United States)

    Conjeevaram Selvakumar, Praveen Kumar; Maksimak, Brian; Hanouneh, Ibrahim; Youssef, Dalia H; Lopez, Rocio; Alkhouri, Naim

    2016-09-01

    SOFT and BAR scores utilize recipient, donor, and graft factors to predict the 3-month survival after LT in adults (≥18 years). Recently, Pedi-SOFT score was developed to predict 3-month survival after LT in young children (≤12 years). These scoring systems have not been studied in adolescent patients (13-17 years). We evaluated the accuracy of these scoring systems in predicting the 3-month post-LT survival in adolescents through a retrospective analysis of data from UNOS of patients aged 13-17 years who received LT between 03/01/2002 and 12/31/2012. Recipients of combined organ transplants, donation after cardiac death, or living donor graft were excluded. A total of 711 adolescent LT recipients were included with a mean age of 15.2±1.4 years. A total of 100 patients died post-LT including 33 within 3 months. SOFT, BAR, and Pedi-SOFT scores were all found to be good predictors of 3-month post-transplant survival outcome with areas under the ROC curve of 0.81, 0.80, and 0.81, respectively. All three scores provided good accuracy for predicting 3-month survival post-LT in adolescents and may help clinical decision making to optimize survival rate and organ utilization. PMID:27478012

  3. Predicting suitable optoelectronic properties of monoclinic VON semiconductor crystals for photovoltaics using accurate first-principles computations.

    Science.gov (United States)

    Harb, Moussab

    2015-10-14

    Using accurate first-principles quantum calculations based on DFT (including the DFPT) with the range-separated hybrid HSE06 exchange-correlation functional, we can predict the essential fundamental properties (such as bandgap, optical absorption co-efficient, dielectric constant, charge carrier effective masses and exciton binding energy) of two stable monoclinic vanadium oxynitride (VON) semiconductor crystals for solar energy conversion applications. In addition to the predicted band gaps in the optimal range for making single-junction solar cells, both polymorphs exhibit a relatively high absorption efficiency in the visible range, high dielectric constant, high charge carrier mobility and much lower exciton binding energy than the thermal energy at room temperature. Moreover, their optical absorption, dielectric and exciton dissociation properties were found to be better than those obtained for semiconductors frequently utilized in photovoltaic devices such as Si, CdTe and GaAs. These novel results offer a great opportunity for this stoichiometric VON material to be properly synthesized and considered as a new good candidate for photovoltaic applications. PMID:26351755

  4. Predicting suitable optoelectronic properties of monoclinic VON semiconductor crystals for photovoltaics using accurate first-principles computations

    KAUST Repository

    Harb, Moussab

    2015-08-26

    Using accurate first-principles quantum calculations based on DFT (including the perturbation theory DFPT) with the range-separated hybrid HSE06 exchange-correlation functional, we predict essential fundamental properties (such as bandgap, optical absorption coefficient, dielectric constant, charge carrier effective masses and exciton binding energy) of two stable monoclinic vanadium oxynitride (VON) semiconductor crystals for solar energy conversion applications. In addition to the predicted band gaps in the optimal range for making single-junction solar cells, both polymorphs exhibit relatively high absorption efficiencies in the visible range, high dielectric constants, high charge carrier mobilities and much lower exciton binding energies than the thermal energy at room temperature. Moreover, their optical absorption, dielectric and exciton dissociation properties are found to be better than those obtained for semiconductors frequently utilized in photovoltaic devices like Si, CdTe and GaAs. These novel results offer a great opportunity for this stoichiometric VON material to be properly synthesized and considered as a new good candidate for photovoltaic applications.

  5. NEOCIVET: Towards accurate morphometry of neonatal gyrification and clinical applications in preterm newborns.

    Science.gov (United States)

    Kim, Hosung; Lepage, Claude; Maheshwary, Romir; Jeon, Seun; Evans, Alan C; Hess, Christopher P; Barkovich, A James; Xu, Duan

    2016-09-01

    Cerebral cortical folding becomes dramatically more complex in the fetal brain during the 3rd trimester of gestation; the process continues in a similar fashion in children who are born prematurely. To quantify this morphological development, it is necessary to extract the interface between gray matter and white matter, which is particularly challenging due to changing tissue contrast during brain maturation. We employed the well-established CIVET pipeline to extract this cortical surface, with point correspondence across subjects, using a surface-based spherical registration. We then developed a variant of the pipeline, called NEOCIVET, that quantified cortical folding using mean curvature and sulcal depth while addressing the well-known problems of poor and temporally-varying gray/white contrast as well as motion artifact in neonatal MRI. NEOCIVET includes: i) a tissue classification technique that analyzed multi-atlas texture patches using the nonlocal mean estimator and subsequently applied a label fusion approach based on a joint probability between templates, ii) neonatal template construction based on age-specific sub-groups, and iii) masking of non-interesting structures using label-fusion approaches. These techniques replaced modules that might be suboptimal for regional analysis of poor-contrast neonatal cortex. The proposed segmentation method showed more accurate results in subjects with various ages and with various degrees of motion compared to state-of-the-art methods. In the analysis of 158 preterm-born neonates, many with multiple scans (n=231; 26-40weeks postmenstrual age at scan), NEOCIVET identified increases in cortical folding over time in numerous cortical regions (mean curvature: +0.003/week; sulcal depth: +0.04mm/week) while folding did not change in major sulci that are known to develop early (corrected p<0.05). The proposed pipeline successfully mapped cortical structural development, supporting current models of cerebral morphogenesis

  6. Accurate electrical prediction of memory array through SEM-based edge-contour extraction using SPICE simulation

    Science.gov (United States)

    Shauly, Eitan; Rotstein, Israel; Peltinov, Ram; Latinski, Sergei; Adan, Ofer; Levi, Shimon; Menadeva, Ovadya

    2009-03-01

    The continues transistors scaling efforts, for smaller devices, similar (or larger) drive current/um and faster devices, increase the challenge to predict and to control the transistor off-state current. Typically, electrical simulators like SPICE, are using the design intent (as-drawn GDS data). At more sophisticated cases, the simulators are fed with the pattern after lithography and etch process simulations. As the importance of electrical simulation accuracy is increasing and leakage is becoming more dominant, there is a need to feed these simulators, with more accurate information extracted from physical on-silicon transistors. Our methodology to predict changes in device performances due to systematic lithography and etch effects was used in this paper. In general, the methodology consists on using the OPCCmaxTM for systematic Edge-Contour-Extraction (ECE) from transistors, taking along the manufacturing and includes any image distortions like line-end shortening, corner rounding and line-edge roughness. These measurements are used for SPICE modeling. Possible application of this new metrology is to provide a-head of time, physical and electrical statistical data improving time to market. In this work, we applied our methodology to analyze a small and large array's of 2.14um2 6T-SRAM, manufactured using Tower Standard Logic for General Purposes Platform. 4 out of the 6 transistors used "U-Shape AA", known to have higher variability. The predicted electrical performances of the transistors drive current and leakage current, in terms of nominal values and variability are presented. We also used the methodology to analyze an entire SRAM Block array. Study of an isolation leakage and variability are presented.

  7. Accurate Prediction of Advanced Liver Fibrosis Using the Decision Tree Learning Algorithm in Chronic Hepatitis C Egyptian Patients

    Directory of Open Access Journals (Sweden)

    Somaya Hashem

    2016-01-01

    Full Text Available Background/Aim. Respectively with the prevalence of chronic hepatitis C in the world, using noninvasive methods as an alternative method in staging chronic liver diseases for avoiding the drawbacks of biopsy is significantly increasing. The aim of this study is to combine the serum biomarkers and clinical information to develop a classification model that can predict advanced liver fibrosis. Methods. 39,567 patients with chronic hepatitis C were included and randomly divided into two separate sets. Liver fibrosis was assessed via METAVIR score; patients were categorized as mild to moderate (F0–F2 or advanced (F3-F4 fibrosis stages. Two models were developed using alternating decision tree algorithm. Model 1 uses six parameters, while model 2 uses four, which are similar to FIB-4 features except alpha-fetoprotein instead of alanine aminotransferase. Sensitivity and receiver operating characteristic curve were performed to evaluate the performance of the proposed models. Results. The best model achieved 86.2% negative predictive value and 0.78 ROC with 84.8% accuracy which is better than FIB-4. Conclusions. The risk of advanced liver fibrosis, due to chronic hepatitis C, could be predicted with high accuracy using decision tree learning algorithm that could be used to reduce the need to assess the liver biopsy.

  8. An Optimized Method for Accurate Fetal Sex Prediction and Sex Chromosome Aneuploidy Detection in Non-Invasive Prenatal Testing.

    Science.gov (United States)

    Wang, Ting; He, Quanze; Li, Haibo; Ding, Jie; Wen, Ping; Zhang, Qin; Xiang, Jingjing; Li, Qiong; Xuan, Liming; Kong, Lingyin; Mao, Yan; Zhu, Yijun; Shen, Jingjing; Liang, Bo; Li, Hong

    2016-01-01

    Massively parallel sequencing (MPS) combined with bioinformatic analysis has been widely applied to detect fetal chromosomal aneuploidies such as trisomy 21, 18, 13 and sex chromosome aneuploidies (SCAs) by sequencing cell-free fetal DNA (cffDNA) from maternal plasma, so-called non-invasive prenatal testing (NIPT). However, many technical challenges, such as dependency on correct fetal sex prediction, large variations of chromosome Y measurement and high sensitivity to random reads mapping, may result in higher false negative rate (FNR) and false positive rate (FPR) in fetal sex prediction as well as in SCAs detection. Here, we developed an optimized method to improve the accuracy of the current method by filtering out randomly mapped reads in six specific regions of the Y chromosome. The method reduces the FNR and FPR of fetal sex prediction from nearly 1% to 0.01% and 0.06%, respectively and works robustly under conditions of low fetal DNA concentration (1%) in testing and simulation of 92 samples. The optimized method was further confirmed by large scale testing (1590 samples), suggesting that it is reliable and robust enough for clinical testing.

  9. An Optimized Method for Accurate Fetal Sex Prediction and Sex Chromosome Aneuploidy Detection in Non-Invasive Prenatal Testing.

    Directory of Open Access Journals (Sweden)

    Ting Wang

    Full Text Available Massively parallel sequencing (MPS combined with bioinformatic analysis has been widely applied to detect fetal chromosomal aneuploidies such as trisomy 21, 18, 13 and sex chromosome aneuploidies (SCAs by sequencing cell-free fetal DNA (cffDNA from maternal plasma, so-called non-invasive prenatal testing (NIPT. However, many technical challenges, such as dependency on correct fetal sex prediction, large variations of chromosome Y measurement and high sensitivity to random reads mapping, may result in higher false negative rate (FNR and false positive rate (FPR in fetal sex prediction as well as in SCAs detection. Here, we developed an optimized method to improve the accuracy of the current method by filtering out randomly mapped reads in six specific regions of the Y chromosome. The method reduces the FNR and FPR of fetal sex prediction from nearly 1% to 0.01% and 0.06%, respectively and works robustly under conditions of low fetal DNA concentration (1% in testing and simulation of 92 samples. The optimized method was further confirmed by large scale testing (1590 samples, suggesting that it is reliable and robust enough for clinical testing.

  10. An Optimized Method for Accurate Fetal Sex Prediction and Sex Chromosome Aneuploidy Detection in Non-Invasive Prenatal Testing

    Science.gov (United States)

    Li, Haibo; Ding, Jie; Wen, Ping; Zhang, Qin; Xiang, Jingjing; Li, Qiong; Xuan, Liming; Kong, Lingyin; Mao, Yan; Zhu, Yijun; Shen, Jingjing; Liang, Bo; Li, Hong

    2016-01-01

    Massively parallel sequencing (MPS) combined with bioinformatic analysis has been widely applied to detect fetal chromosomal aneuploidies such as trisomy 21, 18, 13 and sex chromosome aneuploidies (SCAs) by sequencing cell-free fetal DNA (cffDNA) from maternal plasma, so-called non-invasive prenatal testing (NIPT). However, many technical challenges, such as dependency on correct fetal sex prediction, large variations of chromosome Y measurement and high sensitivity to random reads mapping, may result in higher false negative rate (FNR) and false positive rate (FPR) in fetal sex prediction as well as in SCAs detection. Here, we developed an optimized method to improve the accuracy of the current method by filtering out randomly mapped reads in six specific regions of the Y chromosome. The method reduces the FNR and FPR of fetal sex prediction from nearly 1% to 0.01% and 0.06%, respectively and works robustly under conditions of low fetal DNA concentration (1%) in testing and simulation of 92 samples. The optimized method was further confirmed by large scale testing (1590 samples), suggesting that it is reliable and robust enough for clinical testing. PMID:27441628

  11. Brain Connectivity Predicts Placebo Response across Chronic Pain Clinical Trials

    Science.gov (United States)

    Tétreault, Pascal; Mansour, Ali; Vachon-Presseau, Etienne; Schnitzer, Thomas J.; Apkarian, A. Vania

    2016-01-01

    Placebo response in the clinical trial setting is poorly understood and alleged to be driven by statistical confounds, and its biological underpinnings are questioned. Here we identified and validated that clinical placebo response is predictable from resting-state functional magnetic-resonance-imaging (fMRI) brain connectivity. This also led to discovering a brain region predicting active drug response and demonstrating the adverse effect of active drug interfering with placebo analgesia. Chronic knee osteoarthritis (OA) pain patients (n = 56) underwent pretreatment brain scans in two clinical trials. Study 1 (n = 17) was a 2-wk single-blinded placebo pill trial. Study 2 (n = 39) was a 3-mo double-blinded randomized trial comparing placebo pill to duloxetine. Study 3, which was conducted in additional knee OA pain patients (n = 42), was observational. fMRI-derived brain connectivity maps in study 1 were contrasted between placebo responders and nonresponders and compared to healthy controls (n = 20). Study 2 validated the primary biomarker and identified a brain region predicting drug response. In both studies, approximately half of the participants exhibited analgesia with placebo treatment. In study 1, right midfrontal gyrus connectivity best identified placebo responders. In study 2, the same measure identified placebo responders (95% correct) and predicted the magnitude of placebo’s effectiveness. By subtracting away linearly modeled placebo analgesia from duloxetine response, we uncovered in 6/19 participants a tendency of duloxetine enhancing predicted placebo response, while in another 6/19, we uncovered a tendency for duloxetine to diminish it. Moreover, the approach led to discovering that right parahippocampus gyrus connectivity predicts drug analgesia after correcting for modeled placebo-related analgesia. Our evidence is consistent with clinical placebo response having biological underpinnings and shows that the method can also reveal that active

  12. On-time clinical phenotype prediction based on narrative reports

    Science.gov (United States)

    Bejan, Cosmin A.; Vanderwende, Lucy; Evans, Heather L.; Wurfel, Mark M.; Yetisgen-Yildiz, Meliha

    2013-01-01

    In this paper we describe a natural language processing system which is able to predict whether or not a patient exhibits a specific phenotype using the information extracted from the narrative reports associated with the patient. Furthermore, the phenotypic annotations from our report dataset were performed at the report level which allows us to perform the prediction of the clinical phenotype at any point in time during the patient hospitalization period. Our experiments indicate that an important factor in achieving better results for this problem is to determine how much information to extract from the patient reports in the time interval between the patient admission time and the current prediction time. PMID:24551325

  13. Predicting postoperative mortality after colorectal surgery : a novel clinical model

    NARCIS (Netherlands)

    van der Sluis, F. J.; Espin, E.; Vallribera, F.; de Bock, G. H.; Hoekstra, H. J.; van Leeuwen, B. L.; Engel, A. F.

    2014-01-01

    Aim The aim of this study was to develop and externally validate a clinically, practical and discriminative prediction model designed to estimate in-hospital mortality of patients undergoing colorectal surgery. Method All consecutive patients who underwent elective or emergency colorectal surgery fr

  14. Prediction of human pharmacokinetics using physiologically based modeling: a retrospective analysis of 26 clinically tested drugs.

    Science.gov (United States)

    De Buck, Stefan S; Sinha, Vikash K; Fenu, Luca A; Nijsen, Marjoleen J; Mackie, Claire E; Gilissen, Ron A H J

    2007-10-01

    The aim of this study was to evaluate different physiologically based modeling strategies for the prediction of human pharmacokinetics. Plasma profiles after intravenous and oral dosing were simulated for 26 clinically tested drugs. Two mechanism-based predictions of human tissue-to-plasma partitioning (P(tp)) from physicochemical input (method Vd1) were evaluated for their ability to describe human volume of distribution at steady state (V(ss)). This method was compared with a strategy that combined predicted and experimentally determined in vivo rat P(tp) data (method Vd2). Best V(ss) predictions were obtained using method Vd2, providing that rat P(tp) input was corrected for interspecies differences in plasma protein binding (84% within 2-fold). V(ss) predictions from physicochemical input alone were poor (32% within 2-fold). Total body clearance (CL) was predicted as the sum of scaled rat renal clearance and hepatic clearance projected from in vitro metabolism data. Best CL predictions were obtained by disregarding both blood and microsomal or hepatocyte binding (method CL2, 74% within 2-fold), whereas strong bias was seen using both blood and microsomal or hepatocyte binding (method CL1, 53% within 2-fold). The physiologically based pharmacokinetics (PBPK) model, which combined methods Vd2 and CL2 yielded the most accurate predictions of in vivo terminal half-life (69% within 2-fold). The Gastroplus advanced compartmental absorption and transit model was used to construct an absorption-disposition model and provided accurate predictions of area under the plasma concentration-time profile, oral apparent volume of distribution, and maximum plasma concentration after oral dosing, with 74%, 70%, and 65% within 2-fold, respectively. This evaluation demonstrates that PBPK models can lead to reasonable predictions of human pharmacokinetics. PMID:17620347

  15. Predictive indices of empirical clinical diagnosis of malaria among under-five febrile children attending paediatric outpatient clinic

    Directory of Open Access Journals (Sweden)

    Hassan A Elechi

    2015-01-01

    Full Text Available Background: Malaria has remained an important public health problem in Nigeria with children under 5 years of age bearing the greatest burden. Accurate and prompt diagnosis of malaria is an important element in the fight against the scourge. Due to the several limitations of microscopy, diagnosis of malaria has continued to be made based on clinical ground against several World Health Organization (WHO recommendations. Thus, we aim to assess the performance of empirical clinical diagnosis among febrile children under 5 years of age in a busy pediatric outpatient clinic. Materials and Methods: The study was a cross-sectional study. Children aged <5 years with fever or 72 h history of fever were recruited. Children on antimalarial prophylaxis or on treatment for malaria were excluded. Relevant information was obtained from the caregiver and clinical note of the child using interviewer administered questionnaire. Two thick and two thin films were made, stained, and read for each recruited child. Data was analysed using SPSS version 16. Results: Of the 433 children studied, 98 (22.6% were empirically diagnosed as having malaria and antimalarial drug prescribed. Twenty-three (23.5% of these children were confirmed by microscopy to have malaria parasitemia, while 75 (76.5% were negative for malaria parasitemia. Empirical clinical diagnosis show poor predictive indices with sensitivity of 19.2%, specificity of 76.0%, positive predictive value of 23.5% and negative predictive value of 71%. Conclusion and Recommendations: Empirical clinical diagnosis of malaria among the under-five children with symptoms suggestive of acute malaria is highly not reliable and hence the need to strengthen parasitological diagnosis.

  16. Clinical prediction of occupational and non-specific low back pain

    Directory of Open Access Journals (Sweden)

    Ingrid Tolosa-Guzmán

    2012-09-01

    Full Text Available Non-specific Occupational Low Back Pain (NOLBP is a health condition that generates a high absenteeism and disability. Due to multifactorial causes is difficult to determine accurate diagnosis and prognosis. The clinical prediction of NOLBP is identified as a series of models that integrate a multivariate analysis to determine early diagnosis, course, and occupational impact of this health condition. Objective: to identify predictor factors of NOLBP, and the type of material referred to in the scientific evidence and establish the scopes of the prediction. Materials and method: the title search was conducted in the databases PubMed, Science Direct, and Ebsco Springer, between 1985 and 2012. The selected articles were classified through a bibliometric analysis allowing to define the most relevant ones. Results: 101 titles met the established criteria, but only 43 met the purpose of the review. As for NOLBP prediction, the studies varied in relation to the factors for example: diagnosis, transition of lumbar pain from acute to chronic, absenteeism from work, disability and return to work. Conclusion: clinical prediction is considered as a strategic to determine course and prognostic of NOLBP, and to determine the characteristics that increase the risk of chronicity in workers with this health condition. Likewise, clinical prediction rules are tools that aim to facilitate decision making about the evaluation, diagnosis, prognosis and intervention for low back pain, which should incorporate risk factors of physical, psychological and social.

  17. Predicting dynamic knee joint load with clinical measures in people with medial knee osteoarthritis.

    Science.gov (United States)

    Hunt, Michael A; Bennell, Kim L

    2011-08-01

    Knee joint loading, as measured by the knee adduction moment (KAM), has been implicated in the pathogenesis of knee osteoarthritis (OA). Given that the KAM can only currently be accurately measured in the laboratory setting with sophisticated and expensive equipment, its utility in the clinical setting is limited. This study aimed to determine the ability of a combination of four clinical measures to predict KAM values. Three-dimensional motion analysis was used to calculate the peak KAM at a self-selected walking speed in 47 consecutive individuals with medial compartment knee OA and varus malalignment. Clinical predictors included: body mass; tibial angle measured using an inclinometer; walking speed; and visually observed trunk lean toward the affected limb during the stance phase of walking. Multiple linear regression was performed to predict KAM magnitudes using the four clinical measures. A regression model including body mass (41% explained variance), tibial angle (17% explained variance), and walking speed (9% explained variance) explained a total of 67% of variance in the peak KAM. Our study demonstrates that a set of measures easily obtained in the clinical setting (body mass, tibial alignment, and walking speed) can help predict the KAM in people with medial knee OA. Identifying those patients who are more likely to experience high medial knee loads could assist clinicians in deciding whether load-modifying interventions may be appropriate for patients, whilst repeated assessment of joint load could provide a mechanism to monitor disease progression or success of treatment.

  18. Incentives Increase Participation in Mass Dog Rabies Vaccination Clinics and Methods of Coverage Estimation Are Assessed to Be Accurate.

    Directory of Open Access Journals (Sweden)

    Abel B Minyoo

    2015-12-01

    Full Text Available In this study we show that incentives (dog collars and owner wristbands are effective at increasing owner participation in mass dog rabies vaccination clinics and we conclude that household questionnaire surveys and the mark-re-sight (transect survey method for estimating post-vaccination coverage are accurate when all dogs, including puppies, are included. Incentives were distributed during central-point rabies vaccination clinics in northern Tanzania to quantify their effect on owner participation. In villages where incentives were handed out participation increased, with an average of 34 more dogs being vaccinated. Through economies of scale, this represents a reduction in the cost-per-dog of $0.47. This represents the price-threshold under which the cost of the incentive used must fall to be economically viable. Additionally, vaccination coverage levels were determined in ten villages through the gold-standard village-wide census technique, as well as through two cheaper and quicker methods (randomized household questionnaire and the transect survey. Cost data were also collected. Both non-gold standard methods were found to be accurate when puppies were included in the calculations, although the transect survey and the household questionnaire survey over- and under-estimated the coverage respectively. Given that additional demographic data can be collected through the household questionnaire survey, and that its estimate of coverage is more conservative, we recommend this method. Despite the use of incentives the average vaccination coverage was below the 70% threshold for eliminating rabies. We discuss the reasons and suggest solutions to improve coverage. Given recent international targets to eliminate rabies, this study provides valuable and timely data to help improve mass dog vaccination programs in Africa and elsewhere.

  19. Incentives Increase Participation in Mass Dog Rabies Vaccination Clinics and Methods of Coverage Estimation Are Assessed to Be Accurate.

    Science.gov (United States)

    Minyoo, Abel B; Steinmetz, Melissa; Czupryna, Anna; Bigambo, Machunde; Mzimbiri, Imam; Powell, George; Gwakisa, Paul; Lankester, Felix

    2015-12-01

    In this study we show that incentives (dog collars and owner wristbands) are effective at increasing owner participation in mass dog rabies vaccination clinics and we conclude that household questionnaire surveys and the mark-re-sight (transect survey) method for estimating post-vaccination coverage are accurate when all dogs, including puppies, are included. Incentives were distributed during central-point rabies vaccination clinics in northern Tanzania to quantify their effect on owner participation. In villages where incentives were handed out participation increased, with an average of 34 more dogs being vaccinated. Through economies of scale, this represents a reduction in the cost-per-dog of $0.47. This represents the price-threshold under which the cost of the incentive used must fall to be economically viable. Additionally, vaccination coverage levels were determined in ten villages through the gold-standard village-wide census technique, as well as through two cheaper and quicker methods (randomized household questionnaire and the transect survey). Cost data were also collected. Both non-gold standard methods were found to be accurate when puppies were included in the calculations, although the transect survey and the household questionnaire survey over- and under-estimated the coverage respectively. Given that additional demographic data can be collected through the household questionnaire survey, and that its estimate of coverage is more conservative, we recommend this method. Despite the use of incentives the average vaccination coverage was below the 70% threshold for eliminating rabies. We discuss the reasons and suggest solutions to improve coverage. Given recent international targets to eliminate rabies, this study provides valuable and timely data to help improve mass dog vaccination programs in Africa and elsewhere. PMID:26633821

  20. Incentives Increase Participation in Mass Dog Rabies Vaccination Clinics and Methods of Coverage Estimation Are Assessed to Be Accurate

    Science.gov (United States)

    Steinmetz, Melissa; Czupryna, Anna; Bigambo, Machunde; Mzimbiri, Imam; Powell, George; Gwakisa, Paul

    2015-01-01

    In this study we show that incentives (dog collars and owner wristbands) are effective at increasing owner participation in mass dog rabies vaccination clinics and we conclude that household questionnaire surveys and the mark-re-sight (transect survey) method for estimating post-vaccination coverage are accurate when all dogs, including puppies, are included. Incentives were distributed during central-point rabies vaccination clinics in northern Tanzania to quantify their effect on owner participation. In villages where incentives were handed out participation increased, with an average of 34 more dogs being vaccinated. Through economies of scale, this represents a reduction in the cost-per-dog of $0.47. This represents the price-threshold under which the cost of the incentive used must fall to be economically viable. Additionally, vaccination coverage levels were determined in ten villages through the gold-standard village-wide census technique, as well as through two cheaper and quicker methods (randomized household questionnaire and the transect survey). Cost data were also collected. Both non-gold standard methods were found to be accurate when puppies were included in the calculations, although the transect survey and the household questionnaire survey over- and under-estimated the coverage respectively. Given that additional demographic data can be collected through the household questionnaire survey, and that its estimate of coverage is more conservative, we recommend this method. Despite the use of incentives the average vaccination coverage was below the 70% threshold for eliminating rabies. We discuss the reasons and suggest solutions to improve coverage. Given recent international targets to eliminate rabies, this study provides valuable and timely data to help improve mass dog vaccination programs in Africa and elsewhere. PMID:26633821

  1. [Clinical probability of PE: should we use a clinical prediction rule?].

    Science.gov (United States)

    Le Gal, G; Righini, M; Perrier, A

    2008-12-01

    The determination of the clinical pretest probability using clinical prediction models is an important step in the assessment of patients with suspected pulmonary embolism (PE). It helps establish which test or sequence of tests can effectively corroborate or safely rule out PE. For example, it has been demonstrated that it is safe to withhold anticoagulant therapy in patients with negative d-dimer results and low pretest probability at initial presentation. Clinical probability will also increase the diagnostic yield of ventilation perfusion lung scan. Compared with clinical gestalt, clinical prediction rules provide a standardized and more reproducible estimate of a patient's probability of having a PE. Clinical prediction models combine aspects of the history and physical examination to categorize a patient's probability of having a disease. The models classify patients as having a low, moderate, or high likelihood of having PE. Clinical prediction models have been validated and are well established for the diagnosis of PE in symptomatic patients. They allow all physicians, whatever their expertise, to reliably determine the clinical pretest probability of PE, and thus safely manage their patients using diagnostic and therapeutic algorithms. PMID:19084205

  2. Host genetics predict clinical deterioration in HCV-related cirrhosis.

    Directory of Open Access Journals (Sweden)

    Lindsay Y King

    Full Text Available Single nucleotide polymorphisms (SNPs in the epidermal growth factor (EGF, rs4444903, patatin-like phospholipase domain-containing protein 3 (PNPLA3, rs738409 genes, and near the interleukin-28B (IL28B, rs12979860 gene are linked to treatment response, fibrosis, and hepatocellular carcinoma (HCC in chronic hepatitis C. Whether these SNPs independently or in combination predict clinical deterioration in hepatitis C virus (HCV-related cirrhosis is unknown. We genotyped SNPs in EGF, PNPLA3, and IL28B from liver tissue from 169 patients with biopsy-proven HCV cirrhosis. We estimated risk of clinical deterioration, defined as development of ascites, encephalopathy, variceal hemorrhage, HCC, or liver-related death using Cox proportional hazards modeling. During a median follow-up of 6.6 years, 66 of 169 patients experienced clinical deterioration. EGF non-AA, PNPLA3 non-CC, and IL28B non-CC genotypes were each associated with increased risk of clinical deterioration in age, sex, and race-adjusted analysis. Only EGF non-AA genotype was independently associated with increased risk of clinical deterioration (hazard ratio [HR] 2.87; 95% confidence interval [CI] 1.31-6.25 after additionally adjusting for bilirubin, albumin, and platelets. Compared to subjects who had 0-1 unfavorable genotypes, the HR for clinical deterioration was 1.79 (95%CI 0.96-3.35 for 2 unfavorable genotypes and 4.03 (95%CI 2.13-7.62 for unfavorable genotypes for all three loci (Ptrend<0.0001. In conclusion, among HCV cirrhotics, EGF non-AA genotype is independently associated with increased risk for clinical deterioration. Specific PNPLA3 and IL28B genotypes also appear to be associated with clinical deterioration. These SNPs have potential to identify patients with HCV-related cirrhosis who require more intensive monitoring for decompensation or future therapies preventing disease progression.

  3. Development of transfer standard devices for ensuring the accurate calibration of ultrasonic physical therapy machines in clinical use

    International Nuclear Information System (INIS)

    Physical therapy ultrasound is widely applied to patients. However, many devices do not comply with the relevant standard stating that the actual power output shall be within ±20% of the device indication. Extreme cases have been reported: from delivering effectively no ultrasound or operating at maximum power at all powers indicated. This can potentially lead to patient injury as well as mistreatment. The present European (EC) project is an ongoing attempt to improve the quality of the treatment of patients being treated with ultrasonic physical-therapy. A Portable ultrasound Power Standard (PPS) is being developed and accurately calibrated. The PPS includes: Ultrasound transducers (including one exhibiting an unusual output) and a driver for the ultrasound transducers that has calibration and proficiency test functions. Also included with the PPS is a Cavitation Detector to determine the onset of cavitation occurring within the propagation medium. The PPS will be suitable for conducting in-the-field accreditation (proficiency testing and calibration). In order to be accredited it will be important to be able to show traceability of the calibration, the calibration process and qualification of testing staff. The clinical user will benefit from traceability because treatments will be performed more reliably

  4. Development of transfer standard devices for ensuring the accurate calibration of ultrasonic physical therapy machines in clinical use

    Energy Technology Data Exchange (ETDEWEB)

    Hekkenberg, R T [TNO Prevention and Health, Zernikedreef 9, 2333 CK Leiden (Netherlands); Richards, A [National Measurement Laboratory, CSIRO, Bradfield Rd, West Lindfield 2070, Sydney (Australia); Beissner, K [Physikalisch-Technische Bundesanstalt, PTB, Bundesallee 100, D-38116 Braunschweig (Germany); Zeqiri, B [National Physical Laboratory, NPL, Queens Road, Teddington, TW11 0LW (United Kingdom); Prout, G [National Measurement Laboratory, CSIRO, Bradfield Rd, West Lindfield 2070, Sydney (Australia); Cantrall, Ch [National Measurement Laboratory, CSIRO, Bradfield Rd, West Lindfield 2070, Sydney (Australia); Bezemer, R A [TNO Prevention and Health, Zernikedreef 9, 2333 CK Leiden (Netherlands); Koch, Ch [Physikalisch-Technische Bundesanstalt, PTB, Bundesallee 100, D-38116 Braunschweig, (Germany); Hodnett, M [National Physical Laboratory, NPL, Queens Road, Teddington, TW11 0LW (United Kingdom)

    2004-01-01

    Physical therapy ultrasound is widely applied to patients. However, many devices do not comply with the relevant standard stating that the actual power output shall be within {+-}20% of the device indication. Extreme cases have been reported: from delivering effectively no ultrasound or operating at maximum power at all powers indicated. This can potentially lead to patient injury as well as mistreatment. The present European (EC) project is an ongoing attempt to improve the quality of the treatment of patients being treated with ultrasonic physical-therapy. A Portable ultrasound Power Standard (PPS) is being developed and accurately calibrated. The PPS includes: Ultrasound transducers (including one exhibiting an unusual output) and a driver for the ultrasound transducers that has calibration and proficiency test functions. Also included with the PPS is a Cavitation Detector to determine the onset of cavitation occurring within the propagation medium. The PPS will be suitable for conducting in-the-field accreditation (proficiency testing and calibration). In order to be accredited it will be important to be able to show traceability of the calibration, the calibration process and qualification of testing staff. The clinical user will benefit from traceability because treatments will be performed more reliably.

  5. Islet Oxygen Consumption Rate (OCR Dose Predicts Insulin Independence in Clinical Islet Autotransplantation.

    Directory of Open Access Journals (Sweden)

    Klearchos K Papas

    Full Text Available Reliable in vitro islet quality assessment assays that can be performed routinely, prospectively, and are able to predict clinical transplant outcomes are needed. In this paper we present data on the utility of an assay based on cellular oxygen consumption rate (OCR in predicting clinical islet autotransplant (IAT insulin independence (II. IAT is an attractive model for evaluating characterization assays regarding their utility in predicting II due to an absence of confounding factors such as immune rejection and immunosuppressant toxicity.Membrane integrity staining (FDA/PI, OCR normalized to DNA (OCR/DNA, islet equivalent (IE and OCR (viable IE normalized to recipient body weight (IE dose and OCR dose, and OCR/DNA normalized to islet size index (ISI were used to characterize autoislet preparations (n = 35. Correlation between pre-IAT islet product characteristics and II was determined using receiver operating characteristic analysis.Preparations that resulted in II had significantly higher OCR dose and IE dose (p<0.001. These islet characterization methods were highly correlated with II at 6-12 months post-IAT (area-under-the-curve (AUC = 0.94 for IE dose and 0.96 for OCR dose. FDA/PI (AUC = 0.49 and OCR/DNA (AUC = 0.58 did not correlate with II. OCR/DNA/ISI may have some utility in predicting outcome (AUC = 0.72.Commonly used assays to determine whether a clinical islet preparation is of high quality prior to transplantation are greatly lacking in sensitivity and specificity. While IE dose is highly predictive, it does not take into account islet cell quality. OCR dose, which takes into consideration both islet cell quality and quantity, may enable a more accurate and prospective evaluation of clinical islet preparations.

  6. Clinical prediction rules for failed nonoperative reduction of intussusception

    Science.gov (United States)

    Khorana, Jiraporn; Patumanond, Jayanton; Ukarapol, Nuthapong; Laohapensang, Mongkol; Visrutaratna, Pannee; Singhavejsakul, Jesda

    2016-01-01

    Purpose The nonoperative reduction of intussusception in children can be performed safely if there are no contraindications. Many risk factors associated with failed reduction were defined. The aim of this study was to develop a scoring system for predicting the failure of nonoperative reduction using various determinants. Patients and methods The data were collected from Chiang Mai University Hospital and Siriraj Hospital from January 2006 to December 2012. Inclusion criteria consisted of patients with intussusception aged 0–15 years with no contraindications for nonoperative reduction. The clinical prediction rules were developed using significant risk factors from the multivariable analysis. Results A total of 170 patients with intussusception were included in the study. In the final analysis model, 154 patients were used for identifying the significant risk factors of failure of reduction. Ten factors clustering by the age of 3 years were identified and used for developing the clinical prediction rules, and the factors were as follows: body weight 48 hours (RR =1.26, P37.8°C (RR =1.51, P<0.001), palpable mass (RR =1.26, P<0.001), location of mass (left over right side RR =1.48, P<0.001), ultrasound showed poor prognostic signs (RR =1.35, P<0.001), and the method of reduction (hydrostatic over pneumatic, RR =1.34, P=0.023). Prediction scores ranged from 0 to 16. A high-risk group (scores 12–16) predicted a greater chance of reduction failure (likelihood ratio of positive [LR+] =18.22, P<0.001). A low-risk group (score 0–11) predicted a lower chance of reduction failure (LR+ =0.79, P<0.001). The performance of the scoring model was 80.68% (area under the receiver operating characteristic curve). Conclusion This scoring guideline was used to predict the results of nonoperative reduction and forecast the prognosis of the failed reduction. The usefulness of these prediction scores is for informing the parents before the reduction. This scoring system can be

  7. Formation of NO from N2/O2 mixtures in a flow reactor: Toward an accurate prediction of thermal NO

    DEFF Research Database (Denmark)

    Abian, Maria; Alzueta, Maria U.; Glarborg, Peter

    2015-01-01

    We have conducted flow reactor experiments for NO formation from N2/O2 mixtures at high temperatures and atmospheric pressure, controlling accurately temperature and reaction time. Under these conditions, atomic oxygen equilibrates rapidly with O2. The experimental results were interpreted......, is recommended for use in kinetic modeling....

  8. How to develop, validate, and compare clinical prediction models involving radiological parameters: Study design and statistical methods

    Energy Technology Data Exchange (ETDEWEB)

    Han, Kyung Hwa; Choi, Byoung Wook [Dept. of Radiology, and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul (Korea, Republic of); Song, Ki Jun [Dept. of Biostatistics and Medical Informatics, Yonsei University College of Medicine, Seoul (Korea, Republic of)

    2016-06-15

    Clinical prediction models are developed to calculate estimates of the probability of the presence/occurrence or future course of a particular prognostic or diagnostic outcome from multiple clinical or non-clinical parameters. Radiologic imaging techniques are being developed for accurate detection and early diagnosis of disease, which will eventually affect patient outcomes. Hence, results obtained by radiological means, especially diagnostic imaging, are frequently incorporated into a clinical prediction model as important predictive parameters, and the performance of the prediction model may improve in both diagnostic and prognostic settings. This article explains in a conceptual manner the overall process of developing and validating a clinical prediction model involving radiological parameters in relation to the study design and statistical methods. Collection of a raw dataset; selection of an appropriate statistical model; predictor selection; evaluation of model performance using a calibration plot, Hosmer-Lemeshow test and c-index; internal and external validation; comparison of different models using c-index, net reclassification improvement, and integrated discrimination improvement; and a method to create an easy-to-use prediction score system will be addressed. This article may serve as a practical methodological reference for clinical researchers.

  9. Random forest algorithm yields accurate quantitative prediction models of benthic light at intertidal sites affected by toxic Lyngbya majuscula blooms

    NARCIS (Netherlands)

    M.J. Kehoe; K. O’ Brien; A. Grinham; D. Rissik; K.S. Ahern; P. Maxwell

    2012-01-01

    It is shown that targeted high frequency monitoring and modern machine learning methods lead to highly predictive models of benthic light flux. A state-of-the-art machine learning technique was used in conjunction with a high frequency data set to calibrate and test predictive benthic lights models

  10. Predictable Outcomes with Porcelain Laminate Veneers: A Clinical Report.

    Science.gov (United States)

    Pimentel, Welson; Teixeira, Marcelo Lucchesi; Costa, Priscila Paganini; Jorge, Mônica Zacharias; Tiossi, Rodrigo

    2016-06-01

    This clinical report describes how to achieve predictable outcomes for anterior teeth esthetic restorations with porcelain laminate veneers by associating the digital planning and design of the restoration with interim restorations. The previous digital smile design of the restoration eliminates the communication barrier with the patient and assists the clinician throughout patient treatment. Interim restorations (diagnostic mock-ups) further enhance communication with the patient and prevent unnecessary tooth reduction for conservative tooth preparation. Adequate communication between patient and clinician contributes to successful definitive restorations and patient satisfaction with the final esthetic outcome.

  11. Accurately Predicting the Density and Hydrostatic Compression of Hexahydro-1,3,5-Trinitro-1,3,5-Triazine from First Principles

    Institute of Scientific and Technical Information of China (English)

    SONG HuarJie; HUANG Feng-Lei

    2011-01-01

    @@ We predict the densities of crystalline hexahydro-1,3,5-trinitro-1,3,5-triazine(RDX)by introducing a factor of(1+1.5×10(-4)T)into the wavefunction-based potential of RDX constructed from first principles using the symmetry-adapted perturbation theory and the Williams-Stone-Misquitta method.The predicted values are within an accuracy of 1%of the density from O to 430K and closely reproduced the RDX densities under hydrostatic compression.This work heralds a promising approach to predicting accurately the densities of high explosives at temperatures and pressures to which they are often subjected,which is a long-standing issue in the field of energetic materials.%We predict the densities of crystalline hexahydro-l,3,5-trinitro-l,3,5-triazine (RDX) by introducing a factor of (1+1.5 x 10~* T) into the wavefunction-based potential of RDX constructed from first principles using the symmetry-adapted perturbation theory and the Williams-Stone-Misquitta method. The predicted values are within an accuracy of 1% of the density from 0 to 430 K and closely reproduced the RDX densities under hydrostatic compression. This work heralds a promising approach to predicting accurately the densities of high explosives at temperatures and pressures to which they are often subjected, which is a long-standing issue in the Beld of energetic materials.

  12. PSSP-RFE: accurate prediction of protein structural class by recursive feature extraction from PSI-BLAST profile, physical-chemical property and functional annotations.

    Directory of Open Access Journals (Sweden)

    Liqi Li

    Full Text Available Protein structure prediction is critical to functional annotation of the massively accumulated biological sequences, which prompts an imperative need for the development of high-throughput technologies. As a first and key step in protein structure prediction, protein structural class prediction becomes an increasingly challenging task. Amongst most homological-based approaches, the accuracies of protein structural class prediction are sufficiently high for high similarity datasets, but still far from being satisfactory for low similarity datasets, i.e., below 40% in pairwise sequence similarity. Therefore, we present a novel method for accurate and reliable protein structural class prediction for both high and low similarity datasets. This method is based on Support Vector Machine (SVM in conjunction with integrated features from position-specific score matrix (PSSM, PROFEAT and Gene Ontology (GO. A feature selection approach, SVM-RFE, is also used to rank the integrated feature vectors through recursively removing the feature with the lowest ranking score. The definitive top features selected by SVM-RFE are input into the SVM engines to predict the structural class of a query protein. To validate our method, jackknife tests were applied to seven widely used benchmark datasets, reaching overall accuracies between 84.61% and 99.79%, which are significantly higher than those achieved by state-of-the-art tools. These results suggest that our method could serve as an accurate and cost-effective alternative to existing methods in protein structural classification, especially for low similarity datasets.

  13. Fusion of clinical and stochastic finite element data for hip fracture risk prediction.

    Science.gov (United States)

    Jiang, Peng; Missoum, Samy; Chen, Zhao

    2015-11-26

    Hip fracture affects more than 250,000 people in the US and 1.6 million worldwide per year. With an aging population, the development of reliable fracture risk models is therefore of prime importance. Due to the complexity of the hip fracture phenomenon, the use of clinical data only, as it is done traditionally, might not be sufficient to ensure an accurate and robust hip fracture prediction model. In order to increase the predictive ability of the risk model, the authors propose to supplement the clinical data with computational data from finite element models. The fusion of the two types of data is performed using deterministic and stochastic computational data. In the latter case, uncertainties in loading and material properties of the femur are accounted for and propagated through the finite element model. The predictive capability of a support vector machine (SVM) risk model constructed by combining clinical and finite element data was assessed using a Women׳s Health Initiative (WHI) dataset. The dataset includes common factors such as age and BMD as well as geometric factors obtained from DXA imaging. The fusion of computational and clinical data systematically leads to an increase in predictive ability of the SVM risk model as measured by the AUC metric. It is concluded that the largest gains in AUC are obtained by the stochastic approach. This gain decreases as the dimensionality of the problem increases: a 5.3% AUC improvement was achieved for a 9 dimensional problem involving geometric factors and weight while a 1.3% increase was obtained for a 20 dimensional case including geometric and conventional factors. PMID:26482733

  14. Physiologically-based pharmacokinetic modeling to predict the clinical pharmacokinetics of monoclonal antibodies.

    Science.gov (United States)

    Glassman, Patrick M; Balthasar, Joseph P

    2016-08-01

    Accurate prediction of the clinical pharmacokinetics of new therapeutic entities facilitates decision making during drug discovery, and increases the probability of success for early clinical trials. Standard strategies employed for predicting the pharmacokinetics of small-molecule drugs (e.g., allometric scaling) are often not useful for predicting the disposition monoclonal antibodies (mAbs), as mAbs frequently demonstrate species-specific non-linear pharmacokinetics that is related to mAb-target binding (i.e., target-mediated drug disposition, TMDD). The saturable kinetics of TMDD are known to be influenced by a variety of factors, including the sites of target expression (which determines the accessibility of target to mAb), the extent of target expression, the rate of target turnover, and the fate of mAb-target complexes. In most cases, quantitative information on the determinants of TMDD is not available during early phases of drug discovery, and this has complicated attempts to employ mechanistic mathematical models to predict the clinical pharmacokinetics of mAbs. In this report, we introduce a simple strategy, employing physiologically-based modeling, to predict mAb disposition in humans. The approach employs estimates of inter-antibody variability in rate processes of extravasation in tissues and fluid-phase endocytosis, estimates for target concentrations in tissues derived through use of categorical immunohistochemical scores, and in vitro measures of the turnover of target and target-mAb complexes. Monte Carlo simulations were performed for four mAbs (cetuximab, figitumumab, dalotuzumab, trastuzumab) directed against three targets (epidermal growth factor receptor, insulin-like growth factor receptor 1, human epidermal growth factor receptor 2). The proposed modeling strategy was able to predict well the pharmacokinetics of cetuximab, dalotuzumab, and trastuzumab at a range of doses, but trended towards underprediction of figitumumab concentrations

  15. Formalized prediction of clinically significant prostate cancer: is it possible?

    Institute of Scientific and Technical Information of China (English)

    Carvell T Nguyen; Michael W Kattan

    2012-01-01

    Greater understanding of the biology and epidemiology of prostate cancer in the last several decades have led to significant advances in its management.Prostate cancer is now detected in greater numbers at lower stages of disease and is amenable to multiple forms of efficacious treatment.However,there is a lack of conclusive data demonstrating a definitive mortality benefit from this earlier diagnosis and treatment of prostate cancer.It is likely due to the treatment of a large proportion of indolent cancers that would have had little adverse impact on health or lifespan if left alone.Due to this overtreatment phenomenon,active surveillance with delayed intervention is gaining traction as a viable management approach in contemporary practice.The ability to distinguish clinically insignificant cancers from those with a high risk of progression and/or lethality is critical to the appropriate selection of patients for surveillance protocols versus immediate intervention.This chapter will review the ability of various prediction models,including risk groupings and nomograms,to predict indolent disease and determine their role in the contemporary management of clinically localized prostate cancer.

  16. An Accurate GPS-IMU/DR Data Fusion Method for Driverless Car Based on a Set of Predictive Models and Grid Constraints

    OpenAIRE

    Shiyao Wang; Zhidong Deng; Gang Yin

    2016-01-01

    A high-performance differential global positioning system (GPS)  receiver with real time kinematics provides absolute localization for driverless cars. However, it is not only susceptible to multipath effect but also unable to effectively fulfill precise error correction in a wide range of driving areas. This paper proposes an accurate GPS–inertial measurement unit (IMU)/dead reckoning (DR) data fusion method based on a set of predictive models and occupancy grid constraints. First, we employ...

  17. Clinical implications of omics and systems medicine: focus on predictive and individualized treatment.

    Science.gov (United States)

    Benson, M

    2016-03-01

    Many patients with common diseases do not respond to treatment. This is a key challenge to modern health care, which causes both suffering and enormous costs. One important reason for the lack of treatment response is that common diseases are associated with altered interactions between thousands of genes, in combinations that differ between subgroups of patients who do or do not respond to a given treatment. Such subgroups, or even distinct disease entities, have been described recently in asthma, diabetes, autoimmune diseases and cancer. High-throughput techniques (omics) allow identification and characterization of such subgroups or entities. This may have important clinical implications, such as identification of diagnostic markers for individualized medicine, as well as new therapeutic targets for patients who do not respond to existing drugs. For example, whole-genome sequencing may be applied to more accurately guide treatment of neurodevelopmental diseases, or to identify drugs specifically targeting mutated genes in cancer. A study published in 2015 showed that 28% of hepatocellular carcinomas contained mutated genes that potentially could be targeted by drugs already approved by the US Food and Drug Administration. A translational study, which is described in detail, showed how combined omics, computational, functional and clinical studies could identify and validate a novel diagnostic and therapeutic candidate gene in allergy. Another important clinical implication is the identification of potential diagnostic markers and therapeutic targets for predictive and preventative medicine. By combining computational and experimental methods, early disease regulators may be identified and potentially used to predict and treat disease before it becomes symptomatic. Systems medicine is an emerging discipline, which may contribute to such developments through combining omics with computational, functional and clinical studies. The aims of this review are to provide

  18. A time accurate prediction of the viscous flow in a turbine stage including a rotor in motion

    Science.gov (United States)

    Shavalikul, Akamol

    In this current study, the flow field in the Pennsylvania State University Axial Flow Turbine Research Facility (AFTRF) was simulated. This study examined four sets of simulations. The first two sets are for an individual NGV and for an individual rotor. The last two sets use a multiple reference frames approach for a complete turbine stage with two different interface models: a steady circumferential average approach called a mixing plane model, and a time accurate flow simulation approach called a sliding mesh model. The NGV passage flow field was simulated using a three-dimensional Reynolds Averaged Navier-Stokes finite volume solver (RANS) with a standard kappa -- epsilon turbulence model. The mean flow distributions on the NGV surfaces and endwall surfaces were computed. The numerical solutions indicate that two passage vortices begin to be observed approximately at the mid axial chord of the NGV suction surface. The first vortex is a casing passage vortex which occurs at the corner formed by the NGV suction surface and the casing. This vortex is created by the interaction of the passage flow and the radially inward flow, while the second vortex, the hub passage vortex, is observed near the hub. These two vortices become stronger towards the NGV trailing edge. By comparing the results from the X/Cx = 1.025 plane and the X/Cx = 1.09 plane, it can be concluded that the NGV wake decays rapidly within a short axial distance downstream of the NGV. For the rotor, a set of simulations was carried out to examine the flow fields associated with different pressure side tip extension configurations, which are designed to reduce the tip leakage flow. The simulation results show that significant reductions in tip leakage mass flow rate and aerodynamic loss reduction are possible by using suitable tip platform extensions located near the pressure side corner of the blade tip. The computations used realistic turbine rotor inlet flow conditions in a linear cascade arrangement

  19. Accurate prediction of the toxicity of benzoic acid compounds in mice via oral without using any computer codes

    International Nuclear Information System (INIS)

    Highlights: ► A novel method is introduced for desk calculation of toxicity of benzoic acid derivatives. ► There is no need to use QSAR and QSTR methods, which are based on computer codes. ► The predicted results of 58 compounds are more reliable than those predicted by QSTR method. ► The present method gives good predictions for further 324 benzoic acid compounds. - Abstract: Most of benzoic acid derivatives are toxic, which may cause serious public health and environmental problems. Two novel simple and reliable models are introduced for desk calculations of the toxicity of benzoic acid compounds in mice via oral LD50 with more reliance on their answers as one could attach to the more complex outputs. They require only elemental composition and molecular fragments without using any computer codes. The first model is based on only the number of carbon and hydrogen atoms, which can be improved by several molecular fragments in the second model. For 57 benzoic compounds, where the computed results of quantitative structure–toxicity relationship (QSTR) were recently reported, the predicted results of two simple models of present method are more reliable than QSTR computations. The present simple method is also tested with further 324 benzoic acid compounds including complex molecular structures, which confirm good forecasting ability of the second model.

  20. Accurate prediction of the toxicity of benzoic acid compounds in mice via oral without using any computer codes

    Energy Technology Data Exchange (ETDEWEB)

    Keshavarz, Mohammad Hossein, E-mail: mhkeshavarz@mut-es.ac.ir [Department of Chemistry, Malek-ashtar University of Technology, Shahin-shahr P.O. Box 83145/115, Isfahan, Islamic Republic of Iran (Iran, Islamic Republic of); Gharagheizi, Farhad [Department of Chemical Engineering, Buinzahra Branch, Islamic Azad University, Buinzahra, Islamic Republic of Iran (Iran, Islamic Republic of); Shokrolahi, Arash; Zakinejad, Sajjad [Department of Chemistry, Malek-ashtar University of Technology, Shahin-shahr P.O. Box 83145/115, Isfahan, Islamic Republic of Iran (Iran, Islamic Republic of)

    2012-10-30

    Highlights: Black-Right-Pointing-Pointer A novel method is introduced for desk calculation of toxicity of benzoic acid derivatives. Black-Right-Pointing-Pointer There is no need to use QSAR and QSTR methods, which are based on computer codes. Black-Right-Pointing-Pointer The predicted results of 58 compounds are more reliable than those predicted by QSTR method. Black-Right-Pointing-Pointer The present method gives good predictions for further 324 benzoic acid compounds. - Abstract: Most of benzoic acid derivatives are toxic, which may cause serious public health and environmental problems. Two novel simple and reliable models are introduced for desk calculations of the toxicity of benzoic acid compounds in mice via oral LD{sub 50} with more reliance on their answers as one could attach to the more complex outputs. They require only elemental composition and molecular fragments without using any computer codes. The first model is based on only the number of carbon and hydrogen atoms, which can be improved by several molecular fragments in the second model. For 57 benzoic compounds, where the computed results of quantitative structure-toxicity relationship (QSTR) were recently reported, the predicted results of two simple models of present method are more reliable than QSTR computations. The present simple method is also tested with further 324 benzoic acid compounds including complex molecular structures, which confirm good forecasting ability of the second model.

