Profiling persistent tubercule bacilli from patient sputa during therapy predicts early drug efficacy.

Science.gov (United States)

Honeyborne, Isobella; McHugh, Timothy D; Kuittinen, Iitu; Cichonska, Anna; Evangelopoulos, Dimitrios; Ronacher, Katharina; van Helden, Paul D; Gillespie, Stephen H; Fernandez-Reyes, Delmiro; Walzl, Gerhard; Rousu, Juho; Butcher, Philip D; Waddell, Simon J

2016-04-07

New treatment options are needed to maintain and improve therapy for tuberculosis, which caused the death of 1.5 million people in 2013 despite potential for an 86 % treatment success rate. A greater understanding of Mycobacterium tuberculosis (M.tb) bacilli that persist through drug therapy will aid drug development programs. Predictive biomarkers for treatment efficacy are also a research priority. Genome-wide transcriptional profiling was used to map the mRNA signatures of M.tb from the sputa of 15 patients before and 3, 7 and 14 days after the start of standard regimen drug treatment. The mRNA profiles of bacilli through the first 2 weeks of therapy reflected drug activity at 3 days with transcriptional signatures at days 7 and 14 consistent with reduced M.tb metabolic activity similar to the profile of pre-chemotherapy bacilli. These results suggest that a pre-existing drug-tolerant M.tb population dominates sputum before and after early drug treatment, and that the mRNA signature at day 3 marks the killing of a drug-sensitive sub-population of bacilli. Modelling patient indices of disease severity with bacterial gene expression patterns demonstrated that both microbiological and clinical parameters were reflected in the divergent M.tb responses and provided evidence that factors such as bacterial load and disease pathology influence the host-pathogen interplay and the phenotypic state of bacilli. Transcriptional signatures were also defined that predicted measures of early treatment success (rate of decline in bacterial load over 3 days, TB test positivity at 2 months, and bacterial load at 2 months). This study defines the transcriptional signature of M.tb bacilli that have been expectorated in sputum after two weeks of drug therapy, characterizing the phenotypic state of bacilli that persist through treatment. We demonstrate that variability in clinical manifestations of disease are detectable in bacterial sputa signatures, and that the changing M.tb m

Gaussian interaction profile kernels for predicting drug-target interaction.

Science.gov (United States)

van Laarhoven, Twan; Nabuurs, Sander B; Marchiori, Elena

2011-11-01

The in silico prediction of potential interactions between drugs and target proteins is of core importance for the identification of new drugs or novel targets for existing drugs. However, only a tiny portion of all drug-target pairs in current datasets are experimentally validated interactions. This motivates the need for developing computational methods that predict true interaction pairs with high accuracy. We show that a simple machine learning method that uses the drug-target network as the only source of information is capable of predicting true interaction pairs with high accuracy. Specifically, we introduce interaction profiles of drugs (and of targets) in a network, which are binary vectors specifying the presence or absence of interaction with every target (drug) in that network. We define a kernel on these profiles, called the Gaussian Interaction Profile (GIP) kernel, and use a simple classifier, (kernel) Regularized Least Squares (RLS), for prediction drug-target interactions. We test comparatively the effectiveness of RLS with the GIP kernel on four drug-target interaction networks used in previous studies. The proposed algorithm achieves area under the precision-recall curve (AUPR) up to 92.7, significantly improving over results of state-of-the-art methods. Moreover, we show that using also kernels based on chemical and genomic information further increases accuracy, with a neat improvement on small datasets. These results substantiate the relevance of the network topology (in the form of interaction profiles) as source of information for predicting drug-target interactions. Software and Supplementary Material are available at http://cs.ru.nl/~tvanlaarhoven/drugtarget2011/. tvanlaarhoven@cs.ru.nl; elenam@cs.ru.nl. Supplementary data are available at Bioinformatics online.

Comparison of predicted and measured pulsed-column profiles and inventories

International Nuclear Information System (INIS)

Ostenak, C.A.; Cermak, A.F.

1983-01-01

Nuclear materials accounting and process control in fuels reprocessing plants can be improved by near-real-time estimation of the in-process inventory in solvent-extraction contactors. Experimental studies were conducted on pilot- and plant-scale pulsed columns by Allied-General Nuclear Service (AGNS), and the extensive uranium concentration-profile and inventory data were analyzed by Los Alamos and AGNS to develop and evaluate different predictive inventory techniques. Preliminary comparisons of predicted and measured pulsed-column profiles and inventories show promise for using these predictive techniques to improve nuclear materials accounting and process control in fuels reprocessing plants

Comparison of Cluster Lensing Profiles with Lambda CDM Predictions

Energy Technology Data Exchange (ETDEWEB)

Broadhurst, Tom; /Tel Aviv U.; Umetsu, Keiichi; /Taipei, Inst. Astron. Astrophys.; Medezinski, Elinor; /Tel Aviv U.; Oguri, Masamune; /KIPAC, Menlo Park; Rephaeli, Yoel; /Tel Aviv U. /San Diego, CASS

2008-05-21

We derive lens distortion and magnification profiles of four well known clusters observed with Subaru. Each cluster is very well fitted by the general form predicted for Cold Dark Matter (CDM) dominated halos, with good consistency found between the independent distortion and magnification measurements. The inferred level of mass concentration is surprisingly high, 8 < c{sub vir} < 15 ( = 10.39 {+-} 0.91), compared to the relatively shallow profiles predicted by the {Lambda}CDM model, c{sub vir} = 5.06 {+-} 1.10 (for = 1.25 x 10{sup 15} M{sub {circle_dot}}/h). This represents a 4{sigma} discrepancy, and includes the relatively modest effects of projection bias and profile evolution derived from N-body simulations, which oppose each other with little residual effect. In the context of CDM based cosmologies, this discrepancy implies some modification of the widely assumed spectrum of initial density perturbations, so clusters collapse earlier (z {ge} 1) than predicted (z < 0.5) when the Universe was correspondingly denser.

Expression profiling to predict the clinical behaviour of ovarian cancer fails independent evaluation

International Nuclear Information System (INIS)

Gevaert, Olivier; De Smet, Frank; Van Gorp, Toon; Pochet, Nathalie; Engelen, Kristof; Amant, Frederic; De Moor, Bart; Timmerman, Dirk; Vergote, Ignace

2008-01-01

In a previously published pilot study we explored the performance of microarrays in predicting clinical behaviour of ovarian tumours. For this purpose we performed microarray analysis on 20 patients and estimated that we could predict advanced stage disease with 100% accuracy and the response to platin-based chemotherapy with 76.92% accuracy using leave-one-out cross validation techniques in combination with Least Squares Support Vector Machines (LS-SVMs). In the current study we evaluate whether tumour characteristics in an independent set of 49 patients can be predicted using the pilot data set with principal component analysis or LS-SVMs. The results of the principal component analysis suggest that the gene expression data from stage I, platin-sensitive advanced stage and platin-resistant advanced stage tumours in the independent data set did not correspond to their respective classes in the pilot study. Additionally, LS-SVM models built using the data from the pilot study – although they only misclassified one of four stage I tumours and correctly classified all 45 advanced stage tumours – were not able to predict resistance to platin-based chemotherapy. Furthermore, models based on the pilot data and on previously published gene sets related to ovarian cancer outcomes, did not perform significantly better than our models. We discuss possible reasons for failure of the model for predicting response to platin-based chemotherapy and conclude that existing results based on gene expression patterns of ovarian tumours need to be thoroughly scrutinized before these results can be accepted to reflect the true performance of microarray technology

The prediction of BRDFs from surface profile measurements

International Nuclear Information System (INIS)

Church, E.L.; Takacs, P.Z.; Leonard, T.A.

1989-01-01

This paper discusses methods of predicting the BRDF of smooth surfaces from profile measurements of their surface finish. The conversion of optical profile data to the BRDF at the same wavelength is essentially independent of scattering models, while the conversion of mechanical measurements, and wavelength scaling in general, are model dependent. Procedures are illustrated for several surfaces, including two from the recent HeNe BRDF round robin, and results are compared with measured data. Reasonable agreement is found except for surfaces which involve significant scattering from isolated surface defects which are poorly sampled in the profile data

Is There a Characteristic Clinical Profile for Patients with Dementia and Sundown Syndrome?

Science.gov (United States)

Angulo Sevilla, David; Carreras Rodríguez, María Teresa; Heredia Rodríguez, Patricia; Fernández Sánchez, Marisa; Vivancos Mora, José Aurelio; Gago-Veiga, Ana Beatriz

2018-01-01

Sundown syndrome (SS) is the onset or worsening of behavioral symptoms in the evening in patients with dementia. To identify the differential clinical profile of patients with dementia who present SS. A cross-sectional, case-control observational study was conducted by retrospectively reviewing the medical records of patients with dementia in a specialized Memory Unit. We compared the characteristics of patients with and without SS, including sociodemographic variables, etiology, and severity of the dementia, behavioral symptoms, sleep disorders (considering insomnia and hypersomnia), other diseases and treatments employed. We identified the factors related to SS and conducted a logistic regression analysis to establish a predictive nomogram. Of the 216 study patients with dementia, 41 (19%) had SS. There was a predominance of women (2.4:1), advanced age (p = 0.0001), dependence (p patients with dementia, with a predictive capacity of 80.1%. In our study, age, a higher score on the GDS, and the presence of insomnia or hypersomnia are differential clinical characteristics of patients with SS. We defined a nomogram that helps predicting the occurrence of SS in patients with dementia.

Anxiety and Mood Clinical Profile following Sport-related Concussion: From Risk Factors to Treatment.

Science.gov (United States)

Sandel, Natalie; Reynolds, Erin; Cohen, Paul E; Gillie, Brandon L; Kontos, Anthony P

2017-08-01

Conceptual models for assessing and treating sport-related concussion (SRC) have evolved from a homogenous approach to include different clinical profiles that reflect the heterogeneous nature of this injury and its effects. There are six identified clinical profiles, or subtypes from SRC, and one such clinical profile is the anxiety/mood profile. Athletes with this profile experience predominant emotional disturbance and anxiety following SRC. The purpose of this targeted review was to present an overview of the empirical evidence to support factors contributing to the anxiety/mood profile, along with methods of evaluation and treatment of this clinical profile following SRC. We discuss the potential underlying mechanisms and risk factors for this clinical profile, describe comprehensive assessments to evaluate concussed athletes with an anxiety/mood clinical profile, and explore behavioral and other interventions for treating these athletes. Although there is limited, but growing empirical evidence for the anxiety/mood clinical profile following SRC, understanding this clinical profile is germane for clinicians who are treating athletes with emotional sequelae after SRC.

Non-invasively predicting differentiation of pancreatic cancer through comparative serum metabonomic profiling.

Science.gov (United States)

Wen, Shi; Zhan, Bohan; Feng, Jianghua; Hu, Weize; Lin, Xianchao; Bai, Jianxi; Huang, Heguang

2017-11-02

The differentiation of pancreatic ductal adenocarcinoma (PDAC) could be associated with prognosis and may influence the choices of clinical management. No applicable methods could reliably predict the tumor differentiation preoperatively. Thus, the aim of this study was to compare the metabonomic profiling of pancreatic ductal adenocarcinoma with different differentiations and assess the feasibility of predicting tumor differentiations through metabonomic strategy based on nuclear magnetic resonance spectroscopy. By implanting pancreatic cancer cell strains Panc-1, Bxpc-3 and SW1990 in nude mice in situ, we successfully established the orthotopic xenograft models of PDAC with different differentiations. The metabonomic profiling of serum from different PDAC was achieved and analyzed by using 1 H nuclear magnetic resonance (NMR) spectroscopy combined with the multivariate statistical analysis. Then, the differential metabolites acquired were used for enrichment analysis of metabolic pathways to get a deep insight. An obvious metabonomic difference was demonstrated between all groups and the pattern recognition models were established successfully. The higher concentrations of amino acids, glycolytic and glutaminolytic participators in SW1990 and choline-contain metabolites in Panc-1 relative to other PDAC cells were demonstrated, which may be served as potential indicators for tumor differentiation. The metabolic pathways and differential metabolites identified in current study may be associated with specific pathways such as serine-glycine-one-carbon and glutaminolytic pathways, which can regulate tumorous proliferation and epigenetic regulation. The NMR-based metabonomic strategy may be served as a non-invasive detection method for predicting tumor differentiation preoperatively.

Validity of a manual soft tissue profile prediction method following mandibular setback osteotomy.

Science.gov (United States)

Kolokitha, Olga-Elpis

2007-10-01

The aim of this study was to determine the validity of a manual cephalometric method used for predicting the post-operative soft tissue profiles of patients who underwent mandibular setback surgery and compare it to a computerized cephalometric prediction method (Dentofacial Planner). Lateral cephalograms of 18 adults with mandibular prognathism taken at the end of pre-surgical orthodontics and approximately one year after surgery were used. To test the validity of the manual method the prediction tracings were compared to the actual post-operative tracings. The Dentofacial Planner software was used to develop the computerized post-surgical prediction tracings. Both manual and computerized prediction printouts were analyzed by using the cephalometric system PORDIOS. Statistical analysis was performed by means of t-test. Comparison between manual prediction tracings and the actual post-operative profile showed that the manual method results in more convex soft tissue profiles; the upper lip was found in a more prominent position, upper lip thickness was increased and, the mandible and lower lip were found in a less posterior position than that of the actual profiles. Comparison between computerized and manual prediction methods showed that in the manual method upper lip thickness was increased, the upper lip was found in a more anterior position and the lower anterior facial height was increased as compared to the computerized prediction method. Cephalometric simulation of post-operative soft tissue profile following orthodontic-surgical management of mandibular prognathism imposes certain limitations related to the methods implied. However, both manual and computerized prediction methods remain a useful tool for patient communication.

The Reliability and Predictive Validity of the Stalking Risk Profile.