  1. Externally validated HPV-based prognostic nomogram for oropharyngeal carcinoma patients yields more accurate predictions than TNM staging

    International Nuclear Information System (INIS)

    Purpose: Due to the established role of the human papillomavirus (HPV), the optimal treatment for oropharyngeal carcinoma is currently under debate. We evaluated the most important determinants of treatment outcome to develop a multifactorial predictive model that could provide individualized predictions of treatment outcome in oropharyngeal carcinoma patients. Methods: We analyzed the association between clinico-pathological factors and overall and progression-free survival in 168 OPSCC patients treated with curative radiotherapy or concurrent chemo-radiation. A multivariate model was validated in an external dataset of 189 patients and compared to the TNM staging system. This nomogram will be made publicly available at (www.predictcancer.org). Results: Predictors of unfavorable outcomes were negative HPV-status, moderate to severe comorbidity, T3–T4 classification, N2b–N3 stage, male gender, lower hemoglobin levels and smoking history of more than 30 pack years. Prediction of overall survival using the multi-parameter model yielded a C-index of 0.82 (95% CI, 0.76–0.88). Validation in an independent dataset yielded a C-index of 0.73 (95% CI, 0.66–0.79. For progression-free survival, the model’s C-index was 0.80 (95% CI, 0.76–0.88), with a validation C-index of 0.67, (95% CI, 0.59–0.74). Stratification of model estimated probabilities showed statistically different prognosis groups in both datasets (p < 0.001). Conclusion: This nomogram was superior to TNM classification or HPV status alone in an independent validation dataset for prediction of overall and progression-free survival in OPSCC patients, assigning patients to distinct prognosis groups. These individualized predictions could be used to stratify patients for treatment de-escalation trials

  2. Fecal Calprotectin is an Accurate Tool and Correlated to Seo Index in Prediction of Relapse in Iranian Patients With Ulcerative Colitis

    OpenAIRE

    Hosseini, Seyed Vahid; Jafari, Peyman; Taghavi, Seyed Alireza; Safarpour, Ali Reza; Rezaianzadeh, Abbas; Moini, Maryam; Mehrabi, Manoosh

    2015-01-01

    Background: The natural clinical course of Ulcerative Colitis (UC) is characterized by episodes of relapse and remission. Fecal Calprotectin (FC) is a relatively new marker of intestinal inflammation and is an available, non-expensive tool for predicting relapse of quiescent UC. The Seo colitis activity index is a clinical index for assessment of the severity of UC. Objectives: The present study aimed to evaluate the accuracy of FC and the Seo colitis activity index and their correlation in p...

  3. Accurate prediction of secreted substrates and identification of a conserved putative secretion signal for type III secretion systems.

    Directory of Open Access Journals (Sweden)

    Ram Samudrala

    2009-04-01

    Full Text Available The type III secretion system is an essential component for virulence in many Gram-negative bacteria. Though components of the secretion system apparatus are conserved, its substrates--effector proteins--are not. We have used a novel computational approach to confidently identify new secreted effectors by integrating protein sequence-based features, including evolutionary measures such as the pattern of homologs in a range of other organisms, G+C content, amino acid composition, and the N-terminal 30 residues of the protein sequence. The method was trained on known effectors from the plant pathogen Pseudomonas syringae and validated on a set of effectors from the animal pathogen Salmonella enterica serovar Typhimurium (S. Typhimurium after eliminating effectors with detectable sequence similarity. We show that this approach can predict known secreted effectors with high specificity and sensitivity. Furthermore, by considering a large set of effectors from multiple organisms, we computationally identify a common putative secretion signal in the N-terminal 20 residues of secreted effectors. This signal can be used to discriminate 46 out of 68 total known effectors from both organisms, suggesting that it is a real, shared signal applicable to many type III secreted effectors. We use the method to make novel predictions of secreted effectors in S. Typhimurium, some of which have been experimentally validated. We also apply the method to predict secreted effectors in the genetically intractable human pathogen Chlamydia trachomatis, identifying the majority of known secreted proteins in addition to providing a number of novel predictions. This approach provides a new way to identify secreted effectors in a broad range of pathogenic bacteria for further experimental characterization and provides insight into the nature of the type III secretion signal.

  4. How accurate is our prediction of biopsy outcome? PCA3-based nomograms in personalized diagnosis of prostate cancer

    OpenAIRE

    Salagierski, Maciej; Sosnowski, Marek; Schalken, Jack A.

    2012-01-01

    Purpose The sensitivity and specificity of prostate-specific antigen (PSA) alone to select men for prostate biopsy remain suboptimal. This review aims at presenting a review of current prostate cancer (PCa) nomograms that incorporate Prostate Cancer Gene 3 (PCA3), which was designed to outperform PSA at predicting biopsy outcome. Materials and methods The PubMed database and current literature search was conducted for reports on PCA3-based nomograms and tools for examining the risk of a posit...

  5. Accurate microRNA target prediction using detailed binding site accessibility and machine learning on proteomics data

    Directory of Open Access Journals (Sweden)

    Martin eReczko

    2012-01-01

    Full Text Available MicroRNAs (miRNAs are a class of small regulatory genes regulating gene expression by targetingmessenger RNA. Though computational methods for miRNA target prediction are the prevailingmeans to analyze their function, they still miss a large fraction of the targeted genes and additionallypredict a large number of false positives. Here we introduce a novel algorithm called DIANAmicroT-ANN which combines multiple novel target site features through an artificial neural network(ANN and is trained using recently published high-throughput data measuring the change of proteinlevels after miRNA overexpression, providing positive and negative targeting examples. The featurescharacterizing each miRNA recognition element include binding structure, conservation level and aspecific profile of structural accessibility. The ANN is trained to integrate the features of eachrecognition element along the 3’ untranslated region into a targeting score, reproducing the relativerepression fold change of the protein. Tested on two different sets the algorithm outperforms otherwidely used algorithms and also predicts a significant number of unique and reliable targets notpredicted by the other methods. For 542 human miRNAs DIANA-microT-ANN predicts 120,000targets not provided by TargetScan 5.0. The algorithm is freely available athttp://microrna.gr/microT-ANN.

  6. A highly accurate protein structural class prediction approach using auto cross covariance transformation and recursive feature elimination.

    Science.gov (United States)

    Li, Xiaowei; Liu, Taigang; Tao, Peiying; Wang, Chunhua; Chen, Lanming

    2015-12-01

    Structural class characterizes the overall folding type of a protein or its domain. Many methods have been proposed to improve the prediction accuracy of protein structural class in recent years, but it is still a challenge for the low-similarity sequences. In this study, we introduce a feature extraction technique based on auto cross covariance (ACC) transformation of position-specific score matrix (PSSM) to represent a protein sequence. Then support vector machine-recursive feature elimination (SVM-RFE) is adopted to select top K features according to their importance and these features are input to a support vector machine (SVM) to conduct the prediction. Performance evaluation of the proposed method is performed using the jackknife test on three low-similarity datasets, i.e., D640, 1189 and 25PDB. By means of this method, the overall accuracies of 97.2%, 96.2%, and 93.3% are achieved on these three datasets, which are higher than those of most existing methods. This suggests that the proposed method could serve as a very cost-effective tool for predicting protein structural class especially for low-similarity datasets.

  7. Accurately Predicting the Density and Hydrostatic Compression of Hexahydro-1,3,5-Trinitro-1,3,5-Triazine from First Principles

    International Nuclear Information System (INIS)

    We predict the densities of crystalline hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) by introducing a factor of (1+1.5 × 10−4T) into the wavefunction-based potential of RDX constructed from first principles using the symmetry-adapted perturbation theory and the Williams—Stone—Misquitta method. The predicted values are within an accuracy of 1% of the density from 0 to 430 K and closely reproduced the RDX densities under hydrostatic compression. This work heralds a promising approach to predicting accurately the densities of high explosives at temperatures and pressures to which they are often subjected, which is a long-standing issue in the field of energetic materials. (condensed matter: structure, mechanical and thermal properties)

  8. aPPRove: An HMM-Based Method for Accurate Prediction of RNA-Pentatricopeptide Repeat Protein Binding Events

    Science.gov (United States)

    Harrison, Thomas; Ruiz, Jaime; Sloan, Daniel B.; Ben-Hur, Asa; Boucher, Christina

    2016-01-01

    Pentatricopeptide repeat containing proteins (PPRs) bind to RNA transcripts originating from mitochondria and plastids. There are two classes of PPR proteins. The P class contains tandem P-type motif sequences, and the PLS class contains alternating P, L and S type sequences. In this paper, we describe a novel tool that predicts PPR-RNA interaction; specifically, our method, which we call aPPRove, determines where and how a PLS-class PPR protein will bind to RNA when given a PPR and one or more RNA transcripts by using a combinatorial binding code for site specificity proposed by Barkan et al. Our results demonstrate that aPPRove successfully locates how and where a PPR protein belonging to the PLS class can bind to RNA. For each binding event it outputs the binding site, the amino-acid-nucleotide interaction, and its statistical significance. Furthermore, we show that our method can be used to predict binding events for PLS-class proteins using a known edit site and the statistical significance of aligning the PPR protein to that site. In particular, we use our method to make a conjecture regarding an interaction between CLB19 and the second intronic region of ycf3. The aPPRove web server can be found at www.cs.colostate.edu/~approve. PMID:27560805

  9. A 3D-CFD code for accurate prediction of fluid flows and fluid forces in seals

    Science.gov (United States)

    Athavale, M. M.; Przekwas, A. J.; Hendricks, R. C.

    1994-01-01

    Current and future turbomachinery requires advanced seal configurations to control leakage, inhibit mixing of incompatible fluids and to control the rotodynamic response. In recognition of a deficiency in the existing predictive methodology for seals, a seven year effort was established in 1990 by NASA's Office of Aeronautics Exploration and Technology, under the Earth-to-Orbit Propulsion program, to develop validated Computational Fluid Dynamics (CFD) concepts, codes and analyses for seals. The effort will provide NASA and the U.S. Aerospace Industry with advanced CFD scientific codes and industrial codes for analyzing and designing turbomachinery seals. An advanced 3D CFD cylindrical seal code has been developed, incorporating state-of-the-art computational methodology for flow analysis in straight, tapered and stepped seals. Relevant computational features of the code include: stationary/rotating coordinates, cylindrical and general Body Fitted Coordinates (BFC) systems, high order differencing schemes, colocated variable arrangement, advanced turbulence models, incompressible/compressible flows, and moving grids. This paper presents the current status of code development, code demonstration for predicting rotordynamic coefficients, numerical parametric study of entrance loss coefficients for generic annular seals, and plans for code extensions to labyrinth, damping, and other seal configurations.

  10. aPPRove: An HMM-Based Method for Accurate Prediction of RNA-Pentatricopeptide Repeat Protein Binding Events.

    Science.gov (United States)

    Harrison, Thomas; Ruiz, Jaime; Sloan, Daniel B; Ben-Hur, Asa; Boucher, Christina

    2016-01-01

    Pentatricopeptide repeat containing proteins (PPRs) bind to RNA transcripts originating from mitochondria and plastids. There are two classes of PPR proteins. The [Formula: see text] class contains tandem [Formula: see text]-type motif sequences, and the [Formula: see text] class contains alternating [Formula: see text], [Formula: see text] and [Formula: see text] type sequences. In this paper, we describe a novel tool that predicts PPR-RNA interaction; specifically, our method, which we call aPPRove, determines where and how a [Formula: see text]-class PPR protein will bind to RNA when given a PPR and one or more RNA transcripts by using a combinatorial binding code for site specificity proposed by Barkan et al. Our results demonstrate that aPPRove successfully locates how and where a PPR protein belonging to the [Formula: see text] class can bind to RNA. For each binding event it outputs the binding site, the amino-acid-nucleotide interaction, and its statistical significance. Furthermore, we show that our method can be used to predict binding events for [Formula: see text]-class proteins using a known edit site and the statistical significance of aligning the PPR protein to that site. In particular, we use our method to make a conjecture regarding an interaction between CLB19 and the second intronic region of ycf3. The aPPRove web server can be found at www.cs.colostate.edu/~approve. PMID:27560805

  11. Accurate prediction of secreted substrates and identification of a conserved putative secretion signal for type III secretion systems

    Energy Technology Data Exchange (ETDEWEB)

    Samudrala, Ram; Heffron, Fred; McDermott, Jason E.

    2009-04-24

    The type III secretion system is an essential component for virulence in many Gram-negative bacteria. Though components of the secretion system apparatus are conserved, its substrates, effector proteins, are not. We have used a machine learning approach to identify new secreted effectors. The method integrates evolutionary measures, such as the pattern of homologs in a range of other organisms, and sequence-based features, such as G+C content, amino acid composition and the N-terminal 30 residues of the protein sequence. The method was trained on known effectors from Salmonella typhimurium and validated on a corresponding set of effectors from Pseudomonas syringae, after eliminating effectors with detectable sequence similarity. The method was able to identify all of the known effectors in P. syringae with a specificity of 84% and sensitivity of 82%. The reciprocal validation, training on P. syringae and validating on S. typhimurium, gave similar results with a specificity of 86% when the sensitivity level was 87%. These results show that type III effectors in disparate organisms share common features. We found that maximal performance is attained by including an N-terminal sequence of only 30 residues, which agrees with previous studies indicating that this region contains the secretion signal. We then used the method to define the most important residues in this putative secretion signal. Finally, we present novel predictions of secreted effectors in S. typhimurium, some of which have been experimentally validated, and apply the method to predict secreted effectors in the genetically intractable human pathogen Chlamydia trachomatis. This approach is a novel and effective way to identify secreted effectors in a broad range of pathogenic bacteria for further experimental characterization and provides insight into the nature of the type III secretion signal.

  12. Predictive value of multi-detector computed tomography for accurate diagnosis of serous cystadenoma: Radiologic-pathologic correlation

    Institute of Scientific and Technical Information of China (English)

    Anjuli A Shah; Nisha I Sainani; Avinash Kambadakone Ramesh; Zarine K Shah; Vikram Deshpande; Peter F Hahn; Dushyant V Sahani

    2009-01-01

    AIM:To identify multi-detector computed tomography (MDCT) features mos t predi c t i ve of serous cystadenomas (SCAs),correlating with histopathology,and to study the impact of cyst size and MDCT technique on reader performance.METHODS:The MDCT scans of 164 patients with surgically verified pancreatic cystic lesions were reviewed by two readers to study the predictive value of various morphological features for establishing a diagnosis of SCAs.Accuracy in lesion characterization and reader confidence were correlated with lesion size (≤3 cm or ≥3 cm) and scanning protocols (dedicated vs routine).RESULTS:28/164 cysts (mean size,39 mm;range,8-92 mm) were diagnosed as SCA on pathology.The MDCT features predictive of diagnosis of SCA were microcystic appearance (22/28,78.6%),surface lobulations (25/28,89.3%) and central scar (9/28,32.4%).Stepwise logistic regression analysis showed that only microcystic appearance was significant for CT diagnosis of SCA (P=0.0001).The sensitivity,specificity and PPV of central scar and of combined microcystic appearance and lobulations were 32.4%/100%/100% and 68%/100%/100%,respectively.The reader confidence was higher for lesions>3 cm (P=0.02) and for MDCT scans performed using thin collimation (1.25-2.5 mm) compared to routine 5 mm collimation exams (P>0.05).CONCLUSION:Central scar on MDCT is diagnostic of SCA but is seen in only one third of SCAs.Microcystic morphology is the most significant CT feature in diagnosis of SCA.A combination of microcystic appearance and surface lobulations offers accuracy comparable to central scar with higher sensitivity.

  13. Predicting College Students' First Year Success: Should Soft Skills Be Taken into Consideration to More Accurately Predict the Academic Achievement of College Freshmen?

    Science.gov (United States)

    Powell, Erica Dion

    2013-01-01

    This study presents a survey developed to measure the skills of entering college freshmen in the areas of responsibility, motivation, study habits, literacy, and stress management, and explores the predictive power of this survey as a measure of academic performance during the first semester of college. The survey was completed by 334 incoming…

  14. Predicting Antimicrobial Resistance Prevalence and Incidence from Indicators of Antimicrobial Use: What Is the Most Accurate Indicator for Surveillance in Intensive Care Units?

    Directory of Open Access Journals (Sweden)

    Élise Fortin

    Full Text Available The optimal way to measure antimicrobial use in hospital populations, as a complement to surveillance of resistance is still unclear. Using respiratory isolates and antimicrobial prescriptions of nine intensive care units (ICUs, this study aimed to identify the indicator of antimicrobial use that predicted prevalence and incidence rates of resistance with the best accuracy.Retrospective cohort study including all patients admitted to three neonatal (NICU, two pediatric (PICU and four adult ICUs between April 2006 and March 2010. Ten different resistance/antimicrobial use combinations were studied. After adjustment for ICU type, indicators of antimicrobial use were successively tested in regression models, to predict resistance prevalence and incidence rates, per 4-week time period, per ICU. Binomial regression and Poisson regression were used to model prevalence and incidence rates, respectively. Multiplicative and additive models were tested, as well as no time lag and a one 4-week-period time lag. For each model, the mean absolute error (MAE in prediction of resistance was computed. The most accurate indicator was compared to other indicators using t-tests.Results for all indicators were equivalent, except for 1/20 scenarios studied. In this scenario, where prevalence of carbapenem-resistant Pseudomonas sp. was predicted with carbapenem use, recommended daily doses per 100 admissions were less accurate than courses per 100 patient-days (p = 0.0006.A single best indicator to predict antimicrobial resistance might not exist. Feasibility considerations such as ease of computation or potential external comparisons could be decisive in the choice of an indicator for surveillance of healthcare antimicrobial use.

  15. Integration of noninvasive prenatal prediction of fetal blood group into clinical prenatal care.

    Science.gov (United States)

    Clausen, Frederik Banch

    2014-05-01

    Incompatibility of red blood cell blood group antigens between a pregnant woman and her fetus can cause maternal immunization and, consequently, hemolytic disease of the fetus and newborn. Noninvasive prenatal testing of cell-free fetal DNA can be used to assess the risk of hemolytic disease of the fetus and newborn to fetuses of immunized women. Prediction of the fetal RhD type has been very successful and is now integrated into clinical practice to assist in the management of the pregnancies of RhD immunized women. In addition, noninvasive prediction of the fetal RhD type can be applied to guide targeted prenatal prophylaxis, thus avoiding unnecessary exposure to anti-D in pregnant women. The analytical aspect of noninvasive fetal RHD typing is very robust and accurate, and its routine utilization has demonstrated high sensitivities for fetal RHD detection. A high compliance with administering anti-D is essential for obtaining a clinical effect. Noninvasive fetal typing of RHC/c, RHE/e, and KEL may become more widely used in the future. PMID:24431264

  16. Integrating metabolic performance, thermal tolerance, and plasticity enables for more accurate predictions on species vulnerability to acute and chronic effects of global warming.

    Science.gov (United States)

    Magozzi, Sarah; Calosi, Piero

    2015-01-01

    Predicting species vulnerability to global warming requires a comprehensive, mechanistic understanding of sublethal and lethal thermal tolerances. To date, however, most studies investigating species physiological responses to increasing temperature have focused on the underlying physiological traits of either acute or chronic tolerance in isolation. Here we propose an integrative, synthetic approach including the investigation of multiple physiological traits (metabolic performance and thermal tolerance), and their plasticity, to provide more accurate and balanced predictions on species and assemblage vulnerability to both acute and chronic effects of global warming. We applied this approach to more accurately elucidate relative species vulnerability to warming within an assemblage of six caridean prawns occurring in the same geographic, hence macroclimatic, region, but living in different thermal habitats. Prawns were exposed to four incubation temperatures (10, 15, 20 and 25 °C) for 7 days, their metabolic rates and upper thermal limits were measured, and plasticity was calculated according to the concept of Reaction Norms, as well as Q10 for metabolism. Compared to species occupying narrower/more stable thermal niches, species inhabiting broader/more variable thermal environments (including the invasive Palaemon macrodactylus) are likely to be less vulnerable to extreme acute thermal events as a result of their higher upper thermal limits. Nevertheless, they may be at greater risk from chronic exposure to warming due to the greater metabolic costs they incur. Indeed, a trade-off between acute and chronic tolerance was apparent in the assemblage investigated. However, the invasive species P. macrodactylus represents an exception to this pattern, showing elevated thermal limits and plasticity of these limits, as well as a high metabolic control. In general, integrating multiple proxies for species physiological acute and chronic responses to increasing

  17. An Accurate GPS-IMU/DR Data Fusion Method for Driverless Car Based on a Set of Predictive Models and Grid Constraints.

    Science.gov (United States)

    Wang, Shiyao; Deng, Zhidong; Yin, Gang

    2016-01-01

    A high-performance differential global positioning system (GPS)  receiver with real time kinematics provides absolute localization for driverless cars. However, it is not only susceptible to multipath effect but also unable to effectively fulfill precise error correction in a wide range of driving areas. This paper proposes an accurate GPS-inertial measurement unit (IMU)/dead reckoning (DR) data fusion method based on a set of predictive models and occupancy grid constraints. First, we employ a set of autoregressive and moving average (ARMA) equations that have different structural parameters to build maximum likelihood models of raw navigation. Second, both grid constraints and spatial consensus checks on all predictive results and current measurements are required to have removal of outliers. Navigation data that satisfy stationary stochastic process are further fused to achieve accurate localization results. Third, the standard deviation of multimodal data fusion can be pre-specified by grid size. Finally, we perform a lot of field tests on a diversity of real urban scenarios. The experimental results demonstrate that the method can significantly smooth small jumps in bias and considerably reduce accumulated position errors due to DR. With low computational complexity, the position accuracy of our method surpasses existing state-of-the-arts on the same dataset and the new data fusion method is practically applied in our driverless car. PMID:26927108

  18. An Accurate GPS-IMU/DR Data Fusion Method for Driverless Car Based on a Set of Predictive Models and Grid Constraints

    Science.gov (United States)

    Wang, Shiyao; Deng, Zhidong; Yin, Gang

    2016-01-01

    A high-performance differential global positioning system (GPS)  receiver with real time kinematics provides absolute localization for driverless cars. However, it is not only susceptible to multipath effect but also unable to effectively fulfill precise error correction in a wide range of driving areas. This paper proposes an accurate GPS–inertial measurement unit (IMU)/dead reckoning (DR) data fusion method based on a set of predictive models and occupancy grid constraints. First, we employ a set of autoregressive and moving average (ARMA) equations that have different structural parameters to build maximum likelihood models of raw navigation. Second, both grid constraints and spatial consensus checks on all predictive results and current measurements are required to have removal of outliers. Navigation data that satisfy stationary stochastic process are further fused to achieve accurate localization results. Third, the standard deviation of multimodal data fusion can be pre-specified by grid size. Finally, we perform a lot of field tests on a diversity of real urban scenarios. The experimental results demonstrate that the method can significantly smooth small jumps in bias and considerably reduce accumulated position errors due to DR. With low computational complexity, the position accuracy of our method surpasses existing state-of-the-arts on the same dataset and the new data fusion method is practically applied in our driverless car. PMID:26927108

  19. An Accurate GPS-IMU/DR Data Fusion Method for Driverless Car Based on a Set of Predictive Models and Grid Constraints

    Directory of Open Access Journals (Sweden)

    Shiyao Wang

    2016-02-01

    Full Text Available A high-performance differential global positioning system (GPS  receiver with real time kinematics provides absolute localization for driverless cars. However, it is not only susceptible to multipath effect but also unable to effectively fulfill precise error correction in a wide range of driving areas. This paper proposes an accurate GPS–inertial measurement unit (IMU/dead reckoning (DR data fusion method based on a set of predictive models and occupancy grid constraints. First, we employ a set of autoregressive and moving average (ARMA equations that have different structural parameters to build maximum likelihood models of raw navigation. Second, both grid constraints and spatial consensus checks on all predictive results and current measurements are required to have removal of outliers. Navigation data that satisfy stationary stochastic process are further fused to achieve accurate localization results. Third, the standard deviation of multimodal data fusion can be pre-specified by grid size. Finally, we perform a lot of field tests on a diversity of real urban scenarios. The experimental results demonstrate that the method can significantly smooth small jumps in bias and considerably reduce accumulated position errors due to DR. With low computational complexity, the position accuracy of our method surpasses existing state-of-the-arts on the same dataset and the new data fusion method is practically applied in our driverless car.

  20. Profile-QSAR: a novel meta-QSAR method that combines activities across the kinase family to accurately predict affinity, selectivity, and cellular activity.

    Science.gov (United States)

    Martin, Eric; Mukherjee, Prasenjit; Sullivan, David; Jansen, Johanna

    2011-08-22

    Profile-QSAR is a novel 2D predictive model building method for kinases. This "meta-QSAR" method models the activity of each compound against a new kinase target as a linear combination of its predicted activities against a large panel of 92 previously studied kinases comprised from 115 assays. Profile-QSAR starts with a sparse incomplete kinase by compound (KxC) activity matrix, used to generate Bayesian QSAR models for the 92 "basis-set" kinases. These Bayesian QSARs generate a complete "synthetic" KxC activity matrix of predictions. These synthetic activities are used as "chemical descriptors" to train partial-least squares (PLS) models, from modest amounts of medium-throughput screening data, for predicting activity against new kinases. The Profile-QSAR predictions for the 92 kinases (115 assays) gave a median external R²(ext) = 0.59 on 25% held-out test sets. The method has proven accurate enough to predict pairwise kinase selectivities with a median correlation of R²(ext) = 0.61 for 958 kinase pairs with at least 600 common compounds. It has been further expanded by adding a "C(k)XC" cellular activity matrix to the KxC matrix to predict cellular activity for 42 kinase driven cellular assays with median R²(ext) = 0.58 for 24 target modulation assays and R²(ext) = 0.41 for 18 cell proliferation assays. The 2D Profile-QSAR, along with the 3D Surrogate AutoShim, are the foundations of an internally developed iterative medium-throughput screening (IMTS) methodology for virtual screening (VS) of compound archives as an alternative to experimental high-throughput screening (HTS). The method has been applied to 20 actual prospective kinase projects. Biological results have so far been obtained in eight of them. Q² values ranged from 0.3 to 0.7. Hit-rates at 10 uM for experimentally tested compounds varied from 25% to 80%, except in K5, which was a special case aimed specifically at finding "type II" binders, where none of the compounds were predicted to be

  1. c-myc, not her-2/neu, can predict the prognosis of breast cancer patients: how novel, how accurate, and how significant?

    International Nuclear Information System (INIS)

    The predictive and prognostic implication of oncogene amplification in breast cancer has received great attention in the past two decades. her-2/neu and c-myc are two oncogenes that are frequently amplified and overexpressed in breast carcinomas. Despite the extensive data on these oncogenes, their prognostic and predictive impact on breast cancer patients remains controversial. Schlotter and colleagues have recently suggested that c-myc, and not her-2/neu, could predict the recurrence and mortality of patients with node-negative breast carcinomas. Regardless of the promising results, caution should be exercised in the interpretation of data from studies assessing gene amplification without in situ analysis. We address the novelty, accuracy and clinical significance of the study by Schlotter and colleagues

  2. ECG dispersion mapping predicts clinical deterioration, measured by increase in the Simple Clinical Score.

    LENUS (Irish Health Repository)

    Kellett, J

    2012-01-01

    Objective: ECG dispersion mapping (ECG-DM) is a novel technique that reports abnormal ECG microalternations. We report the ability of ECG-DM to predict clinical deterioration of acutely ill medical patients, as measured by an increase in the Simple Clinical Score (SCS) the day after admission to hospital. Methods: 453 acutely ill medical patients (mean age 69.7 +\\/- 14.0 years) had the SCS recorded and ECGDM performed immediately after admission to hospital. Results: 46 patients had an SCS increase 20.8 +\\/- 7.6 hours after admission. Abnormal micro-alternations during left ventricular re-polarization had the highest association with SCS increase (p=0.0005). Logistic regression showed that only nursing home residence and abnormal micro-alternations during re-polarization of the left ventricle were independent predictors of SCS increase with an odds ratio of 2.84 and 3.01, respectively. Conclusion: ECG-DM changes during left ventricular re-polarization are independent predictors of clinical deterioration the day after hospital admission.

  3. A combined clinical and biomarker approach to predict diuretic response in acute heart failure

    NARCIS (Netherlands)

    Ter Maaten, Jozine M; Valente, Mattia A E; Metra, Marco; Bruno, Noemi; O'Connor, Christopher M; Ponikowski, Piotr; Teerlink, John R; Cotter, Gad; Davison, Beth; Cleland, John G; Givertz, Michael M; Bloomfield, Daniel M; Dittrich, Howard C; van Veldhuisen, Dirk J; Hillege, Hans L; Damman, Kevin; Voors, Adriaan A

    2015-01-01

    BACKGROUND: Poor diuretic response in acute heart failure is related to poor clinical outcome. The underlying mechanisms and pathophysiology behind diuretic resistance are incompletely understood. We evaluated a combined approach using clinical characteristics and biomarkers to predict diuretic resp

  4. Dealing with missing predictor values when applying clinical prediction models.

    NARCIS (Netherlands)

    Janssen, K.J.; Vergouwe, Y.; Donders, A.R.T.; Harrell Jr, F.E.; Chen, Q.; Grobbee, D.E.; Moons, K.G.

    2009-01-01

    BACKGROUND: Prediction models combine patient characteristics and test results to predict the presence of a disease or the occurrence of an event in the future. In the event that test results (predictor) are unavailable, a strategy is needed to help users applying a prediction model to deal with suc

  5. Rorschach Prediction of Success in Clinical Training: A Second Look

    Science.gov (United States)

    Carlson, Rae

    1969-01-01

    A Rorschach Index based on ego-psychological conceptualization of an optimal personality picture predicted for 155 trainees was compared with predictions from the Miller Analogies Test (MAT) and the Strong Vocational Interest Blank (SVIB). The Index predicted success and failure more effectively. (Author)

  6. Cancer Pharmacogenomics: Integrating Discoveries in Basic, Clinical and Population Sciences to Advance Predictive Cancer Care

    Science.gov (United States)

    Cancer Pharmacogenomics: Integrating Discoveries in Basic, Clinical and Population Sciences to Advance Predictive Cancer Care, a 2010 workshop sponsored by the Epidemiology and Genomics Research Program.

  7. Subjective cognitive complaints included in diagnostic evaluation of dementia helps accurate diagnosis in a mixed memory clinic cohort

    DEFF Research Database (Denmark)

    Salem, L C; Vogel, Asmus Mejling; Ebstrup, J;

    2015-01-01

    OBJECTIVE: Our objective was to examine the quantity and profile of subjective cognitive complaints in young patients as compared with elderly patients referred to a memory clinic. METHODS: Patients were consecutively recruited from the Copenhagen University Hospital Memory Clinic at Rigshospitalet...... functions were assessed with the Mini-mental state examination (MMSE) and Addenbrooke's cognitive examination (ACE), and symptoms of depression were rated with Major Depression Inventory (MDI). All interviews and the diagnostic conclusion were blinded to the SMC score. RESULTS: We found that young patients...... with dementia have a significantly higher level and a different profile of subjective cognitive complaints as compared with elderly patients with dementia. Furthermore, young patients, diagnosed with an affective disorder, had the highest level of subjective cognitive complaints of all patients in a memory...

  8. Predicting Out-of-Office Blood Pressure in the Clinic (PROOF-BP): Derivation and Validation of a Tool to Improve the Accuracy of Blood Pressure Measurement in Clinical Practice.

    Science.gov (United States)

    Sheppard, James P; Stevens, Richard; Gill, Paramjit; Martin, Una; Godwin, Marshall; Hanley, Janet; Heneghan, Carl; Hobbs, F D Richard; Mant, Jonathan; McKinstry, Brian; Myers, Martin; Nunan, David; Ward, Alison; Williams, Bryan; McManus, Richard J

    2016-05-01

    Patients often have lower (white coat effect) or higher (masked effect) ambulatory/home blood pressure readings compared with clinic measurements, resulting in misdiagnosis of hypertension. The present study assessed whether blood pressure and patient characteristics from a single clinic visit can accurately predict the difference between ambulatory/home and clinic blood pressure readings (the home-clinic difference). A linear regression model predicting the home-clinic blood pressure difference was derived in 2 data sets measuring automated clinic and ambulatory/home blood pressure (n=991) using candidate predictors identified from a literature review. The model was validated in 4 further data sets (n=1172) using area under the receiver operator characteristic curve analysis. A masked effect was associated with male sex, a positive clinic blood pressure change (difference between consecutive measurements during a single visit), and a diagnosis of hypertension. Increasing age, clinic blood pressure level, and pulse pressure were associated with a white coat effect. The model showed good calibration across data sets (Pearson correlation, 0.48-0.80) and performed well-predicting ambulatory hypertension (area under the receiver operator characteristic curve, 0.75; 95% confidence interval, 0.72-0.79 [systolic]; 0.87; 0.85-0.89 [diastolic]). Used as a triaging tool for ambulatory monitoring, the model improved classification of a patient's blood pressure status compared with other guideline recommended approaches (93% [92% to 95%] classified correctly; United States, 73% [70% to 75%]; Canada, 74% [71% to 77%]; United Kingdom, 78% [76% to 81%]). This study demonstrates that patient characteristics from a single clinic visit can accurately predict a patient's ambulatory blood pressure. Usage of this prediction tool for triaging of ambulatory monitoring could result in more accurate diagnosis of hypertension and hence more appropriate treatment. PMID:27001299

  9. New evidence-based adaptive clinical trial methods for optimally integrating predictive biomarkers into oncology clinical development programs

    Institute of Scientific and Technical Information of China (English)

    Robert A.Beckman; Cong Chen

    2013-01-01

    Predictive biomarkers are important to the future of oncology; they can be used to identify patient populations who will benefit from therapy,increase the value of cancer medicines,and decrease the size and cost of clinical trials while increasing their chance of success.But predictive biomarkers do not always work.When unsuccessful,they add cost,complexity,and time to drug development.This perspective describes phases 2 and 3 development methods that efficiently and adaptively check the ability of a biomarker to predict clinical outcomes.In the end,the biomarker is emphasized to the extent that it can actually predict.

  10. Elevated expression of stromal palladin predicts poor clinical outcome in renal cell carcinoma.

    Directory of Open Access Journals (Sweden)

    Vivekanand Gupta

    Full Text Available The role that stromal renal cell carcinoma (RCC plays in support of tumor progression is unclear. Here we sought to determine the predictive value on patient survival of several markers of stromal activation and the feasibility of a fibroblast-derived extracellular matrix (ECM based three-dimensional (3D culture stemming from clinical specimens to recapitulate stromal behavior in vitro. The clinical relevance of selected stromal markers was assessed using a well annotated tumor microarray where stromal-marker levels of expression were evaluated and compared to patient outcomes. Also, an in vitro 3D system derived from fibroblasts harvested from patient matched normal kidney, primary RCC and metastatic tumors was employed to evaluate levels and localizations of known stromal markers such as the actin binding proteins palladin, alpha-smooth muscle actin (α-SMA, fibronectin and its spliced form EDA. Results suggested that RCCs exhibiting high levels of stromal palladin correlate with a poor prognosis, as demonstrated by overall survival time. Conversely, cases of RCCs where stroma presents low levels of palladin expression indicate increased survival times and, hence, better outcomes. Fibroblast-derived 3D cultures, which facilitate the categorization of stromal RCCs into discrete progressive stromal stages, also show increased levels of expression and stress fiber localization of α-SMA and palladin, as well as topographical organization of fibronectin and its splice variant EDA. These observations are concordant with expression levels of these markers in vivo. The study proposes that palladin constitutes a useful marker of poor prognosis in non-metastatic RCCs, while in vitro 3D cultures accurately represent the specific patient's tumor-associated stromal compartment. Our observations support the belief that stromal palladin assessments have clinical relevance thus validating the use of these 3D cultures to study both progressive RCC

  11. CLINICAL DATABASE ANALYSIS USING DMDT BASED PREDICTIVE MODELLING

    Directory of Open Access Journals (Sweden)

    Srilakshmi Indrasenan

    2013-04-01

    Full Text Available In recent years, predictive data mining techniques play a vital role in the field of medical informatics. These techniques help the medical practitioners in predicting various classes which is useful in prediction treatment. One of such major difficulty is prediction of survival rate in breast cancer patients. Breast cancer is a common disease these days and fighting against it is a tough battle for both the surgeons and the patients. To predict the survivability rate in breast cancer patients which helps the medical practitioner to select the type of treatment a predictive data mining technique called Diversified Multiple Decision Tree (DMDT classification is used. Additionally, to avoid difficulties from the outlier and skewed data, it is also proposed to perform the improvement of training space by outlier filtering and over sampling. As a result, this novel approach gives the survivability rate of the cancer patients based on which the medical practitioners can choose the type of treatment.

  12. Dose Addition Models Based on Biologically Relevant Reductions in Fetal Testosterone Accurately Predict Postnatal Reproductive Tract Alterations by a Phthalate Mixture in Rats.

    Science.gov (United States)

    Howdeshell, Kembra L; Rider, Cynthia V; Wilson, Vickie S; Furr, Johnathan R; Lambright, Christy R; Gray, L Earl

    2015-12-01

    Challenges in cumulative risk assessment of anti-androgenic phthalate mixtures include a lack of data on all the individual phthalates and difficulty determining the biological relevance of reduction in fetal testosterone (T) on postnatal development. The objectives of the current study were 2-fold: (1) to test whether a mixture model of dose addition based on the fetal T production data of individual phthalates would predict the effects of a 5 phthalate mixture on androgen-sensitive postnatal male reproductive tract development, and (2) to determine the biological relevance of the reductions in fetal T to induce abnormal postnatal reproductive tract development using data from the mixture study. We administered a dose range of the mixture (60, 40, 20, 10, and 5% of the top dose used in the previous fetal T production study consisting of 300 mg/kg per chemical of benzyl butyl (BBP), di(n)butyl (DBP), diethyl hexyl phthalate (DEHP), di-isobutyl phthalate (DiBP), and 100 mg dipentyl (DPP) phthalate/kg; the individual phthalates were present in equipotent doses based on their ability to reduce fetal T production) via gavage to Sprague Dawley rat dams on GD8-postnatal day 3. We compared observed mixture responses to predictions of dose addition based on the previously published potencies of the individual phthalates to reduce fetal T production relative to a reference chemical and published postnatal data for the reference chemical (called DAref). In addition, we predicted DA (called DAall) and response addition (RA) based on logistic regression analysis of all 5 individual phthalates when complete data were available. DA ref and DA all accurately predicted the observed mixture effect for 11 of 14 endpoints. Furthermore, reproductive tract malformations were seen in 17-100% of F1 males when fetal T production was reduced by about 25-72%, respectively. PMID:26350170

  13. PredictSNP2: A Unified Platform for Accurately Evaluating SNP Effects by Exploiting the Different Characteristics of Variants in Distinct Genomic Regions.

    Science.gov (United States)

    Bendl, Jaroslav; Musil, Miloš; Štourač, Jan; Zendulka, Jaroslav; Damborský, Jiří; Brezovský, Jan

    2016-05-01

    An important message taken from human genome sequencing projects is that the human population exhibits approximately 99.9% genetic similarity. Variations in the remaining parts of the genome determine our identity, trace our history and reveal our heritage. The precise delineation of phenotypically causal variants plays a key role in providing accurate personalized diagnosis, prognosis, and treatment of inherited diseases. Several computational methods for achieving such delineation have been reported recently. However, their ability to pinpoint potentially deleterious variants is limited by the fact that their mechanisms of prediction do not account for the existence of different categories of variants. Consequently, their output is biased towards the variant categories that are most strongly represented in the variant databases. Moreover, most such methods provide numeric scores but not binary predictions of the deleteriousness of variants or confidence scores that would be more easily understood by users. We have constructed three datasets covering different types of disease-related variants, which were divided across five categories: (i) regulatory, (ii) splicing, (iii) missense, (iv) synonymous, and (v) nonsense variants. These datasets were used to develop category-optimal decision thresholds and to evaluate six tools for variant prioritization: CADD, DANN, FATHMM, FitCons, FunSeq2 and GWAVA. This evaluation revealed some important advantages of the category-based approach. The results obtained with the five best-performing tools were then combined into a consensus score. Additional comparative analyses showed that in the case of missense variations, protein-based predictors perform better than DNA sequence-based predictors. A user-friendly web interface was developed that provides easy access to the five tools' predictions, and their consensus scores, in a user-understandable format tailored to the specific features of different categories of variations. To

  14. Discovery of a general method of solving the Schrödinger and dirac equations that opens a way to accurately predictive quantum chemistry.

    Science.gov (United States)

    Nakatsuji, Hiroshi

    2012-09-18

    Just as Newtonian law governs classical physics, the Schrödinger equation (SE) and the relativistic Dirac equation (DE) rule the world of chemistry. So, if we can solve these equations accurately, we can use computation to predict chemistry precisely. However, for approximately 80 years after the discovery of these equations, chemists believed that they could not solve SE and DE for atoms and molecules that included many electrons. This Account reviews ideas developed over the past decade to further the goal of predictive quantum chemistry. Between 2000 and 2005, I discovered a general method of solving the SE and DE accurately. As a first inspiration, I formulated the structure of the exact wave function of the SE in a compact mathematical form. The explicit inclusion of the exact wave function's structure within the variational space allows for the calculation of the exact wave function as a solution of the variational method. Although this process sounds almost impossible, it is indeed possible, and I have published several formulations and applied them to solve the full configuration interaction (CI) with a very small number of variables. However, when I examined analytical solutions for atoms and molecules, the Hamiltonian integrals in their secular equations diverged. This singularity problem occurred in all atoms and molecules because it originates from the singularity of the Coulomb potential in their Hamiltonians. To overcome this problem, I first introduced the inverse SE and then the scaled SE. The latter simpler idea led to immediate and surprisingly accurate solution for the SEs of the hydrogen atom, helium atom, and hydrogen molecule. The free complement (FC) method, also called the free iterative CI (free ICI) method, was efficient for solving the SEs. In the FC method, the basis functions that span the exact wave function are produced by the Hamiltonian of the system and the zeroth-order wave function. These basis functions are called complement

  15. Predicting Progression from Mild Cognitive Impairment to Alzheimer's Dementia Using Clinical, MRI, and Plasma Biomarkers via Probabilistic Pattern Classification.

    Directory of Open Access Journals (Sweden)

    Igor O Korolev

    Full Text Available Individuals with mild cognitive impairment (MCI have a substantially increased risk of developing dementia due to Alzheimer's disease (AD. In this study, we developed a multivariate prognostic model for predicting MCI-to-dementia progression at the individual patient level.Using baseline data from 259 MCI patients and a probabilistic, kernel-based pattern classification approach, we trained a classifier to distinguish between patients who progressed to AD-type dementia (n = 139 and those who did not (n = 120 during a three-year follow-up period. More than 750 variables across four data sources were considered as potential predictors of progression. These data sources included risk factors, cognitive and functional assessments, structural magnetic resonance imaging (MRI data, and plasma proteomic data. Predictive utility was assessed using a rigorous cross-validation framework.Cognitive and functional markers were most predictive of progression, while plasma proteomic markers had limited predictive utility. The best performing model incorporated a combination of cognitive/functional markers and morphometric MRI measures and predicted progression with 80% accuracy (83% sensitivity, 76% specificity, AUC = 0.87. Predictors of progression included scores on the Alzheimer's Disease Assessment Scale, Rey Auditory Verbal Learning Test, and Functional Activities Questionnaire, as well as volume/cortical thickness of three brain regions (left hippocampus, middle temporal gyrus, and inferior parietal cortex. Calibration analysis revealed that the model is capable of generating probabilistic predictions that reliably reflect the actual risk of progression. Finally, we found that the predictive accuracy of the model varied with patient demographic, genetic, and clinical characteristics and could be further improved by taking into account the confidence of the predictions.We developed an accurate prognostic model for predicting MCI-to-dementia progression

  16. Predictive value of clinical history compared with urodynamic study in 1,179 women

    Directory of Open Access Journals (Sweden)

    Jorge Milhem Haddad

    2016-02-01

    Full Text Available SUMMARY Objective: to determine the positive predictive value of clinical history in comparison with urodynamic study for the diagnosis of urinary incontinence. Methods: retrospective analysis comparing clinical history and urodynamic evaluation of 1,179 women with urinary incontinence. The urodynamic study was considered the gold standard, whereas the clinical history was the new test to be assessed. This was established after analyzing each method as the gold standard through the difference between their positive predictive values. Results: the positive predictive values of clinical history compared with urodynamic study for diagnosis of stress urinary incontinence, overactive bladder and mixed urinary incontinence were, respectively, 37% (95% CI 31-44, 40% (95% CI 33-47 and 16% (95% CI 14-19. Conclusion: we concluded that the positive predictive value of clinical history was low compared with urodynamic study for urinary incontinence diagnosis. The positive predictive value was low even among women with pure stress urinary incontinence.

  17. Genome-Scale Metabolic Model for the Green Alga Chlorella vulgaris UTEX 395 Accurately Predicts Phenotypes under Autotrophic, Heterotrophic, and Mixotrophic Growth Conditions.

    Science.gov (United States)

    Zuñiga, Cristal; Li, Chien-Ting; Huelsman, Tyler; Levering, Jennifer; Zielinski, Daniel C; McConnell, Brian O; Long, Christopher P; Knoshaug, Eric P; Guarnieri, Michael T; Antoniewicz, Maciek R; Betenbaugh, Michael J; Zengler, Karsten

    2016-09-01

    The green microalga Chlorella vulgaris has been widely recognized as a promising candidate for biofuel production due to its ability to store high lipid content and its natural metabolic versatility. Compartmentalized genome-scale metabolic models constructed from genome sequences enable quantitative insight into the transport and metabolism of compounds within a target organism. These metabolic models have long been utilized to generate optimized design strategies for an improved production process. Here, we describe the reconstruction, validation, and application of a genome-scale metabolic model for C. vulgaris UTEX 395, iCZ843. The reconstruction represents the most comprehensive model for any eukaryotic photosynthetic organism to date, based on the genome size and number of genes in the reconstruction. The highly curated model accurately predicts phenotypes under photoautotrophic, heterotrophic, and mixotrophic conditions. The model was validated against experimental data and lays the foundation for model-driven strain design and medium alteration to improve yield. Calculated flux distributions under different trophic conditions show that a number of key pathways are affected by nitrogen starvation conditions, including central carbon metabolism and amino acid, nucleotide, and pigment biosynthetic pathways. Furthermore, model prediction of growth rates under various medium compositions and subsequent experimental validation showed an increased growth rate with the addition of tryptophan and methionine. PMID:27372244

  18. Clinical diaries in COPD: compliance and utility in predicting acute exacerbations

    Directory of Open Access Journals (Sweden)

    Walters EH

    2012-07-01

    Full Text Available E Haydn Walters,1 Julia Walters,1 Karen E Wills,1 Andrew Robinson,2 Richard Wood-Baker11Menzies Research Institute Tasmania, University of Tasmania, Hobart; 2School of Nursing and Midwifery, University of Tasmania, Hobart, AustraliaBackground: Daily diaries are often used to collect data on disease activity, but are burdensome and compliance may be poor. Their use in chronic obstructive pulmonary disease (COPD and impact on the prevention and treatment of exacerbations is poorly researched.Methods: We investigated diary-keeping in COPD and ascertained items that best predicted emergency attendances for exacerbations. Participants in the active limb of a clinical trial in COPD kept daily diaries rating breathlessness, cough, sputum, physical activity, and use of reliever medication.Results: Data on 55 participants, 67% of whom were female, showed that overall compliance with diary-keeping was 62%. Participants educated to primary school level only had lower compliance (P = 0.05. Twenty patients had at least one emergency attendance, in whom the relative risk of an acute exacerbation for an increase in item score rose from six days prior to hospitalization, most sharply in the last two days. Even for optimal combinations of items, the positive predictive value was poor, the best combination being cough, activity level, and inhaler use.Conclusion: Good compliance can be achieved using daily diaries in COPD, although this is worse in those with a poor educational level. Diary-keeping is not accurate in predicting acute exacerbations, but could be substantially simplified without loss of efficiency.Keywords: chronic obstructive pulmonary disease, daily diary, secondary prevention

  19. A biometric approach to predictable treatment of clinical crown discrepancies.

    Science.gov (United States)

    Chu, Stephen J

    2007-08-01

    Dental professionals have long been guided by mathematical principles when interpreting aesthetic and tooth proportions for their patients. While many acknowledge that such principles are merely launch points for a smile design or reconstructive procedure, their existence appears to indicate practitioners' desire for predictable, objective, and reproducible means of achieving success in aesthetic dentistry. This article introduces innovative aesthetic measurement gauges as a means of objectively quantifying tooth size discrepancies and enabling the clinician to perform aesthetic restorative dentistry with success and predictability.

  20. Islet Oxygen Consumption Rate (OCR) Dose Predicts Insulin Independence in Clinical Islet Autotransplantation

    OpenAIRE

    Papas, Klearchos K; Bellin, Melena D.; Sutherland, David E. R.; Suszynski, Thomas M.; Kitzmann, Jennifer P.; Avgoustiniatos, Efstathios S.; Gruessner, Angelika C.; Mueller, Kathryn R.; Beilman, Gregory J.; Balamurugan, Appakalai N.; Gopalakrishnan Loganathan; Colton, Clark K.; Maria Koulmanda; Weir, Gordon C.; Josh J Wilhelm

    2015-01-01

    Background: Reliable in vitro islet quality assessment assays that can be performed routinely, prospectively, and are able to predict clinical transplant outcomes are needed. In this paper we present data on the utility of an assay based on cellular oxygen consumption rate (OCR) in predicting clinical islet autotransplant (IAT) insulin independence (II). IAT is an attractive model for evaluating characterization assays regarding their utility in predicting II due to an absence of confounding ...

  1. A random forest based risk model for reliable and accurate prediction of receipt of transfusion in patients undergoing percutaneous coronary intervention.

    Directory of Open Access Journals (Sweden)

    Hitinder S Gurm

    Full Text Available BACKGROUND: Transfusion is a common complication of Percutaneous Coronary Intervention (PCI and is associated with adverse short and long term outcomes. There is no risk model for identifying patients most likely to receive transfusion after PCI. The objective of our study was to develop and validate a tool for predicting receipt of blood transfusion in patients undergoing contemporary PCI. METHODS: Random forest models were developed utilizing 45 pre-procedural clinical and laboratory variables to estimate the receipt of transfusion in patients undergoing PCI. The most influential variables were selected for inclusion in an abbreviated model. Model performance estimating transfusion was evaluated in an independent validation dataset using area under the ROC curve (AUC, with net reclassification improvement (NRI used to compare full and reduced model prediction after grouping in low, intermediate, and high risk categories. The impact of procedural anticoagulation on observed versus predicted transfusion rates were assessed for the different risk categories. RESULTS: Our study cohort was comprised of 103,294 PCI procedures performed at 46 hospitals between July 2009 through December 2012 in Michigan of which 72,328 (70% were randomly selected for training the models, and 30,966 (30% for validation. The models demonstrated excellent calibration and discrimination (AUC: full model  = 0.888 (95% CI 0.877-0.899, reduced model AUC = 0.880 (95% CI, 0.868-0.892, p for difference 0.003, NRI = 2.77%, p = 0.007. Procedural anticoagulation and radial access significantly influenced transfusion rates in the intermediate and high risk patients but no clinically relevant impact was noted in low risk patients, who made up 70% of the total cohort. CONCLUSIONS: The risk of transfusion among patients undergoing PCI can be reliably calculated using a novel easy to use computational tool (https://bmc2.org/calculators/transfusion. This risk prediction

  2. Pressure Ulcers in Adults: Prediction and Prevention. Clinical Practice Guideline Number 3.

    Science.gov (United States)

    Agency for Health Care Policy and Research (DHHS/PHS), Rockville, MD.

    This package includes a clinical practice guideline, quick reference guide for clinicians, and patient's guide to predicting and preventing pressure ulcers in adults. The clinical practice guideline includes the following: overview of the incidence and prevalence of pressure ulcers; clinical practice guideline (introduction, risk assessment tools…

  3. Calibrating transition-metal energy levels and oxygen bands in first-principles calculations: Accurate prediction of redox potentials and charge transfer in lithium transition-metal oxides

    Science.gov (United States)

    Seo, Dong-Hwa; Urban, Alexander; Ceder, Gerbrand

    2015-09-01

    Transition-metal (TM) oxides play an increasingly important role in technology today, including applications such as catalysis, solar energy harvesting, and energy storage. In many of these applications, the details of their electronic structure near the Fermi level are critically important for their properties. We propose a first-principles-based computational methodology for the accurate prediction of oxygen charge transfer in TM oxides and lithium TM (Li-TM) oxides. To obtain accurate electronic structures, the Heyd-Scuseria-Ernzerhof (HSE06) hybrid functional is adopted, and the amount of exact Hartree-Fock exchange (mixing parameter) is adjusted to reproduce reference band gaps. We show that the HSE06 functional with optimal mixing parameter yields not only improved electronic densities of states, but also better energetics (Li-intercalation voltages) for LiCo O2 and LiNi O2 as compared to the generalized gradient approximation (GGA), Hubbard U corrected GGA (GGA +U ), and standard HSE06. We find that the optimal mixing parameters for TM oxides are system specific and correlate with the covalency (ionicity) of the TM species. The strong covalent (ionic) nature of TM-O bonding leads to lower (higher) optimal mixing parameters. We find that optimized HSE06 functionals predict stronger hybridization of the Co 3 d and O 2 p orbitals as compared to GGA, resulting in a greater contribution from oxygen states to charge compensation upon delithiation in LiCo O2 . We also find that the band gaps of Li-TM oxides increase linearly with the mixing parameter, enabling the straightforward determination of optimal mixing parameters based on GGA (α =0.0 ) and HSE06 (α =0.25 ) calculations. Our results also show that G0W0@GGA +U band gaps of TM oxides (M O ,M =Mn ,Co ,Ni ) and LiCo O2 agree well with experimental references, suggesting that G0W0 calculations can be used as a reference for the calibration of the mixing parameter in cases when no experimental band gap has been

  4. Somatic cell count distributions during lactation predict clinical mastitis

    NARCIS (Netherlands)

    Green, M.J.; Green, L.E.; Schukken, Y.H.; Bradley, A.J.; Peeler, E.J.; Barkema, H.W.; Haas, de Y.; Collis, V.J.; Medley, G.F.

    2004-01-01

    This research investigated somatic cell count (SCC) records during lactation, with the purpose of identifying distribution characteristics (mean and measures of variation) that were most closely associated with clinical mastitis. Three separate data sets were used, one containing quarter SCC (n = 14

  5. The Prediction of Academic and Clinical Performance in Medical School

    Science.gov (United States)

    Gough, Harrison G.; Hall, Wallace B.

    1975-01-01

    A study of medical student performance showed the clinical performance factor more or less unpredictable from aptitude and premedical academic achievement indices while the academic performance factor was forecast with acceptable accuracy by equations based on the Medical College Admissions Test and premedical grade point average. (JT)

  6. Stable feature selection for clinical prediction: exploiting ICD tree structure using Tree-Lasso.

    Science.gov (United States)

    Kamkar, Iman; Gupta, Sunil Kumar; Phung, Dinh; Venkatesh, Svetha

    2015-02-01

    Modern healthcare is getting reshaped by growing Electronic Medical Records (EMR). Recently, these records have been shown of great value towards building clinical prediction models. In EMR data, patients' diseases and hospital interventions are captured through a set of diagnoses and procedures codes. These codes are usually represented in a tree form (e.g. ICD-10 tree) and the codes within a tree branch may be highly correlated. These codes can be used as features to build a prediction model and an appropriate feature selection can inform a clinician about important risk factors for a disease. Traditional feature selection methods (e.g. Information Gain, T-test, etc.) consider each variable independently and usually end up having a long feature list. Recently, Lasso and related l1-penalty based feature selection methods have become popular due to their joint feature selection property. However, Lasso is known to have problems of selecting one feature of many correlated features randomly. This hinders the clinicians to arrive at a stable feature set, which is crucial for clinical decision making process. In this paper, we solve this problem by using a recently proposed Tree-Lasso model. Since, the stability behavior of Tree-Lasso is not well understood, we study the stability behavior of Tree-Lasso and compare it with other feature selection methods. Using a synthetic and two real-world datasets (Cancer and Acute Myocardial Infarction), we show that Tree-Lasso based feature selection is significantly more stable than Lasso and comparable to other methods e.g. Information Gain, ReliefF and T-test. We further show that, using different types of classifiers such as logistic regression, naive Bayes, support vector machines, decision trees and Random Forest, the classification performance of Tree-Lasso is comparable to Lasso and better than other methods. Our result has implications in identifying stable risk factors for many healthcare problems and therefore can

  7. Defining the Most Accurate Measurable Dimension(s of the Liver in Predicting Liver Volume Based on CT Volumetery and Reconstruction

    Directory of Open Access Journals (Sweden)

    Reza Saadat Mostafavi

    2010-05-01

    Full Text Available Background/Objective: The presence of liver volume has a great effect on diagnosis and management of different diseases such as lymphoproliferative conditions. "nPatients and Methods: Abdominal CT scan of 100 patients without any findings for liver disease (in history and imaging was subjected to volumetry and reconstruction. Along with the liver volume, in axial series, the AP diameter of the left lobe (in midline and right lobe (mid-clavicular and lateral maximum diameter of the liver in the mid-axiliary line and maximum diameter to IVC were calculated. In the coronal mid-axillary and sagittal mid-clavicular plane, maximum superior-inferior dimensions were calculated with their various combinations (multiplying. Regression analysis between dimensions and volume were performed. "nResults: The most accurate combination was the superior inferior sagittal dimension multiplied by AP diameter of the right lobe (R squared 0.78, P-value<0.001 and the most solitary dimension was the lateral dimension to IVC in the axial plane (R squared 0.57, P-value<0.001 with an interval of 9-11cm for 68% of normal. "nConclusion: We recommend the lateral maximum diameter of liver from surface to IVC in the axial plane in ultrasound for liver volume prediction with an interval of 9-11cm for 68% of normal. Out of this range is regarded as abnormal.

  8. Accurate Prediction of Essential Fundamental Properties for Semiconductors Used in Solar-Energy Conversion Devices from Range-Separated Hybrid Density Functional Theory

    KAUST Repository

    Harb, Moussab

    2016-01-05

    An essential issue in developing new semiconductors for photovoltaics devices is to design materials with appropriate fundamental parameters related to the light absorption, photogenerated exciton dissociation and charge carrier diffusion. These phenomena are governed by intrinsic properties of the semiconductor like the bandgap, the dielectric constant, the charge carrier effective masses, and the exciton binding energy. We present here the results of a systematic theoretical study on the fundamental properties of a series of selected semiconductors widely used in inorganic photovoltaic and dye-sensitized solar cells such as Si, Ge, CdS, CdSe, CdTe, and GaAs. These intrinsic properties were computed in the framework of the density functional theory (DFT) along with the standard PBE and the range-separated hybrid (HSE06) exchange-correlation functionals. Our calculations clearly show that the computed values using HSE06 reproduce with high accuracy the experimental data. The evaluation and accurate prediction of these key properties using HSE06 open nice perspectives for in silico design of new suitable candidate materials for solar energy conversion applications.

  9. Near-infrared spectroscopy in schizophrenia: A possible biomarker for predicting clinical outcome and treatment response

    Directory of Open Access Journals (Sweden)

    Shinsuke eKoike

    2013-11-01

    Full Text Available Functional near-infrared spectroscopy (fNIRS is a relatively new technique that can measure hemoglobin changes in brain tissues, and its use in psychiatry has been progressing rapidly. Although it has several disadvantages (e.g., relatively low spatial resolution and the possibility of shallow coverage in the depth of brain regions compared with other functional neuroimaging techniques (e.g., functional magnetic resonance imaging and positron emission tomography, fNIRS may be a candidate instrument for clinical use in psychiatry, as it can measure brain activity in naturalistic position easily and noninvasively. fNIRS instruments are also small and work silently, and can be moved almost everywhere including schools and care units. Previous fNIRS studies have shown that patients with schizophrenia have impaired activity and characteristic waveform patterns in the prefrontal cortex during the letter version of the verbal fluency task, and part of these results have been approved as one of the Advanced Medical Technologies as an aid for the differential diagnosis of depressive symptoms by the Ministry of Health, Labor and Welfare of Japan in 2009, which was the first such approval in the field of psychiatry. Moreover, previous studies suggest that the activity in the frontopolar prefrontal cortex is associated with their functions in chronic schizophrenia and is its next candidate biomarker. Future studies aimed at exploring fNIRS differences in various clinical stages, longitudinal changes, drug effects, and variations during different task paradigms will be needed to develop more accurate biomarkers that can be used to aid differential diagnosis, the comprehension of the present condition, the prediction of outcome, and the decision regarding treatment options in schizophrenia. Future fNIRS researches will require standardized measurement procedures, probe settings, analytical methods and tools, manuscript description, and database systems in an

  10. Prediction of individual clinical scores in patients with Parkinson's disease using resting-state functional magnetic resonance imaging.

    Science.gov (United States)

    Hou, YanBing; Luo, ChunYan; Yang, Jing; Ou, RuWei; Song, Wei; Wei, QianQian; Cao, Bei; Zhao, Bi; Wu, Ying; Shang, Hui-Fang; Gong, QiYong

    2016-07-15

    Neuroimaging holds the promise that it may one day aid the clinical assessment. However, the vast majority of studies using resting-state functional magnetic resonance imaging (fMRI) have reported average differences between Parkinson's disease (PD) patients and healthy controls, which do not permit inferences at the level of individuals. This study was to develop a model for the prediction of PD illness severity ratings from individual fMRI brain scan. The resting-state fMRI scans were obtained from 84 patients with PD and the Unified Parkinson's Disease Rating Scale-III (UPDRS-III) scores were obtained before scanning. The RVR method was used to predict clinical scores (UPDRS-III) from fMRI scans. The application of RVR to whole-brain resting-state fMRI data allowed prediction of UPDRS-III scores with statistically significant accuracy (correlation=0.35, P-value=0.001; mean sum of squares=222.17, P-value=0.002). This prediction was informed strongly by negative weight areas including prefrontal lobe and medial occipital lobe, and positive weight areas including medial parietal lobe. It was suggested that fMRI scans contained sufficient information about neurobiological change in patients with PD to permit accurate prediction about illness severity, on an individual subject basis. Our results provided preliminary evidence, as proof-of-concept, to support that fMRI might be possible to be a clinically useful quantitative assessment aid in PD at individual level. This may enable clinicians to target those uncooperative patients and machines to replace human for a more efficient use of health care resources. PMID:27288771

  11. Prenatal prediction of pulmonary hypoplasia: clinical, biometric, and Doppler velocity correlates

    NARCIS (Netherlands)

    J.A.M. Laudij (Jacqueline); D. Tibboel (Dick); S.G.F. Robben (Simon); R.R. de Krijger (Ronald); M.A.J. de Ridder (Maria); J.W. Wladimiroff (Juriy)

    2002-01-01

    textabstractOBJECTIVES: To determine the value of pulmonary artery Doppler velocimetry relative to fetal biometric indices and clinical correlates in the prenatal prediction of lethal lung hypoplasia (LH) in prolonged (>1 week) oligohydramnios. METHODS: Forty-two singleton pregnanc

  12. Do clinical prediction models improve concordance of treatment decisions in reproductive medicine?

    NARCIS (Netherlands)

    J.W. van der Steeg; P. Steures; M.J.C. Eijkemans; J.D.F. Habbema; P.M.M. Bossuyt; P.G.A. Hompes; F. van der Veen; B.W.J. Mol

    2006-01-01

    Objective To assess whether the use of clinical prediction models improves concordance between gynaecologists with respect to treatment decisions in reproductive medicine. Design We constructed 16 vignettes of subfertile couples by varying fertility history, postcoital test, sperm motility, follicle

  13. Locus heterogeneity for Waardenburg syndrome is predictive of clinical subtypes

    Energy Technology Data Exchange (ETDEWEB)

    Farrer, L.A.; Hoth, C. [Boston Univ. School of Medicine, MA (United States); Arnos, K.S. [Galludet Univ., Washington, DC (United States); Asher, J.H. Jr.; Friedman, T.B. [Michigan State Univ., East Lansing, MI (United States); Grundfast, K.M.; Lalwani, A.K. [National Institute on Deafness and Other Communication Disorders, Bethesda, MD (United States); Greenberg, J. [Univ. of Cape Town (South Africa); Diehl, S.R. [and others

    1994-10-01

    Waardenburg syndrome (WS) is a dominantly inherited and clinically variable syndrome of deafness, pigmentary changes, and distinctive facial features. Clinically, WS type I (WS1) is differentiated from WS type II (WS2) by the high frequency of dystopia canthorum in the family. In some families, WS is caused by mutations in the PAX3 gene on chromosome 2q. We have typed microsatellite markers within and flanking PAX3 in 41 WS1 kindreds and 26 WS2 kindreds in order to estimate the proportion of families with probable mutations in PAX3 and to study the relationship between phenotypic and genotypic heterogeneity. Evaluation of heterogeneity in location scores obtained by multilocus analysis indicated that WS is linked to PAX3 in 60% of all WS families and in 100% of WS1 families. None of the WS2 families were linked. In those families in which equivocal lod scores (between -2 and +1) were found, PAX3 mutations have been identified in 5 of the 15 WS1 families but in none of the 4 WS2 families. Although preliminary studies do not suggest any association between the phenotype and the molecular pathology in 20 families with known PAX3 mutations and in four patients with chromosomal abnormalities in the vicinity of PAX3, the presence of dystopia in multiple family members is a reliable indicator for identifying families likely to have a defect in PAX3. 59 refs., 3 figs., 5 tabs.

  14. How electrodiagnosis predicts clinical outcome of focal peripheral nerve lesions.

    Science.gov (United States)

    Robinson, Lawrence R

    2015-09-01

    This article reviews the electrodiagnostic (EDX) prognostic factors for focal traumatic and nontraumatic peripheral nerve injuries. Referring physicians and patients often benefit from general and nerve-specific prognostic information from the EDX consultant. Knowing the probable outcome from a nerve injury allows the referring physician to choose the best treatment options for his/her patients. Nerve injuries are variable in their mechanism, location, and pathophysiology. The general effects of the injuries on nerve and muscle are well known, but more research is needed for nerve-specific information. Several factors currently known to influence prognosis include: nature of the nerve trauma, amount of axon loss, recruitment in muscles supplied by the nerve, the extent of demyelination, and the distance to reinnervate functional muscles. This article reviews these general concepts and also nerve-specific EDX measures that predict outcome after focal neuropathies.

  15. Accurate Prediction of Hyperfine Coupling Constants in Muoniated and Hydrogenated Ethyl Radicals: Ab Initio Path Integral Simulation Study with Density Functional Theory Method.

    Science.gov (United States)

    Yamada, Kenta; Kawashima, Yukio; Tachikawa, Masanori

    2014-05-13

    We performed ab initio path integral molecular dynamics (PIMD) simulations with a density functional theory (DFT) method to accurately predict hyperfine coupling constants (HFCCs) in the ethyl radical (CβH3-CαH2) and its Mu-substituted (muoniated) compound (CβH2Mu-CαH2). The substitution of a Mu atom, an ultralight isotope of the H atom, with larger nuclear quantum effect is expected to strongly affect the nature of the ethyl radical. The static conventional DFT calculations of CβH3-CαH2 find that the elongation of one Cβ-H bond causes a change in the shape of potential energy curve along the rotational angle via the imbalance of attractive and repulsive interactions between the methyl and methylene groups. Investigation of the methyl-group behavior including the nuclear quantum and thermal effects shows that an unbalanced CβH2Mu group with the elongated Cβ-Mu bond rotates around the Cβ-Cα bond in a muoniated ethyl radical, quite differently from the CβH3 group with the three equivalent Cβ-H bonds in the ethyl radical. These rotations couple with other molecular motions such as the methylene-group rocking motion (inversion), leading to difficulties in reproducing the corresponding barrier heights. Our PIMD simulations successfully predict the barrier heights to be close to the experimental values and provide a significant improvement in muon and proton HFCCs given by the static conventional DFT method. Further investigation reveals that the Cβ-Mu/H stretching motion, methyl-group rotation, methylene-group rocking motion, and HFCC values deeply intertwine with each other. Because these motions are different between the radicals, a proper description of the structural fluctuations reflecting the nuclear quantum and thermal effects is vital to evaluate HFCC values in theory to be comparable to the experimental ones. Accordingly, a fundamental difference in HFCC between the radicals arises from their intrinsic molecular motions at a finite temperature, in

  16. Should I Pack My Umbrella? Clinical versus Statistical Prediction of Mental Health Decisions

    Science.gov (United States)

    Aegisdottir, Stefania; Spengler, Paul M.; White, Michael J.

    2006-01-01

    In this rejoinder, the authors respond to the insightful commentary of Strohmer and Arm, Chwalisz, and Hilton, Harris, and Rice about the meta-analysis on statistical versus clinical prediction techniques for mental health judgments. The authors address issues including the availability of statistical prediction techniques for real-life psychology…

  17. Critical appraisal of clinical prediction rules that aim to optimize treatment selection for musculoskeletal conditions

    NARCIS (Netherlands)

    T.R. Stanton (Tasha); M.J. Hancock (Mark J.); C. Maher (Chris); B.W. Koes (Bart)

    2010-01-01

    textabstractBackground. Clinical prediction rules (CPRs) for treatment selection in musculoskeletal conditions have become increasingly popular. Purpose. The purposes of this review are: (1) to critically appraise studies evaluating CPRs and (2) to consider the clinical utility and stage of developm

  18. Predicting academic performance and clinical competency for international dental students: seeking the most efficient and effective measures.

    Science.gov (United States)

    Stacey, D Graham; Whittaker, John M

    2005-02-01

    Measures used in the selection of international dental students to a U.S. D.D.S. program were examined to identify the grouping that most effectively and efficiently predicted academic performance and clinical competency. Archival records from the International Dental Program (IDP) at Loma Linda University provided data on 171 students who had trained in countries outside the United States. The students sought admission to the D.D.S. degree program, successful completion of which qualified them to sit for U.S. licensure. As with most dental schools, competition is high for admission to the D.D.S. program. The study's goal was to identify what measures contributed to a fair and accurate selection process for dental school applicants from other nations. Multiple regression analyses identified National Board Part II and dexterity measures as significant predictors of academic performance and clinical competency. National Board Part I, TOEFL, and faculty interviews added no significant additional help in predicting eventual academic performance and clinical competency.

  19. Assessment of clinical methods and ultrasound in predicting fetal birth weight in term pregnant women

    Directory of Open Access Journals (Sweden)

    Ruby Yadav

    2016-08-01

    Conclusions: Clinical estimation of birth weight clearly has a role in management of labour and delivery in a term pregnancy. Clinical estimation especially by SFH and times;AG method is as accurate as routine USG estimated in average birth weight. SFH and times; AG clinical formula can be of great value in developing countries like ours, where ultrasound is not available at many health care centers especially in a rural area. [Int J Reprod Contracept Obstet Gynecol 2016; 5(8.000: 2775-2779

  20. Use of clinical movement screening tests to predict injury in sport

    OpenAIRE

    Chimera, Nicole J.; Warren, Meghan

    2016-01-01

    Clinical movement screening tests are gaining popularity as a means to determine injury risk and to implement training programs to prevent sport injury. While these screens are being used readily in the clinical field, it is only recently that some of these have started to gain attention from a research perspective. This limits applicability and poses questions to the validity, and in some cases the reliability, of the clinical movement tests as they relate to injury prediction, intervention,...

  1. Clinical parameters predictive of malignancy of thyroid follicular neoplasms

    International Nuclear Information System (INIS)

    Needle aspiration biopsy is commonly employed in the evaluation of thyroid nodules. Unfortunately, the cytologic finding of a 'follicular neoplasm' does not distinguish between a thyroid adenoma and a follicular cancer. The purpose of this study was to identify clinical parameters that characterize patients with an increased risk of having a thyroid follicular cancer who preoperatively have a 'follicular neoplasm' identified by needle aspiration biopsy. A total of 395 patients initially treated at Vancouver General Hospital and the British Columbia Cancer Agency between the years of 1965 and 1985 were identified and their data were entered into a computer database. Patients with thyroid adenomas were compared to patients with follicular cancer using the chi-square test and Student's t-test. Statistically significant parameters that distinguished patients at risk of having a thyroid cancer (p less than 0.05) included age greater than 50 years, nodule size greater than 3 cm, and a history of neck irradiation. Sex, family history of goiter or neoplasm, alcohol and tobacco use, and use of exogenous estrogen were not significant parameters. Patients can be identified preoperatively to be at an increased risk of having a follicular cancer and accordingly appropriate surgical resection can be planned

  2. Predicting pressure ulcers: cases missed using a new clinical prediction rule.

    NARCIS (Netherlands)

    Schoonhoven, L.; Grobbee, D.E.; Bousema, M.T.; Buskens, E.

    2005-01-01

    AIM: The aim of this paper is to report a study describing patients with pressure ulcers that were incorrectly classified as 'not at risk' by the prediction rule and comparing them with patients who were correctly classified as 'not at risk'. BACKGROUND: Patients admitted to hospital are at risk of

  3. Can hypoxia-PET map hypoxic cell density heterogeneity accurately in an animal tumor model at a clinically obtainable image contrast?

    International Nuclear Information System (INIS)

    Background: PET allows non-invasive mapping of tumor hypoxia, but the combination of low resolution, slow tracer adduct-formation and slow clearance of unbound tracer remains problematic. Using a murine tumor with a hypoxic fraction within the clinical range and a tracer post-injection sampling time that results in clinically obtainable tumor-to-reference tissue activity ratios, we have analyzed to what extent inherent limitations actually compromise the validity of PET-generated hypoxia maps. Materials and methods: Mice bearing SCCVII tumors were injected with the PET hypoxia-marker fluoroazomycin arabinoside (FAZA), and the immunologically detectable hypoxia marker, pimonidazole. Tumors and reference tissue (muscle, blood) were harvested 0.5, 2 and 4 h after FAZA administration. Tumors were analyzed for global (well counter) and regional (autoradiography) tracer distribution and compared to pimonidazole as visualized using immunofluorescence microscopy. Results: Hypoxic fraction as measured by pimonidazole staining ranged from 0.09 to 0.32. FAZA tumor to reference tissue ratios were close to unity 0.5 h post-injection but reached values of 2 and 6 when tracer distribution time was prolonged to 2 and 4 h, respectively. A fine-scale pixel-by-pixel comparison of autoradiograms and immunofluorescence images revealed a clear spatial link between FAZA and pimonidazole-adduct signal intensities at 2 h and later. Furthermore, when using a pixel size that mimics the resolution in PET, an excellent correlation between pixel FAZA mean intensity and density of hypoxic cells was observed already at 2 h post-injection. Conclusions: Despite inherent weaknesses, PET-hypoxia imaging is able to generate quantitative tumor maps that accurately reflect the underlying microscopic reality (i.e., hypoxic cell density) in an animal model with a clinical realistic image contrast.

  4. Application of a biochemical and clinical model to predict individual survival in patients with end-stage liver disease

    Institute of Scientific and Technical Information of China (English)

    Eduardo Vilar Gomez; Luis Calzadilla Bertot; Bienvenido Gra Oramas; Enrique Arus Soler; Raimundo Llanio Navarro; Javier Diaz Elias; Oscar Villa Jiménez; Maria del Rosario Abreu Vazquez

    2009-01-01

    AIM:To investigate the capability of a biochemical and clinical model,BioCliM,in predicting the survival of cirrhotic patients.METHODS:We prospectively evaluated the survival of 172 cirrhotic patients.The model was constructed using clinical (ascites,encephalopathy and variceal bleeding) and biochemical (serum creatinine and serum total bilirubin) variables that were selected from a Cox proportional hazards model.It was applied to estimate 12-,52- and 104-wk survival.The model's calibration using the Hosmer-Lemeshow statistic was computed at 104 wk in a validation dataset.Finally,the model's validity was tested among an independent set of 85 patients who were stratified into 2 risk groups (low risk ≤8 and high risk>8).RESULTS:In the validation cohort,all measures of fit,discrimination and calibration were improved when the biochemical and clinical model was used.The proposed model had better predictive values (c-statistic:0.90,0.91,0.91) than the Model for End-stage Liver Disease (MELD) and Child-Pugh (CP) scores for 12-,52- and 104-wk mortality,respectively.In addition,the Hosmer-Lemeshow (H-L) statistic revealed that the biochemical and clinical model (H-L,4.69) is better calibrated than MELD (H-L,17.06) and CP (H-L,14.23).There were no significant differences between the observed and expected survival curves in the stratified risk groups (low risk,P=0.61;high risk,P=0.77).CONCLUSION:Our data suggest that the proposed model is able to accurately predict survival in cirrhotic patients.

  5. Prognosis after Acute Myocardial Infarction as Predicted by C-reactive Protein and Clinical Variables

    Directory of Open Access Journals (Sweden)

    Angelo Modica MD, PhD

    2013-02-01

    Full Text Available Background:Raised concentrations of C-reactive protein (CRP have been reported to be strongly related to an adverse long term prognosis in patients with acute myocardial infarction (AMI. However, adjustments for clinical variables as well as interaction between variables have been incomplete. The aims of this study were to examine the predictive value of baseline concentrations of CRP for mortality after adjustment for important clinical variables and to compare the clinical usefulness of CRP with easily available clinical variables in the prediction of long term survival.Methods:Five hundred and thirty-one patients with AMI were included. A blood sample for CRP was obtained on admission. All patients were followed for a minimum of two years and death of any cause was recorded as the study end point.Results:In logistic regression analysis, the interaction term Age by Killip class > 1, the variable glomerular filtration rate as well as the interaction term Age by Atrial fibrillation were retained. The resulting model correctly predicted death or not in 81% of the patients. CRP did not contribute to the final model.Conclusions:CRP does not independently predict long-term mortality after an AMI after adjustments for clinical variables and interaction. CRP has no value beyond clinical variables in predicting death after AMI.

  6. A nomogram to predict Gleason sum upgrading of clinically diagnosed localized prostate cancer among Chinese patients

    Institute of Scientific and Technical Information of China (English)

    Jin-You Wang; Yao Zhu; Chao-Fu Wang; Shi-Lin Zhang; Bo Dai; Ding-Wei Ye

    2014-01-01

    Although several models have been developed to predict the probability of Gleason sum upgrading between biopsy and radical prostatectomy specimens, most of these models are restricted to prostate-specific antigen screening-detected prostate cancer. This study aimed to build a nomogram for the prediction of Gleason sum upgrading in clinical y diagnosed prostate cancer. The study cohort comprised 269 Chinese prostate cancer patients who underwent prostate biopsy with a minimum of 10 cores and were subsequently treated with radical prostatectomy. Of al included patients, 220 (81.8%) were referred with clinical symptoms. The prostate-specific antigen level, primary and secondary biopsy Gleason scores, and clinical T category were used in a multivariate logistic regression model to predict the probability of Gleason sum upgrading. The developed nomogram was validated internally. Gleason sum upgrading was observed in 90 (33.5%) patients. Our nomogram showed a bootstrap-corrected concordance index of 0.789 and good calibration using 4 readily available variables. The nomogram also demonstrated satisfactory statistical performance for predicting significant upgrading. External validation of the nomogram published by Chun et al. in our cohort showed a marked discordance between the observed and predicted probabilities of Gleason sum upgrading. In summary, a new nomogram to predict Gleason sum upgrading in clinically diagnosed prostate cancer was developed, and it demonstrated good statistical performance upon internal validation.

  7. A nomogram to predict Gleason sum upgrading of clinically diagnosed localized prostate cancer among Chinese patients

    Directory of Open Access Journals (Sweden)

    Jin-You Wang

    2014-05-01

    Full Text Available Although several models have been developed to predict the probability of Gleason sum upgrading between biopsy and radical prostatectomy specimens, most of these models are restricted to prostate-specific antigen screening-detected prostate cancer. This study aimed to build a nomogram for the prediction of Gleason sum upgrading in clinically diagnosed prostate cancer. The study cohort comprised 269 Chinese prostate cancer patients who underwent prostate biopsy with a minimum of 10 cores and were subsequently treated with radical prostatectomy. Of all included patients, 220 (81.8% were referred with clinical symptoms. The prostate-specific antigen level, primary and secondary biopsy Gleason scores, and clinical T category were used in a multivariate logistic regression model to predict the probability of Gleason sum upgrading. The developed nomogram was validated internally. Gleason sum upgrading was observed in 90 (33.5% patients. Our nomogram showed a bootstrap-corrected concordance index of 0.789 and good calibration using 4 readily available variables. The nomogram also demonstrated satisfactory statistical performance for predicting significant upgrading. External validation of the nomogram published by Chun et al. in our cohort showed a marked discordance between the observed and predicted probabilities of Gleason sum upgrading. In summary, a new nomogram to predict Gleason sum upgrading in clinically diagnosed prostate cancer was developed, and it demonstrated good statistical performance upon internal validation.

  8. Clinical presentation and outcome prediction of clinical, serological, and histopathological classification schemes in ANCA-associated vasculitis with renal involvement.

    Science.gov (United States)

    Córdova-Sánchez, Bertha M; Mejía-Vilet, Juan M; Morales-Buenrostro, Luis E; Loyola-Rodríguez, Georgina; Uribe-Uribe, Norma O; Correa-Rotter, Ricardo

    2016-07-01

    Several classification schemes have been developed for anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV), with actual debate focusing on their clinical and prognostic performance. Sixty-two patients with renal biopsy-proven AAV from a single center in Mexico City diagnosed between 2004 and 2013 were analyzed and classified under clinical (granulomatosis with polyangiitis [GPA], microscopic polyangiitis [MPA], renal limited vasculitis [RLV]), serological (proteinase 3 anti-neutrophil cytoplasmic antibodies [PR3-ANCA], myeloperoxidase anti-neutrophil cytoplasmic antibodies [MPO-ANCA], ANCA negative), and histopathological (focal, crescenteric, mixed-type, sclerosing) categories. Clinical presentation parameters were compared at baseline between classification groups, and the predictive value of different classification categories for disease and renal remission, relapse, renal, and patient survival was analyzed. Serological classification predicted relapse rate (PR3-ANCA hazard ratio for relapse 2.93, 1.20-7.17, p = 0.019). There were no differences in disease or renal remission, renal, or patient survival between clinical and serological categories. Histopathological classification predicted response to therapy, with a poorer renal remission rate for sclerosing group and those with less than 25 % normal glomeruli; in addition, it adequately delimited 24-month glomerular filtration rate (eGFR) evolution, but it did not predict renal nor patient survival. On multivariate models, renal replacement therapy (RRT) requirement (HR 8.07, CI 1.75-37.4, p = 0.008) and proteinuria (HR 1.49, CI 1.03-2.14, p = 0.034) at presentation predicted renal survival, while age (HR 1.10, CI 1.01-1.21, p = 0.041) and infective events during the induction phase (HR 4.72, 1.01-22.1, p = 0.049) negatively influenced patient survival. At present, ANCA-based serological classification may predict AAV relapses, but neither clinical nor serological

  9. Predictive capacity of risk assessment scales and clinical judgment for pressure ulcers: a meta-analysis.

    Science.gov (United States)

    García-Fernández, Francisco Pedro; Pancorbo-Hidalgo, Pedro L; Agreda, J Javier Soldevilla

    2014-01-01

    A systematic review with meta-analysis was completed to determine the capacity of risk assessment scales and nurses' clinical judgment to predict pressure ulcer (PU) development. Electronic databases were searched for prospective studies on the validity and predictive capacity of PUs risk assessment scales published between 1962 and 2010 in English, Spanish, Portuguese, Korean, German, and Greek. We excluded gray literature sources, integrative review articles, and retrospective or cross-sectional studies. The methodological quality of the studies was assessed according to the guidelines of the Critical Appraisal Skills Program. Predictive capacity was measured as relative risk (RR) with 95% confidence intervals. When 2 or more valid original studies were found, a meta-analysis was conducted using a random-effect model and sensitivity analysis. We identified 57 studies, including 31 that included a validation study. We also retrieved 4 studies that tested clinical judgment as a risk prediction factor. Meta-analysis produced the following pooled predictive capacity indicators: Braden (RR = 4.26); Norton (RR = 3.69); Waterlow (RR = 2.66); Cubbin-Jackson (RR = 8.63); EMINA (RR = 6.17); Pressure Sore Predictor Scale (RR = 21.4); and clinical judgment (RR = 1.89). Pooled analysis of 11 studies found adequate risk prediction capacity in various clinical settings; the Braden, Norton, EMINA (mEntal state, Mobility, Incontinence, Nutrition, Activity), Waterlow, and Cubbin-Jackson scales showed the highest predictive capacity. The clinical judgment of nurses was found to achieve inadequate predictive capacity when used alone, and should be used in combination with a validated scale.

  10. Use of clinical movement screening tests to predict injury in sport.

    Science.gov (United States)

    Chimera, Nicole J; Warren, Meghan

    2016-04-18

    Clinical movement screening tests are gaining popularity as a means to determine injury risk and to implement training programs to prevent sport injury. While these screens are being used readily in the clinical field, it is only recently that some of these have started to gain attention from a research perspective. This limits applicability and poses questions to the validity, and in some cases the reliability, of the clinical movement tests as they relate to injury prediction, intervention, and prevention. This editorial will review the following clinical movement screening tests: Functional Movement Screen™, Star Excursion Balance Test, Y Balance Test, Drop Jump Screening Test, Landing Error Scoring System, and the Tuck Jump Analysis in regards to test administration, reliability, validity, factors that affect test performance, intervention programs, and usefulness for injury prediction. It is important to review the aforementioned factors for each of these clinical screening tests as this may help clinicians interpret the current body of literature. While each of these screening tests were developed by clinicians based on what appears to be clinical practice, this paper brings to light that this is a need for collaboration between clinicians and researchers to ensure validity of clinically meaningful tests so that they are used appropriately in future clinical practice. Further, this editorial may help to identify where the research is lacking and, thus, drive future research questions in regards to applicability and appropriateness of clinical movement screening tools. PMID:27114928

  11. Development and clinical evaluation of a highly accurate dengue NS1 rapid test: from the preparation of a soluble NS1 antigen to the construction of an RDT.

    Science.gov (United States)

    Lee, Jihoo; Kim, Hak-Yong; Chong, Chom-Kyu; Song, Hyun-Ok

    2015-06-01

    Early diagnosis of dengue virus (DENV) is important. There are numerous products on the market claiming to detect DENV NS1, but these are not always reliable. In this study, a highly sensitive and accurate rapid diagnostic test (RDT) was developed using anti-dengue NS1 monoclonal antibodies. A recombinant NS1 protein was produced with high antigenicity and purity. Monoclonal antibodies were raised against this purified NS1 antigen. The RDT was constructed using a capturing (4A6A10, Kd=7.512±0.419×10(-9)) and a conjugating antibody (3E12E6, Kd=7.032±0.322×10(-9)). The diagnostic performance was evaluated with NS1-positive clinical samples collected from various dengue endemic countries and compared to SD BioLine Dengue NS1 Ag kit. The constructed RDT exhibited higher sensitivity (92.9%) with more obvious diagnostic performance than the commercial kit (83.3%). The specificity of constructed RDT was 100%. The constructed RDT could offer a reliable point-of-care testing tool for the early detection of dengue infections in remote areas and contribute to the control of dengue-related diseases.

  12. Clinical algorithm for improved prediction of ambulation and patient stratification after incomplete spinal cord injury.

    Science.gov (United States)

    Zörner, Björn; Blanckenhorn, Wolf U; Dietz, Volker; Curt, Armin

    2010-01-01

    The extent of ambulatory recovery after motor incomplete spinal cord injury (miSCI) differs considerably amongst affected persons. This makes individual outcome prediction difficult and leads to increased within-group variation in clinical trials. The aims of this study on subjects with miSCI were: (1) to rank the strongest single predictors and predictor combinations of later walking capacity; (2) to develop a reliable algorithm for clinical prediction; and (3) to identify subgroups with only limited recovery of walking function. Correlation and logistic regression analyses were performed on a dataset of 90 subjects with tetra- or paraparesis, recruited in a prospective European multicenter study. Eleven measures obtained in the subacute injury period, including clinical examination, tibial somatosensory evoked potentials (tSSEP), and demographic factors, were related to ambulatory outcome (WISCI II, 6minWT) 6 months after injury. The lower extremity motor score (LEMS) alone and in combination was identified as most predictive for later walking capacity in miSCI. Ambulatory outcome of subjects with tetraparesis was correctly predicted for 92% (WISCI II) or 100% (6minWT) of the cases when LEMS was combined with either tSSEP or the ASIA Impairment Scale, respectively. For individuals with paraparesis, prediction was less distinct, mainly due to low prediction rates for individuals with poor walking outcome. A clinical algorithm was generated that allowed for the identification of a subgroup composed of individuals with tetraparesis and poor ambulatory recovery. These data provide evidence that a combination of predictors enables a reliable prediction of walking function and early patient stratification for clinical trials in miSCI.

  13. GliomaPredict: a clinically useful tool for assigning glioma patients to specific molecular subtypes

    Directory of Open Access Journals (Sweden)

    Fine Howard A

    2010-07-01

    Full Text Available Abstract Background Advances in generating genome-wide gene expression data have accelerated the development of molecular-based tumor classification systems. Tools that allow the translation of such molecular classification schemas from research into clinical applications are still missing in the emerging era of personalized medicine. Results We developed GliomaPredict as a computational tool that allows the fast and reliable classification of glioma patients into one of six previously published stratified subtypes based on sets of extensively validated classifiers derived from hundreds of glioma transcriptomic profiles. Our tool utilizes a principle component analysis (PCA-based approach to generate a visual representation of the analyses, quantifies the confidence of the underlying subtype assessment and presents results as a printable PDF file. GliomaPredict tool is implemented as a plugin application for the widely-used GenePattern framework. Conclusions GliomaPredict provides a user-friendly, clinically applicable novel platform for instantly assigning gene expression-based subtype in patients with gliomas thereby aiding in clinical trial design and therapeutic decision-making. Implemented as a user-friendly diagnostic tool, we expect that in time GliomaPredict, and tools like it, will become routinely used in translational/clinical research and in the clinical care of patients with gliomas.

  14. Nomograms for the Prediction of Pathologic Stage of Clinically Localized Prostate Cancer in Korean Men

    OpenAIRE

    Song, Cheryn; Kang, Taejin; Ro, Jae Y.; Lee, Moo-Song; Kim, Choung-Soo; Ahn, Hanjong

    2005-01-01

    We analyzed the prostate cancer data of 317 Korean men with clinically localized prostate cancer who underwent radical prostatectomy at Asan Medical Center between June 1990 and November 2003 to construct nomograms predicting the pathologic stage of these tumors, and compared the outcome with preexisting nomograms. Multinomial log-linear regression was performed for the simultaneous prediction of organ-confined disease (OCD), extracapsular extension (ECE), seminal vesicle invasion (SVI) and l...

  15. A nomogram to predict Gleason sum upgrading of clinically diagnosed localized prostate cancer among Chinese patients

    OpenAIRE

    Jin-You Wang; Yao Zhu; Chao-Fu Wang; Shi-Lin Zhang; Bo Dai; Ding-Wei Ye

    2014-01-01

    Although several models have been developed to predict the probability of Gleason sum upgrading between biopsy and radical prostatectomy specimens, most of these models are restricted to prostate-specific antigen screening-detected prostate cancer. This study aimed to build a nomogram for the prediction of Gleason sum upgrading in clinically diagnosed prostate cancer. The study cohort comprised 269 Chinese prostate cancer patients who underwent prostate biopsy with a minimum of 10 cores and w...

  16. NetMHC-3.0: accurate web accessible predictions of human, mouse and monkey MHC class I affinities for peptides of length 8-11

    DEFF Research Database (Denmark)

    Lundegaard, Claus; Lamberth, K; Harndahl, M;

    2008-01-01

    NetMHC-3.0 is trained on a large number of quantitative peptide data using both affinity data from the Immune Epitope Database and Analysis Resource (IEDB) and elution data from SYFPEITHI. The method generates high-accuracy predictions of major histocompatibility complex (MHC): peptide binding....... The predictions are based on artificial neural networks trained on data from 55 MHC alleles (43 Human and 12 non-human), and position-specific scoring matrices (PSSMs) for additional 67 HLA alleles. As only the MHC class I prediction server is available, predictions are possible for peptides of length 8......–11 for all 122 alleles. artificial neural network predictions are given as actual IC50 values whereas PSSM predictions are given as a log-odds likelihood scores. The output is optionally available as download for easy post-processing. The training method underlying the server is the best available, and has...

  17. Pulmonary embolism in intensive care unit: Predictive factors, clinical manifestations and outcome

    OpenAIRE

    Bahloul Mabrouk; Chaari Anis; Kallel Hatem; Abid Leila; Hamida Chokri Ben; Dammak Hassen; Rekik Noureddine; Mnif Jameleddine; Chelly Hedi; Bouaziz Mounir

    2010-01-01

    Objective : To determine predictive factors, clinical and demographics characteristics of patients with pulmonary embolism (PE) in ICU, and to identify factors associated with poor outcome in the hospital and in the ICU. Methods : During a four-year prospective study, a medical committee of six ICU physicians prospectively examined all available data for each patient in order to classify patients according to the level of clinical suspicion of pulmonary thromboembolism. During the study...

  18. Clinical Nomogram for Predicting Survival of Esophageal Cancer Patients after Esophagectomy

    OpenAIRE

    Jinlin Cao; Ping Yuan; Luming Wang; Yiqing Wang; Honghai Ma; Xiaoshuai Yuan; Wang Lv; Jian Hu

    2016-01-01

    The aim of this study was to construct an effective clinical nomogram for predicting the survival of esophageal cancer patients after esophagectomy. We identified esophageal cancer patients (n = 4,281) who underwent esophagectomy between 1988 and 2007 from the Surveillance, Epidemiology, and End Results (SEER) 18 registries database. Clinically significant parameters for survival were used to construct a nomogram based on Cox regression analyses. The model was validated using bootstrap resamp...

  19. Early seizures in patients with acute stroke: Frequency, predictive factors, and effect on clinical outcome

    OpenAIRE

    Andrea Alberti; Maurizio Paciaroni; Valeria Caso; Michele Venti; Francesco Palmerini; Giancarlo Agnelli

    2008-01-01

    Andrea Alberti, Maurizio Paciaroni, Valeria Caso, Michele Venti, Francesco Palmerini, Giancarlo AgnelliStroke Unit and Division of Internal and Cardiovascular Medicine, University of Perugia, Perugia, ItalyBackground: Early seizure (ES) may complicate the clinical course of patients with acute stroke. The aim of this study was to assess the rate of and the predictive factors for ES as well the effects of ES on the clinical outcome at hospital discharge in patients with first-ever stroke.Patie...

  20. Comparison of four clinical scores for the predicting lower limb deep venous thrombosis in Chinese patients

    Institute of Scientific and Technical Information of China (English)

    Li Zhua; Min Liu; Xiaojuan Guo; Jianguo Wang; Youmin Guo; Chen Wang; Hongxia Ma; Yulin Guo

    2008-01-01

    To evaluate Wells, Kahn, St.Andr é and Constans scores for the prediction of deep venous thrombosis in Chinese patients.Methods:One hundred and seventy-two patients, prospectively, blinded referred for evaluation with four clinical-score systems for suspected deep venous thrombosis, were examined by ultrasonography.Sensitivity, specificity, positive predictive value, nega- tive predictive value and receiver operation curves were calculated for four clinical scores.The difference between areas of the ROC curve for each of the scores was compared with others and reference line.Results:Forty-six of 172 patients had deep venous throm- bosis proven by sonography.The sensitivity, specificity, positive predictive value and negative predictive value for Wells score was 91.3%, 27.4% and 74.2% respectively, for Constans score; 95.7%, 34.9%, 34.9% and 95.7% respectively.Area under ROV curve of Constans with the reference line.Conclusion:Based on the results of our study, the sensitivity, negative prediction value and area under ROC Considering the aim of the clinical assessment, Constans score and Wells score are more efficient for Chinese hospitalized patients.

  1. A Multi-Center Prospective Derivation and Validation of a Clinical Prediction Tool for Severe Clostridium difficile Infection.

    LENUS (Irish Health Repository)

    Na, Xi

    2015-04-23

    Prediction of severe clinical outcomes in Clostridium difficile infection (CDI) is important to inform management decisions for optimum patient care. Currently, treatment recommendations for CDI vary based on disease severity but validated methods to predict severe disease are lacking. The aim of the study was to derive and validate a clinical prediction tool for severe outcomes in CDI.

  2. Rapid and accurate detection of Mycobacterium tuberculosis in sputum samples by Cepheid Xpert MTB/RIF assay--a clinical validation study.

    Directory of Open Access Journals (Sweden)

    Andrea Rachow

    Full Text Available BACKGROUND: A crucial impediment to global tuberculosis control is the lack of an accurate, rapid diagnostic test for detection of patients with active TB. A new, rapid diagnostic method, (Cepheid Xpert MTB/RIF Assay, is an automated sample preparation and real-time PCR instrument, which was shown to have good potential as an alternative to current reference standard sputum microscopy and culture. METHODS: We performed a clinical validation study on diagnostic accuracy of the Xpert MTB/RIF Assay in a TB and HIV endemic setting. Sputum samples from 292 consecutively enrolled adults from Mbeya, Tanzania, with suspected TB were subject to analysis by the Xpert MTB/RIF Assay. The diagnostic performance of Xpert MTB/RIF Assay was compared to standard sputum smear microscopy and culture. Confirmed Mycobacterium tuberculosis in a positive culture was used as a reference standard for TB diagnosis. RESULTS: Xpert MTB/RIF Assay achieved 88.4% (95%CI = 78.4% to 94.9% sensitivity among patients with a positive culture and 99% (95%CI = 94.7% to 100.0% specificity in patients who had no TB. HIV status did not affect test performance in 172 HIV-infected patients (58.9% of all participants. Seven additional cases (9.1% of 77 were detected by Xpert MTB/RIF Assay among the group of patients with clinical TB who were culture negative. Within 45 sputum samples which grew non-tuberculous mycobacteria the assay's specificity was 97.8% (95%CI = 88.2% to 99.9%. CONCLUSIONS: The Xpert MTB/RIF Assay is a highly sensitive, specific and rapid method for diagnosing TB which has potential to complement the current reference standard of TB diagnostics and increase its overall sensitivity. Its usefulness in detecting sputum smear and culture negative patients needs further study. Further evaluation in high burden TB and HIV areas under programmatic health care settings to ascertain applicability, cost-effectiveness, robustness and local acceptance are required.

  3. Prediction of Clinical Deterioration in Hospitalized Adult Patients with Hematologic Malignancies Using a Neural Network Model

    Science.gov (United States)

    Hu, Scott B.; Wong, Deborah J. L.; Correa, Aditi; Li, Ning; Deng, Jane C.

    2016-01-01

    Introduction Clinical deterioration (ICU transfer and cardiac arrest) occurs during approximately 5–10% of hospital admissions. Existing prediction models have a high false positive rate, leading to multiple false alarms and alarm fatigue. We used routine vital signs and laboratory values obtained from the electronic medical record (EMR) along with a machine learning algorithm called a neural network to develop a prediction model that would increase the predictive accuracy and decrease false alarm rates. Design Retrospective cohort study. Setting The hematologic malignancy unit in an academic medical center in the United States. Patient Population Adult patients admitted to the hematologic malignancy unit from 2009 to 2010. Intervention None. Measurements and Main Results Vital signs and laboratory values were obtained from the electronic medical record system and then used as predictors (features). A neural network was used to build a model to predict clinical deterioration events (ICU transfer and cardiac arrest). The performance of the neural network model was compared to the VitalPac Early Warning Score (ViEWS). Five hundred sixty five consecutive total admissions were available with 43 admissions resulting in clinical deterioration. Using simulation, the neural network outperformed the ViEWS model with a positive predictive value of 82% compared to 24%, respectively. Conclusion We developed and tested a neural network-based prediction model for clinical deterioration in patients hospitalized in the hematologic malignancy unit. Our neural network model outperformed an existing model, substantially increasing the positive predictive value, allowing the clinician to be confident in the alarm raised. This system can be readily implemented in a real-time fashion in existing EMR systems. PMID:27532679

  4. NetMHC-3.0: accurate web accessible predictions of human, mouse and monkey MHC class I affinities for peptides of length 8-11.

    Science.gov (United States)

    Lundegaard, Claus; Lamberth, Kasper; Harndahl, Mikkel; Buus, Søren; Lund, Ole; Nielsen, Morten

    2008-07-01

    NetMHC-3.0 is trained on a large number of quantitative peptide data using both affinity data from the Immune Epitope Database and Analysis Resource (IEDB) and elution data from SYFPEITHI. The method generates high-accuracy predictions of major histocompatibility complex (MHC): peptide binding. The predictions are based on artificial neural networks trained on data from 55 MHC alleles (43 Human and 12 non-human), and position-specific scoring matrices (PSSMs) for additional 67 HLA alleles. As only the MHC class I prediction server is available, predictions are possible for peptides of length 8-11 for all 122 alleles. artificial neural network predictions are given as actual IC(50) values whereas PSSM predictions are given as a log-odds likelihood scores. The output is optionally available as download for easy post-processing. The training method underlying the server is the best available, and has been used to predict possible MHC-binding peptides in a series of pathogen viral proteomes including SARS, Influenza and HIV, resulting in an average of 75-80% confirmed MHC binders. Here, the performance is further validated and benchmarked using a large set of newly published affinity data, non-redundant to the training set. The server is free of use and available at: http://www.cbs.dtu.dk/services/NetMHC.

  5. Predictive Validity of DSM-IV Oppositional Defiant and Conduct Disorders in Clinically Referred Preschoolers

    Science.gov (United States)

    Keenan, Kate; Boeldt, Debra; Chen, Diane; Coyne, Claire; Donald, Radiah; Duax, Jeanne; Hart, Katherine; Perrott, Jennifer; Strickland, Jennifer; Danis, Barbara; Hill, Carri; Davis, Shante; Kampani, Smita; Humphries, Marisha

    2011-01-01

    Background: Diagnostic validity of oppositional defiant and conduct disorders (ODD and CD) for preschoolers has been questioned based on concerns regarding the ability to differentiate normative, transient disruptive behavior from clinical symptoms. Data on concurrent validity have accumulated, but predictive validity is limited. Predictive…

  6. Is scoring system of computed tomography based metric parameters can accurately predicts shock wave lithotripsy stone-free rates and aid in the development of treatment strategies?

    Directory of Open Access Journals (Sweden)

    Yasser ALI Badran

    2016-01-01

    Conclusion: Stone size, stone density (HU, and SSD is simple to calculate and can be reported by radiologists to applying combined score help to augment predictive power of SWL, reduce cost, and improving of treatment strategies.

  7. Clinical and Radiographic Factors Predicting Hearing Preservation Rates in Large Vestibular Schwannomas.

    Science.gov (United States)

    Mendelsohn, Daniel; Westerberg, Brian D; Dong, Charles; Akagami, Ryojo

    2016-06-01

    Objectives Postoperative hearing preservation rates for patients with large vestibular schwannomas range from 0 to 43%. The clinical and radiographic factors predicting hearing preservation in smaller vestibular schwannomas are well described; however, their importance in larger tumors is unclear. We investigated factors predicting hearing preservation in large vestibular schwannomas. Design Retrospective review. Setting Quaternary care academic center. Participants A total of 85 patients with unilateral vestibular schwannomas > 3 cm underwent retrosigmoid resections. Main Outcomes Measures Preoperative and postoperative serviceable hearing rates. Methods Clinical and radiographic data including preoperative and postoperative audiograms, preoperative symptoms, magnetic resonance imaging features, and postoperative facial weakness were analyzed. Results Hearing was preserved in 41% of patients (17 of 42) with preoperative serviceable hearing. Hypertension and diabetes increased the likelihood of preoperative hearing loss. Preoperative tinnitus predicted a lower likelihood of hearing preservation. No radiographic factors predicted hearing preservation; however, larger tumor size, smaller fourth ventricular width, and the presence of a cerebrospinal fluid cleft surrounding the tumor predicted postoperative facial weakness. Conclusion Systemic comorbidities may influence hearing loss preoperatively in patients with large vestibular schwannomas. The absence of tinnitus may reflect hearing reserve and propensity for hearing preservation. Preoperative radiographic features did not predict hearing preservation despite some associations with postoperative facial weakness. PMID:27175312

  8. The accurate definition of metabolic volumes on 18F-FDG-PET before treatment allows the response to chemoradiotherapy to be predicted in the case of oesophagus cancers

    International Nuclear Information System (INIS)

    This study aims at assessing the possibility of prediction of the response of locally advanced oesophagus cancers, even before the beginning of treatment, by using metabolic volume measurements performed on 18F-FDG PET images made before the treatment. Medical files of 50 patients have been analyzed. According to the observed responses, and to metabolic volume and Total Lesion Glycosis (TLG) values, it appears that the images allow the extraction of parameters, such as the TLG, which are criteria for the prediction of the therapeutic response. Short communication

  9. EHRs Connect Research and Practice: Where Predictive Modeling, Artificial Intelligence, and Clinical Decision Support Intersect

    CERN Document Server

    Bennett, Casey; Selove, Rebecca

    2012-01-01

    Objectives: Electronic health records (EHRs) are only a first step in capturing and utilizing health-related data - the challenge is turning that data into useful information. Furthermore, EHRs are increasingly likely to include data relating to patient outcomes, functionality such as clinical decision support, and genetic information as well, and, as such, can be seen as repositories of increasingly valuable information about patients' health conditions and responses to treatment over time. Methods: We describe a case study of 423 patients treated by Centerstone within Tennessee and Indiana in which we utilized electronic health record data to generate predictive algorithms of individual patient treatment response. Multiple models were constructed using predictor variables derived from clinical, financial and geographic data. Results: For the 423 patients, 101 deteriorated, 223 improved and in 99 there was no change in clinical condition. Based on modeling of various clinical indicators at baseline, the high...

  10. Prediction of postoperative liver regeneration from clinical information using a data-led mathematical model

    Science.gov (United States)

    Yamamoto, Kimiyo N.; Ishii, Masatsugu; Inoue, Yoshihiro; Hirokawa, Fumitoshi; MacArthur, Ben D.; Nakamura, Akira; Haeno, Hiroshi; Uchiyama, Kazuhisa

    2016-01-01

    Although the capacity of the liver to recover its size after resection has enabled extensive liver resection, post-hepatectomy liver failure remains one of the most lethal complications of liver resection. Therefore, it is clinically important to discover reliable predictive factors after resection. In this study, we established a novel mathematical framework which described post-hepatectomy liver regeneration in each patient by incorporating quantitative clinical data. Using the model fitting to the liver volumes in series of computed tomography of 123 patients, we estimated liver regeneration rates. From the estimation, we found patients were divided into two groups: i) patients restored the liver to its original size (Group 1, n = 99); and ii) patients experienced a significant reduction in size (Group 2, n = 24). From discriminant analysis in 103 patients with full clinical variables, the prognosis of patients in terms of liver recovery was successfully predicted in 85–90% of patients. We further validated the accuracy of our model prediction using a validation cohort (prediction = 84–87%, n = 39). Our interdisciplinary approach provides qualitative and quantitative insights into the dynamics of liver regeneration. A key strength is to provide better prediction in patients who had been judged as acceptable for resection by current pragmatic criteria. PMID:27694914

  11. An Intelligent Clinical Decision Support System for Patient-Specific Predictions to Improve Cervical Intraepithelial Neoplasia Detection

    Directory of Open Access Journals (Sweden)

    Panagiotis Bountris

    2014-01-01

    Full Text Available Nowadays, there are molecular biology techniques providing information related to cervical cancer and its cause: the human Papillomavirus (HPV, including DNA microarrays identifying HPV subtypes, mRNA techniques such as nucleic acid based amplification or flow cytometry identifying E6/E7 oncogenes, and immunocytochemistry techniques such as overexpression of p16. Each one of these techniques has its own performance, limitations and advantages, thus a combinatorial approach via computational intelligence methods could exploit the benefits of each method and produce more accurate results. In this article we propose a clinical decision support system (CDSS, composed by artificial neural networks, intelligently combining the results of classic and ancillary techniques for diagnostic accuracy improvement. We evaluated this method on 740 cases with complete series of cytological assessment, molecular tests, and colposcopy examination. The CDSS demonstrated high sensitivity (89.4%, high specificity (97.1%, high positive predictive value (89.4%, and high negative predictive value (97.1%, for detecting cervical intraepithelial neoplasia grade 2 or worse (CIN2+. In comparison to the tests involved in this study and their combinations, the CDSS produced the most balanced results in terms of sensitivity, specificity, PPV, and NPV. The proposed system may reduce the referral rate for colposcopy and guide personalised management and therapeutic interventions.

  12. Predicting Ovarian Cancer Patients' Clinical Response to Platinum-Based Chemotherapy by Their Tumor Proteomic Signatures.