Science.gov (United States)

McEwan, Troy E; Shea, Daniel E; Daffern, Michael; MacKenzie, Rachel D; Ogloff, James R P; Mullen, Paul E

2018-03-01

This study assessed the reliability and validity of the Stalking Risk Profile (SRP), a structured measure for assessing stalking risks. The SRP was administered at the point of assessment or retrospectively from file review for 241 adult stalkers (91% male) referred to a community-based forensic mental health service. Interrater reliability was high for stalker type, and moderate-to-substantial for risk judgments and domain scores. Evidence for predictive validity and discrimination between stalking recidivists and nonrecidivists for risk judgments depended on follow-up duration. Discrimination was moderate (area under the curve = 0.66-0.68) and positive and negative predictive values good over the full follow-up period ( Mdn = 170.43 weeks). At 6 months, discrimination was better than chance only for judgments related to stalking of new victims (area under the curve = 0.75); however, high-risk stalkers still reoffended against their original victim(s) 2 to 4 times as often as low-risk stalkers. Implications for the clinical utility and refinement of the SRP are discussed.

A comparison on radar range profiles between in-flight measurements and RCS-predictions

NARCIS (Netherlands)

Heiden, R. van der; Ewijk, L.J. van; Groen, F.C.A.

1998-01-01

The validation of Radar Cross Section (RCS) prediction techniques against real measurements is crucial to acquire confidence in predictions when measurements are nut available. In this paper we present the results of a comparison on one-dimensional signatures, i.e. radar range profiles. The profiles

Random Subspace Aggregation for Cancer Prediction with Gene Expression Profiles

Directory of Open Access Journals (Sweden)

Liying Yang

2016-01-01

Full Text Available Background. Precisely predicting cancer is crucial for cancer treatment. Gene expression profiles make it possible to analyze patterns between genes and cancers on the genome-wide scale. Gene expression data analysis, however, is confronted with enormous challenges for its characteristics, such as high dimensionality, small sample size, and low Signal-to-Noise Ratio. Results. This paper proposes a method, termed RS_SVM, to predict gene expression profiles via aggregating SVM trained on random subspaces. After choosing gene features through statistical analysis, RS_SVM randomly selects feature subsets to yield random subspaces and training SVM classifiers accordingly and then aggregates SVM classifiers to capture the advantage of ensemble learning. Experiments on eight real gene expression datasets are performed to validate the RS_SVM method. Experimental results show that RS_SVM achieved better classification accuracy and generalization performance in contrast with single SVM, K-nearest neighbor, decision tree, Bagging, AdaBoost, and the state-of-the-art methods. Experiments also explored the effect of subspace size on prediction performance. Conclusions. The proposed RS_SVM method yielded superior performance in analyzing gene expression profiles, which demonstrates that RS_SVM provides a good channel for such biological data.

The clinical profile of high-risk mentally disordered offenders.

Science.gov (United States)

Yiend, Jenny; Freestone, Mark; Vazquez-Montes, Maria; Holland, Josephine; Burns, Tom

2013-07-01

High-risk mentally disordered offenders present a diverse array of clinical characteristics. To contain and effectively treat this heterogeneous population requires a full understanding of the group's clinical profile. This study aimed to identify and validate clusters of clinically coherent profiles within one high-risk mentally disordered population in the UK. Latent class analysis (a statistical technique to identify clustering of variance from a set of categorical variables) was applied to 174 cases using clinical diagnostic information to identify the most parsimonious model of best fit. Validity analyses were performed. Three identified classes were a 'delinquent' group (n = 119) characterised by poor educational history, strong criminal careers and high recidivism risk; a 'primary psychopathy' group (n = 38) characterised by good educational profiles and homicide offences and an 'expressive psychopathy' group (n = 17) presenting the lowest risk and characterised by more special educational needs and sexual offences. Individuals classed as high-risk mentally disordered offenders can be loosely segregated into three discrete subtypes: 'delinquent', 'psychopathic' or 'expressive psychopathic', respectively. These groups represent different levels of risk to society and reflect differing treatment needs.

Clinical Profile and HIV/AIDS Prevalence of Patients with ...

African Journals Online (AJOL)

Background: Clinical features of HIV/AIDS and various malignancies are similar. Clinical profiles and HIV/AIDS prevalence in Nigerian cancer patients have been poorly documented. Aim: To identify the patterns of clinical presentations in patients with malignancies and to determine the prevalence of HIV infection in cancer ...

Predicting Low Energy Dopant Implant Profiles in Semiconductors using Molecular Dynamics

Energy Technology Data Exchange (ETDEWEB)

Beardmore, K.M.; Gronbech-Jensen, N.

1999-05-02

The authors present a highly efficient molecular dynamics scheme for calculating dopant density profiles in group-IV alloy, and III-V zinc blende structure materials. Their scheme incorporates several necessary methods for reducing computational overhead, plus a rare event algorithm to give statistical accuracy over several orders of magnitude change in the dopant concentration. The code uses a molecular dynamics (MD) model to describe ion-target interactions. Atomic interactions are described by a combination of 'many-body' and pair specific screened Coulomb potentials. Accumulative damage is accounted for using a Kinchin-Pease type model, inelastic energy loss is represented by a Firsov expression, and electronic stopping is described by a modified Brandt-Kitagawa model which contains a single adjustable ion-target dependent parameter. Thus, the program is easily extensible beyond a given validation range, and is therefore truly predictive over a wide range of implant energies and angles. The scheme is especially suited for calculating profiles due to low energy and to situations where a predictive capability is required with the minimum of experimental validation. They give examples of using the code to calculate concentration profiles and 2D 'point response' profiles of dopants in crystalline silicon and gallium-arsenide. Here they can predict the experimental profile over five orders of magnitude for <100> and <110> channeling and for non-channeling implants at energies up to hundreds of keV.

Automatic selection of reference taxa for protein-protein interaction prediction with phylogenetic profiling

DEFF Research Database (Denmark)

Simonsen, Martin; Maetschke, S.R.; Ragan, M.A.

2012-01-01

Motivation: Phylogenetic profiling methods can achieve good accuracy in predicting protein–protein interactions, especially in prokaryotes. Recent studies have shown that the choice of reference taxa (RT) is critical for accurate prediction, but with more than 2500 fully sequenced taxa publicly......: We present three novel methods for automating the selection of RT, using machine learning based on known protein–protein interaction networks. One of these methods in particular, Tree-Based Search, yields greatly improved prediction accuracies. We further show that different methods for constituting...... phylogenetic profiles often require very different RT sets to support high prediction accuracy....

Geometrical theory to predict eccentric photorefraction intensity profiles in the human eye

Science.gov (United States)

Roorda, Austin; Campbell, Melanie C. W.; Bobier, W. R.