    Science.gov (United States)

    Yu, Kun-Hsing; Levine, Douglas A; Zhang, Hui; Chan, Daniel W; Zhang, Zhen; Snyder, Michael

    2016-08-01

    Ovarian cancer is the deadliest gynecologic malignancy in the United States with most patients diagnosed in the advanced stage of the disease. Platinum-based antineoplastic therapeutics is indispensable to treating advanced ovarian serous carcinoma. However, patients have heterogeneous responses to platinum drugs, and it is difficult to predict these interindividual differences before administering medication. In this study, we investigated the tumor proteomic profiles and clinical characteristics of 130 ovarian serous carcinoma patients analyzed by the Clinical Proteomic Tumor Analysis Consortium (CPTAC), predicted the platinum drug response using supervised machine learning methods, and evaluated our prediction models through leave-one-out cross-validation. Our data-driven feature selection approach indicated that tumor proteomics profiles contain information for predicting binarized platinum response (P drug responses as well as provided insights into the biological processes influencing the efficacy of platinum-based therapeutics. Our analytical approach is also extensible to predicting response to other antineoplastic agents or treatment modalities for both ovarian and other cancers. PMID:27312948

  13. Predicting reoffense in pedophilic child molesters by clinical diagnoses and risk assessment.

    Science.gov (United States)

    Eher, Reinhard; Olver, Mark E; Heurix, Isabelle; Schilling, Frank; Rettenberger, Martin

    2015-12-01

    A Diagnostic and Statistical Manual of Mental Disorders (DSM)-based diagnosis of pedophilia has so far failed to predict sexual reoffense in convicted child molesters, probably because of its broad and unspecific conceptualization. In this study, therefore, we investigated the prognostic value of the subtype exclusive pedophilia and a series of customary risk assessment instruments (SSPI, Static-99, Stable-2007, VRS:SO) and the PCL-R in a sample of prison released pedophilic sexual offenders. First, we examined the convergent validity of risk assessment instruments (N = 261). Then, we calculated the predictive accuracy of the measures and diagnosis for sexual recidivism by ROC analyses and subsequent Cox regression (N = 189). Also, predictive values with more clinical immediacy were calculated (sensitivity, specificity, PPV and NPV). The VRS:SO, the SSPI, and the Static-99 significantly predicted sexual recidivism, as did a diagnosis of exclusive pedophilia. Also, the VRS:SO predicted sexual reoffense significantly better than the Stable-2007, the Static-99/Stable-2007 combined score, and the PCL-R. When used combined, only the VRS:SO and a diagnosis of exclusive pedophilia added incremental validity to each other. Our findings support that the clinical diagnosis of an exclusive pedophilia based on DSM criteria and VRS:SO defined risk factors can reliably discriminate higher from lower risk offenders, even within the select subgroup of pedophilic child molesters. PMID:26146817

  14. A novel neural-inspired learning algorithm with application to clinical risk prediction.

    Science.gov (United States)

    Tay, Darwin; Poh, Chueh Loo; Kitney, Richard I

    2015-04-01

    Clinical risk prediction - the estimation of the likelihood an individual is at risk of a disease - is a coveted and exigent clinical task, and a cornerstone to the recommendation of life saving management strategies. This is especially important for individuals at risk of cardiovascular disease (CVD) given the fact that it is the leading causes of death in many developed counties. To this end, we introduce a novel learning algorithm - a key factor that influences the performance of machine learning-based prediction models - and utilities it to develop CVD risk prediction tool. This novel neural-inspired algorithm, called the Artificial Neural Cell System for classification (ANCSc), is inspired by mechanisms that develop the brain and empowering it with capabilities such as information processing/storage and recall, decision making and initiating actions on external environment. Specifically, we exploit on 3 natural neural mechanisms responsible for developing and enriching the brain - namely neurogenesis, neuroplasticity via nurturing and apoptosis - when implementing ANCSc algorithm. Benchmark testing was conducted using the Honolulu Heart Program (HHP) dataset and results are juxtaposed with 2 other algorithms - i.e. Support Vector Machine (SVM) and Evolutionary Data-Conscious Artificial Immune Recognition System (EDC-AIRS). Empirical experiments indicate that ANCSc algorithm (statistically) outperforms both SVM and EDC-AIRS algorithms. Key clinical markers identified by ANCSc algorithm include risk factors related to diet/lifestyle, pulmonary function, personal/family/medical history, blood data, blood pressure, and electrocardiography. These clinical markers, in general, are also found to be clinically significant - providing a promising avenue for identifying potential cardiovascular risk factors to be evaluated in clinical trials. PMID:25576352

  15. Prediction of Clinically Relevant Safety Signals of Nephrotoxicity through Plasma Metabolite Profiling

    Directory of Open Access Journals (Sweden)

    W. B. Mattes

    2013-01-01

    Full Text Available Addressing safety concerns such as drug-induced kidney injury (DIKI early in the drug pharmaceutical development process ensures both patient safety and efficient clinical development. We describe a unique adjunct to standard safety assessment wherein the metabolite profile of treated animals is compared with the MetaMap Tox metabolomics database in order to predict the potential for a wide variety of adverse events, including DIKI. To examine this approach, a study of five compounds (phenytoin, cyclosporin A, doxorubicin, captopril, and lisinopril was initiated by the Technology Evaluation Consortium under the auspices of the Drug Safety Executive Council (DSEC. The metabolite profiles for rats treated with these compounds matched established reference patterns in the MetaMap Tox metabolomics database indicative of each compound’s well-described clinical toxicities. For example, the DIKI associated with cyclosporine A and doxorubicin was correctly predicted by metabolite profiling, while no evidence for DIKI was found for phenytoin, consistent with its clinical picture. In some cases the clinical toxicity (hepatotoxicity, not generally seen in animal studies, was detected with MetaMap Tox. Thus metabolite profiling coupled with the MetaMap Tox metabolomics database offers a unique and powerful approach for augmenting safety assessment and avoiding clinical adverse events such as DIKI.

  16. External model validation of binary clinical risk prediction models in cardiovascular and thoracic surgery.

    Science.gov (United States)

    Hickey, Graeme L; Blackstone, Eugene H

    2016-08-01

    Clinical risk-prediction models serve an important role in healthcare. They are used for clinical decision-making and measuring the performance of healthcare providers. To establish confidence in a model, external model validation is imperative. When designing such an external model validation study, thought must be given to patient selection, risk factor and outcome definitions, missing data, and the transparent reporting of the analysis. In addition, there are a number of statistical methods available for external model validation. Execution of a rigorous external validation study rests in proper study design, application of suitable statistical methods, and transparent reporting.

  17. Use of quantitative shape-activity relationships to model the photoinduced toxicity of polycyclic aromatic hydrocarbons: Electron density shape features accurately predict toxicity

    Energy Technology Data Exchange (ETDEWEB)

    Mezey, P.G.; Zimpel, Z.; Warburton, P.; Walker, P.D.; Irvine, D.G. [Univ. of Saskatchewan, Saskatoon, Saskatchewan (Canada); Huang, X.D.; Dixon, D.G.; Greenberg, B.M. [Univ. of Waterloo, Ontario (Canada). Dept. of Biology

    1998-07-01

    The quantitative shape-activity relationship (QShAR) methodology, based on accurate three-dimensional electron densities and detailed shape analysis methods, has been applied to a Lemna gibba photoinduced toxicity data set of 16 polycyclic aromatic hydrocarbon (PAH) molecules. In the first phase of the studies, a shape fragment QShAR database of PAHs was developed. The results provide a very good match to toxicity based on a combination of the local shape features of single rings in comparison to the central ring of anthracene and a more global shape feature involving larger molecular fragments. The local shape feature appears as a descriptor of the susceptibility of PAHs to photomodification and the global shape feature is probably related to photosensitization activity.

  18. Clinical Significance of Serum Cytokeratin 19 Fragment in the Prediction of Chemotherapy Efficacy and Prognosis in Patients with Advanced Non-small Cell Lung Cancer

    OpenAIRE

    Chong'an XU; Liu, Jiali; Xing, Lili; Liu, Shu

    2010-01-01

    Background and objective RECIST (Response Evaluation Criteria in Solid Tumors) criteria could not be used to detect viable tumor tissue and is not an accurate tool for evaluation of objective response (OR) in non-small cell lung cancer (NSCLC) patients without measurable lesions. The aim of this study is to detect the pre- and post-chemotherapy serum cytokeratin 19 fragment (CYFRA21-1) expression levels in advanced NSCLC patients to evaluate the clinical value of CYFRA21-1 in the prediction o...

  19. Clinical prediction of the need for interventions for the control of myopia.

    Science.gov (United States)

    McMonnies, Charles W

    2015-11-01

    The prevalence of myopia is increasing in Western populations but in East Asian countries, it is increasing to epidemic levels, where there are also markedly increased rates of progression to pathological myopia. Measures to more effectively control the development and progression of myopia are urgently needed. Notwithstanding a large volume of research, especially regarding the different mechanisms for the development of myopia and the efficacy of particular methods of intervention, there is still a great need and scope for improvements in clinical efforts to prevent and/or control myopic progression. Too often clinical efforts may involve only one method of intervention; however, the heterogenous nature of myopia suggests that clinical intervention may be more successful when interventions are employed in combination. The decision to prescribe interventions for the control of myopia in children, especially prior to onset, may be better framed by a comprehensive estimation of the degree of risk for the development and/or progression of myopia. For example, rather than ascribing equal weight to any degree of parental myopia, more accurate estimates may be obtained, if risk is judged to increase with the degree of parental myopia and the extent of any associated degenerative pathology. Risk estimates may be limited to broad mild, moderate and severe classifications due to lack of accurate weighting of risk factors. Nevertheless, comprehensive assessment of risk factors appears likely to better inform a prognosis and discussions with parents. Consideration of numerous environmental influences, for example, such as continuity and intensity of near work and time spent outdoors, may contribute to better risk estimation. Family-based practice appears to be ideally suited for risk estimation and the clinical application of approaches to control myopia. A proactive approach to estimating risk of developing myopia prior to its onset may be beneficial. Earlier implementation

  20. TU-EF-204-01: Accurate Prediction of CT Tube Current Modulation: Estimating Tube Current Modulation Schemes for Voxelized Patient Models Used in Monte Carlo Simulations.

    OpenAIRE

    McMillan, K; Bostani, M; McCollough, C; McNitt-Gray, M

    2015-01-01

    PURPOSE: Most patient models used in Monte Carlo-based estimates of CT dose, including computational phantoms, do not have tube current modulation (TCM) data associated with them. While not a problem for fixed tube current simulations, this is a limitation when modeling the effects of TCM. Therefore, the purpose of this work was to develop and validate methods to estimate TCM schemes for any voxelized patient model. METHODS: For 10 patients who received clinically-indicated chest (n=5) and ab...

  1. PredPPCrys: accurate prediction of sequence cloning, protein production, purification and crystallization propensity from protein sequences using multi-step heterogeneous feature fusion and selection.

    Directory of Open Access Journals (Sweden)

    Huilin Wang

    Full Text Available X-ray crystallography is the primary approach to solve the three-dimensional structure of a protein. However, a major bottleneck of this method is the failure of multi-step experimental procedures to yield diffraction-quality crystals, including sequence cloning, protein material production, purification, crystallization and ultimately, structural determination. Accordingly, prediction of the propensity of a protein to successfully undergo these experimental procedures based on the protein sequence may help narrow down laborious experimental efforts and facilitate target selection. A number of bioinformatics methods based on protein sequence information have been developed for this purpose. However, our knowledge on the important determinants of propensity for a protein sequence to produce high diffraction-quality crystals remains largely incomplete. In practice, most of the existing methods display poorer performance when evaluated on larger and updated datasets. To address this problem, we constructed an up-to-date dataset as the benchmark, and subsequently developed a new approach termed 'PredPPCrys' using the support vector machine (SVM. Using a comprehensive set of multifaceted sequence-derived features in combination with a novel multi-step feature selection strategy, we identified and characterized the relative importance and contribution of each feature type to the prediction performance of five individual experimental steps required for successful crystallization. The resulting optimal candidate features were used as inputs to build the first-level SVM predictor (PredPPCrys I. Next, prediction outputs of PredPPCrys I were used as the input to build second-level SVM classifiers (PredPPCrys II, which led to significantly enhanced prediction performance. Benchmarking experiments indicated that our PredPPCrys method outperforms most existing procedures on both up-to-date and previous datasets. In addition, the predicted crystallization

  2. Predictive Power of the Baseline QRS Complex Duration for Clinical Response to Cardiac Resynchronisation Therapy

    Directory of Open Access Journals (Sweden)

    Ali Kazemisaeid

    2011-02-01

    Full Text Available Background: Determination of predictors of response to cardiac resynchronisation therapy (CRT in patients with moderate to severe heart failure accompanied by a ventricular dyssynchrony can play a major role in improving candidate selection for CRT.Objectives: We evaluated whether the baseline QRS duration could be used to discriminate responders from non-responders to CRT.Methods: Eighty three consecutive patients with moderate to severe heart failure and with successful implantation of a CRT device at our centre were included in the study. QRS durations were measured on 12-lead surface electrocardiogram before and 6 months after implantation of the CRT device, using the widest QRS complex in leads II, V1 and V6. Clinical response to CRT was defined as an improvement of ≥1 grade in NYHA class.Results: Optimal cut-off value to discriminate baseline QRS duration for predicting clinical response to CRT was identified at 152 ms, yielding a sensitivity of 73.3%, a specificity of 56.5% as well as positive and negative predictive values of 81.5% and 44.8%, respectively. The discriminatory pow- er of the baseline QRS duration for response to CRT assessed by the ROC curve was 0.6402 (95% CI: 0.4976 – 0.7829. Baseline QRS duration ≥ 152 ms could effectively predict clinical response to CRT after adjusting for covariates (OR = 3.743, p = 0.017.Conclusion: Baseline QRS duration can effectively predict clinical response to CRT and optimal cut-off value to discriminate baseline QRS duration for response to CRT is 152 ms.

  3. A Clinical Scoring System to Predict the Development of Bronchopulmonary Dysplasia

    OpenAIRE

    Gürsoy, Tuğba; Hayran, Mutlu; Derin, Hatice; Ovalı, Fahri

    2015-01-01

    ObjectiveThis study aims to develop a scoring system for the prediction of bronchopulmonary dysplasia (BPD). MethodsMedical records of 652 infants whose gestational age and birth weight were below 32 weeks and 1,500g, respectively, and who survived beyond 28th postnatal day were reviewed retrospectively. Logistic regression methods were used to determine the clinical and demographic risk factors within the first 72 hours of life associated with BPD, as well as the weights of these factors on ...

  4. Evaluating clinical abdominal scoring system in predict- ing the necessity of laparotomy in blunt abdominal trauma

    Directory of Open Access Journals (Sweden)

    Erfantalab-Avini Peyman

    2011-06-01

    Full Text Available 【Abstract】 Objectives: Trauma is among the lead- ing causes of death. Medical management of blunt abdomi- nal trauma (BAT relies on judging patients for whom lap- arotomy is mandatory. This study aimed to determine BAT patients’ signs, as well as paraclinical data, and to clarify the accuracy, sensitivity, specificity, positive and negative predictive value of clinical abdominal scoring system (CASS, a new scoring system based on clinical signs, in predicting whether a BAT patient needs laparotomy or not. Methods: Totally 400 patients suspected of BAT that arrived at the emergency department of two university hos- pitals in Tehran from March 20, 2007 to March 19, 2009 were included in this study. They were evaluated for age, sex, type of trauma, systolic blood pressure, Glasgow coma scale (GCS, pulse rate, time of presentation after trauma, abdomi- nal clinical findings, respiratory rate, temperature, hemoglo- bin (Hb concentration, focused abdominal sonography in trauma (FAST and CASS. Results: Our measurements showed that CASS had an accuracy of 94%, sensitivity of 100%, specificity of 88%, positive predictive value of 90% and negative predictive value of 100% in determining the necessity of laparotomy in BAT patients. Moreover, in our analysis, systolic blood pressure, GCS, pulse rate, Hb concentration, time of presen- tation after trauma, abdominal clinical findings and FAST were also shown to be helpful in confirming the need for laparotomy (P<0.05. Conclusion: CASS is a promising scoring system in rapid detection of the need for laparotomy as well as in minimizing auxiliary expense for further evaluation in BAT patients, thus to promote the cost-benefit ratio and accu- racy of diagnosis. Key words: Abdominal injuries; Laparotomy; Patients; Wounds, nonpenetrating

  5. Idiopathic normal pressure hydrocephalus: diagnostic and predictive value of clinical testing, lumbar drainage, and CSF dynamics.

    Science.gov (United States)

    Mahr, Cynthia V; Dengl, Markus; Nestler, Ulf; Reiss-Zimmermann, Martin; Eichner, Gerrit; Preuß, Matthias; Meixensberger, Jürgen

    2016-09-01

    OBJECTIVE The aim of the study was to analyze the diagnostic and predictive values of clinical tests, CSF dynamics, and intracranial pulsatility tests, compared with external lumbar drainage (ELD), for shunt response in patients with idiopathic normal pressure hydrocephalus (iNPH). METHODS Sixty-eight consecutive patients with suspected iNPH were prospectively evaluated. Preoperative assessment included clinical tests, overnight intracranial pressure (ICP) monitoring, lumbar infusion test (LIFT), and ELD for 24-72 hours. Simple and multiple linear regression analyses were conducted to identify predictive parameters concerning the outcome after shunt therapy. RESULTS Positive response to ELD correctly predicted improvement after CSF diversion in 87.9% of the patients. A Mini-Mental State Examination (MMSE) value below 21 was associated with nonresponse after shunt insertion (specificity 93%, sensitivity 67%). Resistance to outflow of CSF (ROut) > 12 mm Hg/ml/min was false negative in 21% of patients. Intracranial pulsatility parameters yielded different results in various parameters (correlation coefficient between pulse amplitude and ICP, slow wave amplitude, and mean ICP) but did not correlate to outcome. In multiple linear regression analysis, a calculation of presurgical MMSE versus the value after ELD, ROut, and ICP amplitude quotient during LIFT was significantly associated with outcome (p = 0.04). CONCLUSIONS Despite a multitude of invasive tests, presurgical clinical testing and response to ELD yielded the best prediction for improvement of symptoms following surgery. The complication rate of invasive testing was 5.4%. Multiple and simple linear regression analyses indicated that outcome can only be predicted by a combination of parameters, in accordance with a multifactorial pathogenesis of iNPH. PMID:26824377

  6. Modeling and Predicting AD Progression by Regression Analysis of Sequential Clinical Data

    KAUST Repository

    Xie, Qing

    2016-02-23

    Alzheimer\\'s Disease (AD) is currently attracting much attention in elders\\' care. As the increasing availability of massive clinical diagnosis data, especially the medical images of brain scan, it is highly significant to precisely identify and predict the potential AD\\'s progression based on the knowledge in the diagnosis data. In this paper, we follow a novel sequential learning framework to model the disease progression for AD patients\\' care. Different from the conventional approaches using only initial or static diagnosis data to model the disease progression for different durations, we design a score-involved approach and make use of the sequential diagnosis information in different disease stages to jointly simulate the disease progression. The actual clinical scores are utilized in progress to make the prediction more pertinent and reliable. We examined our approach by extensive experiments on the clinical data provided by the Alzheimer\\'s Disease Neuroimaging Initiative (ADNI). The results indicate that the proposed approach is more effective to simulate and predict the disease progression compared with the existing methods.

  7. Endovascular Treatment of Malignant Superior Vena Cava Syndrome: Results and Predictive Factors of Clinical Efficacy

    Energy Technology Data Exchange (ETDEWEB)

    Fagedet, Dorothee, E-mail: DFagedet@chu-grenoble.fr [CHU de Grenoble, Clinique universitaire de medecine interne, Pole Pluridisciplinaire de Medecine (France); Thony, Frederic, E-mail: FThony@chu-grenoble.fr [CHU de Grenoble, Clinique universitaire de radiologie et imagerie medicale, Pole d' Imagerie (France); Timsit, Jean-Francois, E-mail: JFTimsit@chu-grenoble.fr [CHU de Grenoble, Clinique universitaire de reanimation, Pole Medecine Aiguee Communautaire (France); Rodiere, Mathieu, E-mail: MRodiere@chu-grenoble.fr [CHU de Grenoble, Clinique universitaire de radiologie et imagerie medicale, Pole d' Imagerie (France); Monnin-Bares, Valerie, E-mail: v-monnin@chu-montpellier.fr [CHRU Arnaud de Villeneuve, Imagerie Medicale Thoracique Cardiovasculaire (France); Ferretti, Gilbert R., E-mail: GFerretti@chu-grenoble.fr [CHU de Grenoble, Clinique universitaire de radiologie et imagerie medicale, Pole d' Imagerie (France); Vesin, Aurelien; Moro-Sibilot, Denis, E-mail: DMoro.pneumo@chu-grenoble.fr [University Grenoble 1 e Albert Bonniot Institute, Inserm U823 (France)

    2013-02-15

    To demonstrate the effectiveness of endovascular treatment (EVT) with self-expandable bare stents for malignant superior vena cava syndrome (SVCS) and to analyze predictive factors of EVT efficacy. Retrospective review of the 164 patients with malignant SVCS treated with EVT in our hospital from August 1992 to December 2007 and followed until February 2009. Endovascular treatment includes angioplasty before and after stent placement. We used self-expandable bare stents. We studied results of this treatment and looked for predictive factors of clinical efficacy, recurrence, and complications by statistical analysis. Endovascular treatment was clinically successful in 95% of cases, with an acceptable rate of early mortality (2.4%). Thrombosis of the superior vena cava was the only independent factor for EVT failure. The use of stents over 16 mm in diameter was a predictive factor for complications (P = 0.008). Twenty-one complications (12.8%) occurred during the follow-up period. Relapse occurred in 36 patients (21.9%), with effective restenting in 75% of cases. Recurrence of SVCS was significantly increased in cases of occlusion (P = 0.01), initial associated thrombosis (P = 0.006), or use of steel stents (P = 0.004). Long-term anticoagulant therapy did not influence the risk of recurrence or complications. In malignancy, EVT with self-expandable bare stents is an effective SVCS therapy. These results prompt us to propose treatment with stents earlier in the clinical course of patients with SVCS and to avoid dilatation greater than 16 mm.

  8. PREDICTION OF CLINICAL EFFICIENCY OF SIMVASTATIN TREATMENT IN PATIENTS WITH RHEUMATOID ARTHRITIS

    Directory of Open Access Journals (Sweden)

    I. V. Shirinsky

    2009-01-01

    Full Text Available Abstract. Treatment with statins results in reduction of disease activity in one-third of patients with rheumatoid arthritis (RA. The aim of this study was to assess some factors that may predict clinical response to simvastatin therapy before starting the treatment. We evaluated an association of treatment efficacy with baseline clinical and laboratory parameters including disease activity measures, cytokine profiles in sera and culture supernatants of peripheral blood mononuclear cells. Thirty-three patients with active RA were enrolled in the study. The patients were treated with simvastatin at 40 mg/day for three months. Eleven patients (33% developed a moderate response according to EULAR criteria. It was shown that serum IL-10 concentrations was higher in responders, and positively correlated with clinical response to simvastatin. We carried out a receiver operating characteristic curve (ROC analysis in order to assess the accuracy of serum IL-10 for the predicting of EULAR response development. The cut-off threshold corresponding to the highest sensitivity (89% and specificity (62% was a value of 6.5 pg/ml. In conclusion, the performance characteristics of serum IL-10 measurement proved to be good enough to predict EULAR response to simvastatin therapy in RA patients.

  9. Levels of uninvolved immunoglobulins predict clinical status and progression-free survival for multiple myeloma patients.

    Science.gov (United States)

    Harutyunyan, Nika M; Vardanyan, Suzie; Ghermezi, Michael; Gottlieb, Jillian; Berenson, Ariana; Andreu-Vieyra, Claudia; Berenson, James R

    2016-07-01

    Multiple myeloma (MM) is characterized by the enhanced production of the same monoclonal immunoglobulin (M-Ig or M protein). Techniques such as serum protein electrophoresis and nephelometry are routinely used to quantify levels of this protein in the serum of MM patients. However, these methods are not without their shortcomings and problems accurately quantifying M proteins remain. Precise quantification of the types and levels of M-Ig present is critical to monitoring patient response to therapy. In this study, we investigated the ability of the HevyLite (HLC) immunoassay to correlate with clinical status based on levels of involved and uninvolved antibodies. In our cohort of MM patients, we observed that significantly higher ratios and greater differences of involved HLC levels compared to uninvolved HLC levels correlated with a worse clinical status. Similarly, higher absolute levels of involved HLC antibodies and lower levels of uninvolved HLC antibodies also correlated with a worse clinical status and a shorter progression-free survival. These findings suggest that the HLC assay is a useful and a promising tool for determining the clinical status and survival time for patients with multiple myeloma. PMID:27017948

  10. Levels of uninvolved immunoglobulins predict clinical status and progression-free survival for multiple myeloma patients.

    Science.gov (United States)

    Harutyunyan, Nika M; Vardanyan, Suzie; Ghermezi, Michael; Gottlieb, Jillian; Berenson, Ariana; Andreu-Vieyra, Claudia; Berenson, James R

    2016-07-01

    Multiple myeloma (MM) is characterized by the enhanced production of the same monoclonal immunoglobulin (M-Ig or M protein). Techniques such as serum protein electrophoresis and nephelometry are routinely used to quantify levels of this protein in the serum of MM patients. However, these methods are not without their shortcomings and problems accurately quantifying M proteins remain. Precise quantification of the types and levels of M-Ig present is critical to monitoring patient response to therapy. In this study, we investigated the ability of the HevyLite (HLC) immunoassay to correlate with clinical status based on levels of involved and uninvolved antibodies. In our cohort of MM patients, we observed that significantly higher ratios and greater differences of involved HLC levels compared to uninvolved HLC levels correlated with a worse clinical status. Similarly, higher absolute levels of involved HLC antibodies and lower levels of uninvolved HLC antibodies also correlated with a worse clinical status and a shorter progression-free survival. These findings suggest that the HLC assay is a useful and a promising tool for determining the clinical status and survival time for patients with multiple myeloma.

  11. Race-specific genetic risk score is more accurate than nonrace-specific genetic risk score for predicting prostate cancer and high-grade diseases

    Science.gov (United States)

    Na, Rong; Ye, Dingwei; Qi, Jun; Liu, Fang; Lin, Xiaoling; Helfand, Brian T; Brendler, Charles B; Conran, Carly; Gong, Jian; Wu, Yishuo; Gao, Xu; Chen, Yaqing; Zheng, S Lilly; Mo, Zengnan; Ding, Qiang; Sun, Yinghao; Xu, Jianfeng

    2016-01-01

    Genetic risk score (GRS) based on disease risk-associated single nucleotide polymorphisms (SNPs) is an informative tool that can be used to provide inherited information for specific diseases in addition to family history. However, it is still unknown whether only SNPs that are implicated in a specific racial group should be used when calculating GRSs. The objective of this study is to compare the performance of race-specific GRS and nonrace-specific GRS for predicting prostate cancer (PCa) among 1338 patients underwent prostate biopsy in Shanghai, China. A race-specific GRS was calculated with seven PCa risk-associated SNPs implicated in East Asians (GRS7), and a nonrace-specific GRS was calculated based on 76 PCa risk-associated SNPs implicated in at least one racial group (GRS76). The means of GRS7 and GRS76 were 1.19 and 1.85, respectively, in the study population. Higher GRS7 and GRS76 were independent predictors for PCa and high-grade PCa in univariate and multivariate analyses. GRS7 had a better area under the receiver-operating curve (AUC) than GRS76 for discriminating PCa (0.602 vs 0.573) and high-grade PCa (0.603 vs 0.575) but did not reach statistical significance. GRS7 had a better (up to 13% at different cutoffs) positive predictive value (PPV) than GRS76. In conclusion, a race-specific GRS is more robust and has a better performance when predicting PCa in East Asian men than a GRS calculated using SNPs that are not shown to be associated with East Asians. PMID:27140652

  12. Development of an algorithm to predict comfort of wheelchair fit based on clinical measures.

    Science.gov (United States)

    Kon, Keisuke; Hayakawa, Yasuyuki; Shimizu, Shingo; Nosaka, Toshiya; Tsuruga, Takeshi; Matsubara, Hiroyuki; Nomura, Tomohiro; Murahara, Shin; Haruna, Hirokazu; Ino, Takumi; Inagaki, Jun; Kobayashi, Toshiki

    2015-09-01

    [Purpose] The purpose of this study was to develop an algorithm to predict the comfort of a subject seated in a wheelchair, based on common clinical measurements and without depending on verbal communication. [Subjects] Twenty healthy males (mean age: 21.5 ± 2 years; height: 171 ± 4.3 cm; weight: 56 ± 12.3 kg) participated in this study. [Methods] Each experimental session lasted for 60 min. The clinical measurements were obtained under 4 conditions (good posture, with and without a cushion; bad posture, with and without a cushion). Multiple regression analysis was performed to determine the relationship between a visual analogue scale and exercise physiology parameters (respiratory and metabolism), autonomic nervous parameters (heart rate, blood pressure, and salivary amylase level), and 3D-coordinate posture parameters (good or bad posture). [Results] For the equation (algorithm) to predict the visual analogue scale score, the adjusted multiple correlation coefficient was 0.72, the residual standard deviation was 1.2, and the prediction error was 12%. [Conclusion] The algorithm developed in this study could predict the comfort of healthy male seated in a wheelchair with 72% accuracy. PMID:26504299

  13. Microsatellite Instability Predicts Clinical Outcome in Radiation-Treated Endometrioid Endometrial Cancer

    International Nuclear Information System (INIS)

    Purpose: To elucidate whether microsatellite instability (MSI) predicts clinical outcome in radiation-treated endometrioid endometrial cancer (EEC). Methods and Materials: A consecutive series of 93 patients with EEC treated with extrafascial hysterectomy and postoperative radiotherapy was studied. The median clinical follow-up of patients was 138 months, with a maximum of 232 months. Five quasimonomorphic mononucleotide markers (BAT-25, BAT-26, NR21, NR24, and NR27) were used for MSI classification. Results: Twenty-five patients (22%) were classified as MSI. Both in the whole series and in early stages (I and II), univariate analysis showed a significant association between MSI and poorer 10-year local disease-free survival, disease-free survival, and cancer-specific survival. In multivariate analysis, MSI was excluded from the final regression model in the whole series, but in early stages MSI provided additional significant predictive information independent of traditional prognostic and predictive factors (age, stage, grade, and vascular invasion) for disease-free survival (hazard ratio [HR] 3.25, 95% confidence interval [CI] 1.01-10.49; p = 0.048) and cancer-specific survival (HR 4.20, 95% CI 1.23-14.35; p = 0.022) and was marginally significant for local disease-free survival (HR 3.54, 95% CI 0.93-13.46; p = 0.064). Conclusions: These results suggest that MSI may predict radiotherapy response in early-stage EEC.

  14. Stable, high-order SBP-SAT finite difference operators to enable accurate simulation of compressible turbulent flows on curvilinear grids, with application to predicting turbulent jet noise

    Science.gov (United States)

    Byun, Jaeseung; Bodony, Daniel; Pantano, Carlos

    2014-11-01

    Improved order-of-accuracy discretizations often require careful consideration of their numerical stability. We report on new high-order finite difference schemes using Summation-By-Parts (SBP) operators along with the Simultaneous-Approximation-Terms (SAT) boundary condition treatment for first and second-order spatial derivatives with variable coefficients. In particular, we present a highly accurate operator for SBP-SAT-based approximations of second-order derivatives with variable coefficients for Dirichlet and Neumann boundary conditions. These terms are responsible for approximating the physical dissipation of kinetic and thermal energy in a simulation, and contain grid metrics when the grid is curvilinear. Analysis using the Laplace transform method shows that strong stability is ensured with Dirichlet boundary conditions while weaker stability is obtained for Neumann boundary conditions. Furthermore, the benefits of the scheme is shown in the direct numerical simulation (DNS) of a Mach 1.5 compressible turbulent supersonic jet using curvilinear grids and skew-symmetric discretization. Particularly, we show that the improved methods allow minimization of the numerical filter often employed in these simulations and we discuss the qualities of the simulation.

  15. Clinical picture and risk prediction of short-term mortality in cardiogenic shock

    DEFF Research Database (Denmark)

    Harjola, Veli-Pekka; Lassus, Johan; Sionis, Alessandro;

    2015-01-01

    AIMS: The aim of this study was to investigate the clinical picture and outcome of cardiogenic shock and to develop a risk prediction score for short-term mortality. METHODS AND RESULTS: The CardShock study was a multicentre, prospective, observational study conducted between 2010 and 2012....... Patients with either acute coronary syndrome (ACS) or non-ACS aetiologies were enrolled within 6 h from detection of cardiogenic shock defined as severe hypotension with clinical signs of hypoperfusion and/or serum lactate >2 mmol/L despite fluid resuscitation (n = 219, mean age 67, 74% men). Data...... on clinical presentation, management, and biochemical variables were compared between different aetiologies of shock. Systolic blood pressure was on average 78 mmHg (standard deviation 14 mmHg) and mean arterial pressure 57 (11) mmHg. The most common cause (81%) was ACS (68% ST-elevation myocardial infarction...

  16. A New Strategy for Accurately Predicting I-V Electrical Characteristics of PV Modules Using a Nonlinear Five-Point Model

    Directory of Open Access Journals (Sweden)

    Sakaros Bogning Dongue

    2013-01-01

    Full Text Available This paper presents the modelling of electrical I-V response of illuminated photovoltaic crystalline modules. As an alternative method to the linear five-parameter model, our strategy uses advantages of a nonlinear analytical five-point model to take into account the effects of nonlinear variations of current with respect to solar irradiance and of voltage with respect to cells temperature. We succeeded in this work to predict with great accuracy the I-V characteristics of monocrystalline shell SP75 and polycrystalline GESOLAR GE-P70 photovoltaic modules. The good comparison of our calculated results to experimental data provided by the modules manufacturers makes it possible to appreciate the contribution of taking into account the nonlinear effect of operating conditions data on I-V characteristics of photovoltaic modules.

  17. Anthropometric variables accurately predict dual energy x-ray absorptiometric-derived body composition and can be used to screen for diabetes.

    Directory of Open Access Journals (Sweden)

    Reza Yavari

    Full Text Available The current world-wide epidemic of obesity has stimulated interest in developing simple screening methods to identify individuals with undiagnosed diabetes mellitus type 2 (DM2 or metabolic syndrome (MS. Prior work utilizing body composition obtained by sophisticated technology has shown that the ratio of abdominal fat to total fat is a good predictor for DM2 or MS. The goals of this study were to determine how well simple anthropometric variables predict the fat mass distribution as determined by dual energy x-ray absorptometry (DXA, and whether these are useful to screen for DM2 or MS within a population. To accomplish this, the body composition of 341 females spanning a wide range of body mass indices and with a 23% prevalence of DM2 and MS was determined using DXA. Stepwise linear regression models incorporating age, weight, height, waistline, and hipline predicted DXA body composition (i.e., fat mass, trunk fat, fat free mass, and total mass with good accuracy. Using body composition as independent variables, nominal logistic regression was then performed to estimate the probability of DM2. The results show good discrimination with the receiver operating characteristic (ROC having an area under the curve (AUC of 0.78. The anthropometrically-derived body composition equations derived from the full DXA study group were then applied to a group of 1153 female patients selected from a general endocrinology practice. Similar to the smaller study group, the ROC from logistical regression using body composition had an AUC of 0.81 for the detection of DM2. These results are superior to screening based on questionnaires and compare favorably with published data derived from invasive testing, e.g., hemoglobin A1c. This anthropometric approach offers promise for the development of simple, inexpensive, non-invasive screening to identify individuals with metabolic dysfunction within large populations.

  18. Is the predicted postoperative FEV1 estimated by planar lung perfusion scintigraphy accurate in patients undergoing pulmonary resection? Comparison of two processing methods

    International Nuclear Information System (INIS)

    Estimation of postoperative forced expiratory volume in 1 s (FEV1) with radionuclide lung scintigraphy is frequently used to define functional operability in patients undergoing lung resection. We conducted a study to outline the reliability of planar quantitative lung perfusion scintigraphy (QLPS) with two different processing methods to estimate the postoperative lung function in patients with resectable lung disease. Forty-one patients with a mean age of 57±12 years who underwent either a pneumonectomy (n=14) or a lobectomy (n=27) were included in the study. QLPS with Tc-99m macroaggregated albumin was performed. Both three equal zones were generated for each lung [zone method (ZM)] and more precise regions of interest were drawn according to their anatomical shape in the anterior and posterior projections [lobe mapping method (LMM)] for each patient. The predicted postoperative (ppo) FEV1 values were compared with actual FEV1 values measured on postoperative day 1 (pod1 FEV1) and day 7 (pod7 FEV1). The mean of preoperative FEV 1 and ppoFEV1 values was 2.10±0.57 and 1.57±0.44 L, respectively. The mean of Pod1FEV1 (1.04±0.30 L) was lower than ppoFEV1 (p0.05). PpoFEV1 values predicted by both the zone and LMMs overestimated the actual measured lung volumes in patients undergoing pulmonary resection in the early postoperative period. LMM is not superior to ZM. (author)

  19. Clinical signs of pneumonia in children: association with and prediction of diagnosis by fuzzy sets theory

    Directory of Open Access Journals (Sweden)

    Pereira J.C.R.

    2004-01-01

    Full Text Available The present study compares the performance of stochastic and fuzzy models for the analysis of the relationship between clinical signs and diagnosis. Data obtained for 153 children concerning diagnosis (pneumonia, other non-pneumonia diseases, absence of disease and seven clinical signs were divided into two samples, one for analysis and other for validation. The former was used to derive relations by multi-discriminant analysis (MDA and by fuzzy max-min compositions (fuzzy, and the latter was used to assess the predictions drawn from each type of relation. MDA and fuzzy were closely similar in terms of prediction, with correct allocation of 75.7 to 78.3% of patients in the validation sample, and displaying only a single instance of disagreement: a patient with low level of toxemia was mistaken as not diseased by MDA and correctly taken as somehow ill by fuzzy. Concerning relations, each method provided different information, each revealing different aspects of the relations between clinical signs and diagnoses. Both methods agreed on pointing X-ray, dyspnea, and auscultation as better related with pneumonia, but only fuzzy was able to detect relations of heart rate, body temperature, toxemia and respiratory rate with pneumonia. Moreover, only fuzzy was able to detect a relationship between heart rate and absence of disease, which allowed the detection of six malnourished children whose diagnoses as healthy are, indeed, disputable. The conclusion is that even though fuzzy sets theory might not improve prediction, it certainly does enhance clinical knowledge since it detects relationships not visible to stochastic models.

  20. Accurate prediction of the binding free energy and analysis of the mechanism of the interaction of replication protein A (RPA) with ssDNA.

    Science.gov (United States)

    Carra, Claudio; Cucinotta, Francis A

    2012-06-01

    The eukaryotic replication protein A (RPA) has several pivotal functions in the cell metabolism, such as chromosomal replication, prevention of hairpin formation, DNA repair and recombination, and signaling after DNA damage. Moreover, RPA seems to have a crucial role in organizing the sequential assembly of DNA processing proteins along single stranded DNA (ssDNA). The strong RPA affinity for ssDNA, K(A) between 10(-9)-10(-10) M, is characterized by a low cooperativity with minor variation for changes on the nucleotide sequence. Recently, new data on RPA interactions was reported, including the binding free energy of the complex RPA70AB with dC(8) and dC(5), which has been estimated to be -10 ± 0.4 kcal mol(-1) and -7 ± 1 kcal mol(-1), respectively. In view of these results we performed a study based on molecular dynamics aimed to reproduce the absolute binding free energy of RPA70AB with the dC(5) and dC(8) oligonucleotides. We used several tools to analyze the binding free energy, rigidity, and time evolution of the complex. The results obtained by MM-PBSA method, with the use of ligand free geometry as a reference for the receptor in the separate trajectory approach, are in excellent agreement with the experimental data, with ±4 kcal mol(-1) error. This result shows that the MM-PB(GB)SA methods can provide accurate quantitative estimates of the binding free energy for interacting complexes when appropriate geometries are used for the receptor, ligand and complex. The decomposition of the MM-GBSA energy for each residue in the receptor allowed us to correlate the change of the affinity of the mutated protein with the ΔG(gas+sol) contribution of the residue considered in the mutation. The agreement with experiment is optimal and a strong change in the binding free energy can be considered as the dominant factor in the loss for the binding affinity resulting from mutation. PMID:22116609

  1. Acute pyelonephritis: role of enhanced CT scan in the prediction of clinical outcome

    Energy Technology Data Exchange (ETDEWEB)

    Jo, Byung June; Kim, Ki Whang; Yu, Jeong Sik; Kim, Jai Keun; Yoon, Sang Wook; Ha, Sung Kyu; Park, Chong Hoon [Yonsei Univ. College of Medicine, Seoul (Korea, Republic of)

    1997-04-01

    To correlate the CT findings of acute pyelonephritis with its outcome and with clinical data. Thirty five contrast enhanced CT scans in patients diagnosed as suffering from acute pyelonephritis were retrospectively analyzed. Findings based on the morphology of perfusion defect in the renal parenchyma were classified as normal, focal wedge, multifocal wedge, focal mass, or mixed form composed of wedge and mass. These findings were correlated with clinical data such as degree of fever, leukocytosis, the period after antibiotic treatment during which fever was reduced, and the presence of pyuria in each group Analysis was then performed. Perfusion defects were seen in 23 of 35 cases, and their morphology was classified as follow; focal wedge (n=2), multifocal wedge (n=8), focal mass (n=4), and mixed form (n=9). Twelve cases (34.3%) showed no perfusion defect. The duration of fever was significantly prolonged in patients with focal mass form (p < .05). There was no significant correlation between the morphology of perfusion defect, bilaterality, and other clinical factors. The present study shows that the clinical course of the focal mass form of perfusion defect, as seen on CT, is different from that of other types. CT could be effective in predicting clinical progress and the outcome of treatment in cases of acute pyelonephritis.

  2. Accurate prediction of hard-sphere virial coefficients B6 to B12 from a compressibility-based equation of state

    Science.gov (United States)

    Hansen-Goos, Hendrik

    2016-04-01

    We derive an analytical equation of state for the hard-sphere fluid that is within 0.01% of computer simulations for the whole range of the stable fluid phase. In contrast, the commonly used Carnahan-Starling equation of state deviates by up to 0.3% from simulations. The derivation uses the functional form of the isothermal compressibility from the Percus-Yevick closure of the Ornstein-Zernike relation as a starting point. Two additional degrees of freedom are introduced, which are constrained by requiring the equation of state to (i) recover the exact fourth virial coefficient B4 and (ii) involve only integer coefficients on the level of the ideal gas, while providing best possible agreement with the numerical result for B5. Virial coefficients B6 to B10 obtained from the equation of state are within 0.5% of numerical computations, and coefficients B11 and B12 are within the error of numerical results. We conjecture that even higher virial coefficients are reliably predicted.

  3. Clinical Nomogram for Predicting Survival of Esophageal Cancer Patients after Esophagectomy

    Science.gov (United States)

    Cao, Jinlin; Yuan, Ping; Wang, Luming; Wang, Yiqing; Ma, Honghai; Yuan, Xiaoshuai; Lv, Wang; Hu, Jian

    2016-01-01

    The aim of this study was to construct an effective clinical nomogram for predicting the survival of esophageal cancer patients after esophagectomy. We identified esophageal cancer patients (n = 4,281) who underwent esophagectomy between 1988 and 2007 from the Surveillance, Epidemiology, and End Results (SEER) 18 registries database. Clinically significant parameters for survival were used to construct a nomogram based on Cox regression analyses. The model was validated using bootstrap resampling and a Chinese cohort (n = 145). A total of 4,109 patients from the SEER database were included for analysis. The multivariate analyses showed that the factors of age, race, histology, tumor site, tumor size, grade and depth of invasion, and the numbers of metastases and retrieved nodes were independent prognostic factors. All of these factors were selected into the nomogram. The nomogram showed a clear prognostic superiority over the seventh AJCC-TNM classification (C-index: SEER cohort, 0.716 vs 0.693, respectively; P nomogram predicted the probabilities of 3- and 5-year survival, which corresponded closely with the actual survival rates. This novel prognostic model may improve clinicians’ abilities to predict individualized survival and to make treatment recommendations. PMID:27215834

  4. Predicting clinically unrecognized coronary artery disease: use of two- dimensional echocardiography

    Directory of Open Access Journals (Sweden)

    Nagueh Sherif F

    2009-03-01

    Full Text Available Abstract Background 2-D Echo is often performed in patients without history of coronary artery disease (CAD. We sought to determine echo features predictive of CAD. Methods 2-D Echo of 328 patients without known CAD performed within one year prior to stress myocardial SPECT and angiography were reviewed. Echo features examined were left ventricular and atrial enlargement, LV hypertrophy, wall motion abnormality (WMA, LV ejection fraction (EF 15% LV perfusion defect or multivessel distribution. Severe coronary artery stenosis (CAS was defined as left main, 3 VD or 2VD involving proximal LAD. Results The mean age was 62 ± 13 years, 59% men, 29% diabetic (DM and 148 (45% had > 2 risk factors. Pharmacologic stress was performed in 109 patients (33%. MPA was present in 200 pts (60% of which, 137 were high risk. CAS was present in 166 pts (51%, 75 were severe. Of 87 patients with WMA, 83% had MPA and 78% had CAS. Multivariate analysis identified age >65, male, inability to exercise, DM, WMA, MAC and AS as independent predictors of MPA and CAS. Independent predictors of high risk MPA and severe CAS were age, DM, inability to exercise and WMA. 2-D echo findings offered incremental value over clinical information in predicting CAD by angiography. (Chi square: 360 vs. 320 p = 0.02. Conclusion 2-D Echo was valuable in predicting presence of physiological and anatomical CAD in addition to clinical information.

  5. Early seizures in patients with acute stroke: Frequency, predictive factors, and effect on clinical outcome

    Directory of Open Access Journals (Sweden)

    Andrea Alberti

    2008-06-01

    Full Text Available Andrea Alberti, Maurizio Paciaroni, Valeria Caso, Michele Venti, Francesco Palmerini, Giancarlo AgnelliStroke Unit and Division of Internal and Cardiovascular Medicine, University of Perugia, Perugia, ItalyBackground: Early seizure (ES may complicate the clinical course of patients with acute stroke. The aim of this study was to assess the rate of and the predictive factors for ES as well the effects of ES on the clinical outcome at hospital discharge in patients with first-ever stroke.Patients and methods: A total of 638 consecutive patients with first-ever stroke (543 ischemic, 95 hemorrhagic, admitted to our Stroke Unit, were included in this prospective study. ES were defined as seizures occurring within 7 days from acute stroke. Patients with history of epilepsy were excluded.Results: Thirty-one patients (4.8% had ES. Seizures were significantly more common in patients with cortical involvement, severe and large stroke, and in patient with cortical hemorrhagic transformation of ischemic stroke. ES was not associated with an increase in adverse outcome (mortality and disability. After multivariate analysis, hemorrhagic transformation resulted as an independent predictive factor for ES (OR = 6.5; 95% CI: 1.95–22.61; p = 0.003.Conclusion: ES occur in about 5% of patients with acute stroke. In these patients hemorrhagic transformation is a predictive factor for ES. ES does not seem to be associated with an adverse outcome at hospital discharge after acute stroke.Keywords: seizures, stroke, cortical involvement, hemorrhagic transformation

  6. Early seizures in patients with acute stroke: Frequency, predictive factors, and effect on clinical outcome

    Science.gov (United States)

    Alberti, Andrea; Paciaroni, Maurizio; Caso, Valeria; Venti, Michele; Palmerini, Francesco; Agnelli, Giancarlo

    2008-01-01

    Background Early seizure (ES) may complicate the clinical course of patients with acute stroke. The aim of this study was to assess the rate of and the predictive factors for ES as well the effects of ES on the clinical outcome at hospital discharge in patients with first-ever stroke. Patients and methods A total of 638 consecutive patients with first-ever stroke (543 ischemic, 95 hemorrhagic), admitted to our Stroke Unit, were included in this prospective study. ES were defined as seizures occurring within 7 days from acute stroke. Patients with history of epilepsy were excluded. Results Thirty-one patients (4.8%) had ES. Seizures were significantly more common in patients with cortical involvement, severe and large stroke, and in patient with cortical hemorrhagic transformation of ischemic stroke. ES was not associated with an increase in adverse outcome (mortality and disability). After multivariate analysis, hemorrhagic transformation resulted as an independent predictive factor for ES (OR = 6.5; 95% CI: 1.95–22.61; p = 0.003). Conclusion ES occur in about 5% of patients with acute stroke. In these patients hemorrhagic transformation is a predictive factor for ES. ES does not seem to be associated with an adverse outcome at hospital discharge after acute stroke. PMID:18827922

  7. Biomarkers for predicting clinical response to immunosuppressive therapy in aplastic anemia.

    Science.gov (United States)

    Narita, Atsushi; Kojima, Seiji

    2016-08-01

    The decision to select hematopoietic stem cell transplantation (HSCT) or immunosuppressive therapy (IST) as initial therapy in acquired aplastic anemia (AA) is currently based on patient age and the availability of a human leukocyte antigen (HLA)-matched donor. Although IST is a promising treatment option, the ability to predict its long-term outcomes remains poor due to refractoriness, relapses, and the risk of clonal evolution. Several predictive biomarkers for response to IST have been posited, including age, gender, pre-treatment blood cell counts, cytokines, gene mutations, paroxysmal nocturnal hemoglobinuria (PNH), and telomere length (TL). While previous studies have provided substantial biological insights into the utility of IST, the prognostic power of the reported biomarkers is currently insufficient to contribute to clinical decision making. Recently, a large retrospective analysis proposed the combination of minor PNH clones and TL as an efficient predictor of IST response. Identification of a reliable predictor would provide a useful tool for determining the most appropriate treatment choice for AA patients, including up-front HSCT from HLA-matched unrelated donor. The present review summarizes studies evaluating the utility of biomarkers in predicting the clinical response to IST of patients with AA, and provides a baseline for prospective studies aimed at validating previously reported biomarkers. PMID:27091471

  8. The clinical factors′ prediction of increased intradialytic qt dispersion on the electrocardiograms of chronic hemodialysis patients

    Directory of Open Access Journals (Sweden)

    Dina Oktavia

    2013-01-01

    Full Text Available Ventricular arrhythmias and sudden death are common in patients on maintenance hemodialysis (HD. The increase in QT dispersion (QTd on the electrocardiogram (ECG reflects increased tendency for ventricular repolarization that predisposes to arrhythmias. The purpose of the study was to identify the clinical factors that may predict the increased intradialytic QTd and to assess differences in QTd before and after HD. Each of 61 chronic HD patients underwent 12-lead ECG and blood pressure (BP measurement before and every 1 h during a single HD session. The QT intervals were corrected for heart rate using Bazett′s formula. Intradialytic QTd increased in 30 (49% patients. There was no correlation between the increased QTd and the clinical factors including hypertension, pulse pressure, intradialytic hypotension, left ventricular hypertrophy, old myocardial infarct, diabetes mellitus, and nutritional status. The means of QT interval and QTd increased after HD session (from 382 ± 29 to 444 ± 26 ms, P <0.05; and from 74 ± 21 to 114 ± 53 ms, respectively, P <0.05. We conclude that the increased intradialytic QTd could not be predicted by any of the clinical factors evaluated in this study. There was significant difference in the means of QTd before and after HD session.

  9. A Panel of Cancer Testis Antigens and Clinical Risk Factors to Predict Metastasis in Colorectal Cancer

    Directory of Open Access Journals (Sweden)

    Ramyar Molania

    2014-01-01

    Full Text Available Colorectal cancer (CRC is the third common carcinoma with a high rate of mortality worldwide and several studies have investigated some molecular and clinicopathological markers for diagnosis and prognosis of its malignant phenotypes. The aim of this study is to evaluate expression frequency of PAGE4, SCP-1, and SPANXA/D cancer testis antigen (CTA genes as well as some clinical risk markers to predict liver metastasis of colorectal cancer patients. The expression frequency of PAGE4, SCP-1, and SPANXA/D cancer/testis antigen (CTA genes was obtained using reverse transcription polymerase chain reaction (RT-PCR assay in 90 colorectal tumor samples including both negative and positive liver metastasis tumors. Statistical analysis was performed to assess the association of three studied genes and clinical risk factors with CRC liver metastasis. The frequency of PAGE4 and SCP-1 genes expression was significantly higher in the primary tumours with liver metastasis when statistically compared with primary tumors with no liver metastasis (P<0.05. Among all clinical risk factors studied, the lymph node metastasis and the depth of invasion were statistically correlated with liver metastasis of CRC patients. In addition, using multiple logistic regression, we constructed a model based on PAGE4 and lymph node metastasis to predict liver metastasis of CRC.

  10. Predicting PTSD using the New York Risk Score with genotype data: potential clinical and research opportunities

    Directory of Open Access Journals (Sweden)

    Boscarino JA

    2013-04-01

    Full Text Available Joseph A Boscarino,1,2 H Lester Kirchner,3,4 Stuart N Hoffman,5 Porat M Erlich1,4 1Center for Health Research, Geisinger Clinic, Danville, 2Department of Psychiatry, Temple University School of Medicine, Philadelphia, 3Division of Medicine, Geisinger Clinic, Danville, 4Department of Medicine, Temple University School of Medicine, Philadelphia, 5Department of Neurology, Geisinger Clinic, Danville, PA, USA Background: We previously developed a post-traumatic stress disorder (PTSD screening instrument, ie, the New York PTSD Risk Score (NYPRS, that was effective in predicting PTSD. In the present study, we assessed a version of this risk score that also included genetic information. Methods: Utilizing diagnostic testing methods, we hierarchically examined different prediction variables identified in previous NYPRS research, including genetic risk-allele information, to assess lifetime and current PTSD status among a population of trauma-exposed adults. Results: We found that, in predicting lifetime PTSD, the area under the receiver operating characteristic curve (AUC for the Primary Care PTSD Screen alone was 0.865. When we added psychosocial predictors from the original NYPRS to the model, including depression, sleep disturbance, and a measure of health care access, the AUC increased to 0.902, which was a significant improvement (P = 0.0021. When genetic information was added in the form of a count of PTSD risk alleles located within FKBP, COMT, CHRNA5, and CRHR1 genetic loci (coded 0–6, the AUC increased to 0.920, which was also a significant improvement (P = 0.0178. The results for current PTSD were similar. In the final model for current PTSD with the psychosocial risk factors included, genotype resulted in a prediction weight of 17 for each risk allele present, indicating that a person with six risk alleles or more would receive a PTSD risk score of 17 × 6 = 102, the highest risk score for any of the predictors studied. Conclusion: Genetic

  11. The M. D. Anderson Symptom Inventory-Head and Neck Module, a Patient-Reported Outcome Instrument, Accurately Predicts the Severity of Radiation-Induced Mucositis

    International Nuclear Information System (INIS)

    Purpose: To compare the M. D. Anderson Symptom Inventory-Head and Neck (MDASI-HN) module, a symptom burden instrument, with the Functional Assessment of Cancer Therapy-Head and Neck (FACT-HN) module, a quality-of-life instrument, for the assessment of mucositis in patients with head-and-neck cancer treated with radiotherapy and to identify the most distressing symptoms from the patient's perspective. Methods and Materials: Consecutive patients with head-and-neck cancer (n = 134) completed the MDASI-HN and FACT-HN before radiotherapy (time 1) and after 6 weeks of radiotherapy or chemoradiotherapy (time 2). The mean global and subscale scores for each instrument were compared with the objective mucositis scores determined from the National Cancer Institute Common Terminology Criteria for Adverse Events, version 3.0. Results: The global and subscale scores for each instrument showed highly significant changes from time 1 to time 2 and a significant correlation with the objective mucositis scores at time 2. Only the MDASI scores, however, were significant predictors of objective Common Terminology Criteria for Adverse Events mucositis scores on multivariate regression analysis (standardized regression coefficient, 0.355 for the global score and 0.310 for the head-and-neck cancer-specific score). Most of the moderate and severe symptoms associated with mucositis as identified on the MDASI-HN are not present on the FACT-HN. Conclusion: Both the MDASI-HN and FACT-HN modules can predict the mucositis scores. However, the MDASI-HN, a symptom burden instrument, was more closely associated with the severity of radiation-induced mucositis than the FACT-HN on multivariate regression analysis. This greater association was most likely related to the inclusion of a greater number of face-valid mucositis-related items in the MDASI-HN compared with the FACT-HN

  12. Clinical prediction rules in Staphylococcus aureus bacteremia demonstrate the usefulness of reporting likelihood ratios in infectious diseases.