1995-08-01

In eccentric photorefraction, light returning from the retina of the eye is photographed by a camera focused on the eye's pupil. We use a geometrical model of eccentric photorefraction to generate intensity profiles across the pupil image. The intensity profiles for three different monochromatic aberration functions induced in a single eye are predicted and show good agreement with the measured eccentric photorefraction intensity profiles. A directional reflection from the retina is incorporated into the calculation. Intensity profiles for symmetric and asymmetric aberrations are generated and measured. The latter profile shows a dependency on the source position and the meridian. The magnitude of the effect of thresholding on measured pattern extents is predicted. Monochromatic aberrations in human eyes will cause deviations in the eccentric photorefraction measurements from traditional crescents caused by defocus and may cause misdiagnoses of ametropia or anisometropia. Our results suggest that measuring refraction along the vertical meridian is preferred for screening studies with the eccentric photorefractor.

Predictive properties of plasma amino acid profile for cardiovascular disease in patients with type 2 diabetes.

Directory of Open Access Journals (Sweden)

Shinji Kume

Full Text Available Prevention of cardiovascular disease (CVD is an important therapeutic object of diabetes care. This study assessed whether an index based on plasma free amino acid (PFAA profiles could predict the onset of CVD in diabetic patients. The baseline concentrations of 31 PFAAs were measured with high-performance liquid chromatography-electrospray ionization-mass spectrometry in 385 Japanese patients with type 2 diabetes registered in 2001 for our prospective observational follow-up study. During 10 years of follow-up, 63 patients developed cardiovascular composite endpoints (myocardial infarction, angina pectoris, worsening of heart failure and stroke. Using the PFAA profiles and clinical information, an index (CVD-AI consisting of six amino acids to predict the onset of any endpoints was retrospectively constructed. CVD-AI levels were significantly higher in patients who did than did not develop CVD. The area under the receiver-operator characteristic curve of CVD-AI (0.72 [95% confidence interval (CI: 0.64-0.79] showed equal or slightly better discriminatory capacity than urinary albumin excretion rate (0.69 [95% CI: 0.62-0.77] on predicting endpoints. A multivariate Cox proportional hazards regression analysis showed that the high level of CVD-AI was identified as an independent risk factor for CVD (adjusted hazard ratio: 2.86 [95% CI: 1.57-5.19]. This predictive effect of CVD-AI was observed even in patients with normoalbuminuria, as well as those with albuminuria. In conclusion, these results suggest that CVD-AI based on PFAA profiles is useful for identifying diabetic patients at risk for CVD regardless of the degree of albuminuria, or for improving the discriminative capability by combining it with albuminuria.

Predictive Properties of Plasma Amino Acid Profile for Cardiovascular Disease in Patients with Type 2 Diabetes

Science.gov (United States)

Kume, Shinji; Araki, Shin-ichi; Ono, Nobukazu; Shinhara, Atsuko; Muramatsu, Takahiko; Araki, Hisazumi; Isshiki, Keiji; Nakamura, Kazuki; Miyano, Hiroshi; Koya, Daisuke; Haneda, Masakazu; Ugi, Satoshi; Kawai, Hiromichi; Kashiwagi, Atsunori; Uzu, Takashi; Maegawa, Hiroshi

2014-01-01

Prevention of cardiovascular disease (CVD) is an important therapeutic object of diabetes care. This study assessed whether an index based on plasma free amino acid (PFAA) profiles could predict the onset of CVD in diabetic patients. The baseline concentrations of 31 PFAAs were measured with high-performance liquid chromatography-electrospray ionization-mass spectrometry in 385 Japanese patients with type 2 diabetes registered in 2001 for our prospective observational follow-up study. During 10 years of follow-up, 63 patients developed cardiovascular composite endpoints (myocardial infarction, angina pectoris, worsening of heart failure and stroke). Using the PFAA profiles and clinical information, an index (CVD-AI) consisting of six amino acids to predict the onset of any endpoints was retrospectively constructed. CVD-AI levels were significantly higher in patients who did than did not develop CVD. The area under the receiver-operator characteristic curve of CVD-AI (0.72 [95% confidence interval (CI): 0.64–0.79]) showed equal or slightly better discriminatory capacity than urinary albumin excretion rate (0.69 [95% CI: 0.62–0.77]) on predicting endpoints. A multivariate Cox proportional hazards regression analysis showed that the high level of CVD-AI was identified as an independent risk factor for CVD (adjusted hazard ratio: 2.86 [95% CI: 1.57–5.19]). This predictive effect of CVD-AI was observed even in patients with normoalbuminuria, as well as those with albuminuria. In conclusion, these results suggest that CVD-AI based on PFAA profiles is useful for identifying diabetic patients at risk for CVD regardless of the degree of albuminuria, or for improving the discriminative capability by combining it with albuminuria. PMID:24971671

Epidemiology and clinical profile of common musculoskeletal ...

African Journals Online (AJOL)

Epidemiology and clinical profile of common musculoskeletal diseases in patients with diabetes mellitus at Tikur Anbessa Specialized Hospital in Addis Ababa, Ethiopia. ... or worsening of MSD. Keywords: musculoskeletal complications; diabetic foot; foot care; trigger finger; Dupuytren's contracture; stiff frozen shoulder ...

Computational Analysis of Epidermal Growth Factor Receptor Mutations Predicts Differential Drug Sensitivity Profiles toward Kinase Inhibitors.

Science.gov (United States)

Akula, Sravani; Kamasani, Swapna; Sivan, Sree Kanth; Manga, Vijjulatha; Vudem, Dashavantha Reddy; Kancha, Rama Krishna

2018-05-01

A significant proportion of patients with lung cancer carry mutations in the EGFR kinase domain. The presence of a deletion mutation in exon 19 or L858R point mutation in the EGFR kinase domain has been shown to cause enhanced efficacy of inhibitor treatment in patients with NSCLC. Several less frequent (uncommon) mutations in the EGFR kinase domain with potential implications in treatment response have also been reported. The role of a limited number of uncommon mutations in drug sensitivity was experimentally verified. However, a huge number of these mutations remain uncharacterized for inhibitor sensitivity or resistance. A large-scale computational analysis of clinically reported 298 point mutants of EGFR kinase domain has been performed, and drug sensitivity profiles for each mutant toward seven kinase inhibitors has been determined by molecular docking. In addition, the relative inhibitor binding affinity toward each drug as compared with that of adenosine triphosphate was calculated for each mutant. The inhibitor sensitivity profiles predicted in this study for a set of previously characterized mutants correlated well with the published clinical, experimental, and computational data. Both the single and compound mutations displayed differential inhibitor sensitivity toward first- and next-generation kinase inhibitors. The present study provides predicted drug sensitivity profiles for a large panel of uncommon EGFR mutations toward multiple inhibitors, which may help clinicians in deciding mutant-specific treatment strategies. Copyright © 2018 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.

A lifetime prediction method for LEDs considering mission profiles

DEFF Research Database (Denmark)

Qu, Xiaohui; Wang, Huai; Zhan, Xiaoqing

2016-01-01

and to benchmark the cost-competitiveness of different lighting technologies. The existing lifetime data released by LED manufacturers or standard organizations are usually applicable only for specific temperature and current levels. Significant lifetime discrepancies may be observed in field operations due...... to the varying operational and environmental conditions during the entire service time (i.e., mission profiles). To overcome the challenge, this paper proposes an advanced lifetime prediction method, which takes into account the field operation mission profiles and the statistical properties of the life data...