    Science.gov (United States)

    Bai, A D; Showler, A; Burry, L; Steinberg, M; Tomlinson, G A; Bell, C M; Morris, A M

    2016-09-01

    Infectious diseases specialists often use diagnostic tests to assess the probability of a disease based on knowledge of the diagnostic properties. It has become standard for published studies on diagnostic tests to report sensitivity, specificity and predictive values. Likelihood ratios are often omitted. We compared published clinical prediction rules in Staphylococcus aureus bacteremia to illustrate the importance of likelihood ratios. We performed a narrative review comparing published clinical prediction rules used for excluding endocarditis in S. aureus bacteremia. Of nine published clinical prediction rules, only three studies reported likelihood ratios. Many studies concluded that the clinical prediction rule could safely exclude endocarditis based on high sensitivity and high negative predictive value. Of the studies with similar high sensitivity and high negative predictive value, calculated negative likelihood ratios were able to differentiate and identify the best clinical prediction rule for excluding endocarditis. Compared to sensitivity, specificity and predictive values, likelihood ratios can be more directly used to interpret diagnostic test results to assist in ruling in or ruling out a disease. Therefore, a new standard should be set to include likelihood ratios in reporting of diagnostic tests in infectious diseases research. PMID:27357965

  13. Preoperative MRI findings predict two-year postoperative clinical outcome in lumbar spinal stenosis.

    Directory of Open Access Journals (Sweden)

    Pekka Kuittinen

    Full Text Available To study the predictive value of preoperative magnetic resonance imaging (MRI findings for the two-year postoperative clinical outcome in lumbar spinal stenosis (LSS.84 patients (mean age 63±11 years, male 43% with symptoms severe enough to indicate LSS surgery were included in this prospective observational single-center study. Preoperative MRI of the lumbar spine was performed with a 1.5-T unit. The imaging protocol conformed to the requirements of the American College of Radiology for the performance of MRI of the adult spine. Visual and quantitative assessment of MRI was performed by one experienced neuroradiologist. At the two-year postoperative follow-up, functional ability was assessed with the Oswestry Disability Index (ODI 0-100% and treadmill test (0-1000 m, pain symptoms with the overall Visual Analogue Scale (VAS 0-100 mm, and specific low back pain (LBP and specific leg pain (LP separately with a numeric rating scale from 0-10 (NRS-11. Satisfaction with the surgical outcome was also assessed.Preoperative severe central stenosis predicted postoperatively lower LP, LBP, and VAS when compared in patients with moderate central stenosis (p<0.05. Moreover, severe stenosis predicted higher postoperative satisfaction (p = 0.029. Preoperative scoliosis predicted an impaired outcome in the ODI (p = 0.031 and lowered the walking distance in the treadmill test (p = 0.001. The preoperative finding of only one stenotic level in visual assessment predicted less postoperative LBP when compared with patients having 2 or more stenotic levels (p = 0.026. No significant differences were detected between quantitative measurements and the patient outcome.Routine preoperative lumbar spine MRI can predict the patient outcome in a two-year follow up in patients with LSS surgery. Severe central stenosis and one-level central stenosis are predictors of good outcome. Preoperative finding of scoliosis may indicate worse functional ability.

  14. Sensitivity, specificity and predictive value of blood cultures from cattle clinically suspected of bacterial endocarditis

    DEFF Research Database (Denmark)

    Houe, Hans; Eriksen, L.; Jungersen, Gregers;

    1993-01-01

    This study investigated the number of blood culture-positive cattle among 215 animals clinically suspected of having bacterial endocarditis. For animals that were necropsied, the sensitivity, specificity and predictive value of the diagnosis of endocarditis were calculated on the basis...... of the isolation of the causative bacteria from blood. Furthermore, it was investigated whether the glutaraldehyde coagulation time, total leucocyte count, per cent neutrophil granulocytes, pulse rate and duration of disease could help to discriminate endocarditis from other diseases. Among 138 animals necropsied...... the sensitivity, specificity and predictive value of blood cultivation were 70.7 per cent, 93.8 per cent and 89.1 per cent, respectively. None of the other measurements could be used to discriminate between endocarditis and non-endocarditis cases....

  15. Predictive Factors of Gastrointestinal Caustic Injury According to Clinical and Endoscopic Findings

    Directory of Open Access Journals (Sweden)

    Cherie Quingking

    2013-03-01

    Full Text Available Background: Ingestion of caustic substances is the main reason for referral to Philippines National Poison Management and Control Center among other causes of acute poisoning. Rapid assessment of severity of injury is important for treatment and prognosis of these cases. This study was aimed to investigate the correlation of clinical factors with severity of gastrointestinal (GI mucosal injury. Methods: In this retrospective study, a total of 105 patients were included. Patients were categorized into two groups including 35 patients with low grade and 70 patients with high grade GI injury to compare the predictive value of clinical findings. Results: Mean (SD age of patients was 27 (10 and 47% of patients were male. Oral burns (P

  16. An Update on Crown Lengthening. Part 2: Increasing Clinical Crown Height to Facilitate Predictable Restorations.

    Science.gov (United States)

    Kalsi, Harpoonam Jeet; Bomfim, Deborah Iola; Darbar, Ulpee

    2015-04-01

    This is the second paper in this two-part series. Paper one provided an overview of managing gingival tissue excess and paper two will focus on increasing clinical crown height to facilitate restorative treatment. Crown lengthening is a surgical procedure aimed at the removal of gingival tissue with or without adjunctive bone removal. The different types of procedure undertaken will be discussed over the two papers. In order to provide predictable restorations, care must be taken to ensure the integrity of the margins. If this is not taken into account it can lead to an impingement on the biologic width, which may in turn lead to chronic inflammation resulting in recession or the development of periodontal problems which can be hard to manage. Clinical Relevance: This paper aims to reinforce the need for thorough diagnosis and treatment planning and provides an overview of the various procedures that can be undertaken.

  17. Molecular biomarkers of colorectal cancer: prognostic and predictive tools for clinical practice

    Institute of Scientific and Technical Information of China (English)

    Wei-qin JIANG; Fang-fang FU; Yang-xia LI; Wei-bin WANG; Hao-hao WANG; Hai-ping JIANG; Li-song TENG

    2012-01-01

    Colorectal cancer remains one of the most common types of cancer and leading causes of cancer death worldwide.Although we have made steady progress in chemotherapy and targeted therapy,evidence suggests that the majority of patients undergoing drug therapy experience severe,debilitating,and even lethal adverse drug events which considerably outweigh the benefits.The identification of suitable biomarkers will allow clinicians to deliver the most appropriate drugs to specific patients and spare them ineffective and expensive treatments.Prognostic and predictive biomarkers have been the subjects of many published papers,but few have been widely incorporated into clinical practice.Here,we want to review recent biomarker data related to colorectal cancer,which may have been ready for clinical use.

  18. Optimal marker-strategy clinical trial design to detect predictive markers for targeted therapy.

    Science.gov (United States)

    Zang, Yong; Liu, Suyu; Yuan, Ying

    2016-07-01

    In developing targeted therapy, the marker-strategy design (MSD) provides an important approach to evaluate the predictive marker effect. This design first randomizes patients into non-marker-based or marker-based strategies. Patients allocated to the non-marker-based strategy are then further randomized to receive either the standard or targeted treatments, while patients allocated to the marker-based strategy receive treatments based on their marker statuses. Little research has been done on the statistical properties of the MSD, which has led to some widespread misconceptions and placed clinical researchers at high risk of using inefficient designs. In this article, we show that the commonly used between-strategy comparison has low power to detect the predictive effect and is valid only under a restrictive condition that the randomization ratio within the non-marker-based strategy matches the marker prevalence. We propose a Wald test that is generally valid and also uniformly more powerful than the between-strategy comparison. Based on that, we derive an optimal MSD that maximizes the power to detect the predictive marker effect by choosing the optimal randomization ratios between the two strategies and treatments. Our numerical study shows that using the proposed optimal designs can substantially improve the power of the MSD to detect the predictive marker effect. We use a lung cancer trial to illustrate the proposed optimal designs.

  19. Sputum biomarkers and the prediction of clinical outcomes in patients with cystic fibrosis.

    Directory of Open Access Journals (Sweden)

    Theodore G Liou

    Full Text Available Lung function, acute pulmonary exacerbations (APE, and weight are the best clinical predictors of survival in cystic fibrosis (CF; however, underlying mechanisms are incompletely understood. Biomarkers of current disease state predictive of future outcomes might identify mechanisms and provide treatment targets, trial endpoints and objective clinical monitoring tools. Such CF-specific biomarkers have previously been elusive. Using observational and validation cohorts comprising 97 non-transplanted consecutively-recruited adult CF patients at the Intermountain Adult CF Center, University of Utah, we identified biomarkers informative of current disease and predictive of future clinical outcomes. Patients represented the majority of sputum producers. They were recruited March 2004-April 2007 and followed through May 2011. Sputum biomarker concentrations were measured and clinical outcomes meticulously recorded for a median 5.9 (interquartile range 5.0 to 6.6 years to study associations between biomarkers and future APE and time-to-lung transplantation or death. After multivariate modeling, only high mobility group box-1 protein (HMGB-1, mean=5.84 [log ng/ml], standard deviation [SD] =1.75 predicted time-to-first APE (hazard ratio [HR] per log-unit HMGB-1=1.56, p-value=0.005, number of future APE within 5 years (0.338 APE per log-unit HMGB-1, p<0.001 by quasi-Poisson regression and time-to-lung transplantation or death (HR=1.59, p=0.02. At APE onset, sputum granulocyte macrophage colony stimulating factor (GM-CSF, mean 4.8 [log pg/ml], SD=1.26 was significantly associated with APE-associated declines in lung function (-10.8 FEV(1% points per log-unit GM-CSF, p<0.001 by linear regression. Evaluation of validation cohorts produced similar results that passed tests of mutual consistency. In CF sputum, high HMGB-1 predicts incidence and recurrence of APE and survival, plausibly because it mediates long-term airway inflammation. High APE-associated GM

  20. Per-beam, planar IMRT QA passing rates do not predict clinically relevant patient dose errors

    Energy Technology Data Exchange (ETDEWEB)

    Nelms, Benjamin E.; Zhen Heming; Tome, Wolfgang A. [Canis Lupus LLC and Department of Human Oncology, University of Wisconsin, Merrimac, Wisconsin 53561 (United States); Department of Medical Physics, University of Wisconsin, Madison, Wisconsin 53705 (United States); Departments of Human Oncology, Medical Physics, and Biomedical Engineering, University of Wisconsin, Madison, Wisconsin 53792 (United States)

    2011-02-15

    Purpose: The purpose of this work is to determine the statistical correlation between per-beam, planar IMRT QA passing rates and several clinically relevant, anatomy-based dose errors for per-patient IMRT QA. The intent is to assess the predictive power of a common conventional IMRT QA performance metric, the Gamma passing rate per beam. Methods: Ninety-six unique data sets were created by inducing four types of dose errors in 24 clinical head and neck IMRT plans, each planned with 6 MV Varian 120-leaf MLC linear accelerators using a commercial treatment planning system and step-and-shoot delivery. The error-free beams/plans were used as ''simulated measurements'' (for generating the IMRT QA dose planes and the anatomy dose metrics) to compare to the corresponding data calculated by the error-induced plans. The degree of the induced errors was tuned to mimic IMRT QA passing rates that are commonly achieved using conventional methods. Results: Analysis of clinical metrics (parotid mean doses, spinal cord max and D1cc, CTV D95, and larynx mean) vs IMRT QA Gamma analysis (3%/3 mm, 2/2, 1/1) showed that in all cases, there were only weak to moderate correlations (range of Pearson's r-values: -0.295 to 0.653). Moreover, the moderate correlations actually had positive Pearson's r-values (i.e., clinically relevant metric differences increased with increasing IMRT QA passing rate), indicating that some of the largest anatomy-based dose differences occurred in the cases of high IMRT QA passing rates, which may be called ''false negatives.'' The results also show numerous instances of false positives or cases where low IMRT QA passing rates do not imply large errors in anatomy dose metrics. In none of the cases was there correlation consistent with high predictive power of planar IMRT passing rates, i.e., in none of the cases did high IMRT QA Gamma passing rates predict low errors in anatomy dose metrics or vice versa

  1. Do clinical factors help to predict disease course in inflammatory bowel disease?

    Institute of Scientific and Technical Information of China (English)

    Edouard; Louis; Jacques; Belaiche; Catherine; Reenaers

    2010-01-01

    While therapeutic strategies able to change the natural history of the disease are developing,it is of major importance to have available predictive factors for aggressive disease to try and target these therapeutic strategies.Clinical predictors have probably been the most broadly studied.In both Crohn's disease(CD) and ulcerative colitis(UC),age at diagnosis,disease location and smoking habit are currently the strongest predictors of disease course.A younger age at onset is associated with more aggressive...

  2. Clinical prediction model to aid emergency doctors managing febrile children at risk of serious bacterial infections: Diagnostic study

    NARCIS (Netherlands)

    R.G. Nijman (Ruud); Y. Vergouwe (Yvonne); M.J. Thompson (Matthew); M.V. Veen (Mirjam Van); A.H.J. van Meurs (Alfred); J. van der Lei (Johan); E.W. Steyerberg (Ewout); H.A. Moll (Henriëtte); R. Oostenbrink (Rianne)

    2013-01-01

    textabstractObjective: To derive, cross validate, and externally validate a clinical prediction model that assesses the risks of different serious bacterial infections in children with fever at the emergency department. Design: Prospective observational diagnostic study. Setting: Three paediatric em

  3. Factors predicting suicidal ideation in the preceding 12 months among patients attending a community psychiatric outpatient clinic.

    LENUS (Irish Health Repository)

    Anyansi, Tochukwu E

    2013-06-01

    Predictive factors are used to alert the clinician to the necessity of carrying out a suicide risk assessment in those patients whose demographic and clinical characteristics suggest the possibility of suicide.

  4. Developing a clinical utility framework to evaluate prediction models in radiogenomics

    Science.gov (United States)

    Wu, Yirong; Liu, Jie; Munoz del Rio, Alejandro; Page, David C.; Alagoz, Oguzhan; Peissig, Peggy; Onitilo, Adedayo A.; Burnside, Elizabeth S.

    2015-03-01

    Combining imaging and genetic information to predict disease presence and behavior is being codified into an emerging discipline called "radiogenomics." Optimal evaluation methodologies for radiogenomics techniques have not been established. We aim to develop a clinical decision framework based on utility analysis to assess prediction models for breast cancer. Our data comes from a retrospective case-control study, collecting Gail model risk factors, genetic variants (single nucleotide polymorphisms-SNPs), and mammographic features in Breast Imaging Reporting and Data System (BI-RADS) lexicon. We first constructed three logistic regression models built on different sets of predictive features: (1) Gail, (2) Gail+SNP, and (3) Gail+SNP+BI-RADS. Then, we generated ROC curves for three models. After we assigned utility values for each category of findings (true negative, false positive, false negative and true positive), we pursued optimal operating points on ROC curves to achieve maximum expected utility (MEU) of breast cancer diagnosis. We used McNemar's test to compare the predictive performance of the three models. We found that SNPs and BI-RADS features augmented the baseline Gail model in terms of the area under ROC curve (AUC) and MEU. SNPs improved sensitivity of the Gail model (0.276 vs. 0.147) and reduced specificity (0.855 vs. 0.912). When additional mammographic features were added, sensitivity increased to 0.457 and specificity to 0.872. SNPs and mammographic features played a significant role in breast cancer risk estimation (p-value < 0.001). Our decision framework comprising utility analysis and McNemar's test provides a novel framework to evaluate prediction models in the realm of radiogenomics.

  5. Can clinical colour vision tests be used to predict the results of the Farnsworth lantern test?

    Science.gov (United States)

    Cole, B L; Maddocks, J D

    1998-11-01

    Clinicians usually do not have access to a lantern test when making an occupational assessment of the ability of a person with defective colour vision to recognise signal light colours: they must rely on the results of ordinary clinical tests. While all colour vision defectives fail the Holmes Wright Type B lantern test and most fail the Holmes Wright Type A lantern, 35% of colour vision defectives pass the Farnsworth lantern. Can clinical tests predict who will pass and fail the Farnsworth lantern? We find that a pass (less than two or more diametrical crossings) at the Farnsworth Panel D 15 Dichotomous test has a sensitivity of 0.67 and specificity of 0.94 in predicting a pass or fail at the Farnsworth lantern test: a Nagel range of > 10 has a sensitivity of 0.87 and a specificity of 0.57. We conclude that neither the D 15 nor the Nagel Anomaloscope matching range are satisfactory predictors of performance on the Farnsworth Lantern.

  6. Predicting the risk of suicide by analyzing the text of clinical notes.

    Directory of Open Access Journals (Sweden)

    Chris Poulin

    Full Text Available We developed linguistics-driven prediction models to estimate the risk of suicide. These models were generated from unstructured clinical notes taken from a national sample of U.S. Veterans Administration (VA medical records. We created three matched cohorts: veterans who committed suicide, veterans who used mental health services and did not commit suicide, and veterans who did not use mental health services and did not commit suicide during the observation period (n = 70 in each group. From the clinical notes, we generated datasets of single keywords and multi-word phrases, and constructed prediction models using a machine-learning algorithm based on a genetic programming framework. The resulting inference accuracy was consistently 65% or more. Our data therefore suggests that computerized text analytics can be applied to unstructured medical records to estimate the risk of suicide. The resulting system could allow clinicians to potentially screen seemingly healthy patients at the primary care level, and to continuously evaluate the suicide risk among psychiatric patients.

  7. Knee shape might predict clinical outcome after an anterior cruciate ligament rupture.

    Science.gov (United States)

    Eggerding, V; van Kuijk, K S R; van Meer, B L; Bierma-Zeinstra, S M A; van Arkel, E R A; Reijman, M; Waarsing, J H; Meuffels, D E

    2014-06-01

    We have investigated whether shape of the knee can predict the clinical outcome of patients after an anterior cruciate ligament rupture. We used statistical shape modelling to measure the shape of the knee joint of 182 prospectively followed patients on lateral and Rosenberg view radiographs of the knee after a rupture of the anterior cruciate ligament. Subsequently, we associated knee shape with the International Knee Documentation Committee subjective score at two years follow-up. The mean age of patients was 31 years (21 to 51), the majority were male (n = 121) and treated operatively (n = 135). We found two modes (shape variations) that were significantly associated with the subjective score at two years: one for the operatively treated group (p = 0.002) and one for the non-operatively treated group (p = 0.003). Operatively treated patients who had higher subjective scores had a smaller intercondylar notch and a smaller width of the intercondylar eminence. Non-operatively treated patients who scored higher on the subjective score had a more pyramidal intercondylar notch as opposed to one that was more dome-shaped. We conclude that the shape of the femoral notch and the intercondylar eminence is predictive of clinical outcome two years after a rupture of the anterior cruciate ligament.

  8. Clinical manifestations that predict abnormal brain computed tomography (CT in children with minor head injury

    Directory of Open Access Journals (Sweden)

    Nesrin Alharthy

    2015-01-01

    Full Text Available Background: Computed tomography (CT used in pediatric pediatrics brain injury (TBI to ascertain neurological manifestations. Nevertheless, this practice is associated with adverse effects. Reports in the literature suggest incidents of morbidity and mortality in children due to exposure to radiation. Hence, it is found imperative to search for a reliable alternative. Objectives: The aim of this study is to find a reliable clinical alternative to detect an intracranial injury without resorting to the CT. Materials and Methods: Retrospective cross-sectional study was undertaken in patients (1-14 years with blunt head injury and having a Glasgow Coma Scale (GCS of 13-15 who had CT performed on them. Using statistical analysis, the correlation between clinical examination and positive CT manifestation is analyzed for different age-groups and various mechanisms of injury. Results: No statistically significant association between parameteres such as Loss of Consciousness, ′fall′ as mechanism of injury, motor vehicle accidents (MVA, more than two discrete episodes of vomiting and the CT finding of intracranial injury could be noted. Analyzed data have led to believe that GCS of 13 at presentation is the only important clinical predictor of intracranial injury. Conclusion: Retrospective data, small sample size and limited number of factors for assessing clinical manifestation might present constraints on the predictive rule that was derived from this review. Such limitations notwithstanding, the decision to determine which patients should undergo neuroimaging is encouraged to be based on clinical judgments. Further analysis with higher sample sizes may be required to authenticate and validate findings.

  9. Comparison of Existing Clinical Scoring Systems in Predicting Severity and Prognoses of Hyperlipidemic Acute Pancreatitis in Chinese Patients

    OpenAIRE

    Qiu, Lei; Sun, Rui Qing; Jia, Rong Rong; Ma, Xiu Ying; Cheng, Li; Tang, Mao Chun; Zhao, Yan

    2015-01-01

    Abstract It is important to identify the severity of acute pancreatitis (AP) in the early course of the disease. Clinical scoring systems may be helpful to predict the prognosis of patients with early AP; however, few analysts have forecast the accuracy of scoring systems for the prognosis in hyperlipidemic acute pancreatitis (HLAP). The purpose of this study was to summarize the clinical characteristics of HLAP and compare the accuracy of conventional scoring systems in predicting the progno...

  10. Analytical and Clinical Validation of a Digital Sequencing Panel for Quantitative, Highly Accurate Evaluation of Cell-Free Circulating Tumor DNA.

    Directory of Open Access Journals (Sweden)

    Richard B Lanman

    Full Text Available Next-generation sequencing of cell-free circulating solid tumor DNA addresses two challenges in contemporary cancer care. First this method of massively parallel and deep sequencing enables assessment of a comprehensive panel of genomic targets from a single sample, and second, it obviates the need for repeat invasive tissue biopsies. Digital Sequencing™ is a novel method for high-quality sequencing of circulating tumor DNA simultaneously across a comprehensive panel of over 50 cancer-related genes with a simple blood test. Here we report the analytic and clinical validation of the gene panel. Analytic sensitivity down to 0.1% mutant allele fraction is demonstrated via serial dilution studies of known samples. Near-perfect analytic specificity (> 99.9999% enables complete coverage of many genes without the false positives typically seen with traditional sequencing assays at mutant allele frequencies or fractions below 5%. We compared digital sequencing of plasma-derived cell-free DNA to tissue-based sequencing on 165 consecutive matched samples from five outside centers in patients with stage III-IV solid tumor cancers. Clinical sensitivity of plasma-derived NGS was 85.0%, comparable to 80.7% sensitivity for tissue. The assay success rate on 1,000 consecutive samples in clinical practice was 99.8%. Digital sequencing of plasma-derived DNA is indicated in advanced cancer patients to prevent repeated invasive biopsies when the initial biopsy is inadequate, unobtainable for genomic testing, or uninformative, or when the patient's cancer has progressed despite treatment. Its clinical utility is derived from reduction in the costs, complications and delays associated with invasive tissue biopsies for genomic testing.

  11. Analytical and Clinical Validation of a Digital Sequencing Panel for Quantitative, Highly Accurate Evaluation of Cell-Free Circulating Tumor DNA

    Science.gov (United States)

    Zill, Oliver A.; Sebisanovic, Dragan; Lopez, Rene; Blau, Sibel; Collisson, Eric A.; Divers, Stephen G.; Hoon, Dave S. B.; Kopetz, E. Scott; Lee, Jeeyun; Nikolinakos, Petros G.; Baca, Arthur M.; Kermani, Bahram G.; Eltoukhy, Helmy; Talasaz, AmirAli

    2015-01-01

    Next-generation sequencing of cell-free circulating solid tumor DNA addresses two challenges in contemporary cancer care. First this method of massively parallel and deep sequencing enables assessment of a comprehensive panel of genomic targets from a single sample, and second, it obviates the need for repeat invasive tissue biopsies. Digital SequencingTM is a novel method for high-quality sequencing of circulating tumor DNA simultaneously across a comprehensive panel of over 50 cancer-related genes with a simple blood test. Here we report the analytic and clinical validation of the gene panel. Analytic sensitivity down to 0.1% mutant allele fraction is demonstrated via serial dilution studies of known samples. Near-perfect analytic specificity (> 99.9999%) enables complete coverage of many genes without the false positives typically seen with traditional sequencing assays at mutant allele frequencies or fractions below 5%. We compared digital sequencing of plasma-derived cell-free DNA to tissue-based sequencing on 165 consecutive matched samples from five outside centers in patients with stage III-IV solid tumor cancers. Clinical sensitivity of plasma-derived NGS was 85.0%, comparable to 80.7% sensitivity for tissue. The assay success rate on 1,000 consecutive samples in clinical practice was 99.8%. Digital sequencing of plasma-derived DNA is indicated in advanced cancer patients to prevent repeated invasive biopsies when the initial biopsy is inadequate, unobtainable for genomic testing, or uninformative, or when the patient’s cancer has progressed despite treatment. Its clinical utility is derived from reduction in the costs, complications and delays associated with invasive tissue biopsies for genomic testing. PMID:26474073

  12. Outcomes of Health System Structures, Highly Pertinent Clinical Information, Idea Stimulators, Clinical Reviews, and Prediction Tools: JABFM Exemplified.

    Science.gov (United States)

    Bowman, Marjorie A; Neale, Anne Victoria; Seehusen, Dean A

    2016-01-01

    This issue exemplifies the types of articles that JABFM publishes to advance family medicine. We have articles on the implications of health system organizational structures. Three of these are international articles at the level of the national health system (1 from China) and systematic local health interventions (1 from Canada and 1 from Netherlands). Inside the United States, where there are more family physicians, there is less obesity, and designation as a Patient Centered Medical Home is related to increased rates of colorectal cancer screening. Review articles on common clinical topics discuss treatments that are changing (acne in pregnancy) or lack consensus (distal radial fractures). We have articles on making life easier in the office, such as for predicting Vitamin D levels, osteoporosis, and pre-diabetes in normal weight adults. There are articles to raise awareness of the "newest" testing or treatments, that is, auditory brainstem implants. "Reminder" articles highlight known entities that need to be reinforced to prevent over-/underdiagnosis or treatment, for example, "cotton fever." Another article discusses the increased risk for postoperative complications with sleep apnea. We also provide "thought" pieces, in this case about the terminology we are using to extend our concept of patient-centered medical homes.

  13. Outcomes of Health System Structures, Highly Pertinent Clinical Information, Idea Stimulators, Clinical Reviews, and Prediction Tools: JABFM Exemplified.

    Science.gov (United States)

    Bowman, Marjorie A; Neale, Anne Victoria; Seehusen, Dean A

    2016-01-01

    This issue exemplifies the types of articles that JABFM publishes to advance family medicine. We have articles on the implications of health system organizational structures. Three of these are international articles at the level of the national health system (1 from China) and systematic local health interventions (1 from Canada and 1 from Netherlands). Inside the United States, where there are more family physicians, there is less obesity, and designation as a Patient Centered Medical Home is related to increased rates of colorectal cancer screening. Review articles on common clinical topics discuss treatments that are changing (acne in pregnancy) or lack consensus (distal radial fractures). We have articles on making life easier in the office, such as for predicting Vitamin D levels, osteoporosis, and pre-diabetes in normal weight adults. There are articles to raise awareness of the "newest" testing or treatments, that is, auditory brainstem implants. "Reminder" articles highlight known entities that need to be reinforced to prevent over-/underdiagnosis or treatment, for example, "cotton fever." Another article discusses the increased risk for postoperative complications with sleep apnea. We also provide "thought" pieces, in this case about the terminology we are using to extend our concept of patient-centered medical homes. PMID:26957371

  14. Prediction of outcome in patients with low back pain

    DEFF Research Database (Denmark)

    Kongsted, Alice; Andersen, Cathrine Hedegaard; Hansen, Martin Mørk;

    2016-01-01

    The clinical course of low back pain (LBP) cannot be accurately predicted by existing prediction tools. Therefore clinicians rely largely on their experience and clinical judgement. The objectives of this study were to investigate 1) which patient characteristics were associated with chiropractors......' expectations of outcome from a LBP episode, 2) if clinicians' expectations related to outcome, 3) how accurate clinical predictions were as compared to those of the STarT Back Screening Tool (SBT), and 4) if accuracy was improved by combining clinicians' expectations and the SBT. Outcomes were measured as LBP...... investigating if more accurate tools can be developed to assist clinicians in prediction of outcome....

  15. Predicting progression of IgA nephropathy: new clinical progression risk score.

    Directory of Open Access Journals (Sweden)

    Jingyuan Xie

    Full Text Available IgA nephropathy (IgAN is a common cause of end-stage renal disease (ESRD in Asia. In this study, based on a large cohort of Chinese patients with IgAN, we aim to identify independent predictive factors associated with disease progression to ESRD. We collected retrospective clinical data and renal outcomes on 619 biopsy-diagnosed IgAN patients with a mean follow-up time of 41.3 months. In total, 67 individuals reached the study endpoint defined by occurrence of ESRD necessitating renal replacement therapy. In the fully adjusted Cox proportional hazards model, there were four baseline variables with a significant independent effect on the risk of ESRD. These included: eGFR [HR = 0.96(0.95-0.97], serum albumin [HR = 0.47(0.32-0.68], hemoglobin [HR = 0.79(0.72-0.88], and SBP [HR = 1.02(1.00-1.03]. Based on these observations, we developed a 4-variable equation of a clinical risk score for disease progression. Our risk score explained nearly 22% of the total variance in the primary outcome. Survival ROC curves revealed that the risk score provided improved prediction of ESRD at 24th, 60th and 120th month of follow-up compared to the three previously proposed risk scores. In summary, our data indicate that IgAN patients with higher systolic blood pressure, lower eGFR, hemoglobin, and albumin levels at baseline are at a greatest risk of progression to ESRD. The new progression risk score calculated based on these four baseline variables offers a simple clinical tool for risk stratification.

  16. Translation of clinical prediction rules for febrile children to primary care practice: an observational cohort study

    Science.gov (United States)

    van Ierland, Yvette; Elshout, Gijs; Berger, Marjolein Y; Vergouwe, Yvonne; de Wilde, Marcel; van der Lei, Johan; Mol, Henriëtte A; Oostenbrink, Rianne

    2015-01-01

    Background Clinical prediction rules (CPRs) to identify children with serious infections lack validation in low-prevalence populations, which hampers their implementation in primary care practice. Aim To evaluate the diagnostic value of published CPRs for febrile children in primary care. Design and setting Observational cohort study among febrile children (<16 years) who consulted five GP cooperatives (GPCs) in the Netherlands. Method Alarm signs of serious infection and clinical management were extracted from routine clinical practice data and manually recoded with a structured electronic data-entry program. Eight CPRs were selected from literature. CPR-variables were matched with alarm signs and CPRs were applied to the GPC-population. ‘Referral to emergency department (ED)’ was used as a proxy outcome measure for ‘serious infection’. CPR performance was assessed by calibration analyses, sensitivity, specificity, and area under the ROC-curve (ROC-area). Results A total of 9794 GPC-contacts were eligible, 54% male, median age 2.3 years (interquartile range 1.0–4.6 years) and 8.1% referred to ED. Frequencies of CPR-variables varied from 0.5% (cyanosis, drowsy) to 25% (temperature ≥40°C). Alarm signs frequently included in CPRs were ‘ill appearance’, ‘inconsolable’, and ‘abnormal circulatory or respiratory signs’. The height of the CPR’s predicted risks generally corresponded with being (or not being) referred to the ED in practice. However, calibration-slopes indicated that three CPRs underestimated the risk of serious infection in the GPC-population. Sensitivities ranged from 42% to 54%, specificities from 68% to 89%. ROC-areas ranged from 0.52 to 0.81, with best performance of CPRs for children aged <3 months. Conclusion Published CPRs performed moderately well in the primary out-of-hours care population. Advice is given on how to improve translation of CPRs to primary care practice. PMID:25824182

  17. TH-E-BRF-05: Comparison of Survival-Time Prediction Models After Radiotherapy for High-Grade Glioma Patients Based On Clinical and DVH Features

    Energy Technology Data Exchange (ETDEWEB)

    Magome, T; Haga, A; Igaki, H; Sekiya, N; Masutani, Y; Sakumi, A; Mukasa, A; Nakagawa, K [The University of Tokyo Hospital, Tokyo, JP (Japan)

    2014-06-15

    Purpose: Although many outcome prediction models based on dose-volume information have been proposed, it is well known that the prognosis may be affected also by multiple clinical factors. The purpose of this study is to predict the survival time after radiotherapy for high-grade glioma patients based on features including clinical and dose-volume histogram (DVH) information. Methods: A total of 35 patients with high-grade glioma (oligodendroglioma: 2, anaplastic astrocytoma: 3, glioblastoma: 30) were selected in this study. All patients were treated with prescribed dose of 30–80 Gy after surgical resection or biopsy from 2006 to 2013 at The University of Tokyo Hospital. All cases were randomly separated into training dataset (30 cases) and test dataset (5 cases). The survival time after radiotherapy was predicted based on a multiple linear regression analysis and artificial neural network (ANN) by using 204 candidate features. The candidate features included the 12 clinical features (tumor location, extent of surgical resection, treatment duration of radiotherapy, etc.), and the 192 DVH features (maximum dose, minimum dose, D95, V60, etc.). The effective features for the prediction were selected according to a step-wise method by using 30 training cases. The prediction accuracy was evaluated by a coefficient of determination (R{sup 2}) between the predicted and actual survival time for the training and test dataset. Results: In the multiple regression analysis, the value of R{sup 2} between the predicted and actual survival time was 0.460 for the training dataset and 0.375 for the test dataset. On the other hand, in the ANN analysis, the value of R{sup 2} was 0.806 for the training dataset and 0.811 for the test dataset. Conclusion: Although a large number of patients would be needed for more accurate and robust prediction, our preliminary Result showed the potential to predict the outcome in the patients with high-grade glioma. This work was partly supported by

  18. TH-E-BRF-05: Comparison of Survival-Time Prediction Models After Radiotherapy for High-Grade Glioma Patients Based On Clinical and DVH Features

    International Nuclear Information System (INIS)

    Purpose: Although many outcome prediction models based on dose-volume information have been proposed, it is well known that the prognosis may be affected also by multiple clinical factors. The purpose of this study is to predict the survival time after radiotherapy for high-grade glioma patients based on features including clinical and dose-volume histogram (DVH) information. Methods: A total of 35 patients with high-grade glioma (oligodendroglioma: 2, anaplastic astrocytoma: 3, glioblastoma: 30) were selected in this study. All patients were treated with prescribed dose of 30–80 Gy after surgical resection or biopsy from 2006 to 2013 at The University of Tokyo Hospital. All cases were randomly separated into training dataset (30 cases) and test dataset (5 cases). The survival time after radiotherapy was predicted based on a multiple linear regression analysis and artificial neural network (ANN) by using 204 candidate features. The candidate features included the 12 clinical features (tumor location, extent of surgical resection, treatment duration of radiotherapy, etc.), and the 192 DVH features (maximum dose, minimum dose, D95, V60, etc.). The effective features for the prediction were selected according to a step-wise method by using 30 training cases. The prediction accuracy was evaluated by a coefficient of determination (R2) between the predicted and actual survival time for the training and test dataset. Results: In the multiple regression analysis, the value of R2 between the predicted and actual survival time was 0.460 for the training dataset and 0.375 for the test dataset. On the other hand, in the ANN analysis, the value of R2 was 0.806 for the training dataset and 0.811 for the test dataset. Conclusion: Although a large number of patients would be needed for more accurate and robust prediction, our preliminary Result showed the potential to predict the outcome in the patients with high-grade glioma. This work was partly supported by the JSPS Core

  19. A Clinical Indications Prediction Scale Based on TWIST1 for Human Mesenchymal Stem Cells

    Directory of Open Access Journals (Sweden)

    Siddaraju V. Boregowda

    2016-02-01

    Full Text Available In addition to their stem/progenitor properties, mesenchymal stem cells (MSCs also exhibit potent effector (angiogenic, antiinflammatory, immuno-modulatory functions that are largely paracrine in nature. It is widely believed that effector functions underlie most of the therapeutic potential of MSCs and are independent of their stem/progenitor properties. Here we demonstrate that stem/progenitor and effector functions are coordinately regulated at the cellular level by the transcription factor Twist1 and specified within populations according to a hierarchical model. We further show that manipulation of Twist1 levels by genetic approaches or by exposure to widely used culture supplements including fibroblast growth factor 2 (Ffg2 and interferon gamma (IFN-gamma alters MSC efficacy in cell-based and in vivo assays in a predictable manner. Thus, by mechanistically linking stem/progenitor and effector functions our studies provide a unifying framework in the form of an MSC hierarchy that models the functional complexity of populations. Using this framework, we developed a CLinical Indications Prediction (CLIP scale that predicts how donor-to-donor heterogeneity and culture conditions impact the therapeutic efficacy of MSC populations for different disease indications.

  20. A Clinical Indications Prediction Scale Based on TWIST1 for Human Mesenchymal Stem Cells.

    Science.gov (United States)

    Boregowda, Siddaraju V; Krishnappa, Veena; Haga, Christopher L; Ortiz, Luis A; Phinney, Donald G

    2016-02-01

    In addition to their stem/progenitor properties, mesenchymal stem cells (MSCs) also exhibit potent effector (angiogenic, antiinflammatory, immuno-modulatory) functions that are largely paracrine in nature. It is widely believed that effector functions underlie most of the therapeutic potential of MSCs and are independent of their stem/progenitor properties. Here we demonstrate that stem/progenitor and effector functions are coordinately regulated at the cellular level by the transcription factor Twist1 and specified within populations according to a hierarchical model. We further show that manipulation of Twist1 levels by genetic approaches or by exposure to widely used culture supplements including fibroblast growth factor 2 (Ffg2) and interferon gamma (IFN-gamma) alters MSC efficacy in cell-based and in vivo assays in a predictable manner. Thus, by mechanistically linking stem/progenitor and effector functions our studies provide a unifying framework in the form of an MSC hierarchy that models the functional complexity of populations. Using this framework, we developed a CLinical Indications Prediction (CLIP) scale that predicts how donor-to-donor heterogeneity and culture conditions impact the therapeutic efficacy of MSC populations for different disease indications. PMID:26981553

  1. Thyroid Hormones, Autoantibodies, Ultrasonography, and Clinical Parameters for Predicting Thyroid Cancer

    Science.gov (United States)

    He, Lin-zheng; Zeng, Tian-shu; Pu, Lin; Pan, Shi-xiu; Xia, Wen-fang; Chen, Lu-lu

    2016-01-01

    Our objective was to evaluate thyroid nodule malignancy prediction using thyroid function tests, autoantibodies, ultrasonographic imaging, and clinical data. We conducted a retrospective cohort study in 1400 patients with nodular thyroid disease (NTD). The thyroid stimulating hormone (TSH) concentration was significantly higher in patients with differentiated thyroid cancer (DTC) versus benign thyroid nodular disease (BTND) (p = 0.004). The receiver operating characteristic curve of TSH showed an AUC of 0.58 (95% CI 0.53–0.62, p = 0.001), sensitivity of 74%, and specificity of 57% at a cut-off of 1.59 mIU/L. There was an incremental increase in TSH concentration along with the increasing tumor size (p < 0.001). Thyroglobulin antibody (TgAb) concentration was associated with an increased risk of malignancy (p = 0.029), but this association was lost when the effect of TSH was taken into account (p = 0.11). Thyroid ultrasonographic characteristics, including fewer than three nodules, hypoechoic appearance, solid component, poorly defined margin, intranodular or peripheral-intranodular flow, and punctate calcification, can be used to predict the risk of thyroid cancer. In conclusion, our study suggests that preoperative serum TSH concentration, age, and ultrasonographic features can be used to predict the risk of malignancy in patients with NTD. PMID:27313612

  2. Advanced Online Survival Analysis Tool for Predictive Modelling in Clinical Data Science.

    Science.gov (United States)

    Montes-Torres, Julio; Subirats, José Luis; Ribelles, Nuria; Urda, Daniel; Franco, Leonardo; Alba, Emilio; Jerez, José Manuel

    2016-01-01

    One of the prevailing applications of machine learning is the use of predictive modelling in clinical survival analysis. In this work, we present our view of the current situation of computer tools for survival analysis, stressing the need of transferring the latest results in the field of machine learning to biomedical researchers. We propose a web based software for survival analysis called OSA (Online Survival Analysis), which has been developed as an open access and user friendly option to obtain discrete time, predictive survival models at individual level using machine learning techniques, and to perform standard survival analysis. OSA employs an Artificial Neural Network (ANN) based method to produce the predictive survival models. Additionally, the software can easily generate survival and hazard curves with multiple options to personalise the plots, obtain contingency tables from the uploaded data to perform different tests, and fit a Cox regression model from a number of predictor variables. In the Materials and Methods section, we depict the general architecture of the application and introduce the mathematical background of each of the implemented methods. The study concludes with examples of use showing the results obtained with public datasets. PMID:27532883

  3. Cross-sectional imaging for diagnosis and clinical outcome prediction of acute basilar artery thrombosis

    International Nuclear Information System (INIS)

    Basilar artery occlusion is a potentially fatal condition and imaging findings can be subtle. Prompt diagnosis is vital, as recognition may lead to therapeutic recanalization that may improve functional outcome and survival. Furthermore, cross-sectional imaging signs may help predict eventual outcome and, therefore, guide which patients should be subjected to aggressive treatment. Computed tomography (CT) signs include a hyperdense basilar artery that has a high specificity, accuracy, positive and negative predictive value. Evidence regarding the prognostic significance of the hyperdense basilar artery sign is conflicting. Early magnetic resonance imaging (MRI) features include loss of flow void, seen as increased signal intensity within the basilar artery on T2-weigted images and identification of acute thrombus, seen as intermediate signal on T1-weighted images. MRI sequences are more sensitive for early detection of acute ischaemia or infarction, ideally with diffusion-weighted imaging (DWI). Both CT and MR angiography are sensitive for detection of acute thrombus, seen as a filling defect or occlusion. These are the non-invasive imaging techniques of choice to confirm diagnosis, with perhaps the speed and accessibility of CT angiography resulting in this technique being valuable in the acute setting. Several new scoring systems based on arterial segmentation rather than global volume assessment using CT angiography source images and DWI have shown early promise in the prediction of eventual clinical outcome in order to isolate those patients who may benefit from therapeutic recanalization.

  4. Predictive Value of IL-8 for Sepsis and Severe Infections After Burn Injury: A Clinical Study.

    Science.gov (United States)

    Kraft, Robert; Herndon, David N; Finnerty, Celeste C; Cox, Robert A; Song, Juquan; Jeschke, Marc G

    2015-03-01

    The inflammatory response induced by burn injury contributes to increased incidence of infections, sepsis, organ failure, and mortality. Thus, monitoring postburn inflammation is of paramount importance but, so far, there are no reliable biomarkers available to monitor and/or predict infectious complications after burn. As interleukin 8 (IL-8) is a major mediator for inflammatory responses, the aim of our study was to determine whether IL-8 expression can be used to predict postburn sepsis, infections, and mortality. Plasma cytokines, acute-phase proteins, constitutive proteins, and hormones were analyzed during the first 60 days after injury from 468 pediatric burn patients. Demographics and clinical outcome variables (length of stay, infection, sepsis, multiorgan failure [MOF], and mortality) were recorded. A cutoff level for IL-8 was determined using receiver operating characteristic analysis. Statistical significance is set at P Patients were grouped according to their average IL-8 levels relative to this cutoff and stratified into high (H) (n = 133) and low (L) (n = 335) groups. In the L group, regression analysis revealed a significant predictive value of IL-8 to percent of total body surface area burned and incidence of MOF (P inflammatory and acute-phase responses compared with the L group (P burn patients.

  5. Prediction of clinical factors associated with pandemic influenza A (H1N1 2009 in Pakistan.

    Directory of Open Access Journals (Sweden)

    Nadia Nisar

    Full Text Available BACKGROUND: Influenza is a viral infection that can lead to serious complications and death(s in vulnerable groups if not diagnosed and managed in a timely manner. This study was conducted to improve the accuracy of predicting influenza through various clinical and statistical models. METHODOLOGY: A retrospective cross sectional analysis was done on demographic and epidemiological data collected from March 2009 to March 2010. Patients were classified as ILI or SARI using WHO case definitions. Respiratory specimens were tested by RT-PCR. Clinical symptoms and co-morbid conditions were analyzed using binary logistic regression models. RESULTS: In the first approach, analysis compared children (≤12 and adults (>12. Of 1,243 cases, 262 (21% tested positive for A(H1N1pdm09 and the proportion of children (≤12 and adults (>12 were 27% and 73% respectively. Four symptoms predicted influenza in children: fever (OR 2.849, 95% CI 1.931-8.722, cough (OR 1.99, 95% CI 1.512-3.643, diarrhea (OR 2.100, 95% CI 2.040-3.25 and respiratory disease (OR 3.269, 95% CI 2.128-12.624. In adults, the strongest clinical predictor was fever (OR 2.80, 95% CI 1.025-3.135 followed by cough (OR 1.431, 95% CI 1.032-2.815. In the second instance, patients were separated into two groups: SARI 326 (26% and ILI 917 (74% cases. Male to female ratio was 1.41∶1.12 for SARI and 2∶1.5 for ILI cases. Chi-square test showed that fever, cough and sore throat were significant factors for A(H1N1pdm09 infections (p = 0.008. CONCLUSION: Studies in a primary care setting should be encouraged focused on patients with influenza-like illness to develop sensitive clinical case definition that will help to improve accuracy of detecting influenza infections. Formulation of a standard "one size fits all" case definition that best correlates with influenza infections can help guide decisions for additional diagnostic testing and also discourage unjustified antibiotic prescription and usage

  6. Prediction of clinical response based on pharmacokinetic/pharmacodynamic models of 5-hydroxytryptamine reuptake inhibitors in mice

    DEFF Research Database (Denmark)

    Kreilgaard, Mads; Smith, D. G.; Brennum, L. T.;

    2008-01-01

    Bridging the gap between preclinical research and clinical trials is vital for drug development. Predicting clinically relevant steady-state drug concentrations (Css) in serum from preclinical animal models may facilitate this transition. Here we used a pharmacokinetic/pharmacodynamic (PK/PD) mod...

  7. Innovative Drugs to Treat Depression: Did Animal Models Fail to Be Predictive or Did Clinical Trials Fail to Detect Effects?

    OpenAIRE

    Belzung, Catherine

    2014-01-01

    Over recent decades, encouraging preclinical evidence using rodent models pointed to innovative pharmacological targets to treat major depressive disorder. However, subsequent clinical trials have failed to show convincing results. Two explanations for these rather disappointing results can be put forward, either animal models of psychiatric disorders have failed to predict the clinical effectiveness of treatments or clinical trials have failed to detect the effects of these new drugs. A care...

  8. Predictive Value of IL-8 for Sepsis and Severe Infections after Burn Injury - A Clinical Study

    Science.gov (United States)

    Kraft, Robert; Herndon, David N; Finnerty, Celeste C; Cox, Robert A; Song, Juquan; Jeschke, Marc G

    2014-01-01

    The inflammatory response induced by burn injury contributes to increased incidence of infections, sepsis, organ failure, and mortality. Thus, monitoring post-burn inflammation is of paramount importance but so far there are no reliable biomarkers available to monitor and/or predict infectious complications after burn. As IL-8 is a major mediator for inflammatory responses, the aim of our study was to determine whether IL-8 expression can be used to predict post-burn sepsis, infections, and mortality other outcomes post-burn. Plasma cytokines, acute phase proteins, constitutive proteins, and hormones were analyzed during the first 60 days post injury from 468 pediatric burn patients. Demographics and clinical outcome variables (length of stay, infection, sepsis, multiorgan failure (MOF), and mortality were recorded. A cut-off level for IL-8 was determined using receiver operating characteristic (ROC) analysis. Statistical significance is set at (p<0.05). ROC analysis identified a cut-off level of 234 pg/ml for IL-8 for survival. Patients were grouped according to their average IL-8 levels relative to this cut off and stratified into high (H) (n=133) and low (L) (n=335) groups. In the L group, regression analysis revealed a significant predictive value of IL-8 to percent of total body surface area (TBSA) burned and incidence of MOF (p<0.001). In the H group IL-8 levels were able to predict sepsis (p<0.002). In the H group, elevated IL-8 was associated with increased inflammatory and acute phase responses compared to the L group (p<0.05). High levels of IL-8 correlated with increased MOF, sepsis, and mortality. These data suggest that serum levels of IL-8 may be a valid biomarker for monitoring sepsis, infections, and mortality in burn patients. PMID:25514427

  9. Myalgic Encephalomyelitis (ME and Chronic Fatigue Syndrome (CFS: The essence of objective assessment, accurate diagnosis, and acknowledging biological and clinical subgroups.

    Directory of Open Access Journals (Sweden)

    Frank N.M. Twisk

    2014-03-01

    Full Text Available Myalgic Encephalomyelitis (ME was identified as a new clinical entity in 1959 and has been acknowledged as a disease of the central nervous system/neurological disease by the World Health Organisation since 1969. Cognitive impairment, (muscle weakness, circulatory disturbances, marked variability of symptoms, and, above all, post-exertional malaise: a long-lasting increase of symptoms after minor exertion, are distinctive symptoms of ME.Chronic Fatigue Syndrome (CFS was introduced in 1988 and was redefined into clinically evaluated, unexplained (persistent or relapsing chronic fatigue, accompanied by at least four out of a list of eight symptoms, e.g. headaches and unrefreshing sleep, in 1994.Although the labels are used interchangeably, ME and CFS define distinct diagnostic entities. Post-exertional malaise and cognitive deficits e.g. are not mandatory for the diagnosis CFS, while obligatory for the diagnosis ME. Fatigue is not obligatory for the diagnosis ME.Since fatigue and other symptoms are subjective and ambiguous, research has been hampered. Despite this and other methodological issues, research has observed specific abnormalities in ME/CFS repetitively, e.g. immunological abnormalities, oxidative and nitrosative

  10. Statistical analysis of accurate prediction of local atmospheric optical attenuation with a new model according to weather together with beam wandering compensation system: a season-wise experimental investigation

    Science.gov (United States)

    Arockia Bazil Raj, A.; Padmavathi, S.

    2016-07-01

    Atmospheric parameters strongly affect the performance of Free Space Optical Communication (FSOC) system when the optical wave is propagating through the inhomogeneous turbulent medium. Developing a model to get an accurate prediction of optical attenuation according to meteorological parameters becomes significant to understand the behaviour of FSOC channel during different seasons. A dedicated free space optical link experimental set-up is developed for the range of 0.5 km at an altitude of 15.25 m. The diurnal profile of received power and corresponding meteorological parameters are continuously measured using the developed optoelectronic assembly and weather station, respectively, and stored in a data logging computer. Measured meteorological parameters (as input factors) and optical attenuation (as response factor) of size [177147 × 4] are used for linear regression analysis and to design the mathematical model that is more suitable to predict the atmospheric optical attenuation at our test field. A model that exhibits the R2 value of 98.76% and average percentage deviation of 1.59% is considered for practical implementation. The prediction accuracy of the proposed model is investigated along with the comparative results obtained from some of the existing models in terms of Root Mean Square Error (RMSE) during different local seasons in one-year period. The average RMSE value of 0.043-dB/km is obtained in the longer range dynamic of meteorological parameters variations.

  11. Towards understanding and predicting suicidality in women: biomarkers and clinical risk assessment.

    Science.gov (United States)

    Levey, D F; Niculescu, E M; Le-Niculescu, H; Dainton, H L; Phalen, P L; Ladd, T B; Weber, H; Belanger, E; Graham, D L; Khan, F N; Vanipenta, N P; Stage, E C; Ballew, A; Yard, M; Gelbart, T; Shekhar, A; Schork, N J; Kurian, S M; Sandusky, G E; Salomon, D R; Niculescu, A B

    2016-06-01

    Women are under-represented in research on suicidality to date. Although women have a lower rate of suicide completion than men, due in part to the less-violent methods used, they have a higher rate of suicide attempts. Our group has previously identified genomic (blood gene expression biomarkers) and clinical information (apps) predictors for suicidality in men. We now describe pilot studies in women. We used a powerful within-participant discovery approach to identify genes that change in expression between no suicidal ideation (no SI) and high suicidal ideation (high SI) states (n=12 participants out of a cohort of 51 women psychiatric participants followed longitudinally, with diagnoses of bipolar disorder, depression, schizoaffective disorder and schizophrenia). We then used a Convergent Functional Genomics (CFG) approach to prioritize the candidate biomarkers identified in the discovery step by using all the prior evidence in the field. Next, we validated for suicidal behavior the top-ranked biomarkers for SI, in a demographically matched cohort of women suicide completers from the coroner's office (n=6), by assessing which markers were stepwise changed from no SI to high SI to suicide completers. We then tested the 50 biomarkers that survived Bonferroni correction in the validation step, as well as top increased and decreased biomarkers from the discovery and prioritization steps, in a completely independent test cohort of women psychiatric disorder participants for prediction of SI (n=33) and in a future follow-up cohort of psychiatric disorder participants for prediction of psychiatric hospitalizations due to suicidality (n=24). Additionally, we examined how two clinical instruments in the form of apps, Convergent Functional Information for Suicidality (CFI-S) and Simplified Affective State Scale (SASS), previously tested in men, perform in women. The top CFI-S item distinguishing high SI from no SI states was the chronic stress of social isolation. We

  12. Stereotactic hypofractionated accurate radiotherapy of the prostate (SHARP), 33.5 Gy in five fractions for localized disease: First clinical trial results

    International Nuclear Information System (INIS)

    Purpose: To evaluate the feasibility and toxicity of stereotactic hypofractionated accurate radiotherapy (SHARP) for localized prostate cancer. Methods and Materials: A Phase I/II trial of SHARP performed for localized prostate cancer using 33.5 Gy in 5 fractions, calculated to be biologically equivalent to 78 Gy in 2 Gy fractions (α/β ratio of 1.5 Gy). Noncoplanar conformal fields and daily stereotactic localization of implanted fiducials were used for treatment. Genitourinary (GU) and gastrointestinal (GI) toxicity were evaluated by American Urologic Association (AUA) score and Common Toxicity Criteria (CTC). Prostate-specific antigen (PSA) values and self-reported sexual function were recorded at specified follow-up intervals. Results: The study includes 40 patients. The median follow-up is 41 months (range, 21-60 months). Acute toxicity Grade 1-2 was 48.5% (GU) and 39% (GI); 1 acute Grade 3 GU toxicity. Late Grade 1-2 toxicity was 45% (GU) and 37% (GI). No late Grade 3 or higher toxicity was reported. Twenty-six patients reported potency before therapy; 6 (23%) have developed impotence. Median time to PSA nadir was 18 months with the majority of nadirs less than 1.0 ng/mL. The actuarial 48-month biochemical freedom from relapse is 70% for the American Society for Therapeutic Radiology and Oncology definition and 90% by the alternative nadir + 2 ng/mL failure definition. Conclusions: SHARP for localized prostate cancer is feasible with minimal acute or late toxicity. Dose escalation should be possible

  13. Predicting long-term independency in activities of daily living after middle cerebral artery stroke: does information from MRI have added predictive value compared with clinical information?