Insulin Resistance Predicts Atherogenic Lipoprotein Profile in Nondiabetic Subjects

Directory of Open Access Journals (Sweden)

Flávia De C. Cartolano

2017-01-01

Full Text Available Background. Atherogenic diabetes is associated with an increased cardiovascular risk and mortality in diabetic individuals; however, the impact of insulin resistance (IR in lipid metabolism in preclinical stages is generally underreported. For that, we evaluated the capacity of IR to predict an atherogenic lipid subfraction profile. Methods. Complete clinical evaluation and biochemical analysis (lipid, glucose profile, LDL, and HDL subfractions and LDL phenotype and size were performed in 181 patients. The impact of IR as a predictor of atherogenic lipoproteins was tested by logistic regression analysis in raw and adjusted models. Results. HDL-C and Apo AI were significantly lower in individuals with IR. Individuals with IR had a higher percentage of small HDL particles, lower percentage in the larger ones, and reduced frequency of phenotype A (IR = 62%; non-IR = 83%. IR individuals had reduced probability to have large HDL (OR = 0.213; CI = 0.999–0.457 and had twice more chances to show increased small HDL (OR = 2.486; CI = 1.341–7.051. IR was a significant predictor of small LDL (OR = 3.075; CI = 1.341–7.051 and atherogenic phenotype (OR = 3.176; CI = 1.469–6.867. Conclusion. IR, previously DM2 diagnosis, is a strong predictor of quantitative and qualitative features of lipoproteins directly associated with an increased atherogenic risk.

HMMBinder: DNA-Binding Protein Prediction Using HMM Profile Based Features.

Science.gov (United States)

Zaman, Rianon; Chowdhury, Shahana Yasmin; Rashid, Mahmood A; Sharma, Alok; Dehzangi, Abdollah; Shatabda, Swakkhar

2017-01-01

DNA-binding proteins often play important role in various processes within the cell. Over the last decade, a wide range of classification algorithms and feature extraction techniques have been used to solve this problem. In this paper, we propose a novel DNA-binding protein prediction method called HMMBinder. HMMBinder uses monogram and bigram features extracted from the HMM profiles of the protein sequences. To the best of our knowledge, this is the first application of HMM profile based features for the DNA-binding protein prediction problem. We applied Support Vector Machines (SVM) as a classification technique in HMMBinder. Our method was tested on standard benchmark datasets. We experimentally show that our method outperforms the state-of-the-art methods found in the literature.

HMMBinder: DNA-Binding Protein Prediction Using HMM Profile Based Features

Directory of Open Access Journals (Sweden)

Rianon Zaman

2017-01-01

Full Text Available DNA-binding proteins often play important role in various processes within the cell. Over the last decade, a wide range of classification algorithms and feature extraction techniques have been used to solve this problem. In this paper, we propose a novel DNA-binding protein prediction method called HMMBinder. HMMBinder uses monogram and bigram features extracted from the HMM profiles of the protein sequences. To the best of our knowledge, this is the first application of HMM profile based features for the DNA-binding protein prediction problem. We applied Support Vector Machines (SVM as a classification technique in HMMBinder. Our method was tested on standard benchmark datasets. We experimentally show that our method outperforms the state-of-the-art methods found in the literature.

Clinical symptoms in fibromyalgia are associated to overweight and lipid profile.

Science.gov (United States)

Cordero, Mario D; Alcocer-Gómez, Elísabet; Cano-García, Francisco J; Sánchez-Domínguez, Benito; Fernández-Riejo, Patricia; Moreno Fernández, Ana M; Fernández-Rodríguez, Ana; De Miguel, Manuel

2014-03-01

In order to analyze the association between body mass index (BMI), lipid profile and clinical symptoms in patients with fibromyalgia, we assessed BMI levels, lipid profile and its association with clinical symptoms in 183 patients with fibromyalgia. The patients were evaluated using tender points, FIQ and Visual Analogue Scales of pain (VAS). Serum lipid profile analysis (total cholesterol, triglyceride, HDL, LDL and VLDL), and biochemical parameters were measured in the biochemistry laboratory. The BMI distribution of the nonobese, overweight and obese patients' groups were relatively even with 37.7, 35.5 and 26.8%, respectively, with a mean BMI of 27.3 ± 4.9. The number of tender points showed significantly positive correlation with higher BMI (P BMI, total cholesterol and triglycerides showed high association with some clinical parameters. Overweight and lipid profile could be associated with fibromyalgia symptoms. A treatment program with weight loss strategies, and control in diet and increased physical activity is advised to patients.

Predicting survival in patients with metastatic kidney cancer by gene-expression profiling in the primary tumor.

Science.gov (United States)

Vasselli, James R; Shih, Joanna H; Iyengar, Shuba R; Maranchie, Jodi; Riss, Joseph; Worrell, Robert; Torres-Cabala, Carlos; Tabios, Ray; Mariotti, Andra; Stearman, Robert; Merino, Maria; Walther, McClellan M; Simon, Richard; Klausner, Richard D; Linehan, W Marston

2003-06-10

To identify potential molecular determinants of tumor biology and possible clinical outcomes, global gene-expression patterns were analyzed in the primary tumors of patients with metastatic renal cell cancer by using cDNA microarrays. We used grossly dissected tumor masses that included tumor, blood vessels, connective tissue, and infiltrating immune cells to obtain a gene-expression "profile" from each primary tumor. Two patterns of gene expression were found within this uniformly staged patient population, which correlated with a significant difference in overall survival between the two patient groups. Subsets of genes most significantly associated with survival were defined, and vascular cell adhesion molecule-1 (VCAM-1) was the gene most predictive for survival. Therefore, despite the complex biological nature of metastatic cancer, basic clinical behavior as defined by survival may be determined by the gene-expression patterns expressed within the compilation of primary gross tumor cells. We conclude that survival in patients with metastatic renal cell cancer can be correlated with the expression of various genes based solely on the expression profile in the primary kidney tumor.

Clinical pharmacology profile of vorinostat, a histone deacetylase inhibitor.

Science.gov (United States)

Iwamoto, Marian; Friedman, Evan J; Sandhu, Punam; Agrawal, Nancy G B; Rubin, Eric H; Wagner, John A

2013-09-01

Vorinostat is a histone deacetylase inhibitor that has demonstrated preclinical activity in numerous cancer models. Clinical activity has been demonstrated in patients with a variety of malignancies. Vorinostat is presently indicated for the treatment of patients with advanced cutaneous T cell lymphoma (CTCL). Clinical investigation is ongoing for therapy of other solid tumors and hematological malignancies either as monotherapy or in combination with other chemotherapeutic agents. This review summarizes the pharmacokinetic properties of vorinostat. Monotherapy pharmacokinetic data across a number of pharmacokinetic studies were reviewed, and data are presented. In addition, literature review was performed to obtain published Phase I and II pharmacokinetic combination therapy data to identify and characterize potential drug interactions with vorinostat. Pharmacokinetic data in special populations were also reviewed. The clinical pharmacology profile of vorinostat is favorable, exhibiting dose-proportional pharmacokinetics and modest food effect. There appear to be no major differences in the pharmacokinetics of vorinostat in special populations, including varying demographics and hepatic dysfunction. Combination therapy pharmacokinetic data indicate that vorinostat has a low propensity for drug interactions. Vorinostat's favorable clinical pharmacology and drug interaction profile aid in the ease of administration of vorinostat for the treatment of advanced CTCL and will be beneficial in continued assessment for other oncologic indications. Although a number of studies have been conducted to elucidate the detailed pharmacokinetic profile of vorinostat, more rigorous assessment of vorinostat pharmacokinetics, including clinical drug interaction studies, will be informative.

A new algorithm predicts pressure and temperature profiles of gas/gas-condensate transmission pipelines

Energy Technology Data Exchange (ETDEWEB)

Mokhatab, Saied [OIEC - Oil Industries' Engineering and Construction Group, Tehran (Iran, Islamic Republic of); Vatani, Ali [University of Tehran (Iran, Islamic Republic of)

2003-07-01

The main objective of the present study has been the development of a relatively simple analytical algorithm for predicting flow temperature and pressure profiles along the two-phase, gas/gas-condensate transmission pipelines. Results demonstrate the ability of the method to predict reasonably accurate pressure gradient and temperature gradient profiles under operating conditions. (author)

A supply-demand model of fetal energy sufficiency predicts lipid profiles in male but not female Filipino adolescents.

Science.gov (United States)

Kuzawa, C W; Adair, L S

2004-03-01

To test the hypothesis that the balance between fetal nutritional demand and maternal nutritional supply during pregnancy will predict lipid profiles in offspring measured in adolescence. A total of 296 male and 307 female Filipino offspring (aged 14-16 y) and mothers enrolled in a longitudinal birth cohort study (begun in 1983-84) had lipid profiles measured. Data on maternal height (as a proxy for offspring growth potential and thus fetal nutritional demand) and third trimester maternal arm fat area (as a proxy for maternal supply) were used to create four groups hypothesized to reflect a gradient of fetal energy sufficiency. As fetal energy sufficiency increased among males, there was a decrease in total cholesterol (TC) (Psupply-demand model did not predict any lipid outcome or clinical risk criteria. Our findings in males support the hypothesis that the balance between fetal nutritional demand and maternal nutritional supply has implications for future lipid profiles. The lack of significant associations in females adds to mounting evidence for sex differences in lipid metabolism programming, and may reflect sex differences in fetal nutritional demand. The National Science Foundation, the Mellon Foundation, the Nestle Foundation, and the Emory University Internationalization Program.

Prediction of metastasis from low-malignant breast cancer by gene expression profiling

DEFF Research Database (Denmark)

Thomassen, Mads; Tan, Qihua; Eiriksdottir, Freyja

2007-01-01

examined in these studies is the low-risk patients for whom outcome is very difficult to predict with currently used methods. These patients do not receive adjuvant treatment according to the guidelines of the Danish Breast Cancer Cooperative Group (DBCG). In this study, 26 tumors from low-risk patients...... with different characteristics and risk, expression-based classification specifically developed in low-risk patients have higher predictive power in this group.......Promising results for prediction of outcome in breast cancer have been obtained by genome wide gene expression profiling. Some studies have suggested that an extensive overtreatment of breast cancer patients might be reduced by risk assessment with gene expression profiling. A patient group hardly...

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...

A Lifetime Prediction Method for LEDs Considering Real Mission Profiles

DEFF Research Database (Denmark)

Qu, Xiaohui; Wang, Huai; Zhan, Xiaoqing

2017-01-01

operations due to the varying operational and environmental conditions during the entire service time (i.e., mission profiles). To overcome the challenge, this paper proposes an advanced lifetime prediction method, which takes into account the field operation mission profiles and also the statistical......The Light-Emitting Diode (LED) has become a very promising alternative lighting source with the advantages of longer lifetime and higher efficiency than traditional ones. The lifetime prediction of LEDs is important to guide the LED system designers to fulfill the design specifications...... properties of the life data available from accelerated degradation testing. The electrical and thermal characteristics of LEDs are measured by a T3Ster system, used for the electro-thermal modeling. It also identifies key variables (e.g., heat sink parameters) that can be designed to achieve a specified...

Exploring the Inflammatory Metabolomic Profile to Predict Response to TNF-α Inhibitors in Rheumatoid Arthritis.

Directory of Open Access Journals (Sweden)

Bart V J Cuppen

Full Text Available In clinical practice, approximately one-third of patients with rheumatoid arthritis (RA respond insufficiently to TNF-α inhibitors (TNFis. The aim of the study was to explore the use of a metabolomics to identify predictors for the outcome of TNFi therapy, and study the metabolomic fingerprint in active RA irrespective of patients' response. In the metabolomic profiling, lipids, oxylipins, and amines were measured in serum samples of RA patients from the observational BiOCURA cohort, before start of biological treatment. Multivariable logistic regression models were established to identify predictors for good- and non-response in patients receiving TNFi (n = 124. The added value of metabolites over prediction using clinical parameters only was determined by comparing the area under receiver operating characteristic curve (AUC-ROC, sensitivity, specificity, positive- and negative predictive value and by the net reclassification index (NRI. The models were further validated by 10-fold cross validation and tested on the complete TNFi treatment cohort including moderate responders. Additionally, metabolites were identified that cross-sectionally associated with the RA disease activity score based on a 28-joint count (DAS28, erythrocyte sedimentation rate (ESR or C-reactive protein (CRP. Out of 139 metabolites, the best-performing predictors were sn1-LPC(18:3-ω3/ω6, sn1-LPC(15:0, ethanolamine, and lysine. The model that combined the selected metabolites with clinical parameters showed a significant larger AUC-ROC than that of the model containing only clinical parameters (p = 0.01. The combined model was able to discriminate good- and non-responders with good accuracy and to reclassify non-responders with an improvement of 30% (total NRI = 0.23 and showed a prediction error of 0.27. For the complete TNFi cohort, the NRI was 0.22. In addition, 88 metabolites were associated with DAS28, ESR or CRP (p<0.05. Our study established an accurate

NESmapper: accurate prediction of leucine-rich nuclear export signals using activity-based profiles.