    NARCIS (Netherlands)

    Schiemanck, S.K.; Kwakkel, G.; Post, M.W.; Kappelle, L.J.; Prevo, A.J.

    2006-01-01

    BACKGROUND AND PURPOSE: To investigate whether neuroimaging information has added predictive value compared with clinical information for independency in activities of daily living (ADL) 1 year after stroke. METHODS: Seventy-five first-ever middle cerebral artery stroke survivors were evaluated in l

  14. Pulmonary embolism in intensive care unit: Predictive factors, clinical manifestations and outcome

    Directory of Open Access Journals (Sweden)

    Bahloul Mabrouk

    2010-01-01

    Full Text Available Objective : To determine predictive factors, clinical and demographics characteristics of patients with pulmonary embolism (PE in ICU, and to identify factors associated with poor outcome in the hospital and in the ICU. Methods : During a four-year prospective study, a medical committee of six ICU physicians prospectively examined all available data for each patient in order to classify patients according to the level of clinical suspicion of pulmonary thromboembolism. During the study periods, all patients admitted to our ICU were classified into four groups. The first group includes all patients with confirmed PE; the second group includes some patients without clinical manifestations of PE; the third group includes patients with suspected and not confirmed PE and the fourth group includes all patients with only deep vein thromboses (DVTs without suspicion of PE. The diagnosis of PE was confirmed either by a high-probability ventilation/perfusion (V/Q scan or by a spiral computed tomography (CT scan showing one or more filling defects in the pulmonary artery or in its branches. The diagnosis was also confirmed by echocardiography when a thrombus in the pulmonary artery was observed. Results : During the study periods, 4408 patients were admitted in our ICU. The diagnosis of PE was confirmed in 87 patients (1.9%. The mean delay of development of PE was 7.8 ± 9.5 days. On the day of PE diagnosis, clinical examination showed that 50 patients (57.5% were hypotensive, 63 (72.4% have SIRS, 15 (17.2% have clinical manifestations of DVT and 71 (81.6% have respiratory distress requiring mechanical ventilation. In our study, intravenous unfractionated heparin was used in 81 cases (93.1% and low molecular weight heparins were used in 4 cases (4.6%. The mean ICU stay was 20.2 ± 25.3 days and the mean hospital stay was 25.5 ± 25 days. The mortality rate in ICU was 47.1% and the in-hospital mortality rate was 52.9%. Multivariate analysis showed that

  15. DNA Methylation-Guided Prediction of Clinical Failure in High-Risk Prostate Cancer.

    Directory of Open Access Journals (Sweden)

    Kirill Litovkin

    Full Text Available Prostate cancer (PCa is a very heterogeneous disease with respect to clinical outcome. This study explored differential DNA methylation in a priori selected genes to diagnose PCa and predict clinical failure (CF in high-risk patients.A quantitative multiplex, methylation-specific PCR assay was developed to assess promoter methylation of the APC, CCND2, GSTP1, PTGS2 and RARB genes in formalin-fixed, paraffin-embedded tissue samples from 42 patients with benign prostatic hyperplasia and radical prostatectomy specimens of patients with high-risk PCa, encompassing training and validation cohorts of 147 and 71 patients, respectively. Log-rank tests, univariate and multivariate Cox models were used to investigate the prognostic value of the DNA methylation.Hypermethylation of APC, CCND2, GSTP1, PTGS2 and RARB was highly cancer-specific. However, only GSTP1 methylation was significantly associated with CF in both independent high-risk PCa cohorts. Importantly, trichotomization into low, moderate and high GSTP1 methylation level subgroups was highly predictive for CF. Patients with either a low or high GSTP1 methylation level, as compared to the moderate methylation groups, were at a higher risk for CF in both the training (Hazard ratio [HR], 3.65; 95% CI, 1.65 to 8.07 and validation sets (HR, 4.27; 95% CI, 1.03 to 17.72 as well as in the combined cohort (HR, 2.74; 95% CI, 1.42 to 5.27 in multivariate analysis.Classification of primary high-risk tumors into three subtypes based on DNA methylation can be combined with clinico-pathological parameters for a more informative risk-stratification of these PCa patients.

  16. A clinical index to predict progression from mild cognitive impairment to dementia due to Alzheimer's disease.

    Directory of Open Access Journals (Sweden)

    Sei J Lee

    Full Text Available BACKGROUND: Mild cognitive impairment is often a precursor to dementia due to Alzheimer's disease, but many patients with mild cognitive impairment never develop dementia. New diagnostic criteria may lead to more patients receiving a diagnosis of mild cognitive impairment. OBJECTIVE: To develop a prediction index for the 3-year risk of progression from mild cognitive impairment to dementia relying only on information that can be readily obtained in most clinical settings. DESIGN AND PARTICIPANTS: 382 participants diagnosed with amnestic mild cognitive impairment enrolled in the Alzheimer's Disease Neuroimaging Initiative (ADNI, a multi-site, longitudinal, observational study. MAIN PREDICTORS MEASURES: Demographics, comorbid conditions, caregiver report of participant symptoms and function, and participant performance on individual items from basic neuropsychological scales. MAIN OUTCOME MEASURE: Progression to probable Alzheimer's disease. KEY RESULTS: Subjects had a mean (SD age of 75 (7 years and 43% progressed to probable Alzheimer's disease within 3 years. Important independent predictors of progression included being female, resisting help, becoming upset when separated from caregiver, difficulty shopping alone, forgetting appointments, number of words recalled from a 10-word list, orientation and difficulty drawing a clock. The final point score could range from 0 to 16 (mean [SD]: 4.2 [2.9]. The optimism-corrected Harrell's c-statistic was 0.71(95% CI: 0.68-0.75. Fourteen percent of subjects with low risk scores (0-2 points, n = 124 converted to probable Alzheimer's disease over 3 years, compared to 51% of those with moderate risk scores (3-8 points, n = 223 and 91% of those with high risk scores (9-16 points, n = 35. CONCLUSIONS: An index using factors that can be obtained in most clinical settings can predict progression from amnestic mild cognitive impairment to probable Alzheimer's disease and may help clinicians

  17. Endometrial thickness, Caucasian ethnicity, and age predict clinical pregnancy following fresh blastocyst embryo transfer: a retrospective cohort

    Directory of Open Access Journals (Sweden)

    Santoro Nanette

    2009-04-01

    Full Text Available Abstract Background In-vitro fertilization (IVF with blastocyst as opposed to cleavage stage embryos has been advocated to improve success rates. Limited information exists on which to predict which patients undergoing blastocyst embryo transfer (BET will achieve pregnancy. This study's objective was to evaluate the predictive value of patient and cycle characteristics for clinical pregnancy following fresh BET. Methods This was a retrospective cohort study from 2003–2007 at an academic assisted reproductive program. 114 women with infertility underwent fresh IVF with embryo transfer. We studied patients undergoing transfer of embryos at the blastocyst stage of development. Our main outcome of interest was clinical pregnancy. Clinical pregnancy and its associations with patient characteristics (age, body mass index, FSH, ethnicity and cycle parameters (thickness of endometrial stripe, number eggs, available cleaving embryos, number blastocysts available, transferred, and cryopreserved, and embryo quality were examined using Student's T test and Mann-Whitney-U tests as appropriate. Multivariable logistic regression models were created to determine independent predictors of CP following BET. Receiver Operating Characteristic analyses were used to determine the optimal thickness of endometrial stripe for predicting clinical pregnancy. Results Patients achieving clinical pregnancy demonstrated a thicker endometrial stripe and were younger preceding embryo transfer. On multivariable logistic regression analyses, Caucasian ethnicity (OR 2.641, 95% CI 1.054–6.617, thickness of endometrial stripe, (OR 1.185, 95% CI 1.006–1.396 and age (OR 0.879, 95% CI 0.789–0.980 predicted clinical pregnancy. By receiver operating characteristic analysis, endometrial stripe ≥ 9.4 mm demonstrated a sensitivity of 83% for predicting clinical pregnancy following BET. Conclusion In a cohort of patients undergoing fresh BET, thicker endometrial stripe, Caucasian

  18. Multidetector-CT angiography in pulmonary embolism - can image parameters predict clinical outcome?

    Energy Technology Data Exchange (ETDEWEB)

    Heyer, Christoph M.; Lemburg, Stefan P.; Nicolas, Volkmar; Roggenland, Daniela [Berufsgenossenschaftliches Universitaetsklinikum Bergmannsheil GmbH, Ruhr-University of Bochum, Institute of Diagnostic Radiology, Interventional Radiology and Nuclear Medicine, Bochum (Germany); Knoop, Heiko [Berufsgenossenschaftliches Universitaetsklinikum Bergmannsheil GmbH, Medical Clinic III - Pneumology, Allergology, and Sleep Medicine, Bochum (Germany); Holland-Letz, Tim [Ruhr-University of Bochum, Department of Medical Informatics, Biometry and Epidemiology, Bochum (Germany)

    2011-09-15

    To assess if pulmonary CT angiography (CTA) can predict outcome in patients with pulmonary embolism (PE). Retrospective analysis of CTA studies of patients with PE and documentation of pulmonary artery (PA)/aorta ratio, right ventricular (RV)/left ventricular (LV) ratio, superior vena cava (SVC) diameter, pulmonary obstruction index (POI), ventricular septal bowing (VSB), venous contrast reflux (VCR), pulmonary infarction and pleural effusion. Furthermore, duration of total hospital stay, necessity for/duration of ICU therapy, necessity for mechanical ventilation and mortality were recorded. Comparison was performed by logistic/linear regression analysis with significance at 5%. 152 patients were investigated. Mean duration of hospital stay was 21 {+-} 24 days. 66 patients were admitted to the ICU; 20 received mechanical ventilation. Mean duration of ICU therapy was 3 {+-} 8 days. Mortality rate was 8%. Significant positive associations of POI, VCR and pulmonary infarction with necessity for ICU therapy were shown. VCR was significantly associated with necessity for mechanical ventilation and duration of ICU treatment. Pleural effusions were significantly associated with duration of total hospital stay whereas the RV/LV ratio correlated with mortality. Selected CTA findings showed significant associations with the clinical course of PE and may thus be used as predictive parameters. (orig.)

  19. Multidetector-CT angiography in pulmonary embolism - can image parameters predict clinical outcome?

    International Nuclear Information System (INIS)

    To assess if pulmonary CT angiography (CTA) can predict outcome in patients with pulmonary embolism (PE). Retrospective analysis of CTA studies of patients with PE and documentation of pulmonary artery (PA)/aorta ratio, right ventricular (RV)/left ventricular (LV) ratio, superior vena cava (SVC) diameter, pulmonary obstruction index (POI), ventricular septal bowing (VSB), venous contrast reflux (VCR), pulmonary infarction and pleural effusion. Furthermore, duration of total hospital stay, necessity for/duration of ICU therapy, necessity for mechanical ventilation and mortality were recorded. Comparison was performed by logistic/linear regression analysis with significance at 5%. 152 patients were investigated. Mean duration of hospital stay was 21 ± 24 days. 66 patients were admitted to the ICU; 20 received mechanical ventilation. Mean duration of ICU therapy was 3 ± 8 days. Mortality rate was 8%. Significant positive associations of POI, VCR and pulmonary infarction with necessity for ICU therapy were shown. VCR was significantly associated with necessity for mechanical ventilation and duration of ICU treatment. Pleural effusions were significantly associated with duration of total hospital stay whereas the RV/LV ratio correlated with mortality. Selected CTA findings showed significant associations with the clinical course of PE and may thus be used as predictive parameters. (orig.)

  20. Prognostic prediction through biclustering-based classification of clinical gene expression time series.

    Science.gov (United States)

    Carreiro, André V; Anunciação, Orlando; Carriço, João A; Madeira, Sara C

    2011-01-01

    The constant drive towards a more personalized medicine led to an increasing interest in temporal gene expression analyzes. It is now broadly accepted that considering a temporal perpective represents a great advantage to better understand disease progression and treatment results at a molecular level. In this context, biclustering algorithms emerged as an important tool to discover local expression patterns in biomedical applications, and CCC-Biclustering arose as an efficient algorithm relying on the temporal nature of data to identify all maximal temporal patterns in gene expression time series. In this work, CCC-Biclustering was integrated in new biclustering-based classifiers for prognostic prediction. As case study we analyzed multiple gene expression time series in order to classify the response of Multiple Sclerosis patients to the standard treatment with Interferon-β, to which nearly half of the patients reveal a negative response. In this scenario, using an effective predictive model of a patient's response would avoid useless and possibly harmful therapies for the non-responder group. The results revealed interesting potentialities to be further explored in classification problems involving other (clinical) time series. PMID:21926438

  1. Clinical usefulness of the clock drawing test applying rasch analysis in predicting of cognitive impairment.

    Science.gov (United States)

    Yoo, Doo Han; Lee, Jae Shin

    2016-07-01

    [Purpose] This study examined the clinical usefulness of the clock drawing test applying Rasch analysis for predicting the level of cognitive impairment. [Subjects and Methods] A total of 187 stroke patients with cognitive impairment were enrolled in this study. The 187 patients were evaluated by the clock drawing test developed through Rasch analysis along with the mini-mental state examination of cognitive evaluation tool. An analysis of the variance was performed to examine the significance of the mini-mental state examination and the clock drawing test according to the general characteristics of the subjects. Receiver operating characteristic analysis was performed to determine the cutoff point for cognitive impairment and to calculate the sensitivity and specificity values. [Results] The results of comparison of the clock drawing test with the mini-mental state showed significant differences in according to gender, age, education, and affected side. A total CDT of 10.5, which was selected as the cutoff point to identify cognitive impairement, showed a sensitivity, specificity, Youden index, positive predictive, and negative predicive values of 86.4%, 91.5%, 0.8, 95%, and 88.2%. [Conclusion] The clock drawing test is believed to be useful in assessments and interventions based on its excellent ability to identify cognitive disorders.

  2. Framework for the impact analysis and implementation of Clinical Prediction Rules (CPRs)

    LENUS (Irish Health Repository)

    Wallace, Emma

    2011-10-14

    Abstract Clinical Prediction Rules (CPRs) are tools that quantify the contribution of symptoms, clinical signs and available diagnostic tests, and in doing so stratify patients according to the probability of having a target outcome or need for a specified treatment. Most focus on the derivation stage with only a minority progressing to validation and very few undergoing impact analysis. Impact analysis studies remain the most efficient way of assessing whether incorporating CPRs into a decision making process improves patient care. However there is a lack of clear methodology for the design of high quality impact analysis studies. We have developed a sequential four-phased framework based on the literature and the collective experience of our international working group to help researchers identify and overcome the specific challenges in designing and conducting an impact analysis of a CPR. There is a need to shift emphasis from deriving new CPRs to validating and implementing existing CPRs. The proposed framework provides a structured approach to this topical and complex area of research.

  3. Framework for the impact analysis and implementation of Clinical Prediction Rules (CPRs

    Directory of Open Access Journals (Sweden)

    Verbakel Jan

    2011-10-01

    Full Text Available Abstract Clinical Prediction Rules (CPRs are tools that quantify the contribution of symptoms, clinical signs and available diagnostic tests, and in doing so stratify patients according to the probability of having a target outcome or need for a specified treatment. Most focus on the derivation stage with only a minority progressing to validation and very few undergoing impact analysis. Impact analysis studies remain the most efficient way of assessing whether incorporating CPRs into a decision making process improves patient care. However there is a lack of clear methodology for the design of high quality impact analysis studies. We have developed a sequential four-phased framework based on the literature and the collective experience of our international working group to help researchers identify and overcome the specific challenges in designing and conducting an impact analysis of a CPR. There is a need to shift emphasis from deriving new CPRs to validating and implementing existing CPRs. The proposed framework provides a structured approach to this topical and complex area of research.

  4. Clinical Outcome Prediction in Aneurysmal Subarachnoid Hemorrhage Using Bayesian Neural Networks with Fuzzy Logic Inferences

    Directory of Open Access Journals (Sweden)

    Benjamin W. Y. Lo

    2013-01-01

    Full Text Available Objective. The novel clinical prediction approach of Bayesian neural networks with fuzzy logic inferences is created and applied to derive prognostic decision rules in cerebral aneurysmal subarachnoid hemorrhage (aSAH. Methods. The approach of Bayesian neural networks with fuzzy logic inferences was applied to data from five trials of Tirilazad for aneurysmal subarachnoid hemorrhage (3551 patients. Results. Bayesian meta-analyses of observational studies on aSAH prognostic factors gave generalizable posterior distributions of population mean log odd ratios (ORs. Similar trends were noted in Bayesian and linear regression ORs. Significant outcome predictors include normal motor response, cerebral infarction, history of myocardial infarction, cerebral edema, history of diabetes mellitus, fever on day 8, prior subarachnoid hemorrhage, admission angiographic vasospasm, neurological grade, intraventricular hemorrhage, ruptured aneurysm size, history of hypertension, vasospasm day, age and mean arterial pressure. Heteroscedasticity was present in the nontransformed dataset. Artificial neural networks found nonlinear relationships with 11 hidden variables in 1 layer, using the multilayer perceptron model. Fuzzy logic decision rules (centroid defuzzification technique denoted cut-off points for poor prognosis at greater than 2.5 clusters. Discussion. This aSAH prognostic system makes use of existing knowledge, recognizes unknown areas, incorporates one's clinical reasoning, and compensates for uncertainty in prognostication.

  5. Traditional clinical risk factors predict clopidogrel hypo-responsiveness in unselected patients undergoing non-emergent percutaneous coronary intervention

    DEFF Research Database (Denmark)

    Ratcovich, Hanna; Holmvang, Lene; Johansson, Pär Inge;

    2016-01-01

    High and low platelet reactivity, HPR and LPR respectively, to clopidogrel and aspirin have previously been associated with adverse events following percutaneous coronary intervention (PCI). The aim is to test the ability of a previously developed clinical risk-score, the PREDICT score, to identify...... of PREDICT score variables and the incidence of HPR for clopidogrel (HPR (ADP)) (p ... = 0.003); 7-9 points OR 9.84 (95% CI 3.49-27.7, p clopidogrel LPR (LPR (ADP)). On the other hand, there was no clear association between PREDICT score and AA response. The PREDICT...

  6. Prognostic and Predictive Biomarkers in Colorectal Cancer. From the Preclinical Setting to Clinical Practice.

    Science.gov (United States)

    Maurel, Joan; Postigo, Antonio

    2015-01-01

    Colorectal cancer (CRC) is the second largest cause of cancer mortality in Western countries, mostly due to metastasis. Understanding the natural history and prognostic factors in patients with metastatic CRC (mCRC) is essential for the optimal design of clinical trials. The main prognostic factors currently used in clinical practice are related to tumor behavior (e.g., white blood counts, levels of lactate dehydrogenase, levels of alkaline phosphatase) disease extension (e.g., presence of extrahepatic spread, number of organs affected) and general functional status (e.g., performance status as defined by the Eastern Cooperative Oncology Group). However, these parameters are not always sufficient to establish appropriate therapeutic strategies. First-line therapy in mCRC combines conventional chemotherapy (CHT) (e.g., FOLFOX, FOLFIRI, CAPOX) with a number of agents targeted to specific signaling pathways (TA) (e.g., panitumumab and cetuximab for cases KRAS/NRAS WT, and bevacizumab). Although the response rate to this combination regime exceeds 50%, progression of the disease is almost universal and only less than 10% of patients are free of disease at 2 years. Current clinical trials with second and third line therapy include new TA, such as tyrosin-kinase receptors inhibitors (MET, HER2, IGF-1R), inhibitors of BRAF, MEK, PI3K, AKT, mTORC, NOTCH and JAK1/JAK2, immunotherapy modulators and check point inhibitors (anti-PD-L1 and anti- PD1). Despite the identification of multiple prognostic and predictive biomarkers and signatures, it is still unclear how expression of many of these biomarkers is modulated by CHT and/or TA, thus potentially affecting response to treatment. In this review we analyzed how certain biomarkers in tumor cells and microenvironment influence the response to new TA and immune-therapies strategies in mCRC pre-treated patients. PMID:26452385

  7. PREDICTING OUTCOME AND SEVERITY IN ACUTE ORGANOPHOSPHOROUS POISONING WITH CLINICAL SCORING AND SERUM CHOLINESTERASE LEVELS

    Directory of Open Access Journals (Sweden)

    Basavaraj R

    2014-11-01

    Full Text Available BACKGROUND AND OBJECTIVES: Organophosphorus compound poisoning is the most common medico toxic emergency in India the increase in pesticide use in agriculture has paralleled the increase in the use of these products for deliberate self-warm. Respiratory failure is the most common complication of OP poisoning leading to death. Early recognition and prompt ventilator support may improve survival. Owing to limited availability of resources, all OP poisoning patients are not managed in ICUs in Indian setup. It is therefore important that clinical features and criteria to predict the need for ventilator support be identified at initial examination. Hence this study was undertaken to assess the severity of organophosphorus compound poisoning both clinically by using Peradeniya scoring and by estimating serum choline esterase levels. METHODS: Cross sectional study was done at basaveswar teaching and general hospital attached to MR Medical College. Cases with history of exposure to organophosphorus compound within previous 24 hours were chosen after applying inclusion and exclusion criteria. Patients were evaluated for Peradeniya OP poisoning scale and serum cholinesterase levels for assessment of severity of poisoning. Serum cholinesterase levels and Peradeniya OP poisoning scale were studied to predict the need for ventilator support. The results were analyzed using Chi-square test. STATISTICAL ANALYSIS: It was done using pearson’s chi square test. RESULTS: In this study requirement of ventilator support was seen in 36% of patients. Mortality in our study was 18%. Only 15.6% of patients with mild grade of poisoning according to Peradeniya OP poisoning scale required ventilator support, whereas 84.4% did not require ventilator support. Most of patients with moderate (70.6% and severe poisoning (100% according to Peradeniya OP poisoning scale required ventilator support. 93.7% of patients with serum cholinesterase levels more than 50% did not require

  8. Predictive factors of clinical response in steroid-refractory ulcerative colitis treated with granulocyte-monocyte apheresis

    Institute of Scientific and Technical Information of China (English)

    Valeria D'Ovidio; Donatella Meo; Angelo Viscido; Giampaolo Bresci; Piero Vernia; Renzo Caprilli

    2011-01-01

    AIM: To identify factors predicting the clinical response of ulcerative colitis patients to granulocyte-monocyte apheresis (GMA).METHODS: Sixty-nine ulcerative colitis patients (39 F, 30 M) dependent upon/refractory to steroids were treated with GMA.Steroid dependency, clinical activity index (CAI), C reactive protein (CRP) level, erythrocyte sedimentation rate (ESR), values at baseline, use of immunosuppressant, duration of disease, and age and extent of disease were considered for statistical analysis as predictive factors of clinical response.Univariate and multivariate logistic regression models were used.RESULTS: In the univariate analysis, CAI (P = 0.039) and ESR (P = 0.017) levels at baseline were singled out as predictive of clinical remission.In the multivariate analysis steroid dependency [Odds ratio (OR) = 0.390, 95% Confidence interval (CI): 0.176-0.865, Wald 5.361, P = 0.0160] and low CAI levels at baseline (4 < CAI < 7) (OR = 0.770, 95% CI: 0.425-1.394, Wald 3.747, P = 0.028) proved to be effective as factors predicting clinical response.CONCLUSION: GMA may be a valid therapeutic option for steroid-dependent ulcerative colitis patients with mild-moderate disease and its clinical efficacy seems to persist for 12 mo.

  9. Evaluation of clinical and immunological markers for predicting virological failure in a HIV/AIDS treatment cohort in Busia, Kenya.

    Directory of Open Access Journals (Sweden)

    Cecilia Ferreyra

    Full Text Available BACKGROUND: In resource-limited settings where viral load (VL monitoring is scarce or unavailable, clinicians must use immunological and clinical criteria to define HIV virological treatment failure. This study examined the performance of World Health Organization (WHO clinical and immunological failure criteria in predicting virological failure in HIV patients receiving antiretroviral therapy (ART. METHODS: In a HIV/AIDS program in Busia District Hospital, Kenya, a retrospective, cross-sectional cohort analysis was performed in April 2008 for all adult patients (>18 years old on ART for ≥12 months, treatment-naive at ART start, attending the clinic at least once in last 6 months, and who had given informed consent. Treatment failure was assessed per WHO clinical (disease stage 3 or 4 and immunological (CD4 cell count criteria, and compared with virological failure (VL >5,000 copies/mL. RESULTS: Of 926 patients, 123 (13.3% had clinically defined treatment failure, 53 (5.7% immunologically defined failure, and 55 (6.0% virological failure. Sensitivity, specificity, positive predictive value, and negative predictive value of both clinical and immunological criteria (combined in predicting virological failure were 36.4%, 83.5%, 12.3%, and 95.4%, respectively. CONCLUSIONS: In this analysis, clinical and immunological criteria were found to perform relatively poorly in predicting virological failure of ART. VL monitoring and new algorithms for assessing clinical or immunological treatment failure, as well as improved adherence strategies, are required in ART programs in resource-limited settings.

  10. Prediction consistency and clinical presentations of breast cancer molecular subtypes for Han Chinese population

    Directory of Open Access Journals (Sweden)

    Huang Chi-Cheng

    2012-09-01

    Full Text Available Abstract Background Breast cancer is a heterogeneous disease in terms of transcriptional aberrations; moreover, microarray gene expression profiles had defined 5 molecular subtypes based on certain intrinsic genes. This study aimed to evaluate the prediction consistency of breast cancer molecular subtypes from 3 distinct intrinsic gene sets (Sørlie 500, Hu 306 and PAM50 as well as clinical presentations of each molecualr subtype in Han Chinese population. Methods In all, 169 breast cancer samples (44 from Taiwan and 125 from China of Han Chinese population were gathered, and the gene expression features corresponding to 3 distinct intrinsic gene sets (Sørlie 500, Hu 306 and PAM50 were retrieved for molecular subtype prediction. Results For Sørlie 500 and Hu 306 intrinsic gene set, mean-centring of genes and distance-weighted discrimination (DWD remarkably reduced the number of unclassified cases. Regarding pairwise agreement, the highest predictive consistency was found between Hu 306 and PAM50. In all, 150 and 126 samples were assigned into identical subtypes by both Hu 306 and PAM50 genes, under mean-centring and DWD. Luminal B tended to show a higher nuclear grade and have more HER2 over-expression status than luminal A did. No basal-like breast tumours were ER positive, and most HER2-enriched breast tumours showed HER2 over-expression, whereas, only two-thirds of ER negativity/HER2 over-expression tumros were predicted as HER2-enriched molecular subtype. For 44 Taiwanese breast cancers with survival data, a better prognosis of luminal A than luminal B subtype in ER-postive breast cancers and a better prognosis of basal-like than HER2-enriched subtype in ER-negative breast cancers was observed. Conclusions We suggest that the intrinsic signature Hu 306 or PAM50 be used for breast cancers in the Han Chinese population during molecular subtyping. For the prognostic value and decision making based on intrinsic subtypes, further prospective

  11. Development, external validation and clinical usefulness of a practical prediction model for radiation-induced dysphagia in lung cancer patients

    International Nuclear Information System (INIS)

    Introduction: Acute dysphagia is a distressing dose-limiting toxicity occurring frequently during concurrent chemo-radiation or high-dose radiotherapy for lung cancer. It can lead to treatment interruptions and thus jeopardize survival. Although a number of predictive factors have been identified, it is still not clear how these could offer assistance for treatment decision making in daily clinical practice. Therefore, we have developed and validated a nomogram to predict this side-effect. In addition, clinical usefulness was assessed by comparing model predictions to physicians' predictions. Materials and methods: Clinical data from 469 inoperable lung cancer patients, treated with curative intent, were collected prospectively. A prediction model for acute radiation-induced dysphagia was developed. Model performance was evaluated by the c-statistic and assessed using bootstrapping as well as two external datasets. In addition, a prospective study was conducted comparing model to physicians' predictions in 138 patients. Results: The final multivariate model consisted of age, gender, WHO performance status, mean esophageal dose (MED), maximum esophageal dose (MAXED) and overall treatment time (OTT). The c-statistic, assessed by bootstrapping, was 0.77. External validation yielded an AUC of 0.94 on the Ghent data and 0.77 on the Washington University St. Louis data for dysphagia ≥ grade 3. Comparing model predictions to the physicians' predictions resulted in an AUC of 0.75 versus 0.53, respectively. Conclusions: The proposed model performed well was successfully validated and demonstrated the ability to predict acute severe dysphagia remarkably better than the physicians. Therefore, this model could be used in clinical practice to identify patients at high or low risk.

  12. Predictive validity of measurements of clinical competence using the team objective structured bedside assessment (TOSBA): assessing the clinical competence of final year medical students.

    LENUS (Irish Health Repository)

    Meagher, Frances M

    2009-11-01

    The importance of valid and reliable assessment of student competence and performance is gaining increased recognition. Provision of valid patient-based formative assessment is an increasing challenge for clinical teachers in a busy hospital setting. A formative assessment tool that reliably predicts performance in the summative setting would be of value to both students and teachers.

  13. Predicting asthma in preschool children at high risk presenting in primary care: Development of a clinical asthma prediction score

    NARCIS (Netherlands)

    L.B. Van Der Mark (Lonneke); K.E. Wonderen (Karina); J. Mohrs (Jacob); W.M.C. van Aalderen (Willem); G. ter Riet; P.J.E. Bindels (Patrick)

    2014-01-01

    textabstractBackground: A setting-specific asthma prediction score for preschool children with wheezing and/or dyspnoea presenting in primary healthcare is needed since existing indices are mainly based on general populations. Aims: To find an optimally informative yet practical set of predictors fo

  14. pRRophetic: an R package for prediction of clinical chemotherapeutic response from tumor gene expression levels.

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    Paul Geeleher

    Full Text Available We recently described a methodology that reliably predicted chemotherapeutic response in multiple independent clinical trials. The method worked by building statistical models from gene expression and drug sensitivity data in a very large panel of cancer cell lines, then applying these models to gene expression data from primary tumor biopsies. Here, to facilitate the development and adoption of this methodology we have created an R package called pRRophetic. This also extends the previously described pipeline, allowing prediction of clinical drug response for many cancer drugs in a user-friendly R environment. We have developed several other important use cases; as an example, we have shown that prediction of bortezomib sensitivity in multiple myeloma may be improved by training models on a large set of neoplastic hematological cell lines. We have also shown that the package facilitates model development and prediction using several different classes of data.

  15. READMIT: a clinical risk index to predict 30-day readmission after discharge from acute psychiatric units.

    Science.gov (United States)

    Vigod, Simone N; Kurdyak, Paul A; Seitz, Dallas; Herrmann, Nathan; Fung, Kinwah; Lin, Elizabeth; Perlman, Christopher; Taylor, Valerie H; Rochon, Paula A; Gruneir, Andrea

    2015-02-01

    Our aim was to create a clinically useful risk index, administered prior to discharge, for determining the probability of psychiatric readmission within 30 days of hospital discharge for general psychiatric inpatients. We used population-level sociodemographic and health administrative data to develop a predictive model for 30-day readmission among adults discharged from an acute psychiatric unit in Ontario, Canada (2008-2011), and converted the final model into a risk index system. We derived the predictive model in one-half of the sample (n = 32,749) and validated it in the other half of the sample (n = 32,750). Variables independently associated with 30-day readmission (forming the mnemonic READMIT) were: (R) Repeat admissions; (E) Emergent admissions (i.e. harm to self/others); (D) Diagnoses (psychosis, bipolar and/or personality disorder), and unplanned Discharge; (M) Medical comorbidity; (I) prior service use Intensity; and (T) Time in hospital. Each 1-point increase in READMIT score (range 0-41) increased the odds of 30-day readmission by 11% (odds ratio 1.11, 95% CI 1.10-1.12). The index had moderate discriminative capacity in both derivation (C-statistic = 0.631) and validation (C-statistic = 0.630) datasets. Determining risk of psychiatric readmission for individual patients is a critical step in efforts to address the potentially avoidable high rate of this negative outcome. The READMIT index provides a framework for identifying patients at high risk of 30-day readmission prior to discharge, and for the development, evaluation and delivery of interventions that can assist with optimizing the transition to community care for patients following psychiatric discharge.

  16. Pediatric in-Hospital Death from Infectious Disease in Uganda: Derivation of Clinical Prediction Models.

    Directory of Open Access Journals (Sweden)

    Nasim Lowlaavar

    Full Text Available Pediatric hospital mortality from infectious diseases in resource constrained countries remains unacceptably high. Improved methods of risk-stratification can assist in referral decision making and resource allocation. The purpose of this study was to create prediction models for in-hospital mortality among children admitted with suspected infectious diseases.This two-site prospective observational study enrolled children between 6 months and 5 years admitted with a proven or suspected infection. Baseline clinical and laboratory variables were collected on enrolled children. The primary outcome was death during admission. Stepwise logistic regression minimizing Akaike's information criterion was used to identify the most promising multivariate models. The final model was chosen based on parsimony.1307 children were enrolled consecutively, and 65 (5% of whom died during their admission. Malaria, pneumonia and gastroenteritis were diagnosed in 50%, 31% and 8% of children, respectively. The primary model included an abnormal Blantyre coma scale, HIV and weight-for-age z-score. This model had an area under the curve (AUC of 0.85 (95% CI, 0.80-0.89 with a sensitivity and specificity of 83% and 76%, respectively. The positive and negative predictive values were 15% and 99%, respectively. Two alternate models with similar performance characteristics were developed withholding HIV and weight-for-age z-score, for use when these variables are not available.Risk stratification of children admitted with infectious diseases can be calculated based on several easily measured variables. Risk stratification at admission can be used for allocation of scarce human and physical resources and to guide referral among children admitted to lower level health facilities.

  17. Ruling out coronary heart disease in primary care patients with chest pain: a clinical prediction score

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    Burnand Bernard

    2010-01-01

    Full Text Available Abstract Background Chest pain raises concern for the possibility of coronary heart disease. Scoring methods have been developed to identify coronary heart disease in emergency settings, but not in primary care. Methods Data were collected from a multicenter Swiss clinical cohort study including 672 consecutive patients with chest pain, who had visited one of 59 family practitioners' offices. Using delayed diagnosis we derived a prediction rule to rule out coronary heart disease by means of a logistic regression model. Known cardiovascular risk factors, pain characteristics, and physical signs associated with coronary heart disease were explored to develop a clinical score. Patients diagnosed with angina or acute myocardial infarction within the year following their initial visit comprised the coronary heart disease group. Results The coronary heart disease score was derived from eight variables: age, gender, duration of chest pain from 1 to 60 minutes, substernal chest pain location, pain increasing with exertion, absence of tenderness point at palpation, cardiovascular risks factors, and personal history of cardiovascular disease. Area under the receiver operating characteristics curve was of 0.95 with a 95% confidence interval of 0.92; 0.97. From this score, 413 patients were considered as low risk for values of percentile 5 of the coronary heart disease patients. Internal validity was confirmed by bootstrapping. External validation using data from a German cohort (Marburg, n = 774 revealed a receiver operating characteristics curve of 0.75 (95% confidence interval, 0.72; 0.81 with a sensitivity of 85.6% and a specificity of 47.2%. Conclusions This score, based only on history and physical examination, is a complementary tool for ruling out coronary heart disease in primary care patients complaining of chest pain.

  18. DEVELOPMENT OF THE NOMOGRAM THAT PREDICTS PATHOLOGICAL LYMPH NODE INVOLVEMENT IN BLADDER CANCER PATIENTS BASED ON CLINICAL VARIABLES

    OpenAIRE

    L. V. Mirylenko; O. G. Sukonko; A. V. Pravorov; A. I. Rolevich; A. S. Mavrichev

    2014-01-01

    Objective: to develop nomogram based on clinical variables, that predicts pathological lymph node involvement (рN+) in bladder cancer patients.Material and methods: We used data of 511 patients with bladder cancer, that have undergone radical cystectomy between 1999 and 2008 at N.N. Alexandrov National Cancer Centre. Mono- and multivariate logistic regression analyses were used for pN+ prediction on preoperative data. Coefficients from logistic regression equation were used to construct the n...

  19. Predictive validity of the UK clinical aptitude test in the final years of medical school: a prospective cohort study

    OpenAIRE

    Husbands, Adrian; Mathieson, Alistair; Dowell, Jonathan; Cleland, Jennifer; MacKenzie, Rhoda

    2014-01-01

    Background The UK Clinical Aptitude Test (UKCAT) was designed to address issues identified with traditional methods of selection. This study aims to examine the predictive validity of the UKCAT and compare this to traditional selection methods in the senior years of medical school. This was a follow-up study of two cohorts of students from two medical schools who had previously taken part in a study examining the predictive validity of the UKCAT in first year. Methods The sample consisted of ...

  20. Innovative drugs to treat depression: did animal models fail to be predictive or did clinical trials fail to detect effects?

    Science.gov (United States)

    Belzung, Catherine

    2014-04-01

    Over recent decades, encouraging preclinical evidence using rodent models pointed to innovative pharmacological targets to treat major depressive disorder. However, subsequent clinical trials have failed to show convincing results. Two explanations for these rather disappointing results can be put forward, either animal models of psychiatric disorders have failed to predict the clinical effectiveness of treatments or clinical trials have failed to detect the effects of these new drugs. A careful analysis of the literature reveals that both statements are true. Indeed, in some cases, clinical efficacy has been predicted on the basis of inappropriate animal models, although the contrary is also true, as some clinical trials have not targeted the appropriate dose or clinical population. On the one hand, refinement of animal models requires using species that have better homological validity, designing models that rely on experimental manipulations inducing pathological features, and trying to model subtypes of depression. On the other hand, clinical research should consider carefully the results from preclinical studies, in order to study these compounds at the correct dose, in the appropriate psychiatric nosological entity or symptomatology, in relevant subpopulations of patients characterized by specific biomarkers. To achieve these goals, translational research has to strengthen the dialogue between basic and clinical science. PMID:24345817

  1. Pre- and Post-Operative Nomograms to Predict Recurrence-Free Probability in Korean Men with Clinically Localized Prostate Cancer

    OpenAIRE

    Minyong Kang; Chang Wook Jeong; Woo Suk Choi; Yong Hyun Park; Sung Yong Cho; Sangchul Lee; Seung Bae Lee; Ja Hyeon Ku; Sung Kyu Hong; Seok-Soo Byun; Hyeon Jeong; Cheol Kwak; Hyeon Hoe Kim; Eunsik Lee; Sang Eun Lee

    2014-01-01

    OBJECTIVES: Although the incidence of prostate cancer (PCa) is rapidly increasing in Korea, there are few suitable prediction models for disease recurrence after radical prostatectomy (RP). We established pre- and post-operative nomograms estimating biochemical recurrence (BCR)-free probability after RP in Korean men with clinically localized PCa. PATIENTS AND METHODS: Our sampling frame included 3,034 consecutive men with clinically localized PCa who underwent RP at our tertiary centers from...

  2. Combination of Circulating Tumor Cells with Serum Carcinoembryonic Antigen Enhances Clinical Prediction of Non-Small Cell Lung Cancer

    OpenAIRE

    Xi Chen; Xu Wang; Hua He; Ziling Liu; Ji-Fan Hu; Wei Li

    2015-01-01

    Circulating tumor cells (CTCs) have emerged as a potential biomarker in the diagnosis, prognosis, treatment, and surveillance of lung cancer. However, CTC detection is not only costly, but its sensitivity is also low, thus limiting its usage and the collection of robust data regarding the significance of CTCs in lung cancer. We aimed to seek clinical variables that enhance the prediction of CTCs in patients with non-small cell lung cancer (NSCLC). Clinical samples and pathological data were c...

  3. Preoperative neutrophil response as a predictive marker of clinical outcome following open heart surgery and the impact of leukocyte filtration.

    LENUS (Irish Health Repository)

    Soo, Alan W

    2010-11-01

    Open heart surgery is associated with a massive systemic inflammatory response. Neutrophils, are the main mediator of this response. We hypothesised that the degree of neutrophil activation and inflammatory response to open heart surgery varies individually and correlates with clinical outcome. The aim of this study was to determine if individual clinical outcome can be predicted preoperatively through assessment of in-vitro stimulated neutrophil responses. Following that, the effects of neutrophil depletion through leukocyte filters are examined.

  4. Development of a Simple Clinical Risk Score for Early Prediction of Severe Dengue in Adult Patients.

    Science.gov (United States)

    Lee, Ing-Kit; Liu, Jien-Wei; Chen, Yen-Hsu; Chen, Yi-Chun; Tsai, Ching-Yen; Huang, Shi-Yu; Lin, Chun-Yu; Huang, Chung-Hao

    2016-01-01

    the day of illness onset, suggesting that our simple risk score can be easily implemented in resource-limited countries for early prediction of dengue patients at risk of SD provided that they have rapid dengue confirmed tests. For patients with other acute febrile illnesses or bacterial infections usually have SD risk score of >1. Thus, these scoring algorithms cannot totally replace good clinical judgement of the physician, and most importantly, early differentiating dengue from other febrile illnesses is critical for appropriate monitoring and management. PMID:27138448

  5. Development of a Simple Clinical Risk Score for Early Prediction of Severe Dengue in Adult Patients.

    Directory of Open Access Journals (Sweden)

    Ing-Kit Lee

    , irrespective of the day of illness onset, suggesting that our simple risk score can be easily implemented in resource-limited countries for early prediction of dengue patients at risk of SD provided that they have rapid dengue confirmed tests. For patients with other acute febrile illnesses or bacterial infections usually have SD risk score of >1. Thus, these scoring algorithms cannot totally replace good clinical judgement of the physician, and most importantly, early differentiating dengue from other febrile illnesses is critical for appropriate monitoring and management.

  6. Reduced FDG-PET brain metabolism and executive function predict clinical progression in elderly healthy subjects

    Directory of Open Access Journals (Sweden)

    Michael Ewers

    2014-01-01

    Full Text Available Brain changes reminiscent of Alzheimer disease (AD have been previously reported in a substantial portion of elderly cognitive healthy (HC subjects. The major aim was to evaluate the accuracy of MRI assessed regional gray matter (GM volume, 18F-fluorodeoxyglucose positron emission tomography (FDG-PET, and neuropsychological test scores to identify those HC subjects who subsequently convert to mild cognitive impairment (MCI or AD dementia. We obtained in 54 healthy control (HC subjects a priori defined region of interest (ROI values of medial temporal and parietal FDG-PET and medial temporal GM volume. In logistic regression analyses, these ROI values were tested together with neuropsychological test scores (free recall, trail making test B (TMT-B as predictors of HC conversion during a clinical follow-up between 3 and 4 years. In voxel-based analyses, FDG-PET and MRI GM maps were compared between HC converters and HC non-converters. Out of the 54 HC subjects, 11 subjects converted to MCI or AD dementia. Lower FDG-PET ROI values were associated with higher likelihood of conversion (p = 0.004, with the area under the curve (AUC yielding 82.0% (95% CI = (95.5%, 68.5%. The GM volume ROI was not a significant predictor (p = 0.07. TMT-B but not the free recall tests were a significant predictor (AUC = 71% (95% CI = 50.4%, 91.7%. For the combination of FDG-PET and TMT-B, the AUC was 93.4% (sensitivity = 82%, specificity = 93%. Voxel-based group comparison showed reduced FDG-PET metabolism within the temporo-parietal and prefrontal cortex in HC converters. In conclusion, medial temporal and-parietal FDG-PET and executive function show a clinically acceptable accuracy for predicting clinical progression in elderly HC subjects.

  7. Construction and clinical significance of a predictive system for prognosis of hepatocellular carcinoma

    Institute of Scientific and Technical Information of China (English)

    Jun Cui; Bao-Wei Dong; Ping Liang; Xiao-Ling Yu; De-Jiang Yu

    2005-01-01

    tissue in group A were significantly higher than those in group B (t= 4.57, P= 0.000<0.01; t= 2.08, P= 0.04<0.05;t = 2.38, ,P = 0.02<0.05, respectively); the expressing intensities of c-myc, Ki-67 and VEGF in para-cancer tissue in groups A and B were not significantly different (P>0.05). The coincidence rate of patients undergoing PMCT in group A was 88.00% (22/25), in group B 68.75% (11/16), the total coincidence rate was 80.49% (33/41). CONCLUSION: The regression equation is accurate and feasible and could be used for predicting prognosis of HCC, it helps to select treatment method (resection or PMCT) for HCC patients to realize individualized treatment to improve prognosis.

  8. Prospective assessment of a gene signature potentially predictive of clinical benefit in metastatic melanoma patients following MAGE-A3 immunotherapeutic (PREDICT)

    Science.gov (United States)

    Saiag, P.; Gutzmer, R.; Ascierto, P. A.; Maio, M.; Grob, J.-J.; Murawa, P.; Dreno, B.; Ross, M.; Weber, J.; Hauschild, A.; Rutkowski, P.; Testori, A.; Levchenko, E.; Enk, A.; Misery, L.; Vanden Abeele, C.; Vojtek, I.; Peeters, O.; Brichard, V. G.; Therasse, P.

    2016-01-01

    Background Genomic profiling of tumor tissue may aid in identifying predictive or prognostic gene signatures (GS) in some cancers. Retrospective gene expression profiling of melanoma and non-small-cell lung cancer led to the characterization of a GS associated with clinical benefit, including improved overall survival (OS), following immunization with the MAGE-A3 immunotherapeutic. The goal of the present study was to prospectively evaluate the predictive value of the previously characterized GS. Patients and methods An open-label prospective phase II trial (‘PREDICT’) in patients with MAGE-A3-positive unresectable stage IIIB-C/IV-M1a melanoma. Results Of 123 subjects who received the MAGE-A3 immunotherapeutic, 71 (58.7%) displayed the predictive GS (GS+). The 1-year OS rate was 83.1%/83.3% in the GS+/GS− populations. The rate of progression-free survival at 12 months was 5.8%/4.1% in GS+/GS− patients. The median time-to-treatment failure was 2.7/2.4 months (GS+/GS−). There was one complete response (GS−) and two partial responses (GS+). The MAGE-A3 immunotherapeutic was similarly immunogenic in both populations and had a clinically acceptable safety profile. Conclusion Treatment of patients with MAGE-A3-positive unresectable stage IIIB-C/IV-M1a melanoma with the MAGE-A3 immunotherapeutic demonstrated an overall 1-year OS rate of 83.5%. GS− and GS+ patients had similar 1-year OS rates, indicating that in this study, GS was not predictive of outcome. Unexpectedly, the objective response rate was lower in this study than in other studies carried out in the same setting with the MAGE-A3 immunotherapeutic. Investigation of a GS to predict clinical benefit to adjuvant MAGE-A3 immunotherapeutic treatment is ongoing in another melanoma study. This study is registered at www.clinicatrials.gov NCT00942162. PMID:27502712

  9. XPG rs2296147 T>C polymorphism predicted clinical outcome in colorectal cancer.

    Science.gov (United States)

    Wang, Fang; Zhang, Shao-Dan; Xu, Hong-Mei; Zhu, Jin-Hong; Hua, Rui-Xi; Xue, Wen-Qiong; Li, Xi-Zhao; Wang, Tong-Min; He, Jing; Jia, Wei-Hua

    2016-03-01

    Xeroderma pigmentosum group G (XPG), one of key components of nucleotide excision repair pathway (NER), is involved in excision repair of UV-induced DNA damage. Single nucleotide polymorphisms (SNPs) in the XPG gene have been reported to associate with the clinical outcome of various cancer patients. We aimed to assess the impact of four potentially functional SNPs (rs2094258 C>T, rs2296147 T>C, rs751402 G>A, and rs873601 G>A) in the XPG gene on prognosis in colorectal cancer (CRC) patients. A total of 1901 patients diagnosed with pathologically confirmed CRC were genotyped for four XPG polymorphisms. Cox proportional hazards model analysis controlled for several confounding factors was conducted to compute hazard ratios (HRs) and 95% confidence intervals (CIs). Of the four included SNPs, only rs2296147 was shown to significantly affect progression-free survival (PFS) in CRC. Patients carrying rs2296147 CT/TT genotype had a significantly shorter median 10 years PFS than those carrying CC genotype (88.5 months vs. 118.1 months), and an increased progression risk were observed with rs2296147 (HR = 1.324, 95% CI = 1.046-1.667). Moreover, none of the four SNPs were associated with overall survival. In conclusion, our study showed that XPG rs2296147 CT/TT variants conferred significant survival disadvantage in CRC patients in term of PFS. XPG rs2296147 polymorphism could be predictive of unfavorable prognosis of CRC patients. PMID:26887052

  10. Late gadolinium enhancement cardiovascular magnetic resonance predicts clinical worsening in patients with pulmonary hypertension

    Directory of Open Access Journals (Sweden)

    Freed Benjamin H

    2012-02-01

    Full Text Available Abstract Background Late gadolinium enhancement (LGE occurs at the right ventricular (RV insertion point (RVIP in patients with pulmonary hypertension (PH and has been shown to correlate with cardiovascular magnetic resonance (CMR derived RV indices. However, the prognostic role of RVIP-LGE and other CMR-derived parameters of RV function are not well established. Our aim was to evaluate the predictive value of contrast-enhanced CMR in patients with PH. Methods RV size, ejection fraction (RVEF, and the presence of RVIP-LGE were determined in 58 patients with PH referred for CMR. All patients underwent right heart catheterization, exercise testing, and N-terminal pro-brain natriuretic peptide (NT-proBNP evaluation; results of which were included in the final analysis if performed within 4 months of the CMR study. Patients were followed for the primary endpoint of time to clinical worsening (death, decompensated right ventricular heart failure, initiation of prostacyclin, or lung transplantation. Results Overall, 40/58 (69% of patients had RVIP-LGE. Patients with RVIP- LGE had larger right ventricular volume index, lower RVEF, and higher mean pulmonary artery pressure (mPAP, all p Conclusions The presence of RVIP-LGE in patients with PH is a marker for more advanced disease and poor prognosis. In addition, this study reveals for the first time that CMR-derived RVEF is an independent non-invasive imaging predictor of adverse outcomes in this patient population.

  11. Angiographically Negative Acute Arterial Upper and Lower Gastrointestinal Bleeding: Incidence, Predictive Factors, and Clinical Outcomes

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Jin Hyoung; Shin, Ji Hoon; Yoon, Hyun Ki; Chae, Eun Young; Myung, Seung Jae; Ko, Gi Young; Gwon, Dong Il; Sung, Kyu Bo [Asan Medical Center, Seoul (Korea, Republic of)

    2009-08-15

    To evaluate the incidence, predictive factors, and clinical outcomes of angiographically negative acute arterial upper and lower gastrointestinal (GI) bleeding. From 2001 to 2008, 143 consecutive patients who underwent an angiography for acute arterial upper or lower GI bleeding were examined. The angiographies revealed a negative bleeding focus in 75 of 143 (52%) patients. The incidence of an angiographically negative outcome was significantly higher in patients with a stable hemodynamic status (p < 0.001), or in patients with lower GI bleeding (p = 0.032). A follow-up of the 75 patients (range: 0-72 months, mean: 8 {+-} 14 months) revealed that 60 of the 75 (80%) patients with a negative bleeding focus underwent conservative management only, and acute bleeding was controlled without rebleeding. Three of the 75 (4%) patients underwent exploratory surgery due to prolonged bleeding; however, no bleeding focus was detected. Rebleeding occurred in 12 of 75 (16%) patients. Of these, six patients experienced massive rebleeding and died of disseminated intravascular coagulation within four to nine hours after the rebleeding episode. Four of the 16 patients underwent a repeat angiography and the two remaining patients underwent a surgical intervention to control the bleeding. Angiographically negative results are relatively common in patients with acute GI bleeding, especially in patients with a stable hemodynamic status or lower GI bleeding. Most patients with a negative bleeding focus have experienced spontaneous resolution of their condition.

  12. Prediction of the potential clinical outcomes for post-resuscitated patients after cardiac arrest

    Science.gov (United States)

    Hong, Sungmin; Kwon, Bojun; Yun, Il Dong; Lee, Sang Uk; Kim, Kyuseok; Kim, Joonghee

    2013-02-01

    Cerebral injuries after cardiac arrest are serious causes for morbidity. Many previous researches in the medical society have been proposed to prognosticate the functional recoveries of post-resuscitated patients after cardiac arrest, but the validity of suggested features and the automation of prognostication have not been made yet. This paper presents the automatic classification method which predicts the potential clinical outcomes of post-resuscitated patients who suffered from cardiac arrest. The global features and the local features are adapted from the researches from the medical society. The global features, which are consisted of the percentage of the partial volume under the uniformly increasing thresholds, represent the global tendency of apparent diffusion coefficient value in a DWI. The local features are localized and measured on the refined local apparent diffusion coefficient minimal points. The local features represent the ischemic change of small areas in a brain. The features are trained and classified by the random forest method, which have been widely used in the machine learning society for classification. The validity of features is automatically evaluated during the classification process. The proposed method achieved the 0.129 false-positive rate while maintaining the perfect true-positive rate. The area-under-curve of the proposed method was 0.9516, which showed the feasibility and the robustness of the proposed method.

  13. Primary gastric mucosa associated lymphoid tissue lymphoma: Clinical data predicted treatment outcome

    Institute of Scientific and Technical Information of China (English)

    Milena Todorovic; Miodrag Krstic; Bela Balint; Miodrag Jevtic; Nada Suvajdzic; Amela Ceric; Dragana Stamatovic; Olivera Markovic; Maja Perunicic; Slobodan Marjanovic

    2008-01-01

    AIM: To determine clinical characteristics and treatmentoutcome of gastric lymphoma after chemotherapy and immuno-chemotherapy.METHODS: Thirty four patients with primary gastric mucosa associated lymphoid tissue (MALT) lymphoma (Ann Arbor stages I to IV) were enrolled. All had upper gastric endoscopy, abdominal ultrasonography, CT and H py/or/status assessment (histology and serology).After anti-/-/py/or/treatment and initial chemotherapy,patients were re-examined every 4 mo.RESULTS: Histological regression of the lymphoma wascomplete in 22/34 (64.7%) and partial in 9 (26.5%)patients. Median follow up time for these 31 responders was 60 mo (range 48-120). No regression was noted in 3 patients. Among the 25 (73.5%) H py/or/positive patients, the eradication rate was 100%.CONCLUSION: Using univariate analysis, predictive factors for overall survival were international prognostic index (IPI) score, hemoglobin level, erythrocyte sedimentation rate (ESR), and platelet numbers (P < 0.005). In addition to this, Cox proportion hazard model differentiate IPI score, ESR, and platelets as predictors of survival.