Directory of Open Access Journals (Sweden)

Shunichi Kosugi

2014-09-01

Full Text Available The nuclear export of proteins is regulated largely through the exportin/CRM1 pathway, which involves the specific recognition of leucine-rich nuclear export signals (NESs in the cargo proteins, and modulates nuclear-cytoplasmic protein shuttling by antagonizing the nuclear import activity mediated by importins and the nuclear import signal (NLS. Although the prediction of NESs can help to define proteins that undergo regulated nuclear export, current methods of predicting NESs, including computational tools and consensus-sequence-based searches, have limited accuracy, especially in terms of their specificity. We found that each residue within an NES largely contributes independently and additively to the entire nuclear export activity. We created activity-based profiles of all classes of NESs with a comprehensive mutational analysis in mammalian cells. The profiles highlight a number of specific activity-affecting residues not only at the conserved hydrophobic positions but also in the linker and flanking regions. We then developed a computational tool, NESmapper, to predict NESs by using profiles that had been further optimized by training and combining the amino acid properties of the NES-flanking regions. This tool successfully reduced the considerable number of false positives, and the overall prediction accuracy was higher than that of other methods, including NESsential and Wregex. This profile-based prediction strategy is a reliable way to identify functional protein motifs. NESmapper is available at http://sourceforge.net/projects/nesmapper.

Understanding and Predicting Profile Structure and Parametric Scaling of Intrinsic Rotation

Science.gov (United States)

Wang, Weixing

2016-10-01

It is shown for the first time that turbulence-driven residual Reynolds stress can account for both the shape and magnitude of the observed intrinsic toroidal rotation profile. Nonlinear, global gyrokinetic simulations using GTS of DIII-D ECH plasmas indicate a substantial ITG fluctuation-induced non-diffusive momentum flux generated around a mid-radius-peaked intrinsic toroidal rotation profile. The non-diffusive momentum flux is dominated by the residual stress with a negligible contribution from the momentum pinch. The residual stress profile shows a robust anti-gradient, dipole structure in a set of ECH discharges with varying ECH power. Such interesting features of non-diffusive momentum fluxes, in connection with edge momentum sources and sinks, are found to be critical to drive the non-monotonic core rotation profiles in the experiments. Both turbulence intensity gradient and zonal flow ExB shear are identified as major contributors to the generation of the k∥-asymmetry needed for the residual stress generation. By balancing the residual stress and the momentum diffusion, a self-organized, steady-state rotation profile is calculated. The predicted core rotation profiles agree well with the experimentally measured main-ion toroidal rotation. The validated model is further used to investigate the characteristic dependence of global rotation profile structure in the multi-dimensional parametric space covering turbulence type, q-profile structure and collisionality with the goal of developing physics understanding needed for rotation profile control and optimization. Interesting results obtained include intrinsic rotation reversal induced by ITG-TEM transition in flat-q profile regime and by change in q-profile from weak to normal shear.. Fluctuation-generated poloidal Reynolds stress is also shown to significantly modify the neoclassical poloidal rotation in a way consistent with experimental observations. Finally, the first-principles-based model is applied

Comparisons of Crosswind Velocity Profile Estimates Used in Fast-Time Wake Vortex Prediction Models

Science.gov (United States)

Pruis, Mathew J.; Delisi, Donald P.; Ahmad, Nashat N.

2011-01-01

Five methods for estimating crosswind profiles used in fast-time wake vortex prediction models are compared in this study. Previous investigations have shown that temporal and spatial variations in the crosswind vertical profile have a large impact on the transport and time evolution of the trailing vortex pair. The most important crosswind parameters are the magnitude of the crosswind and the gradient in the crosswind shear. It is known that pulsed and continuous wave lidar measurements can provide good estimates of the wind profile in the vicinity of airports. In this study comparisons are made between estimates of the crosswind profiles from a priori information on the trajectory of the vortex pair as well as crosswind profiles derived from different sensors and a regional numerical weather prediction model.

The demographic, clinical and forensic profile of offenders ...

African Journals Online (AJOL)

The demographic, clinical and forensic profile of offenders diagnosed with epilepsy referred to the Free State Psychiatric Complex Observation Unit in terms of section 77 and/or 78 of the Criminal Procedure Act 51 of 1977.

An audit of the clinical profile of snake bites among female patients ...

African Journals Online (AJOL)

Background: A lot of work had been done on the clinical profiles of patients with snake bites but none on female patients alone. In this medical audit, we undertook to study the clinical profiles of snake bites among female patients seen over a two year period at a federal Government designated treatment centre, Zamko.

Clinical and microbiological profile of infectious keratitis in children

Science.gov (United States)

2013-01-01

Background Infectious keratitis is a sight-threatening condition for children. The purpose of this study was to describe the clinical profile, risk factors and microbiological profile of infectious keratitis in children. Methods Retrospective review of clinical records of patients under 16 years of age with history of microbial keratitis seen at a tertiary referral center. Clinical characteristics, risk factors, visual and surgical outcomes as well as the microbiological profile are analyzed. Results Forty-one eyes of 41 patients. Mean age was 8.7 years. Time between the onset of symptoms and ophthalmological examination was 12.7 days. Predisposing factors were found in 78%; ocular trauma was the most common (25%). Visual acuity equal or worse than 20/200 at admission correlated positively with a poorer visual outcome, p=0.002. Positivity of cultures was 34%. Gram-positive bacteria were isolated in 78.5%; Staphylococcus epidermidis (28.6%) was the most common microorganism. Conclusions Our study emphasizes the importance of a prompt diagnosis and treatment of infectious corneal ulcers in children. Trauma and contact lenses were the main predisposing factors. Gram-positive organisms were isolated in the vast majority of cases and visual outcomes are usually poor. PMID:24131681

APRIL is a novel clinical chemo-resistance biomarker in colorectal adenocarcinoma identified by gene expression profiling

International Nuclear Information System (INIS)

Petty, Russell D; Wang, Weiguang; Gilbert, Fiona; Semple, Scot; Collie-Duguid, Elaina SR; Samuel, Leslie M; Murray, Graeme I; MacDonald, Graham; O'Kelly, Terrence; Loudon, Malcolm; Binnie, Norman; Aly, Emad; McKinlay, Aileen

2009-01-01

5-Fluorouracil(5FU) and oral analogues, such as capecitabine, remain one of the most useful agents for the treatment of colorectal adenocarcinoma. Low toxicity and convenience of administration facilitate use, however clinical resistance is a major limitation. Investigation has failed to fully explain the molecular mechanisms of resistance and no clinically useful predictive biomarkers for 5FU resistance have been identified. We investigated the molecular mechanisms of clinical 5FU resistance in colorectal adenocarcinoma patients in a prospective biomarker discovery project utilising gene expression profiling. The aim was to identify novel 5FU resistance mechanisms and qualify these as candidate biomarkers and therapeutic targets. Putative treatment specific gene expression changes were identified in a transcriptomics study of rectal adenocarcinomas, biopsied and profiled before and after pre-operative short-course radiotherapy or 5FU based chemo-radiotherapy, using microarrays. Tumour from untreated controls at diagnosis and resection identified treatment-independent gene expression changes. Candidate 5FU chemo-resistant genes were identified by comparison of gene expression data sets from these clinical specimens with gene expression signatures from our previous studies of colorectal cancer cell lines, where parental and daughter lines resistant to 5FU were compared. A colorectal adenocarcinoma tissue microarray (n = 234, resected tumours) was used as an independent set to qualify candidates thus identified. APRIL/TNFSF13 mRNA was significantly upregulated following 5FU based concurrent chemo-radiotherapy and in 5FU resistant colorectal adenocarcinoma cell lines but not in radiotherapy alone treated colorectal adenocarcinomas. Consistent withAPRIL's known function as an autocrine or paracrine secreted molecule, stromal but not tumour cell protein expression by immunohistochemistry was correlated with poor prognosis (p = 0.019) in the independent set

Clinical features and endocrine profile of Laron syndrome in Indian children

OpenAIRE

Supriya R Phanse-Gupte; Vaman V Khadilkar; Anuradha V Khadilkar

2014-01-01

Introduction: Patients with growth hormone (GH) insensitivity (also known as Laron syndome) have been reported from the Mediterranean region and Southern Eucador, with few case reports from India. We present here the clinical and endocrine profile of 9 children with Laron syndrome from India. Material and Methods: Nine children diagnosed with Laron syndrome based on clinical features of GH deficiency and biochemical profile suggestive of GH resistance were studied over a period of 5 years fro...