  14. The value of the UK Clinical Aptitude Test in predicting pre-clinical performance: a prospective cohort study at Nottingham Medical School

    Directory of Open Access Journals (Sweden)

    James David

    2010-07-01

    Full Text Available Abstract Background The UK Clinical Aptitude Test (UKCAT was introduced in 2006 as an additional tool for the selection of medical students. It tests mental ability in four distinct domains (Quantitative Reasoning, Verbal Reasoning, Abstract Reasoning, and Decision Analysis, and the results are available to students and admissions panels in advance of the selection process. As yet the predictive validity of the test against course performance is largely unknown. The study objective was to determine whether UKCAT scores predict performance during the first two years of the 5-year undergraduate medical course at Nottingham. Methods We studied a single cohort of students, who entered Nottingham Medical School in October 2007 and had taken the UKCAT. We used linear regression analysis to identify independent predictors of marks for different parts of the 2-year preclinical course. Results Data were available for 204/260 (78% of the entry cohort. The UKCAT total score had little predictive value. Quantitative Reasoning was a significant independent predictor of course marks in Theme A ('The Cell', (p = 0.005, and Verbal Reasoning predicted Theme C ('The Community' (p Conclusion This limited study from a single entry cohort at one medical school suggests that the predictive value of the UKCAT, particularly the total score, is low. Section scores may predict success in specific types of course assessment. The ultimate test of validity will not be available for some years, when current cohorts of students graduate. However, if this test of mental ability does not predict preclinical performance, it is arguably less likely to predict the outcome in the clinical years. Further research from medical schools with different types of curriculum and assessment is needed, with longitudinal studies throughout the course.

  15. Comparison of AIMS65 Score and Other Scoring Systems for Predicting Clinical Outcomes in Koreans with Nonvariceal Upper Gastrointestinal Bleeding

    Science.gov (United States)

    Park, Sung Min; Yeum, Seok Cheon; Kim, Byung-Wook; Kim, Joon Sung; Kim, Ji Hee; Sim, Eun Hui; Ji, Jeong-Seon; Choi, Hwang

    2016-01-01

    Background/Aims The AIMS65 score has not been sufficiently validated in Korea. The objective of this study was to compare the AIMS65 and other scoring systems for the prediction of various clinical outcomes in Korean patients with acute nonvariceal upper gastrointestinal bleeding (NVUGIB). Methods The AIMS65 score, clinical and full Rockall scores (cRS and fRS) and Glasgow-Blatchford (GBS) score were calculated in patients with NVUGIB in a single center retrospectively. The performance of these scores for predicting mortality, rebleeding, transfusion requirement, and endoscopic intervention was assessed by calculating the area under the receiver-operating characteristic curve. Results Of the 523 patients, 3.4% died within 30 days, 2.5% experienced rebleeding, 40.0% required endoscopic intervention, and 75.7% needed transfusion. The AIMS65 score was useful for predicting the 30-day mortality, the need for endoscopic intervention and for transfusion. The fRS was superior to the AIMS65, GBS, and cRS for predicting endoscopic intervention and the GBS was superior to the AIMS65, fRS, and cRS for predicting the transfusion requirement. Conclusions The AIMS65 score was useful for predicting the 30-day mortality, transfusion requirement, and endoscopic intervention in Korean patients with acute NVUGIB. However, it was inferior to the GBS and fRS for predicting the transfusion requirement and endoscopic intervention, respectively. PMID:27377742

  16. Applying psychological theory to evidence-based clinical practice: identifying factors predictive of taking intra-oral radiographs.

    Science.gov (United States)

    Bonetti, Debbie; Pitts, Nigel B; Eccles, Martin; Grimshaw, Jeremy; Johnston, Marie; Steen, Nick; Glidewell, Liz; Thomas, Ruth; Maclennan, Graeme; Clarkson, Jan E; Walker, Anne

    2006-10-01

    This study applies psychological theory to the implementation of evidence-based clinical practice. The first objective was to see if variables from psychological frameworks (developed to understand, predict and influence behaviour) could predict an evidence-based clinical behaviour. The second objective was to develop a scientific rationale to design or choose an implementation intervention. Variables from the Theory of Planned Behaviour, Social Cognitive Theory, Self-Regulation Model, Operant Conditioning, Implementation Intentions and the Precaution Adoption Process were measured, with data collection by postal survey. The primary outcome was the number of intra-oral radiographs taken per course of treatment collected from a central fee claims database. Participants were 214 Scottish General Dental Practitioners. At the theory level, the Theory of Planned Behaviour explained 13% variance in the number of radiographs taken, Social Cognitive Theory explained 7%, Operant Conditioning explained 8%, Implementation Intentions explained 11%. Self-Regulation and Stage Theory did not predict significant variance in radiographs taken. Perceived behavioural control, action planning and risk perception explained 16% of the variance in number of radiographs taken. Knowledge did not predict the number of radiographs taken. The results suggest an intervention targeting predictive psychological variables could increase the implementation of this evidence-based practice, while influencing knowledge is unlikely to do so. Measures which predicted number of radiographs taken also predicted intention to take radiographs, and intention accounted for significant variance in behaviour (adjusted R(2)=5%: F(1,166)=10.28, pservice-level trial. Since psychological frameworks incorporate methodologies to measure and change component variables, taking a theory-based approach enabled the creation of a methodology that can be replicated for identifying factors predictive of clinical behaviour

  17. Factors predictive of clinical pregnancy in the first intrauterine insemination cycle of 306 couples with favourable female patient characteristics.

    Science.gov (United States)

    Aydin, Yunus; Hassa, Hikmet; Oge, Tufan; Tokgoz, Vehbi Yavuz

    2013-12-01

    The objective of this study was to evaluate the factors predictive of clinical pregnancy in the first superovulation/intrauterine insemination (SO/IUI) cycle of couples with favourable female characteristics. We analyzed retrospectively the first SO/IUI cycle of 306 infertile couples with mild male factor infertility and unexplained infertility. The women had a favourable prognosis in terms of ovarian reserve. Univariate logistic regression analyses identified body mass index (BMI) [odds ratio (OR) = 0.9, P = 0.014], sperm concentration [OR = 1.007, P = 0.007] and inseminating motile sperm count (IMC) [OR = 1.007, P = 0.032] as significant predictive factors of clinical pregnancy. Multivariate logistic regression analysis identified BMI [OR = 0.87, P = 0.008] and sperm concentration [OR = 1.008, P = 0.011] as significant factors. Pregnant and non-pregnant groups did not differ significantly in terms of the age and smoking status of the woman, duration and type of infertility, length of the stimulation, total gonadotropin dosage or antral follicle count. Of the female characteristics investigated, BMI was the most significant predictive factor of clinical pregnancy in the first SO/IUI cycle of couples with unexplained or mild male factor infertility and favourable female characteristics. In overweight women, weight loss should be advised before starting SO/IUI. Sperm concentration and IMC were significant male predictive factors for clinical pregnancy in the first SO/IUI. PMID:24171641

  18. Clinical Frailty Scale in an Acute Medicine Unit: a Simple Tool That Predicts Length of Stay

    Science.gov (United States)

    Juma, Salina; Taabazuing, Mary-Margaret; Montero-Odasso, Manuel

    2016-01-01

    Background Frailty is characterized by increased vulnerability to external stressors. When frail older adults are admitted to hospital, they are at increased risk of adverse events including falls, delirium, and disability. The Clinical Frailty Scale (CFS) is a practical and efficient tool for assessing frailty; however, its ability to predict outcomes has not been well studied within the acute medical service. Objective To examine the CFS in elderly patients admitted to the acute medical ward and its association with length of stay. Design Prospective cohort study in an acute care university hospital in London, Ontario, Canada, involving 75 patients over age 65, admitted to the general internal medicine clinical teaching units (CTU). Measurements Patient demographics were collected through chart review, and CFS score was assigned to each patient after brief clinician assessment. The CFS ranges from 1 (very fit) to 9 (terminally ill) based on descriptors and pictographs of activity and functional status. The CFS was collapsed into three categories: non-frail (CFS 1–4), mild-to-moderately frail (CFS 5–6), and severely frail (CFS 7–8). Outcomes of length of stay and 90-day readmission were gathered through the LHSC electronic patient record. Results Severe frailty was associated with longer lengths of stay (Mean = 12.6 ± 12.7 days) compared to mild-to-moderate frailty (mean = 11.2 ± 10.8 days), and non-frailty (mean = 4.1 ± 2.1 days, p = .014). This finding was significant after adjusting for age, sex, and number of medications. Participants with higher frailty scores showed higher readmission rates when compared with those with no frailty (31.2% for severely frail, vs. 34.2% for mild-to-moderately frail vs. 19% for non-frail) although there was no significant difference in the adjusted analysis. Conclusion The CFS helped identify patients that are more likely to have prolonged hospital stays on the acute medical ward. The CFS is an easy to use tool which

  19. A rat retinal damage model predicts for potential clinical visual disturbances induced by Hsp90 inhibitors

    Energy Technology Data Exchange (ETDEWEB)

    Zhou, Dan, E-mail: DZhou@syntapharma.com [Synta Pharmaceuticals Corp., 45 Hartwell Avenue, Lexington, MA 02421 (United States); Liu, Yuan; Ye, Josephine; Ying, Weiwen; Ogawa, Luisa Shin; Inoue, Takayo; Tatsuta, Noriaki; Wada, Yumiko; Koya, Keizo [Synta Pharmaceuticals Corp., 45 Hartwell Avenue, Lexington, MA 02421 (United States); Huang, Qin [Department of Pathology and Laboratory Medicine, Veterans Affairs Boston Healthcare System, 1400 VFW Parkway, West Roxbury, MA 02132 (United States); Bates, Richard C.; Sonderfan, Andrew J. [Synta Pharmaceuticals Corp., 45 Hartwell Avenue, Lexington, MA 02421 (United States)

    2013-12-01

    In human trials certain heat shock protein 90 (Hsp90) inhibitors, including 17-DMAG and NVP-AUY922, have caused visual disorders indicative of retinal dysfunction; others such as 17-AAG and ganetespib have not. To understand these safety profile differences we evaluated histopathological changes and exposure profiles of four Hsp90 inhibitors, with or without clinical reports of adverse ocular effects, using a rat retinal model. Retinal morphology, Hsp70 expression (a surrogate marker of Hsp90 inhibition), apoptotic induction and pharmacokinetic drug exposure analysis were examined in rats treated with the ansamycins 17-DMAG and 17-AAG, or with the second-generation compounds NVP-AUY922 and ganetespib. Both 17-DMAG and NVP-AUY922 induced strong yet restricted retinal Hsp70 up-regulation and promoted marked photoreceptor cell death 24 h after the final dose. In contrast, neither 17-AAG nor ganetespib elicited photoreceptor injury. When the relationship between drug distribution and photoreceptor degeneration was examined, 17-DMAG and NVP-AUY922 showed substantial retinal accumulation, with high retina/plasma (R/P) ratios and slow elimination rates, such that 51% of 17-DMAG and 65% of NVP-AUY922 present at 30 min post-injection were retained in the retina 6 h post-dose. For 17-AAG and ganetespib, retinal elimination was rapid (90% and 70% of drugs eliminated from the retina at 6 h, respectively) which correlated with lower R/P ratios. These findings indicate that prolonged inhibition of Hsp90 activity in the eye results in photoreceptor cell death. Moreover, the results suggest that the retina/plasma exposure ratio and retinal elimination rate profiles of Hsp90 inhibitors, irrespective of their chemical class, may predict for ocular toxicity potential. - Highlights: • In human trials some Hsp90 inhibitors cause visual disorders, others do not. • Prolonged inhibition of Hsp90 in the rat eye results in photoreceptor cell death. • Retina/plasma ratio and retinal

  20. Spontaneous intracerebral hemorrhage: Clinical and computed tomography findings in predicting in-hospital mortality in Central Africans

    Directory of Open Access Journals (Sweden)

    Michel Lelo Tshikwela

    2012-01-01

    Full Text Available Background and Purpose: Intracerebral hemorrhage (ICH constitutes now 52% of all strokes. Despite of its deadly pattern, locally there is no clinical grading scale for ICH-related mortality prediction. The first objective of this study was to develop a risk stratification scale (Kinshasa ICH score by assessing the strength of independent predictors and their association with in-hospital 30-day mortality. The second objective of the study was to create a specific local and African model for ICH prognosis. Materials and Methods: Age, sex, hypertension, type 2 diabetes mellitus (T2DM, smoking, alcohol intake, and neuroimaging data from CT scan (ICH volume, Midline shift of patients admitted with primary ICH and follow-upped in 33 hospitals of Kinshasa, DR Congo, from 2005 to 2008, were analyzed using logistic regression models. Results: A total of 185 adults and known hypertensive patients (140 men and 45 women were examined. 30-day mortality rate was 35% (n=65. ICH volume>25 mL (OR=8 95% CI: 3.1-20.2; P 7 mm, a consequence of ICH volume, was also a significant predictor of mortality. The Kinshasa ICH score was the sum of individual points assigned as follows: Presence of coma coded 2 (2 × 2 = 4, absence of coma coded 1 (1 × 2 = 2, ICH volume>25 mL coded 2 (2 × 2=4, ICH volume of ≤25 mL coded 1(1 × 2=2, left hemispheric site of ICH coded 2 (2 × 1=2, and right hemispheric site of hemorrhage coded 1(1 × 1 = 1. All patients with Kinshasa ICH score ≤7 survived and the patients with a score >7 died. In considering sex influence (Model 3, points were allowed as follows: Presence of coma (2 × 3 = 6, absence of coma (1 × 3 = 3, men (2 × 2 = 4, women (1 × 2 = 2, midline shift ≤7 mm (1 × 3 = 3, and midline shift >7 mm (2 × 3 = 6. Patients who died had the Kinshasa ICH score ≥16. Conclusion: In this study, the Kinshasa ICH score seems to be an accurate method for distinguishing those ICH patients who need continuous and special management

  1. Early Low Urinary CXCL9 and CXCL10 Might Predict Immunological Quiescence in Clinically and Histologically Stable Kidney Recipients.

    Science.gov (United States)

    Rabant, M; Amrouche, L; Morin, L; Bonifay, R; Lebreton, X; Aouni, L; Benon, A; Sauvaget, V; Le Vaillant, L; Aulagnon, F; Sberro, R; Snanoudj, R; Mejean, A; Legendre, C; Terzi, F; Anglicheau, D

    2016-06-01

    We monitored the urinary C-X-C motif chemokine (CXCL)9 and CXCL10 levels in 1722 urine samples from 300 consecutive kidney recipients collected during the first posttransplantation year and assessed their predictive value for subsequent acute rejection (AR). The trajectories of urinary CXCL10 showed an early increase at 1 month (p = 0.0005) and 3 months (p = 0.0009) in patients who subsequently developed AR. At 1 year, the AR-free allograft survival rates were 90% and 54% in patients with CXCL10:creatinine (CXCL10:Cr) levels 2.79 ng/mmoL at 1 month, respectively (p CXCL10:Cr levels 5.32 ng/mmoL at 3 months (p CXCL9:Cr levels also associate, albeit less robustly, with AR-free allograft survival. Early CXCL10:Cr levels predicted clinical and subclinical rejection and both T cell- and antibody-mediated rejection. In 222 stable patients, CXCL10:Cr at 3 months predicted AR independent of concomitant protocol biopsy results (p = 0.009). Although its positive predictive value was low, a high negative predictive value suggests that early CXCL10:Cr might predict immunological quiescence on a triple-drug calcineurin inhibitor-based immunosuppressive regimen in the first posttransplantation year, even in clinically and histologically stable patients. The clinical utility of this test will need to be addressed by dedicated prospective clinical trials. PMID:26694099

  2. The Implications of Endoscopic Ulcer in Early Gastric Cancer: Can We Predict Clinical Behaviors from Endoscopy?

    Science.gov (United States)

    Lee, Yoo Jin; Kim, Jie-Hyun; Park, Jae Jun; Youn, Young Hoon; Park, Hyojin; Kim, Jong Won; Choi, Seung Ho; Noh, Sung Hoon

    2016-01-01

    Background The presence of ulcer in early gastric cancer (EGC) is important for the feasibility of endoscopic resection, only a few studies have examined the clinicopathological implications of endoscopic ulcer in EGC. Objectives To determine the role of endoscopic ulcer as a predictor of clinical behaviors in EGC. Methods Data of 3,270 patients with EGC who underwent surgery between January 2005 and December 2012 were reviewed. Clinicopathological characteristics were analyzed in relation to the presence and stage of ulcer in EGC. Based on endoscopic findings, the stage of ulcer was categorized as active, healing, or scar. Logistic regression analysis was performed to analyze factors associated with lymph node metastasis (LNM). Results 2,343 (71.7%) patients had endoscopic findings of ulceration in EGC. Submucosal (SM) invasion, LNM, lymphovascular invasion (LVI), perineural invasion, and undifferentiated-type histology were significantly higher in ulcerative than non-ulcerative EGC. Comparison across different stages of ulcer revealed that SM invasion, LNM, and LVI were significantly associated with the active stage, and that these features exhibited significant stage-based differences, being most common at the active stage, and least common at the scar stage. The presence of endoscopic ulcer and active status of the ulcer were identified as independent risk factors for LNM. Conclusions Ulcerative EGC detected by endoscopy exhibited more aggressive behaviors than non-ulcerative EGC. Additionally, the endoscopic stage of ulcer may predict the clinicopathological behaviors of EGC. Therefore, the appearance of ulcers should be carefully evaluated to determine an adequate treatment strategy for EGC. PMID:27741275

  3. Clinical prediction and diagnosis of neurosyphilis in HIV-infected patients with early Syphilis.

    Science.gov (United States)

    Dumaresq, Jeannot; Langevin, Stéphanie; Gagnon, Simon; Serhir, Bouchra; Deligne, Benoît; Tremblay, Cécile; Tsang, Raymond S W; Fortin, Claude; Coutlée, François; Roger, Michel

    2013-12-01

    The diagnosis of neurosyphilis (NS) is a challenge, especially in HIV-infected patients, and the criteria for deciding when to perform a lumbar puncture (LP) in HIV-infected patients with syphilis are controversial. We retrospectively reviewed demographic, clinical, and laboratory data from 122 cases of HIV-infected patients with documented early syphilis who underwent an LP to rule out NS, and we evaluated 3 laboratory-developed validated real-time PCR assays, the Treponema pallidum particle agglutination (TPPA) assay, the fluorescent treponemal antibody absorption (FTA-ABS) assay, and the line immunoassay INNO-LIA Syphilis, for the diagnosis of NS from cerebrospinal fluid (CSF) samples of these patients. NS was defined by a reactive CSF-VDRL test result and/or a CSF white blood cell (WBC) count of >20 cells/μl. Thirty of the 122 patients (24.6%) had early NS. Headache, visual symptoms, a CD4 cell count of RPR) titers were not associated with early NS (P = 0.575). For the diagnosis of NS, the PCR, FTA-ABS, TPPA, and INNO-LIA assays had sensitivities of 58%, 100%, 68%, and 100%, specificities of 67%, 12%, 49%, and 13%, and negative predictive values of 85%, 100%, 84%, and 100%, respectively. Visual disturbances, headache, uncontrolled HIV-1 viremia, and a CD4 cell count of syphilis, while blood serum RPR titers were not; therefore, RPR titers should not be used as the sole criterion for deciding whether to perform an LP in early syphilis. When applied to CSF samples, the INNO-LIA Syphilis assay easily helped rule out NS. PMID:24088852

  4. The value of the UK Clinical Aptitude Test in predicting pre-clinical performance: a prospective cohort study at Nottingham Medical School

    OpenAIRE

    James David; Yates Janet

    2010-01-01

    Abstract Background The UK Clinical Aptitude Test (UKCAT) was introduced in 2006 as an additional tool for the selection of medical students. It tests mental ability in four distinct domains (Quantitative Reasoning, Verbal Reasoning, Abstract Reasoning, and Decision Analysis), and the results are available to students and admissions panels in advance of the selection process. As yet the predictive validity of the test against course performance is largely unknown. The study objective was to d...

  5. Positive Predictive Value of the WHO Clinical and Immunologic Criteria to Predict Viral Load Failure among Adults on First, or Second-Line Antiretroviral Therapy in Kenya

    Science.gov (United States)

    Muttai, Hellen; Ng’ang’a, Lucy; Ackers, Marta; Kim, Andrea; Miruka, Fredrick; Erick, Opiyo; Okonji, Julie; Ayuaya, Tolbert; Schwarcz, Sandra

    2016-01-01

    Routine HIV viral load (VL) monitoring is the standard of care for persons receiving antiretroviral therapy (ART) in developed countries. Although the World Health Organization recommends annual VL monitoring of patients on ART, recognizing difficulties in conducting routine VL testing, the WHO continues to recommend targeted VL testing to confirm treatment failure for persons who meet selected immunologic and clinical criteria. Studies have measured positive predictive value (PPV), negative predictive value, sensitivity and specificity of these criteria among patients receiving first-line ART but not specifically among those on second-line or subsequent regimens. Between 2008 and 2011, adult ART patients in Nyanza, Kenya who met national clinical or immunologic criteria for treatment failure received targeted VL testing. We calculated PPV and 95% confidence intervals (CI) of these criteria to detect virologic treatment failure among patients receiving a) first-line ART, b) second/subsequent ART, and c) any regimen. Of 12,134 patient specimens tested, 2,874 (23.7%) were virologically confirmed as treatment failures. The PPV for 2,834 first-line ART patients who met either the clinical or immunologic criteria for treatment failure was 34.4% (95% CI 33.2–35.7), 33.1% (95% CI 24.7–42.3) for the 40 patients on second-line/subsequent regimens, and 33.4% (95% CI 33.1–35.6) for any ART. PPV, regardless of criteria, for first-line ART patients was lowest among patients over 44 years old and highest for patients aged 15 to 34 years. PPV of immunological and clinical criteria for correctly identifying treatment failure was similarly low for adult patients receiving either first-line or second-line/subsequent ART regimens. Our data confirm the inadequacy of clinical and immunologic criteria to correctly identify treatment failure and support the implementation of routine VL testing. PMID:27383834

  6. Prediction

    CERN Document Server

    Sornette, Didier

    2010-01-01

    This chapter first presents a rather personal view of some different aspects of predictability, going in crescendo from simple linear systems to high-dimensional nonlinear systems with stochastic forcing, which exhibit emergent properties such as phase transitions and regime shifts. Then, a detailed correspondence between the phenomenology of earthquakes, financial crashes and epileptic seizures is offered. The presented statistical evidence provides the substance of a general phase diagram for understanding the many facets of the spatio-temporal organization of these systems. A key insight is to organize the evidence and mechanisms in terms of two summarizing measures: (i) amplitude of disorder or heterogeneity in the system and (ii) level of coupling or interaction strength among the system's components. On the basis of the recently identified remarkable correspondence between earthquakes and seizures, we present detailed information on a class of stochastic point processes that has been found to be particu...

  7. Prediction of Metastasis and Recurrence in Colorectal Cancer Based on Gene Expression Analysis: Ready for the Clinic?

    International Nuclear Information System (INIS)

    Cancers of the colon and rectum, which rank among the most frequent human tumors, are currently treated by surgical resection in locally restricted tumor stages. However, disease recurrence and formation of local and distant metastasis frequently occur even in cases with successful curative resection of the primary tumor (R0). Recent technological advances in molecular diagnostic analysis have led to a wealth of knowledge about the changes in gene transcription in all stages of colorectal tumors. Differential gene expression, or transcriptome analysis, has been proposed by many groups to predict disease recurrence, clinical outcome, and also response to therapy, in addition to the well-established clinico-pathological factors. However, the clinical usability of gene expression profiling as a reliable and robust prognostic tool that allows evidence-based clinical decisions is currently under debate. In this review, we will discuss the most recent data on the prognostic significance and potential clinical application of genome wide expression analysis in colorectal cancer

  8. Predicting the onset of psychosis in patients at clinical high risk: practical guide to probabilistic prognostic reasoning.

    Science.gov (United States)

    Fusar-Poli, P; Schultze-Lutter, F

    2016-02-01

    Prediction of psychosis in patients at clinical high risk (CHR) has become a mainstream focus of clinical and research interest worldwide. When using CHR instruments for clinical purposes, the predicted outcome is but only a probability; and, consequently, any therapeutic action following the assessment is based on probabilistic prognostic reasoning. Yet, probabilistic reasoning makes considerable demands on the clinicians. We provide here a scholarly practical guide summarising the key concepts to support clinicians with probabilistic prognostic reasoning in the CHR state. We review risk or cumulative incidence of psychosis in, person-time rate of psychosis, Kaplan-Meier estimates of psychosis risk, measures of prognostic accuracy, sensitivity and specificity in receiver operator characteristic curves, positive and negative predictive values, Bayes' theorem, likelihood ratios, potentials and limits of real-life applications of prognostic probabilistic reasoning in the CHR state. Understanding basic measures used for prognostic probabilistic reasoning is a prerequisite for successfully implementing the early detection and prevention of psychosis in clinical practice. Future refinement of these measures for CHR patients may actually influence risk management, especially as regards initiating or withholding treatment.

  9. More Accurate Definition of Clinical Target Volume Based on the Measurement of Microscopic Extensions of the Primary Tumor Toward the Uterus Body in International Federation of Gynecology and Obstetrics Ib-IIa Squamous Cell Carcinoma of the Cervix

    Energy Technology Data Exchange (ETDEWEB)

    Xie, Wen-Jia [Department of Radiation Oncology, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong Province (China); Wu, Xiao [Department of Pathology, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong Province (China); Xue, Ren-Liang; Lin, Xiang-Ying [Department of Radiation Oncology, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong Province (China); Kidd, Elizabeth A. [Department of Radiation Oncology, Stanford University, Stanford, California (United States); Yan, Shu-Mei [Department of Pathology, Sun Yat-Sen University Cancer Center, Guangzhou, Guangdong Province (China); Zhang, Yao-Hong [Department of Radiation Oncology, Chaozhou Hospital of Chaozhou City, Guangdong Province (China); Zhai, Tian-Tian; Lu, Jia-Yang; Wu, Li-Li; Zhang, Hao [Department of Radiation Oncology, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong Province (China); Huang, Hai-Hua [Department of Pathology, The Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong Province (China); Chen, Zhi-Jian; Li, De-Rui [Department of Radiation Oncology, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong Province (China); Xie, Liang-Xi, E-mail: xieliangxi1@qq.com [Department of Radiation Oncology, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong Province (China)

    2015-01-01

    Purpose: To more accurately define clinical target volume for cervical cancer radiation treatment planning by evaluating tumor microscopic extension toward the uterus body (METU) in International Federation of Gynecology and Obstetrics stage Ib-IIa squamous cell carcinoma of the cervix (SCCC). Patients and Methods: In this multicenter study, surgical resection specimens from 318 cases of stage Ib-IIa SCCC that underwent radical hysterectomy were included. Patients who had undergone preoperative chemotherapy, radiation, or both were excluded from this study. Microscopic extension of primary tumor toward the uterus body was measured. The association between other pathologic factors and METU was analyzed. Results: Microscopic extension toward the uterus body was not common, with only 12.3% of patients (39 of 318) demonstrating METU. The mean (±SD) distance of METU was 0.32 ± 1.079 mm (range, 0-10 mm). Lymphovascular space invasion was associated with METU distance and occurrence rate. A margin of 5 mm added to gross tumor would adequately cover 99.4% and 99% of the METU in the whole group and in patients with lymphovascular space invasion, respectively. Conclusion: According to our analysis of 318 SCCC specimens for METU, using a 5-mm gross tumor volume to clinical target volume margin in the direction of the uterus should be adequate for International Federation of Gynecology and Obstetrics stage Ib-IIa SCCC. Considering the discrepancy between imaging and pathologic methods in determining gross tumor volume extent, we recommend a safer 10-mm margin in the uterine direction as the standard for clinical practice when using MRI for contouring tumor volume.

  10. More Accurate Definition of Clinical Target Volume Based on the Measurement of Microscopic Extensions of the Primary Tumor Toward the Uterus Body in International Federation of Gynecology and Obstetrics Ib-IIa Squamous Cell Carcinoma of the Cervix

    International Nuclear Information System (INIS)

    Purpose: To more accurately define clinical target volume for cervical cancer radiation treatment planning by evaluating tumor microscopic extension toward the uterus body (METU) in International Federation of Gynecology and Obstetrics stage Ib-IIa squamous cell carcinoma of the cervix (SCCC). Patients and Methods: In this multicenter study, surgical resection specimens from 318 cases of stage Ib-IIa SCCC that underwent radical hysterectomy were included. Patients who had undergone preoperative chemotherapy, radiation, or both were excluded from this study. Microscopic extension of primary tumor toward the uterus body was measured. The association between other pathologic factors and METU was analyzed. Results: Microscopic extension toward the uterus body was not common, with only 12.3% of patients (39 of 318) demonstrating METU. The mean (±SD) distance of METU was 0.32 ± 1.079 mm (range, 0-10 mm). Lymphovascular space invasion was associated with METU distance and occurrence rate. A margin of 5 mm added to gross tumor would adequately cover 99.4% and 99% of the METU in the whole group and in patients with lymphovascular space invasion, respectively. Conclusion: According to our analysis of 318 SCCC specimens for METU, using a 5-mm gross tumor volume to clinical target volume margin in the direction of the uterus should be adequate for International Federation of Gynecology and Obstetrics stage Ib-IIa SCCC. Considering the discrepancy between imaging and pathologic methods in determining gross tumor volume extent, we recommend a safer 10-mm margin in the uterine direction as the standard for clinical practice when using MRI for contouring tumor volume

  11. Predicting dangerousness with two Millon Adolescent Clinical Inventory psychopathy scales: the importance of egocentric and callous traits.

    Science.gov (United States)

    Salekin, Randall T; Ziegler, Tracey A; Larrea, Maria A; Anthony, Virginia Lee; Bennett, Allyson D

    2003-04-01

    Psychopathy in youth has received increased recognition as a critical clinical construct for the evaluation and management of adolescents who have come into contact with the law (e.g., Forth, Hare, & Hart, 1990; Frick, 1998; Lynam, 1996, 1998). Although considerable attention has been devoted to the adult construct of psychopathy and its relation to recidivism, psychopathy in adolescents has been less thoroughly researched. Recently, a psychopathy scale (Murrie and Cornell Psychopathy Scale; Murrie & Cornell, 2000) was developed from items of the Millon Adolescent Clinical Inventory (MACI; Millon, 1993). This scale was found to be highly related to the Psychopathy Checklist-Revised (Hare, 1991) and was judged to have demonstrated good criterion validity. A necessary step in the validation process of any psychopathy scale is establishing its predictive validity. With this in mind, we investigated the ability of the MACI Psychopathy Scale to predict recidivism with 55 adolescent offenders 2 years after they had been evaluated at a juvenile court evaluation unit. In addition, we devised a psychopathy scale from MACI items that aligned more closely with Cooke and Michie (2001) and Frick, Bodin, and Barry's (2001) recommendations for the refinement of psychopathy and tested its predictive validity. Results indicate that both scales had predictive utility. Interpersonal and affective components of the revised scale were particularly important in the prediction of both general and violent reoffending. PMID:12700018

  12. Speaking Fluently And Accurately

    Institute of Scientific and Technical Information of China (English)

    JosephDeVeto

    2004-01-01

    Even after many years of study,students make frequent mistakes in English. In addition, many students still need a long time to think of what they want to say. For some reason, in spite of all the studying, students are still not quite fluent.When I teach, I use one technique that helps students not only speak more accurately, but also more fluently. That technique is dictations.

  13. Accurate Finite Difference Algorithms

    Science.gov (United States)

    Goodrich, John W.

    1996-01-01

    Two families of finite difference algorithms for computational aeroacoustics are presented and compared. All of the algorithms are single step explicit methods, they have the same order of accuracy in both space and time, with examples up to eleventh order, and they have multidimensional extensions. One of the algorithm families has spectral like high resolution. Propagation with high order and high resolution algorithms can produce accurate results after O(10(exp 6)) periods of propagation with eight grid points per wavelength.

  14. Cerebrospinal fluid total tau concentration predicts clinical phenotype in Huntington's disease.

    Science.gov (United States)

    Rodrigues, Filipe Brogueira; Byrne, Lauren; McColgan, Peter; Robertson, Nicola; Tabrizi, Sarah J; Leavitt, Blair R; Zetterberg, Henrik; Wild, Edward J

    2016-10-01

    Huntington's disease (HD) is a hereditary neurodegenerative condition with no therapeutic intervention known to alter disease progression, but several trials are ongoing and biomarkers of disease progression are needed. Tau is an axonal protein, often altered in neurodegeneration, and recent studies pointed out its role on HD neuropathology. Our goal was to study whether cerebrospinal fluid (CSF) tau is a biomarker of disease progression in HD. After informed consent, healthy controls, pre-symptomatic and symptomatic gene expansion carriers were recruited from two HD clinics. All participants underwent assessment with the Unified HD Rating Scale '99 (UHDRS). CSF was obtained according to a standardized lumbar puncture protocol. CSF tau was quantified using enzyme-linked immunosorbent assay. Comparisons between two groups were tested using ancova. Pearson's correlation coefficients were calculated for disease progression. Significance level was defined as p international pilot study. Age-adjusted CSF tau was significantly elevated in gene expansion carriers compared with healthy controls (p = 0.002). UHDRS total functional capacity was significantly correlated with CSF tau (r = -0.29, p = 0.004) after adjustment for age, and UHDRS total motor score was significantly correlated with CSF tau after adjustment for age (r = 0.32, p = 0.002). Several UHDRS cognitive tasks were also significantly correlated with CST total tau after age-adjustment. This study confirms that CSF tau concentrations in HD gene mutation carriers are increased compared with healthy controls and reports for the first time that CSF tau concentration is associated with phenotypic variability in HD. These conclusions strengthen the case for CSF tau as a biomarker in HD. In the era of novel targeted approaches to Huntington's disease, reliable biomarkers are needed. We quantified Tau protein, a marker of neuronal death, in cerebrospinal fluid and found it was increased in patients with

  15. The usefulness of holotranscobalamin in predicting vitamin B12 status in different clinical settings.

    Science.gov (United States)

    Herrmann, Wolfgang; Obeid, Rima; Schorr, Heike; Geisel, Jürgen

    2005-02-01

    Serum concentrations of homocysteine (Hcy) and methylmalonic acid (MMA) become increased in B12-deficient subjects and are therefore, considered specific markers of B12 deficiency. Serum level of holotranscobalamin (holoTC) becomes decreased before the development of the metabolic dysfunction. We investigated the usefulness of holoTC in diagnosing B12 deficiency in some clinical settings. We measured serum concentrations of holoTC, MMA, Hcy and total B12 in omnivores, vegetarians, elderly people and haemodialysis patients. Our results indicated that the incidence of holoTC vegans (76%). Low holoTC and elevated MMA were detected in 64% of the vegans and 43% of the lacto- and lacto-ovovegetarians. An elevated MMA and a low holoTC were found in subjects with total serum B12 as high as 300 pmol/L. The distribution of holoTC in elderly people was similar to that in younger adults (median holoTC 55 pmol/L in both groups). A low holoTC and an elevated MMA were found in 16% of the elderly group. An elevated MMA and a normal holoTC were found in 20% of the elderly group who had a relatively high median serum concentration of creatinine (106.1 micromol/L). Serum concentrations of holoTC in dialysis patients were considerably higher than all other groups (median 100 pmol/L). This was also associated with severely increased serum levels of MMA (median 987 nmol/L). From these results it can be concluded that serum concentration of holoTC is a much better predictor of B12 status than total B12. This was particularly evident in case of dietary B12 deficiency. Serum concentrations of holoTC as well as MMA can be affected by renal dysfunction. Elevated MMA and normal holoTC in patients with renal insufficiency may not exclude vitamin B12 deficiency. HoloTC seems not to be a promising marker in predicting B12 status in renal patients.

  16. CREATION OF THE NOMOGRAM THAT PREDICTS PATHOLOGICAL LOCAL EXTENT OF THE BLADDER CANCER BASED ON CLINICAL VARIABLES

    OpenAIRE

    L. V. Mirylenka; O. G. Sukonko; A. V. Pravorov; A. I. Rolevich; A. S. Mavrichev

    2014-01-01

    Objective: to develop nomogram based on clinical variables, that predicts pathological local extent of the bladder cancer рТ3-рТ4 (рТ3+).Material and methods: We used data of 511 patients with bladder cancer, that have undergone radical cystectomy between 1999 and 2008 at N.N. Alexandrov National Cancer Centre. For prediction of pT3+ on preoperative data were used mono- and multivariate logistic regression analysis. Coefficients from logistic regression equalization were used to construct nom...

  17. A clinical prediction rule for ambulation outcomes after traumatic spinal cord injury: a longitudinal cohort study

    NARCIS (Netherlands)

    Middendorp, J.J. van; Hosman, A.J.F.; Donders, A.R.T.; Pouw, M.H.; Ditunno Jr., J.F.; Curt, A.; Geurts, A.C.H.; Meent, H. van de

    2011-01-01

    BACKGROUND: Traumatic spinal cord injury is a serious disorder in which early prediction of ambulation is important to counsel patients and to plan rehabilitation. We developed a reliable, validated prediction rule to assess a patient's chances of walking independently after such injury. METHODS: We

  18. Social Anxiety Predicts Aggression in Children with ASD: Clinical Comparisons with Socially Anxious and Oppositional Youth

    Science.gov (United States)

    Pugliese, Cara E.; White, Bradley A.; White, Susan W.; Ollendick, Thomas H.

    2013-01-01

    The present study examined the degree to which social anxiety predicts aggression in children with high functioning autism spectrum disorders (HFASD, n = 20) compared to children with Social Anxiety Disorder (SAD, n = 20) or with Oppositional Defiant Disorder or Conduct Disorder (ODD/CD, n = 20). As predicted, children with HFASD reported levels…

  19. Predictive biomarker discovery through the parallel integration of clinical trial and functional genomics datasets

    DEFF Research Database (Denmark)

    Swanton, C.; Larkin, J.M.; Gerlinger, M.;

    2010-01-01

    The EU multi-disciplinary personalised RNA interference to enhance the delivery of individualised chemotherapeutics and targeted therapies (PREDICT) consortium has recently initiated a framework to accelerate the development of predictive biomarkers of individual patient response to anti-cancer a...

  20. Common clinical practice versus new PRIM score in predicting coronary heart disease risk

    DEFF Research Database (Denmark)

    Frikke-Schmidt, Ruth; Tybjærg-Hansen, Anne; Schnohr, Peter;

    2010-01-01

    To compare the new Patient Rule Induction Method (PRIM) Score and common clinical practice with the Framingham Point Score for classification of individuals with respect to coronary heart disease (CHD) risk.......To compare the new Patient Rule Induction Method (PRIM) Score and common clinical practice with the Framingham Point Score for classification of individuals with respect to coronary heart disease (CHD) risk....

  1. Acute axonal damage predicts clinical outcome in patients with multiple sclerosis

    DEFF Research Database (Denmark)

    Lim, E.T; Sellebjerg, F; Jensen, C.V;

    2005-01-01

    ) to correlate neurofilament and myelin basic protein (MBP) concentrations, particularly as the latter was previously associated with clinical disability. Fifty subjects participated in two double-blind, randomized, placebo-controlled clinical trials. Eight/18 patients in the ON trial and 15/32 subjects...

  2. Free Recall Episodic Memory Performance Predicts Dementia Ten Years prior to Clinical Diagnosis: Findings from the Betula Longitudinal Study

    OpenAIRE

    Boraxbekk, Carl-Johan; Lundquist, Anders; Nordin, Annelie; Nyberg, Lars; Nilsson, Lars-Göran; Adolfsson, Rolf

    2015-01-01

    Background/Aims: Early dementia diagnosis is a considerable challenge. The present study examined the predictive value of cognitive performance for a future clinical diagnosis of late-onset Alzheimer's disease or vascular dementia in a random population sample. Methods: Cognitive performance was retrospectively compared between three groups of participants from the Betula longitudinal cohort. Group 1 developed dementia 11-22 years after baseline testing (n = 111) and group 2 after 1-10 years ...

  3. A Simple Clinical Score “TOPRS” to Predict Outcome in Pediatric Emergency Department in a Teaching Hospital in India

    OpenAIRE

    Ravinder Kumar Soni; Bains, Harmesh S.

    2012-01-01

    Objective: To develop a simple clinical scoring system for severity of illness to help prioritize care and predict outcome in emergency department.Methods: Prospective hospital based observational study. Out of a total of 874 children who attended emergency department in one year, 777 were included in the study. Data was collected at the time of admission in emergency department. The baseline information like age, gender, etc and variables of ‘toprs’ score viz temperature, oxygen saturation, ...

  4. CREATION OF THE NOMOGRAM THAT PREDICTS PATHOLOGICAL LOCAL EXTENT OF THE BLADDER CANCER BASED ON CLINICAL VARIABLES

    Directory of Open Access Journals (Sweden)

    L. V. Mirylenka

    2012-01-01

    Full Text Available Objective: to develop nomogram based on clinical variables, that predicts pathological local extent of the bladder cancer рТ3-рТ4 (рТ3+.Material and methods: We used data of 511 patients with bladder cancer, that have undergone radical cystectomy between 1999 and 2008 at N.N. Alexandrov National Cancer Centre. For prediction of pT3+ on preoperative data were used mono- and multivariate logistic regression analysis. Coefficients from logistic regression equalization were used to construct nomogram. Nomogram accuracy was evaluated with concordance index (с-index and by building the calibration plot. Internal validation by bootstrap method with 200 variants of dataset was performed.Results: We developed nomogram, that include: clinical stage сТ, tumor grade, tumor macroscopic appearance, presence of upper tract dilatation, prostatic urethra and/or prostatic lobe(s involvement, 3 or more bladder walls involvement, ESR and creatinine level. Bootstrapcorrected prognostic accuracy of nomogram was 81,4%, that 12,6% better than clinical stage accuracy.Conclusion: developed nomogram can significantly improve pathologic tumor stage prediction accuracy that may be used to select patients for neoadjuvant chemotherapy.

  5. Prediction of persistent shoulder pain in general practice: Comparing clinical consensus from a Delphi procedure with a statistical scoring system

    Directory of Open Access Journals (Sweden)

    van der Windt Daniëlle AWM

    2011-06-01

    Full Text Available Abstract Background In prognostic research, prediction rules are generally statistically derived. However the composition and performance of these statistical models may strongly depend on the characteristics of the derivation sample. The purpose of this study was to establish consensus among clinicians and experts on key predictors for persistent shoulder pain three months after initial consultation in primary care and assess the predictive performance of a model based on clinical expertise compared to a statistically derived model. Methods A Delphi poll involving 3 rounds of data collection was used to reach consensus among health care professionals involved in the assessment and management of shoulder pain. Results Predictors selected by the expert panel were: symptom duration, pain catastrophizing, symptom history, fear-avoidance beliefs, coexisting neck pain, severity of shoulder disability, multisite pain, age, shoulder pain intensity and illness perceptions. When tested in a sample of 587 primary care patients consulting with shoulder pain the predictive performance of the two prognostic models based on clinical expertise were lower compared to that of a statistically derived model (Area Under the Curve, AUC, expert-based dichotomous predictors 0.656, expert-based continuous predictors 0.679 vs. 0.702 statistical model. Conclusions The three models were different in terms of composition, but all confirmed the prognostic importance of symptom duration, baseline level of shoulder disability and multisite pain. External validation in other populations of shoulder pain patients should confirm whether statistically derived models indeed perform better compared to models based on clinical expertise.

  6. Evaluation of the Cerebral State Index in Cats under Isoflurane Anaesthesia: Dose-Effect Relationship and Prediction of Clinical Signs

    Directory of Open Access Journals (Sweden)

    Joana R. Sousa

    2014-01-01

    Full Text Available The performance of the cerebral state index (CSI in reflecting different levels of isoflurane anaesthesia was evaluated in ten cats subjected to four end-tidal isoflurane concentrations (EtIso, each maintained for 15 minutes (0.8%, 1.2%, 1.6%, or 2.0% EtIso. The CSI, hemodynamic data, ocular reflexes, and eye position were recorded for each EtIso concentration. Pharmacodynamic analysis of CSI with EtIso was performed, as well as prediction probability analysis with a clinical scale based on the eye reflexes. The CSI values showed great variability. Between all parameters, burst suppression ratio showed the better fitting with the sigmoidal concentration-effect model (R2=0.93 followed by CSI (R2=0.82 and electromyographic activity (R2=0.79. EtIso was the variable with better prediction of the clinical scale of anaesthesia (prediction probability value of 0.94. Although the CSI values decrease with increasing isoflurane concentrations, the huge variability in CSI values may be a strong limitation for its use in cats and it seems to be no better than EtIso as a predictor of clinical signs.

  7. Predicting Clinical Syndrome in Students with Emotional Breakdown Experience based on Personality Structures: the Moderating Role of Perceived Social Support

    Directory of Open Access Journals (Sweden)

    Samad Fahimi

    2015-10-01

    Full Text Available Introduction: This study investigated the role of personality constructs in predicting the clinical syndrome of students with emotional breakdown and moderating role of perceived social support in this relationship. Methods: Using purposive sampling and based on questionnaires of the love trauma, Beck depression and GHQ in students with emotional breakdown experience, 65 students with and 65 students without the clinical syndrome were selected from Payam Noor University of Tabriz, Tabriz University, and Islamic Azad University of Tabriz, and completed HEXACO questionnaire and multidimensional scale of perceived social support (MSPSS. Data analysis was done using SPSS16 and LISREL 8.54 by multivariate analysis of variance (MANOVA and path analysis. Results: The results showed that there was a significant difference between two groups in personality characteristics and social support (P<0.05, and social support had a moderating role in developing clinical syndrome after emotional breakdown. Conclusion: Personality characteristics and social support affect everyone's romantic relationships and would predict how to deal with the challenges in these relationships. After an emotional breakdown, if families are able to bring children out of this crisis with their direct and indirect support, this will lead to passing the trauma naturally and will prevent the continuation of the clinical syndrome.

  8. Procalcitonin Levels Predict Clinical Course and Progression-Free Survival in Patients With Medullary Thyroid Cancer

    NARCIS (Netherlands)

    Walter, Martin A.; Meier, Christian; Radimerski, Tanja; Iten, Fabienne; Kraenzlin, Marius; Mueller-Brand, Jan; de Groot, Jan Willem B.; Kema, Ido P.; Links, Thera P.; Mueller, Beat

    2010-01-01

    BACKGROUND: Procalcitonin has been well established as an important marker of sepsis and systemic infection. The authors evaluated the diagnostic and predictive value of calcitonin and its prohormone procalcitonin in medullary thyroid cancer. METHODS: The authors systematically explored the ability

  9. Predictive Value of IL-8 for Sepsis and Severe Infections after Burn Injury - A Clinical Study

    OpenAIRE

    Kraft, Robert; Herndon, David N; Finnerty, Celeste C.; Cox, Robert A.; Song, Juquan; Jeschke, Marc G.

    2015-01-01

    The inflammatory response induced by burn injury contributes to increased incidence of infections, sepsis, organ failure, and mortality. Thus, monitoring post-burn inflammation is of paramount importance but so far there are no reliable biomarkers available to monitor and/or predict infectious complications after burn. As IL-8 is a major mediator for inflammatory responses, the aim of our study was to determine whether IL-8 expression can be used to predict post-burn sepsis, infections, and m...

  10. Nutrition Screening Tools and the Prediction of Clinical Outcomes among Chinese Hospitalized Gastrointestinal Disease Patients.

    Science.gov (United States)

    Wang, Fang; Chen, Wei; Bruening, Kay Stearns; Raj, Sudha; Larsen, David A

    2016-01-01

    Nutrition risk Screening 2002 (NRS-2002) and Subjective Global Assessment (SGA) are widely used screening tools but have not been compared in a Chinese population. We conducted secondary data analysis of a cross-sectional study which included 332 hospitalized gastrointestinal disease patients, collected by the Gastrointestinal department of Peking Union Medical College Hospital (PUMCH) in 2008. Results of NRS-2002 and SGA screening tools, complications, length of stay (LOS), cost, and death were measured. The agreement between the tools was assessed via Kappa (κ) statistics. The performance of NRS-2002 and SGA in predicting LOS and cost was assessed via linear regression. The complications and death prediction of tools was assessed using receiver operating characteristic (ROC) curves. NRS-2002 and SGA identified nutrition risk at 59.0% and 45.2% respectively. Moderate agreement (κ >0.50) between the two tools was found among all age groups except individuals aged ≤ 20, which only slight agreement was found (κ = 0.087). NRS-2002 (R square 0.130) and SGA (R square 0.140) did not perform differently in LOS prediction. The cost prediction of NRS-2002 (R square 0.198) and SGA (R square 0.190) were not significantly different. There was no difference between NRS-2002 (infectious complications: area under ROC (AUROC) = 0.615, death: AUROC = 0.810) and SGA (infectious complications: AUROC = 0.600, death: AUROC = 0.846) in predicting infectious complication and death, but NRS-2002 (0.738) seemed to perform better than SGA (0.552) in predicting non-infectious complications. The risk of malnutrition among patients was high. NRS-2002 and SGA have similar capacity to predict LOS, cost, infectious complications and death, but NRS-2002 performed better in predicting non-infectious complications. PMID:27490480

  11. Predicting Relapse in Patients With Medulloblastoma by Integrating Evidence From Clinical and Genomic Features

    NARCIS (Netherlands)

    P. Tamayo; Y.J. Cho; A. Tsherniak; H. Greulich; L. Ambrogio; N. Schouten-van Meeteren; T. Zhou; A. Buxton; M. Kool; M. Meyerson; S.L. Pomeroy; J.P. Mesirov

    2011-01-01

    Purpose Despite significant progress in the molecular understanding of medulloblastoma, stratification of risk in patients remains a challenge. Focus has shifted from clinical parameters to molecular markers, such as expression of specific genes and selected genomic abnormalities, to improve accurac

  12. Burnout and Work Demands Predict Reduced Job Satisfaction in Health Professionals Working In a Surgery Clinic

    Directory of Open Access Journals (Sweden)

    Dragan Mijakoski

    2015-03-01

    CONCLUSIONS: Adequate management of work demands, particularly excessive workload, time pressure, and lack of staff can lead to prevention of burnout and reduced job satisfaction in surgery clinic HPs, and contribute to better quality of patient care.

  13. Location of brain lesions predicts conversion of clinically isolated syndromes to multiple sclerosis

    DEFF Research Database (Denmark)

    Giorgio, Antonio; Battaglini, Marco; Rocca, Maria Assunta;

    2013-01-01

    converting group in projection, association, and commissural WM tracts, with larger clusters being in the corpus callosum, corona radiata, and cingulum. CONCLUSIONS: Higher frequency of lesion occurrence in clinically eloquent WM tracts can characterize CIS subjects with different types of onset. The...... involvement of specific WM tracts, in particular those traversed by fibers involved in motor function and near the corpus callosum, seems to be associated with a higher risk of clinical conversion to MS in the short term....

  14. Protein-Based Classifier to Predict Conversion from Clinically Isolated Syndrome to Multiple Sclerosis.

    Science.gov (United States)

    Borràs, Eva; Cantó, Ester; Choi, Meena; Maria Villar, Luisa; Álvarez-Cermeño, José Carlos; Chiva, Cristina; Montalban, Xavier; Vitek, Olga; Comabella, Manuel; Sabidó, Eduard

    2016-01-01

    Multiple sclerosis is an inflammatory, demyelinating, and neurodegenerative disease of the central nervous system. In most patients, the disease initiates with an episode of neurological disturbance referred to as clinically isolated syndrome, but not all patients with this syndrome develop multiple sclerosis over time, and currently, there is no clinical test that can conclusively establish whether a patient with a clinically isolated syndrome will eventually develop clinically defined multiple sclerosis. Here, we took advantage of the capabilities of targeted mass spectrometry to establish a diagnostic molecular classifier with high sensitivity and specificity able to differentiate between clinically isolated syndrome patients with a high and a low risk of developing multiple sclerosis. Based on the combination of abundances of proteins chitinase 3-like 1 and ala-β-his-dipeptidase in cerebrospinal fluid, we built a statistical model able to assign to each patient a precise probability of conversion to clinically defined multiple sclerosis. Our results are of special relevance for patients affected by multiple sclerosis as early treatment can prevent brain damage and slow down the disease progression.

  15. Can Psychological, Social and Demographical Factors Predict Clinical Characteristics Symptomatology of Bipolar Affective Disorder and Schizophrenia?

    Science.gov (United States)

    Maciukiewicz, Malgorzata; Pawlak, Joanna; Kapelski, Pawel; Łabędzka, Magdalena; Skibinska, Maria; Zaremba, Dorota; Leszczynska-Rodziewicz, Anna; Dmitrzak-Weglarz, Monika; Hauser, Joanna

    2016-09-01

    Schizophrenia (SCH) is a complex, psychiatric disorder affecting 1 % of population. Its clinical phenotype is heterogeneous with delusions, hallucinations, depression, disorganized behaviour and negative symptoms. Bipolar affective disorder (BD) refers to periodic changes in mood and activity from depression to mania. It affects 0.5-1.5 % of population. Two types of disorder (type I and type II) are distinguished by severity of mania episodes. In our analysis, we aimed to check if clinical and demographical characteristics of the sample are predictors of symptom dimensions occurrence in BD and SCH cases. We included total sample of 443 bipolar and 439 schizophrenia patients. Diagnosis was based on DSM-IV criteria using Structured Clinical Interview for DSM-IV. We applied regression models to analyse associations between clinical and demographical traits from OPCRIT and symptom dimensions. We used previously computed dimensions of schizophrenia and bipolar affective disorder as quantitative traits for regression models. Male gender seemed protective factor for depression dimension in schizophrenia and bipolar disorder sample. Presence of definite psychosocial stressor prior disease seemed risk factor for depressive and suicidal domain in BD and SCH. OPCRIT items describing premorbid functioning seemed related with depression, positive and disorganised dimensions in schizophrenia and psychotic in BD. We proved clinical and demographical characteristics of the sample are predictors of symptom dimensions of schizophrenia and bipolar disorder. We also saw relation between clinical dimensions and course of disorder and impairment during disorder. PMID:26646576

  16. Predicting Anxiety Among Patients In LPU Clinical Dispensary During Dental Treatment: Towards Student’s Clinical Performance Enhancement

    Directory of Open Access Journals (Sweden)

    Maribel D. Mayuga-Barrion

    2013-12-01

    Full Text Available The study aimed to determine the respondents’ profile in terms of age, gender, frequency of dental visit, and type of patient whether dental phobic or not; to determine the dental anxiety of patients in LPU dental dispensary; to identify the causes and severity of anxiety of the patients in LPU dental dispensary; to determine if there is a significant difference between the respondents’ demographic profile and their level of anxiety; and lastly, to propose a program that will help the patients cope with dental anxiety and a program that will enhance the students’ clinical performance. The study used the descriptive research design with the combination of content analysis of documents and related materials. Results showed that majority of the respondents belonged to age range of 14-18 years old range whereas for gender or sex, majority who avail of the clinic’s services are males. This is because women are more afraid than men in terms of dental problems. Further, younger people are more afraid than older ones. The weighted mean distribution of the level of anxiety showed that the level of anxiety of patients varies on moderately to not anxious. Feeling or experiencing pain during dental treatment ranked first followed by the fear or worry of not working the proposed treatment and thirdly, the dentist is in a hurry while treating also made the patients moderately anxious. Overall, the level of anxiety of patients is moderately anxious. Probing to asses gum disease, dislike the numb feeling and injection were the top three causes of dental anxiety. Only type of patient shows significant difference, thus the null hypothesis of no significant difference on the level of anxiety when grouped according to profile variables is rejected. This means that the level of anxiety of both phobic and not phobic differs.

  17. Pre- and post-operative nomograms to predict recurrence-free probability in korean men with clinically localized prostate cancer.

    Directory of Open Access Journals (Sweden)

    Minyong Kang

    Full Text Available OBJECTIVES: Although the incidence of prostate cancer (PCa is rapidly increasing in Korea, there are few suitable prediction models for disease recurrence after radical prostatectomy (RP. We established pre- and post-operative nomograms estimating biochemical recurrence (BCR-free probability after RP in Korean men with clinically localized PCa. PATIENTS AND METHODS: Our sampling frame included 3,034 consecutive men with clinically localized PCa who underwent RP at our tertiary centers from June 2004 through July 2011. After inappropriate data exclusion, we evaluated 2,867 patients for the development of nomograms. The Cox proportional hazards regression model was used to develop pre- and post-operative nomograms that predict BCR-free probability. Finally, we resampled from our study cohort 200 times to determine the accuracy of our nomograms on internal validation, which were designated with concordance index (c-index and further represented by calibration plots. RESULTS: Over a median of 47 months of follow-up, the estimated BCR-free rate was 87.8% (1 year, 83.8% (2 year, and 72.5% (5 year. In the pre-operative model, Prostate-Specific Antigen (PSA, the proportion of positive biopsy cores, clinical T3a and biopsy Gleason score (GS were independent predictive factors for BCR, while all relevant predictive factors (PSA, extra-prostatic extension, seminal vesicle invasion, lymph node metastasis, surgical margin, and pathologic GS were associated with BCR in the post-operative model. The c-index representing predictive accuracy was 0.792 (pre- and 0.821 (post-operative, showing good fit in the calibration plots. CONCLUSIONS: In summary, we developed pre- and post-operative nomograms predicting BCR-free probability after RP in a large Korean cohort with clinically localized PCa. These nomograms will be provided as the mobile application-based SNUH Prostate Cancer Calculator. Our nomograms can determine patients at high risk of disease recurrence

  18. Predicting clinical outcome from reward circuitry function and white matter structure in behaviorally and emotionally dysregulated youth.

    Science.gov (United States)

    Bertocci, M A; Bebko, G; Versace, A; Fournier, J C; Iyengar, S; Olino, T; Bonar, L; Almeida, J R C; Perlman, S B; Schirda, C; Travis, M J; Gill, M K; Diwadkar, V A; Forbes, E E; Sunshine, J L; Holland, S K; Kowatch, R A; Birmaher, B; Axelson, D; Horwitz, S M; Frazier, T W; Arnold, L E; Fristad, M A; Youngstrom, E A; Findling, R L; Phillips, M L

    2016-09-01

    Behavioral and emotional dysregulation in childhood may be understood as prodromal to adult psychopathology. Additionally, there is a critical need to identify biomarkers reflecting underlying neuropathological processes that predict clinical/behavioral outcomes in youth. We aimed to identify such biomarkers in youth with behavioral and emotional dysregulation in the Longitudinal Assessment of Manic Symptoms (LAMS) study. We examined neuroimaging measures of function and white matter in the whole brain using 80 youth aged 14.0 (s.d.=2.0) from three clinical sites. Linear regression using the LASSO (Least Absolute Shrinkage and Selection Operator) method for variable selection was used to predict severity of future behavioral and emotional dysregulation measured by the Parent General Behavior Inventory-10 Item Mania Scale (PGBI-10M)) at a mean of 14.2 months follow-up after neuroimaging assessment. Neuroimaging measures, together with near-scan PGBI-10M, a score of manic behaviors, depressive behaviors and sex, explained 28% of the variance in follow-up PGBI-10M. Neuroimaging measures alone, after accounting for other identified predictors, explained ~1/3 of the explained variance, in follow-up PGBI-10M. Specifically, greater bilateral cingulum length predicted lower PGBI-10M at follow-up. Greater functional connectivity in parietal-subcortical reward circuitry predicted greater PGBI-10M at follow-up. For the first time, data suggest that multimodal neuroimaging measures of underlying neuropathologic processes account for over a third of the explained variance in clinical outcome in a large sample of behaviorally and emotionally dysregulated youth. This may be an important first step toward identifying neurobiological measures with the potential to act as novel targets for early detection and future therapeutic interventions. PMID:26903272

  19. Predicting beneficial effects of atomoxetine and citalopram on response inhibition in Parkinson's disease with clinical and neuroimaging measures.

    Science.gov (United States)

    Ye, Zheng; Rae, Charlotte L; Nombela, Cristina; Ham, Timothy; Rittman, Timothy; Jones, Peter Simon; Rodríguez, Patricia Vázquez; Coyle-Gilchrist, Ian; Regenthal, Ralf; Altena, Ellemarije; Housden, Charlotte R; Maxwell, Helen; Sahakian, Barbara J; Barker, Roger A; Robbins, Trevor W; Rowe, James B

    2016-03-01

    Recent studies indicate that selective noradrenergic (atomoxetine) and serotonergic (citalopram) reuptake inhibitors may improve response inhibition in selected patients with Parkinson's disease, restoring behavioral performance and brain activity. We reassessed the behavioral efficacy of these drugs in a larger cohort and developed predictive models to identify patient responders. We used a double-blind randomized three-way crossover design to investigate stopping efficiency in 34 patients with idiopathic Parkinson's disease after 40 mg atomoxetine, 30 mg citalopram, or placebo. Diffusion-weighted and functional imaging measured microstructural properties and regional brain activations, respectively. We confirmed that Parkinson's disease impairs response inhibition. Overall, drug effects on response inhibition varied substantially across patients at both behavioral and brain activity levels. We therefore built binary classifiers with leave-one-out cross-validation (LOOCV) to predict patients' responses in terms of improved stopping efficiency. We identified two optimal models: (1) a "clinical" model that predicted the response of an individual patient with 77-79% accuracy for atomoxetine and citalopram, using clinically available information including age, cognitive status, and levodopa equivalent dose, and a simple diffusion-weighted imaging scan; and (2) a "mechanistic" model that explained the behavioral response with 85% accuracy for each drug, using drug-induced changes of brain activations in the striatum and presupplementary motor area from functional imaging. These data support growing evidence for the role of noradrenaline and serotonin in inhibitory control. Although noradrenergic and serotonergic drugs have highly variable effects in patients with Parkinson's disease, the individual patient's response to each drug can be predicted using a pattern of clinical and neuroimaging features. PMID:26757216

  20. Developing a Clinical Prediction Rule for First Hospital-Onset Clostridium difficile Infections: A Retrospective Observational Study.

    Science.gov (United States)

    Press, Anne; Ku, Benson; McCullagh, Lauren; Rosen, Lisa; Richardson, Safiya; McGinn, Thomas

    2016-08-01

    BACKGROUND The healthcare burden of hospital-acquired Clostridium difficile infection (CDI) demands attention and calls for a solution. Identifying patients' risk of developing a primary nosocomial CDI is a critical first step in reducing the development of new cases of CDI. OBJECTIVE To derive a clinical prediction rule that can predict a patient's risk of acquiring a primary CDI. DESIGN Retrospective cohort study. SETTING Large tertiary healthcare center. PATIENTS Total of 61,482 subjects aged at least 18 admitted over a 1-year period (2013). INTERVENTION None. METHODS Patient demographic characteristics, evidence of CDI, and other risk factors were retrospectively collected. To derive the CDI clinical prediction rule the patient population was divided into a derivation and validation cohort. A multivariable analysis was performed in the derivation cohort to identify risk factors individually associated with nosocomial CDI and was validated on the validation sample. RESULTS Among 61,482 subjects, CDI occurred in 0.46%. CDI outcome was significantly associated with age, admission in the past 60 days, mechanical ventilation, dialysis, history of congestive heart failure, and use of antibiotic medications. The sensitivity and specificity of the score, in the validation set, were 82.0% and 75.7%, respectively. The area under the receiver operating characteristic curve was 0.85. CONCLUSION This study successfully derived a clinical prediction rule that will help identify patients at high risk for primary CDI. This tool will allow physicians to systematically recognize those at risk for CDI and will allow for early interventional strategies. Infect Control Hosp Epidemiol 2016;37:896-900. PMID:27123975

  1. Predicting clinical outcome from reward circuitry function and white matter structure in behaviorally and emotionally dysregulated youth

    Science.gov (United States)

    Bertocci, Michele A.; Bebko, Genna; Versace, Amelia; Fournier, Jay C.; Iyengar, Satish; Olino, Thomas; Bonar, Lisa; Almeida, Jorge R. C.; Perlman, Susan B.; Schirda, Claudiu; Travis, Michael J.; Gill, Mary Kay; Diwadkar, Vaibhav A.; Forbes, Erika E.; Sunshine, Jeffrey L.; Holland, Scott K; Kowatch, Robert A.; Birmaher, Boris; Axelson, David; Horwitz, Sarah M.; Frazier, Thomas W.; Arnold, L. Eugene; Fristad, Mary. A; Youngstrom, Eric A.; Findling, Robert L.; Phillips, Mary L.

    2015-01-01

    Behavioral and emotional dysregulation in childhood may be understood as prodromal to adult psychopathology. Additionally, there is a critical need to identify biomarkers reflecting underlying neuropathological processes that predict clinical/behavioral outcomes in youth. We aimed to identify such biomarkers in youth with behavioral and emotional dysregulation in the Longitudinal Assessment of Manic Symptoms (LAMS) study. We examined neuroimaging measures of function and white matter in the whole brain using 80 youth aged 14.0(sd=2.0) from 3 clinical sites. Linear regression using the LASSO method for variable selection was used to predict severity of future behavioral and emotional dysregulation [measured by the Parent General Behavior Inventory-10 Item Mania Scale (PGBI-10M)] at a mean of 14.2 months follow-up after neuroimaging assessment. Neuroimaging measures, together with near-scan PGBI-10M, a score of manic behaviors, depressive behaviors, and sex, explained 28% of the variance in follow-up PGBI-10M. Neuroimaging measures alone, after accounting for other identified predictors, explained approximately one-third of the explained variance, in follow-up PGBI-10M. Specifically, greater bilateral cingulum length predicted lower PGBI-10M at follow-up. Greater functional connectivity in parietal-subcortical reward circuitry predicted greater PGBI-10M at follow-up. For the first time, data suggest that multimodal neuroimaging measures of underlying neuropathologic processes account for over a third of the explained variance in clinical outcome in a large sample of behaviorally and emotionally dysregulated youth. This may be an important first step toward identifying neurobiological measures with the potential to act as novel targets for early detection and future therapeutic interventions. PMID:26903272

  2. Predicted Aerobic Capacity of Asthmatic Children: A Research Study from Clinical Origin

    Directory of Open Access Journals (Sweden)

    Lene Lochte

    2012-01-01

    Full Text Available Objective. To compare longitudinally PAC of asthmatic children against that of healthy controls during ten months. Methods. Twenty-eight asthmatic children aged 7–15 years and 27 matched controls each performed six submaximal exercise tests on treadmill, which included a test of EIA (exercise-induced asthma. Predicted aerobic capacity (mLO2/min/kg was calculated. Spirometry and development were measured. Physical activity, medication, and “ever asthma/current asthma” were reported by questionnaire. Results. Predicted aerobic capacity of asthmatics was lower than that of controls (P=0.0015 across observation times and for both groups an important increase in predicted aerobic capacity according to time was observed (P<0.001. FEV1 of the asthmatic children was within normal range. The majority (86% of the asthmatics reported pulmonary symptoms to accompany their physical activity. Physical activity (hours per week showed important effects for the variation in predicted aerobic capacity at baseline (F=2.28, P=0.061 and at the T4 observation (F=3.03, P=0.027 and the analyses showed important asthma/control group effects at baseline, month four, and month ten. Physical activity of the asthmatics correlated positively with predicted aerobic capacity. Conclusion. The asthmatic children had consistently low PAC when observed across time. Physical activity was positively associated with PAC in the asthmatics.

  3. Selecting new health technologies for evaluation:Can clinical experts predict which new anticancer drugswill impact Danish health care?

    DEFF Research Database (Denmark)

    Douw, Karla; Vondeling, Hindrik

    2007-01-01

    Several countries have systems in place to support the managed entry of new health technologies. The big challenge for these so-called horizon-scanning systems is to select those technologies that require decision support by means of an early evaluation. Clinical experts are considered a valuable...... source of information on new health technologies, but research on the relevance of their input is scarce. In 2000, we asked six Danish expert oncologists to predict whether a sample of 19 new anticancer drugs would impact Danish health care over the next 5 years. In 2005, we assessed the accuracy...... of these predictions in a delayed type cross-sectional study. The specificity of the Danish experts' prediction was 1 (95% confidence interval 0.74-1.00) and the sensitivity was 0.63 (0.31-0.86). The negative predictive value was 0.79 (0.52-0.92) and the positive predictive value was 1 (0.57-1.00). This indicates...

  4. Clinical value of CT-based preoperative software assisted lung lobe volumetry for predicting postoperative pulmonary function after lung surgery

    Science.gov (United States)

    Wormanns, Dag; Beyer, Florian; Hoffknecht, Petra; Dicken, Volker; Kuhnigk, Jan-Martin; Lange, Tobias; Thomas, Michael; Heindel, Walter

    2005-04-01

    This study was aimed to evaluate a morphology-based approach for prediction of postoperative forced expiratory volume in one second (FEV1) after lung resection from preoperative CT scans. Fifteen Patients with surgically treated (lobectomy or pneumonectomy) bronchogenic carcinoma were enrolled in the study. A preoperative chest CT and pulmonary function tests before and after surgery were performed. CT scans were analyzed by prototype software: automated segmentation and volumetry of lung lobes was performed with minimal user interaction. Determined volumes of different lung lobes were used to predict postoperative FEV1 as percentage of the preoperative values. Predicted FEV1 values were compared to the observed postoperative values as standard of reference. Patients underwent lobectomy in twelve cases (6 upper lobes; 1 middle lobe; 5 lower lobes; 6 right side; 6 left side) and pneumonectomy in three cases. Automated calculation of predicted postoperative lung function was successful in all cases. Predicted FEV1 ranged from 54% to 95% (mean 75% +/- 11%) of the preoperative values. Two cases with obviously erroneous LFT were excluded from analysis. Mean error of predicted FEV1 was 20 +/- 160 ml, indicating absence of systematic error; mean absolute error was 7.4 +/- 3.3% respective 137 +/- 77 ml/s. The 200 ml reproducibility criterion for FEV1 was met in 11 of 13 cases (85%). In conclusion, software-assisted prediction of postoperative lung function yielded a clinically acceptable agreement with the observed postoperative values. This method might add useful information for evaluation of functional operability of patients with lung cancer.

  5. A dynamic model of once-daily 5-aminosalicylic acid predicts clinical efficacy

    Institute of Scientific and Technical Information of China (English)

    Deepak; Parakkal; Eli; D; Ehrenpreis; Matthew; P; Thorpe; Karson; S; Putt; Bruce; Hannon

    2010-01-01

    New once daily mesalamine formulations may improve adherence to medication usage.Response to Asacol and other forms of 5-aminosalicyclic acid(5-ASA)is better correlated with tissue concentrations and best predicted by concentrations of the drug within the lumen of the colon.Our group used computer simulation to predict colonic 5-ASA levels after Asacol administration.In our study,the model simulated Asacol distribution in the healthy colon,and during quiescent and active ulcerative colitis.An Asacol dosage ...

  6. Admission to intensive care can be reliably predicted using only clinical judgment

    DEFF Research Database (Denmark)

    Brabrand, M.

    2015-01-01

    Introduction Not all patients in need of critical care arrive in clinical distress and some deteriorate after arrival. Identifying these patients early in their clinical course could potentially improve outcome. The present study was performed with the aim of assessing whether nursing and physician...... staffwere able to identify patients in need of critical care using only clinical judgment and to compare this with the National Early Warning Score (NEWS). Methods This was a prospective cohort study of all adult patients with a first-time admission to a medical admission unit at a 450-bed regional teaching...... hospital over a 3-month period in 2010. All subspecialties of internal medicine are present as well as a level 2 ICU. Upon first contact with the patient after arrival, nursing staffand physicians were asked to report their estimation of the probability of ICU admission (0 to 100%). Survival status...

  7. Accurate cloud-based smart IMT measurement, its validation and stroke risk stratification in carotid ultrasound: A web-based point-of-care tool for multicenter clinical trial.

    Science.gov (United States)

    Saba, Luca; Banchhor, Sumit K; Suri, Harman S; Londhe, Narendra D; Araki, Tadashi; Ikeda, Nobutaka; Viskovic, Klaudija; Shafique, Shoaib; Laird, John R; Gupta, Ajay; Nicolaides, Andrew; Suri, Jasjit S

    2016-08-01

    . Statistical tests were performed to demonstrate consistency, reliability and accuracy of the results. The proposed AtheroCloud™ system is completely reliable, automated, fast (3-5 seconds depending upon the image size having an internet speed of 180Mbps), accurate, and an intelligent, web-based clinical tool for multi-center clinical trials and routine telemedicine clinical care.

  8. Accurate cloud-based smart IMT measurement, its validation and stroke risk stratification in carotid ultrasound: A web-based point-of-care tool for multicenter clinical trial.

    Science.gov (United States)

    Saba, Luca; Banchhor, Sumit K; Suri, Harman S; Londhe, Narendra D; Araki, Tadashi; Ikeda, Nobutaka; Viskovic, Klaudija; Shafique, Shoaib; Laird, John R; Gupta, Ajay; Nicolaides, Andrew; Suri, Jasjit S

    2016-08-01

    . Statistical tests were performed to demonstrate consistency, reliability and accuracy of the results. The proposed AtheroCloud™ system is completely reliable, automated, fast (3-5 seconds depending upon the image size having an internet speed of 180Mbps), accurate, and an intelligent, web-based clinical tool for multi-center clinical trials and routine telemedicine clinical care. PMID:27318571

  9. Presence of Systemic Inflammatory Response Syndrome Predicts a Poor Clinical Outcome in Dogs with a Primary Hepatitis.

    Science.gov (United States)

    Kilpatrick, Scott; Dreistadt, Margaret; Frowde, Polly; Powell, Roger; Milne, Elspeth; Smith, Sionagh; Morrison, Linda; Gow, Adam G; Handel, Ian; Mellanby, Richard J

    2016-01-01

    Primary hepatopathies are a common cause of morbidity and mortality in dogs. The underlying aetiology of most cases of canine hepatitis is unknown. Consequently, treatments are typically palliative and it is difficult to provide accurate prognostic information to owners. In human hepatology there is accumulating data which indicates that the presence of systemic inflammatory response syndrome (SIRS) is a common and debilitating event in patients with liver diseases. For example, the presence of SIRS has been linked to the development of complications such as hepatic encephalopathy (HE) and is associated with a poor clinical outcome in humans with liver diseases. In contrast, the relationship between SIRS and clinical outcome in dogs with a primary hepatitis is unknown. Seventy dogs with histologically confirmed primary hepatitis were enrolled into the study. Additional clinical and clinicopathological information including respiratory rate, heart rate, temperature, white blood cell count, sodium, potassium, sex, presence of ascites, HE score, alanine aminotransferase (ALT), alkaline phosphatase (ALP), bilirubin and red blood cell concentration were available in all cases. The median survival of dogs with a SIRS score of 0 or 1 (SIRS low) was 231 days compared to a median survival of 7 days for dogs with a SIRS score of 2, 3 or 4 (SIRS high) (pdogs with a primary hepatitis is deserving of further study.

  10. A clinical diagnostic model for predicting influenza among young adult military personnel with febrile respiratory illness in Singapore.

    Directory of Open Access Journals (Sweden)

    Vernon J Lee

    Full Text Available INTRODUCTION: Influenza infections present with wide-ranging clinical features. We aim to compare the differences in presentation between influenza and non-influenza cases among those with febrile respiratory illness (FRI to determine predictors of influenza infection. METHODS: Personnel with FRI (defined as fever ≥ 37.5 °C, with cough or sore throat were recruited from the sentinel surveillance system in the Singapore military. Nasal washes were collected, and tested using the Resplex II and additional PCR assays for etiological determination. Interviewer-administered questionnaires collected information on patient demographics and clinical features. Univariate comparison of the various parameters was conducted, with statistically significant parameters entered into a multivariate logistic regression model. The final multivariate model for influenza versus non-influenza cases was used to build a predictive probability clinical diagnostic model. RESULTS: 821 out of 2858 subjects recruited from 11 May 2009 to 25 Jun 2010 had influenza, of which 434 (52.9% had 2009 influenza A (H1N1, 58 (7.1% seasonal influenza A (H3N2 and 269 (32.8% influenza B. Influenza-positive cases were significantly more likely to present with running nose, chills and rigors, ocular symptoms and higher temperature, and less likely with sore throat, photophobia, injected pharynx, and nausea/vomiting. Our clinical diagnostic model had a sensitivity of 65% (95% CI: 58%, 72%, specificity of 69% (95% CI: 62%, 75%, and overall accuracy of 68% (95% CI: 64%, 71%, performing significantly better than conventional influenza-like illness (ILI criteria. CONCLUSIONS: Use of a clinical diagnostic model may help predict influenza better than the conventional ILI definition among young adults with FRI.

  11. Clinical and biomarker changes in premanifest Huntington disease show trial feasibility: a decade of the PREDICT-HD study

    Directory of Open Access Journals (Sweden)

    Jane S Paulsen

    2014-04-01

    Full Text Available There is growing consensus that intervention and treatment of Huntington disease (HD should occur at the earliest stage possible. Various early-intervention methods for this fatal neurodegenerative disease have been identified, but preventive clinical trials for HD are limited by a lack of knowledge of the natural history of the disease and a dearth of appropriate outcome measures. Objectives of the current study are to document the natural history of premanifest HD progression in the largest cohort ever studied and to develop a battery of imaging and clinical markers of premanifest HD progression that can be used as outcome measures in preventive clinical trials. PREDICT-HD is a 32-site, international, observational study of premanifest HD, with annual examination of 1013 participants with premanifest HD and 301 gene-expansion negative controls between 2001 and 2012. Findings document 39 variables representing imaging, motor, cognitive, functional, and psychiatric domains, showing different rates of decline between premanifest Huntington disease and controls. Required sample size and models of premanifest HD are presented to inform future design of clinical and preclinical research. Preventive clinical trials in premanifest HD with participants who have a medium or high probability of motor onset are calculated to be as resource-effective as those conducted in diagnosed HD and could interrupt disease seven to twelve years earlier. Methods and measures for preventive clinical trials in premanifest HD more than a dozen years from motor onset are also feasible. These findings represent the most thorough documentation of a clinical battery for experimental therapeutics in stages of premanifest HD, the time period for which effective intervention may provide the most positive possible outcome for patients and their families affected by this devastating disease.

  12. Simple blood tests as predictive markers of disease severity and clinical condition in patients with venous insufficiency.

    Science.gov (United States)

    Karahan, Oguz; Yavuz, Celal; Kankilic, Nazim; Demirtas, Sinan; Tezcan, Orhan; Caliskan, Ahmet; Mavitas, Binali

    2016-09-01

    Chronic venous insufficiency (CVI) is a progressive inflammatory disease. Because of its inflammatory nature, several circulating markers were investigated for predicting disease progression. We aimed to investigate simple inflammatory blood markers as predictors of clinical class and disease severity in patients with CVI. Eighty patients with CVI were divided into three groups according to clinical class (grade 1, 2 and 3) and score of disease severity (mild, moderate and severe). The basic inflammatory blood markers [neutrophil, lymphocyte, mean platelet volume (MPV), white blood cell (WBC), platelet, albumin, D-dimer, fibrinogen, fibrinogen to albumin ratio, and neutrophil to lymphocyte ratio] were investigated in each group. Serum neutrophil, lymphocyte, MPV, platelet count, D-dimer and neutrophil to lymphocyte ratio levels were similar among the groups (P > 0.05). Although the serum WBC levels were significant in the clinical severity groups (P < 0.05), it was useless to separate each severity class. However, albumin, fibrinogen and the fibrinogen to albumin ratio were significant predictors of clinical class and disease severity. Especially, the fibrinogen to albumin ratio was detected as an independent indicator for a clinical class and disease severity with high sensitivity and specificity (75% sensitivity and 87.5% specificity for clinical class and 90% sensitivity and 88.3% specificity for disease severity). Serum fibrinogen and albumin levels can be useful parameters to determine clinical class and disease severity in patients with CVI. Moreover, the fibrinogen to albumin ratio is a more sensitive and specific predictor of the progression of CVI. PMID:26650463

  13. CRITICAL REVIEW OF PROSTATE CANCER PREDICTIVE TOOLS

    OpenAIRE

    Shahrokh F. Shariat; Michael W Kattan; Vickers, Andrew J; Karakiewicz, Pierre I; Scardino, Peter T.

    2009-01-01

    Prostate cancer is a very complex disease, and the decision-making process requires the clinician to balance clinical benefits, life expectancy, comorbidities, and potential treatment related side effects. Accurate prediction of clinical outcomes may help in the difficult process of making decisions related to prostate cancer. In this review, we discuss attributes of predictive tools and systematically review those available for prostate cancer. Types of tools include probability formulas, lo...

  14. Predictive factors for familiality in a Danish clinical cohort of children with Tourette syndrome

    DEFF Research Database (Denmark)

    Debes, Nanette M M M; Hjalgrim, Helle; Skov, Liselotte

    2010-01-01

    ). The fact that TS aggregates strongly in families suggests that family members share either genetic and/or environmental risk factors contributing to TS. Numerous studies have been performed to examine the familiality in TS, but clear-cut factors to predict hereditability in TS have not been found yet. We...

  15. CONFIRMATION OF CLINICAL-DIAGNOSIS IN REQUESTS FOR PRENATAL PREDICTION OF SMA TYPE-I

    NARCIS (Netherlands)

    COBBEN, JM; DEVISSER, M; SCHEFFER, H; OSINGA, J; VANDERSTEEGE, G; BUYS, CHCM; VANOMMEN, GJ; TENKATE, LP

    1993-01-01

    The recent discovery of a major SMA-locus in the chromosomal region 5q makes it possible to carry out prenatal DNA studies in families in which a child with SMA type I has been born. Since direct mutation analysis is not yet possible, the reliability of prenatal prediction of SMA type I usually depe

  16. Do medical students’ scores using different assessment instruments predict their scores in clinical reasoning using a computer-based simulation?

    Directory of Open Access Journals (Sweden)

    Fida M

    2015-02-01

    Full Text Available Mariam Fida,1 Salah Eldin Kassab2 1Department of Molecular Medicine, College of Medicine and Medical Sciences, Arabian Gulf University, Manama, Bahrain; 2Department of Medical Education, Faculty of Medicine, Suez Canal University, Ismailia, Egypt Purpose: The development of clinical problem-solving skills evolves over time and requires structured training and background knowledge. Computer-based case simulations (CCS have been used for teaching and assessment of clinical reasoning skills. However, previous studies examining the psychometric properties of CCS as an assessment tool have been controversial. Furthermore, studies reporting the integration of CCS into problem-based medical curricula have been limited. Methods: This study examined the psychometric properties of using CCS software (DxR Clinician for assessment of medical students (n=130 studying in a problem-based, integrated multisystem module (Unit IX during the academic year 2011–2012. Internal consistency reliability of CCS scores was calculated using Cronbach's alpha statistics. The relationships between students' scores in CCS components (clinical reasoning, diagnostic performance, and patient management and their scores in other examination tools at the end of the unit including multiple-choice questions, short-answer questions, objective structured clinical examination (OSCE, and real patient encounters were analyzed using stepwise hierarchical linear regression. Results: Internal consistency reliability of CCS scores was high (α=0.862. Inter-item correlations between students' scores in different CCS components and their scores in CCS and other test items were statistically significant. Regression analysis indicated that OSCE scores predicted 32.7% and 35.1% of the variance in clinical reasoning and patient management scores, respectively (P<0.01. Multiple-choice question scores, however, predicted only 15.4% of the variance in diagnostic performance scores (P<0.01, while

  17. Factors Predicting Oncology Care Providers' Behavioral Intention to Adopt Clinical Decision Support Systems

    Science.gov (United States)

    Wolfenden, Andrew

    2012-01-01

    The purpose of this quantitative correlation study was to examine the predictors of user behavioral intention on the decision of oncology care providers to adopt or reject the clinical decision support system. The Unified Theory of Acceptance and Use of Technology (UTAUT) formed the foundation of the research model and survey instrument. The…

  18. Cultural Responsivity in Clinical Psychology Graduate Students: A Developmental Approach to the Prediction of Learning

    Science.gov (United States)

    Berrin, Sebastian Everett

    2010-01-01

    This study used a mixed-method approach to examine students' experiences in multicultural training and their opinions about various aspects of their course(s). A developmental model of learning was employed to analyze results. More specifically, this study explored the relationship between clinical psychology doctoral students' self-reported…

  19. Undergraduate Nurse Variables that Predict Academic Achievement and Clinical Competence in Nursing

    Science.gov (United States)

    Blackman, Ian; Hall, Margaret; Darmawan, I Gusti Ngurah.

    2007-01-01

    A hypothetical model was formulated to explore factors that influenced academic and clinical achievement for undergraduate nursing students. Sixteen latent variables were considered including the students' background, gender, type of first language, age, their previous successes with their undergraduate nursing studies and status given for…

  20. Evaluation of Stream Mining Classifiers for Real-Time Clinical Decision Support System: A Case Study of Blood Glucose Prediction in Diabetes Therapy

    Directory of Open Access Journals (Sweden)

    Simon Fong

    2013-01-01

    Full Text Available Earlier on, a conceptual design on the real-time clinical decision support system (rt-CDSS with data stream mining was proposed and published. The new system is introduced that can analyze medical data streams and can make real-time prediction. This system is based on a stream mining algorithm called VFDT. The VFDT is extended with the capability of using pointers to allow the decision tree to remember the mapping relationship between leaf nodes and the history records. In this paper, which is a sequel to the rt-CDSS design, several popular machine learning algorithms are investigated for their suitability to be a candidate in the implementation of classifier at the rt-CDSS. A classifier essentially needs to accurately map the events inputted to the system into one of the several predefined classes of assessments, such that the rt-CDSS can follow up with the prescribed remedies being recommended to the clinicians. For a real-time system like rt-CDSS, the major technological challenges lie in the capability of the classifier to process, analyze and classify the dynamic input data, quickly and upmost reliably. An experimental comparison is conducted. This paper contributes to the insight of choosing and embedding a stream mining classifier into rt-CDSS with a case study of diabetes therapy.

  1. The accuracy of a clinical parameters-based scoring system to predict spontaneous intracranial hemorrhage in children under one year old

    Directory of Open Access Journals (Sweden)

    Harris Alfan

    2015-05-01

    Full Text Available Background Previous studies show that most children aged less than 1 year had intracranial hemorrhage without any history of trauma. The sign and symptoms of spontaneous intracranial hemorrhage (SIH in children varies. To minimize morbidity and mortality, early detection and accurate diagnosis are required. Head CT scans area widely used for diagnosing SIH. Unfortunately, not all health facilities in Indonesia have CT scans. Objective To determine the accuracy of a clinical parameters-based scoring system in predicting spontaneous intracranial hemorrhage (SIH in children under one year old. Methods This diagnostic study included children aged under one year who were admitted to Mohammad Hoesin Hospital, Palembang. Patients who showed any signs of increased intracranial pressure were recruited. Data were collected from medical records from January 2007 to September 2013. Through the use of logistic regression analysis, clinical parameters showing significant relationships with computerized tomography (CT-scan confirmed SIH were selected as predictors. Each predictor was given a score based on an adjusted ratio. The cut-off point of the total scores from all patients was determined using a receiver operating curve (ROC analysis. The accuracy of the total scores was calculated using a 2x2 validity test. Results Of the 186 children included in this study, 98 (52.7% had SIH and 93 (94.8% were under 3 month-old. The predictors for SIH used included age (>3 months: score 0; 1-3 months: score 3, gender (female: score 0; male: score 1, pallor (no: score 0; yes: score 1, bulging fontanel (no: score 0; yes: score 1, pupil (isocoria: score 0; anisocoria: score 2 and history of shaken baby (no: score 0; yes: score 3. The ROC analysis showed that the area under the curve (AUC was 95.3% with a cut-off point of 4.5, had a sensitivity of 88.7% and a specificity of 93.1% Conclusion This scoring system based on clinical parameters hadgood accuracy for predicting

  2. Presence of Systemic Inflammatory Response Syndrome Predicts a Poor Clinical Outcome in Dogs with a Primary Hepatitis.

    Directory of Open Access Journals (Sweden)

    Scott Kilpatrick

    Full Text Available Primary hepatopathies are a common cause of morbidity and mortality in dogs. The underlying aetiology of most cases of canine hepatitis is unknown. Consequently, treatments are typically palliative and it is difficult to provide accurate prognostic information to owners. In human hepatology there is accumulating data which indicates that the presence of systemic inflammatory response syndrome (SIRS is a common and debilitating event in patients with liver diseases. For example, the presence of SIRS has been linked to the development of complications such as hepatic encephalopathy (HE and is associated with a poor clinical outcome in humans with liver diseases. In contrast, the relationship between SIRS and clinical outcome in dogs with a primary hepatitis is unknown. Seventy dogs with histologically confirmed primary hepatitis were enrolled into the study. Additional clinical and clinicopathological information including respiratory rate, heart rate, temperature, white blood cell count, sodium, potassium, sex, presence of ascites, HE score, alanine aminotransferase (ALT, alkaline phosphatase (ALP, bilirubin and red blood cell concentration were available in all cases. The median survival of dogs with a SIRS score of 0 or 1 (SIRS low was 231 days compared to a median survival of 7 days for dogs with a SIRS score of 2, 3 or 4 (SIRS high (p<0.001. A Cox proportional hazard model, which included all other co-variables, revealed that a SIRS high score was an independent predictor of a poor clinical outcome. The effect of modulating inflammation on treatment outcomes in dogs with a primary hepatitis is deserving of further study.

  3. Accuracy of clinical prediction rules in peptic ulcer perforation: an observational study

    DEFF Research Database (Denmark)

    Buck, David Levarett; Vester-Andersen, Morten; Møller, Morten Hylander

    2012-01-01

    (APACHE) II score, and the sepsis score. Material and methods. Design: an observational multicenter study. Participants and settings: a total of 117 patients surgically treated for PPU between 1 January 2008 and 31 December 2009 in seven gastrointestinal departments in Denmark were included. Pregnant......% of the patients had at least one co-existing disease. The 30-day mortality proportion was 17% (20/117). The AUCs: the Boey score, 0.63; the sepsis score, 0.69; the ASA score, 0.73; and the APACHE II score, 0.76. Overall, the PPVs of all four prediction rules were low and the NPVs high. Conclusions. The Boey score......, the ASA score, the APACHE II score, and the sepsis score predict mortality poorly in patients with PPU....

  4. Effect of differences in saturation sensitivity of phospholipid stains on clinical predictivity of L/S ratios.

    Science.gov (United States)

    Spillman, T; Cotton, D B; Gonik, B

    1985-10-31

    Owing to the importance of the degree of fatty acid side chain saturation in the ability of lecithin molecules to function as surfactant, we assessed the clinical effectiveness of analytical methods which differ with respect to methodologic influences by saturated and unsaturated phospholipids. The lecithin/sphingomyelin ratios, determined with either cupric acetate or phosphomolybdate as the detection reagent, are compared for their abilities to predict respiratory distress syndrome (RDS), transient tachypnea (TTN), or the absence of respiratory difficulty in neonates. A group of 47 amniotic fluids were analyzed from 25 non-problem cases, 13 cases of TTN and 9 cases of RDS. Receiver operating characteristic analysis shows that in our sample population, the measurement of total lecithin for the prediction of neonatal respiratory distress failed to demonstrate an advantage over the measurement of unsaturated lecithin alone. PMID:2414041

  5. Predicted Aerobic Capacity of Asthmatic Children: A Research Study from Clinical Origin

    OpenAIRE

    Lene Lochte

    2012-01-01

    Objective. To compare longitudinally PAC of asthmatic children against that of healthy controls during ten months. Methods. Twenty-eight asthmatic children aged 7–15 years and 27 matched controls each performed six submaximal exercise tests on treadmill, which included a test of EIA (exercise-induced asthma). Predicted aerobic capacity (mLO2/min/kg) was calculated. Spirometry and development were measured. Physical activity, medication, and “ever asthma/current asthma” were reported by questi...

  6. Prediction of clinical outcome in glioblastoma using a biologically relevant nine-microRNA signature

    OpenAIRE

    Hayes, J.; Thygesen, H., Helene; Tumilson, C; Droop, A; Boissinot, M; Hughes, TA; Westhead, D; Alder, JE; Shaw, L; Short, SC; Lawler, SE

    2015-01-01

    Background: Glioblastoma is the most aggressive primary brain tumor, and is associated with a very poor prognosis. In this study we investigated the potential of microRNA expression profiles to predict survival in this challenging disease. Methods: MicroRNA and mRNA expression data from glioblastoma (n=475) and grade II and III glioma (n=178) were accessed from The Cancer Genome Atlas. LASSO regression models were used to identify a prognostic microRNA signature. Functionally relevant targets...

  7. Pediatric in-Hospital Death from Infectious Disease in Uganda: Derivation of Clinical Prediction Models

    OpenAIRE

    Nasim Lowlaavar; Larson, Charles P.; Elias Kumbakumba; Guohai Zhou; J. Mark Ansermino; Joel Singer; Niranjan Kissoon; Hubert Wong; Andrew Ndamira; Jerome Kabakyenga; Julius Kiwanuka; Matthew O Wiens

    2016-01-01

    Background Pediatric hospital mortality from infectious diseases in resource constrained countries remains unacceptably high. Improved methods of risk-stratification can assist in referral decision making and resource allocation. The purpose of this study was to create prediction models for in-hospital mortality among children admitted with suspected infectious diseases. Methods This two-site prospective observational study enrolled children between 6 months and 5 years admitted with a proven...

  8. Validation of a novel clinical prediction score for severe coronary artery diseases before elective coronary angiography.

    Directory of Open Access Journals (Sweden)

    Zhang-Wei Chen

    Full Text Available OBJECTIVES: Coronary artery disease (CAD severity is associated with patient prognosis. However, few efficient scoring systems have been developed to screen severe CAD in patients with stable angina and suspected CAD before coronary angiography. Here, we present a novel scoring system for CAD severity before elective coronary angiography. METHODS: Five hundred fifty-one patients with stable angina who were admitted for coronary angiography were enrolled in this study. Patients were divided into training (n = 347 and validation (n = 204 cohorts. Severe CAD was defined as having a Gensini score of 20 or more. All patients underwent echocardiography (ECG to detect ejection fraction and aortic valve calcification (AVC. Multivariable analysis was applied to determine independent risk factors and develop the scoring system. RESULTS: In the training cohort, age, male sex, AVC, abnormal ECG, diabetes, hyperlipidemia, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol were identified as independent factors for severe CAD by multivariable analysis, and the Severe Prediction Scoring (SPS system was developed. C-indices of receiver operating characteristic (ROC curves for severe CAD were 0.744 and 0.710 in the training and validation groups, respectively. The SPS system also performed well during calibration, as demonstrated by Hosmer-Lemeshow analysis in the validation group. Compared with the Diamond-Forrester score, the SPS system performed better for severe CAD prediction before elective coronary angiography. CONCLUSIONS: Severe CAD prediction was achieved by analyzing age, sex, AVC, ECG, diabetes status, and lipid levels. Angina patients who achieve high scores using this predicting system should undergo early coronary angiography.

  9. Graph-based clinical diagnosis and prediction using multi-modal neuroimaging data

    OpenAIRE

    Klein, Arno; Ghosh, Satrajit

    2016-01-01

    The proposed research develops new computational tools to identify, diagnose, and predict treatment outcome for different mental illnesses. The research will be applied first to major depressive disorder, which affects millions of Americans, but is intended to be applied to any mental illness, such as Alzheimer’s disease, bipolar disorder, schizophrenia – indeed to analyze differences in brain structure, activity, or connectivity between any two populations.

  10. Matrix Metalloproteinase-9/Neutrophil Gelatinase-Associated Lipocalin Complex Activity in Human Glioma Samples Predicts Tumor Presence and Clinical Prognosis

    Directory of Open Access Journals (Sweden)

    Ming-Fa Liu

    2015-01-01

    Full Text Available Matrix metalloproteinase-9/neutrophil gelatinase-associated lipocalin (MMP-9/NGAL complex activity is elevated in brain tumors and may serve as a molecular marker for brain tumors. However, the relationship between MMP-9/NGAL activity in brain tumors and patient prognosis and treatment response remains unclear. Here, we compared the clinical characteristics of glioma patients with the MMP-9/NGAL activity measured in their respective tumor and urine samples. Using gelatin zymography assays, we found that MMP-9/NGAL activity was significantly increased in tumor tissues (TT and preoperative urine samples (Preop-1d urine. Activity was reduced by seven days after surgery (Postop-1w urine and elevated again in cases of tumor recurrence. The MMP-9/NGAL status correlated well with MRI-based tumor assessments. These findings suggest that MMP-9/NGAL activity could be a novel marker to detect gliomas and predict the clinical outcome of patients.

  11. Prediction of new drug indications based on clinical data and network modularity

    Science.gov (United States)

    Yu, Liang; Ma, Xiaoke; Zhang, Long; Zhang, Jing; Gao, Lin

    2016-01-01

    Drug repositioning is commonly done within the drug discovery process in order to adjust or expand the application line of an active molecule. Previous computational methods in this domain mainly focused on shared genes or correlations between genes to construct new drug-disease associations. We propose a method that can not only handle drugs or diseases with or without related genes but consider the network modularity. Our method firstly constructs a drug network and a disease network based on side effects and symptoms respectively. Because similar drugs imply similar diseases, we then cluster the two networks to identify drug and disease modules, and connect all possible drug-disease module pairs. Further, based on known drug-disease associations in CTD and using local connectivity of modules, we predict potential drug-disease associations. Our predictions are validated by testing their overlaps with drug indications reported in published literatures and CTD, and KEGG enrichment analysis are also made on their related genes. The experimental results demonstrate that our approach can complement the current computational approaches and its predictions can provide new clues for the candidate discovery of drug repositioning. PMID:27678071

  12. Prediction of Dengue Disease Severity among Pediatric Thai Patients Using Early Clinical Laboratory Indicators

    OpenAIRE

    James A Potts; Gibbons, Robert V.; Rothman, Alan L.; Anon Srikiatkhachorn; Thomas, Stephen J.; Pra-On Supradish; Lemon, Stephenie C.; Libraty, Daniel H.; Sharone Green; Siripen Kalayanarooj

    2010-01-01

    Background Dengue virus is endemic in tropical and sub-tropical resource-poor countries. Dengue illness can range from a nonspecific febrile illness to a severe disease, Dengue Shock Syndrome (DSS), in which patients develop circulatory failure. Earlier diagnosis of severe dengue illnesses would have a substantial impact on the allocation of health resources in endemic countries. Methods and Findings We compared clinical laboratory findings collected within 72 hours of fever onset from a pros...

  13. Mexiletine Therapy for Chronic Pain: Survival Analysis Identifies Factors Predicting Clinical Success

    OpenAIRE

    Carroll, Ian R; Kaplan, Kimberly M.; Mackey, Sean C.

    2008-01-01

    Mexiletine, a sodium channel blocker, treats neuropathic pain but its clinical value has been questioned due to its significant side effects and limited efficacy. We hypothesized that ongoing therapy with mexiletine would have limited patient acceptance, but that an analgesic response to intravenous (IV) lidocaine (a pharmacologically similar drug) would identify patients most likely to choose ongoing therapy with mexiletine. We identified a cohort of 37 patients with neuropathic pain who und...

  14. Clinical Prediction and Diagnosis of Neurosyphilis in HIV-Infected Patients with Early Syphilis

    OpenAIRE

    Dumaresq, Jeannot; Langevin, Stéphanie; Gagnon, Simon; Serhir, Bouchra; Deligne, Benoît; Tremblay, Cécile; Tsang, Raymond S.W.; Fortin, Claude; Coutlée, François; Roger, Michel

    2013-01-01

    The diagnosis of neurosyphilis (NS) is a challenge, especially in HIV-infected patients, and the criteria for deciding when to perform a lumbar puncture (LP) in HIV-infected patients with syphilis are controversial. We retrospectively reviewed demographic, clinical, and laboratory data from 122 cases of HIV-infected patients with documented early syphilis who underwent an LP to rule out NS, and we evaluated 3 laboratory-developed validated real-time PCR assays, the Treponema pallidum particle...

  15. Do clinical foot and ankle assessments improve the prediction of patient reported outcomes in knee arthroplasty?

    OpenAIRE

    Gates, Lucy

    2015-01-01

    Knee arthroplasty (KA) has been considered to be a successful and cost-effective intervention for individuals with severe end stage Osteoarthritis (OA). A number of clinically important predictors of outcomes following KA have been established, however there are still other factors to be identified to improve our ability to recognise patients at risk of poor KA outcomes. Although the relationship between foot, ankle and knee kinematics has become widely accepted, it is not known whether foot ...

  16. Clinical trial designs for evaluating the medical utility of prognostic and predictive biomarkers in oncology

    OpenAIRE

    Simon, Richard

    2010-01-01

    Physicians need improved tools for selecting treatments for individual patients. Many diagnostic entities hat were traditionally viewed as individual diseases are heterogeneous in their molecular pathogenesis and treatment responsiveness. This results in the treatment of many patients with ineffective drugs, incursion of substantial medical costs for the treatment of patients who do not benefit and the conducting of large clinical trials to identify small, average treatment benefits for heter...

  17. Endomysial antibodies predict celiac disease irrespective of the titers or clinical presentation

    Institute of Scientific and Technical Information of China (English)

    Kalle Kurppa; Markku M(a)ki; Katri Kaukinen; Tiia R(a)s(a)nen; Pekka Collin; Sari Iltanen; Heini Huhtala; Merja Ashorn; P(a)ivi Saavalainen; Katri Haimila; Jukka Partanen

    2012-01-01

    AIM:To investigate the association between serum antibody levels and a subsequent celiac disease diagnosis in a large series of children and adults.METHODS:Besides subjects with classical gastrointestinal presentation of celiac disease,the study cohort included a substantial number of individuals with extraintestinal symptoms and those found by screening in at-risk groups.Altogether 405 patients underwent clinical,serological and histological evaluations.After collection of data,the antibody values were further graded as low [endomysial (EmA) 1:5-200,transglutaminase 2 antibodies (TG2-ab) 5.0-30.0 U/L] and high (EmA 1:≥ 500,TG2-ab ≥ 30.0 U/L),and the serological results were compared with the small intestinal mucosal histology and clinical presentation.RESULTS:In total,79% of the subjects with low and 94% of those with high serum EmA titers showed small-bowel mucosal villous atrophy.Furthermore,96% of the 47 EmA positive subjects who had normal mucosal villi and remained on follow-up either subsequently developed mucosal atrophy while on a glutencontaining diet,or responded positively to a glutenfree diet.CONCLUSION:Irrespective of the initial serum titers or clinical presentation,EmA positivity as such is a very strong predictor of a subsequent celiac disease diagnosis.

  18. Three-tiered risk stratification model to predict progression in Barrett's esophagus using epigenetic and clinical features.

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    Fumiaki Sato

    Full Text Available Barrett's esophagus predisposes to esophageal adenocarcinoma. However, the value of endoscopic surveillance in Barrett's esophagus has been debated because of the low incidence of esophageal adenocarcinoma in Barrett's esophagus. Moreover, high inter-observer and sampling-dependent variation in the histologic staging of dysplasia make clinical risk assessment problematic. In this study, we developed a 3-tiered risk stratification strategy, based on systematically selected epigenetic and clinical parameters, to improve Barrett's esophagus surveillance efficiency.We defined high-grade dysplasia as endpoint of progression, and Barrett's esophagus progressor patients as Barrett's esophagus patients with either no dysplasia or low-grade dysplasia who later developed high-grade dysplasia or esophageal adenocarcinoma. We analyzed 4 epigenetic and 3 clinical parameters in 118 Barrett's esophagus tissues obtained from 35 progressor and 27 non-progressor Barrett's esophagus patients from Baltimore Veterans Affairs Maryland Health Care Systems and Mayo Clinic. Based on 2-year and 4-year prediction models using linear discriminant analysis (area under the receiver-operator characteristic (ROC curve: 0.8386 and 0.7910, respectively, Barrett's esophagus specimens were stratified into high-risk (HR, intermediate-risk (IR, or low-risk (LR groups. This 3-tiered stratification method retained both the high specificity of the 2-year model and the high sensitivity of the 4-year model. Progression-free survivals differed significantly among the 3 risk groups, with p = 0.0022 (HR vs. IR and p<0.0001 (HR or IR vs. LR. Incremental value analyses demonstrated that the number of methylated genes contributed most influentially to prediction accuracy.This 3-tiered risk stratification strategy has the potential to exert a profound impact on Barrett's esophagus surveillance accuracy and efficiency.

  19. A novel model to combine clinical and pathway-based transcriptomic information for the prognosis prediction of breast cancer.

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    Sijia Huang

    2014-09-01

    Full Text Available Breast cancer is the most common malignancy in women worldwide. With the increasing awareness of heterogeneity in breast cancers, better prediction of breast cancer prognosis is much needed for more personalized treatment and disease management. Towards this goal, we have developed a novel computational model for breast cancer prognosis by combining the Pathway Deregulation Score (PDS based pathifier algorithm, Cox regression and L1-LASSO penalization method. We trained the model on a set of 236 patients with gene expression data and clinical information, and validated the performance on three diversified testing data sets of 606 patients. To evaluate the performance of the model, we conducted survival analysis of the dichotomized groups, and compared the areas under the curve based on the binary classification. The resulting prognosis genomic model is composed of fifteen pathways (e.g., P53 pathway that had previously reported cancer relevance, and it successfully differentiated relapse in the training set (log rank p-value = 6.25e-12 and three testing data sets (log rank p-value < 0.0005. Moreover, the pathway-based genomic models consistently performed better than gene-based models on all four data sets. We also find strong evidence that combining genomic information with clinical information improved the p-values of prognosis prediction by at least three orders of magnitude in comparison to using either genomic or clinical information alone. In summary, we propose a novel prognosis model that harnesses the pathway-based dysregulation as well as valuable clinical information. The selected pathways in our prognosis model are promising targets for therapeutic intervention.

  20. Applying psychological theories to evidence-based clinical practice: Identifying factors predictive of managing upper respiratory tract infections without antibiotics

    Directory of Open Access Journals (Sweden)

    Glidewell Elizabeth

    2007-08-01

    Full Text Available Abstract Background Psychological models can be used to understand and predict behaviour in a wide range of settings. However, they have not been consistently applied to health professional behaviours, and the contribution of differing theories is not clear. The aim of this study was to explore the usefulness of a range of psychological theories to predict health professional behaviour relating to management of upper respiratory tract infections (URTIs without antibiotics. Methods Psychological measures were collected by postal questionnaire survey from a random sample of general practitioners (GPs in Scotland. The outcome measures were clinical behaviour (using antibiotic prescription rates as a proxy indicator, behavioural simulation (scenario-based decisions to managing URTI with or without antibiotics and behavioural intention (general intention to managing URTI without antibiotics. Explanatory variables were the constructs within the following theories: Theory of Planned Behaviour (TPB, Social Cognitive Theory (SCT, Common Sense Self-Regulation Model (CS-SRM, Operant Learning Theory (OLT, Implementation Intention (II, Stage Model (SM, and knowledge (a non-theoretical construct. For each outcome measure, multiple regression analysis was used to examine the predictive value of each theoretical model individually. Following this 'theory level' analysis, a 'cross theory' analysis was conducted to investigate the combined predictive value of all significant individual constructs across theories. Results All theories were tested, but only significant results are presented. When predicting behaviour, at the theory level, OLT explained 6% of the variance and, in a cross theory analysis, OLT 'evidence of habitual behaviour' also explained 6%. When predicting behavioural simulation, at the theory level, the proportion of variance explained was: TPB, 31%; SCT, 26%; II, 6%; OLT, 24%. GPs who reported having already decided to change their management to

  1. Applying psychological theories to evidence-based clinical practice: identifying factors predictive of placing preventive fissure sealants

    Directory of Open Access Journals (Sweden)

    Maclennan Graeme

    2010-04-01

    Full Text Available Abstract Background Psychological models are used to understand and predict behaviour in a wide range of settings, but have not been consistently applied to health professional behaviours, and the contribution of differing theories is not clear. This study explored the usefulness of a range of models to predict an evidence-based behaviour -- the placing of fissure sealants. Methods Measures were collected by postal questionnaire from a random sample of general dental practitioners (GDPs in Scotland. Outcomes were behavioural simulation (scenario decision-making, and behavioural intention. Predictor variables were from the Theory of Planned Behaviour (TPB, Social Cognitive Theory (SCT, Common Sense Self-regulation Model (CS-SRM, Operant Learning Theory (OLT, Implementation Intention (II, Stage Model, and knowledge (a non-theoretical construct. Multiple regression analysis was used to examine the predictive value of each theoretical model individually. Significant constructs from all theories were then entered into a 'cross theory' stepwise regression analysis to investigate their combined predictive value Results Behavioural simulation - theory level variance explained was: TPB 31%; SCT 29%; II 7%; OLT 30%. Neither CS-SRM nor stage explained significant variance. In the cross theory analysis, habit (OLT, timeline acute (CS-SRM, and outcome expectancy (SCT entered the equation, together explaining 38% of the variance. Behavioural intention - theory level variance explained was: TPB 30%; SCT 24%; OLT 58%, CS-SRM 27%. GDPs in the action stage had significantly higher intention to place fissure sealants. In the cross theory analysis, habit (OLT and attitude (TPB entered the equation, together explaining 68% of the variance in intention. Summary The study provides evidence that psychological models can be useful in understanding and predicting clinical behaviour. Taking a theory-based approach enables the creation of a replicable methodology for

  2. The impact of p53 in predicting clinical outcome of breast cancer patients with visceral metastasis

    OpenAIRE

    Yang, P.; C. W. Du; Kwan, M.; Liang, S. X.; G. J. Zhang

    2013-01-01

    In the study, we analyzed role of p53 in predicting outcome in visceral metastasis breast cancer (VMBC) patients. 97 consecutive VMBC patients were studied. P53 positivity rate was 29.9%. In the p53-negative group, median disease free survival (DFS), and time from primary breast cancer diagnosis to death (OS1), time from metastases to death (OS2) were 25, 42.5, and 13.5 months, respectively. I