Associations of Streptococcus suis serotype 2 ribotype profiles with clinical disease and antimicrobial resistance

DEFF Research Database (Denmark)

Rasmussen, S. R.; Aarestrup, Frank Møller; Jensen, N. E.

1999-01-01

A total of 122 Streptococcus suis serotype 2 strains were characterized thoroughly by comparing clinical and pathological observations, ribotype profiles, and antimicrobial resistance. Twenty-one different ribotype profiles were found and compared by cluster analysis, resulting in the identificat......A total of 122 Streptococcus suis serotype 2 strains were characterized thoroughly by comparing clinical and pathological observations, ribotype profiles, and antimicrobial resistance. Twenty-one different ribotype profiles were found and compared by cluster analysis, resulting...

Clinical profile of neurological complications in HIV- reactive ...

African Journals Online (AJOL)

McRoy

2014-07-26

Jul 26, 2014 ... reproduction in any medium, provided the original work is properly cited. Clinical profile of ... cytology, staining including grams staining, acid-fast ... manifestation of neurological involvement. Exclusion criteria. HIV-positive patients not showing any manifestation of neurological involvement. Ethical issues.

A prospective, longitudinal study to evaluate the clinical utility of a predictive algorithm that detects risk of opioid use disorder

Science.gov (United States)

Brenton, Ashley; Lee, Chee; Lewis, Katrina; Sharma, Maneesh; Kantorovich, Svetlana; Smith, Gregory A; Meshkin, Brian

2018-01-01

Purpose The purpose of this study was to determine the clinical utility of an algorithm-based decision tool designed to assess risk associated with opioid use. Specifically, we sought to assess how physicians were using the profile in patient care and how its use affected patient outcomes. Patients and methods A prospective, longitudinal study was conducted to assess the utility of precision medicine testing in 5,397 patients across 100 clinics in the USA. Using a patent-protected, validated algorithm combining specific genetic risk factors with phenotypic traits, patients were categorized into low-, moderate-, and high-risk patients for opioid abuse. Physicians who ordered precision medicine testing were asked to complete patient evaluations and document their actions, decisions, and perceptions regarding the utility of the precision medicine tests. The patient outcomes associated with each treatment action were carefully documented. Results Physicians used the profile to guide treatment decisions for over half of the patients. Of those, guided treatment decisions for 24.5% of the patients were opioid related, including changing the opioid prescribed, starting an opioid, or titrating a patient off the opioid. Treatment guidance was strongly influenced by profile-predicted opioid use disorder (OUD) risk. Most importantly, patients whose physicians used the profile to guide opioid-related treatment decisions had improved clinical outcomes, including better pain management by medication adjustments, with an average pain decrease of 3.4 points on a scale of 1–10. Conclusion Patients whose physicians used the profile to guide opioid-related treatment decisions had improved clinical outcomes, as measured by decreased pain levels resulting from better pain management with prescribed medications. The clinical utility of the profile is twofold. It provides clinically actionable recommendations that can be used to 1) prevent OUD through limiting initial opioid

FUNCTIONAL SUBCLONE PROFILING FOR PREDICTION OF TREATMENT-INDUCED INTRA-TUMOR POPULATION SHIFTS AND DISCOVERY OF RATIONAL DRUG COMBINATIONS IN HUMAN GLIOBLASTOMA

Science.gov (United States)

Reinartz, Roman; Wang, Shanshan; Kebir, Sied; Silver, Daniel J.; Wieland, Anja; Zheng, Tong; Küpper, Marius; Rauschenbach, Laurèl; Fimmers, Rolf; Shepherd, Timothy M.; Trageser, Daniel; Till, Andreas; Schäfer, Niklas; Glas, Martin; Hillmer, Axel M.; Cichon, Sven; Smith, Amy A.; Pietsch, Torsten; Liu, Ying; Reynolds, Brent A.; Yachnis, Anthony; Pincus, David W.; Simon, Matthias; Brüstle, Oliver; Steindler, Dennis A.; Scheffler, Björn

2016-01-01

Purpose Investigation of clonal heterogeneity may be key to understanding mechanisms of therapeutic failure in human cancer. However, little is known on the consequences of therapeutic intervention on the clonal composition of solid tumors. Experimental Design Here, we used 33 single cell-derived subclones generated from five clinical glioblastoma specimens for exploring intra- and inter-individual spectra of drug resistance profiles in vitro. In a personalized setting, we explored whether differences in pharmacological sensitivity among subclones could be employed to predict drug-dependent changes to the clonal composition of tumors. Results Subclones from individual tumors exhibited a remarkable heterogeneity of drug resistance to a library of potential anti-glioblastoma compounds. A more comprehensive intra-tumoral analysis revealed that stable genetic and phenotypic characteristics of co-existing subclones could be correlated with distinct drug sensitivity profiles. The data obtained from differential drug response analysis could be employed to predict clonal population shifts within the naïve parental tumor in vitro and in orthotopic xenografts. Furthermore, the value of pharmacological profiles could be shown for establishing rational strategies for individualized secondary lines of treatment. Conclusions Our data provide a previously unrecognized strategy for revealing functional consequences of intra-tumor heterogeneity by enabling predictive modeling of treatment-related subclone dynamics in human glioblastoma. PMID:27521447

Validation of predicted exponential concentration profiles of chemicals in soils

International Nuclear Information System (INIS)

Hollander, Anne; Baijens, Iris; Ragas, Ad; Huijbregts, Mark; Meent, Dik van de

2007-01-01

Multimedia mass balance models assume well-mixed homogeneous compartments. Particularly for soils, this does not correspond to reality, which results in potentially large uncertainties in estimates of transport fluxes from soils. A theoretically expected exponential decrease model of chemical concentrations with depth has been proposed, but hardly tested against empirical data. In this paper, we explored the correspondence between theoretically predicted soil concentration profiles and 84 field measured profiles. In most cases, chemical concentrations in soils appear to decline exponentially with depth, and values for the chemical specific soil penetration depth (d p ) are predicted within one order of magnitude. Over all, the reliability of multimedia models will improve when they account for depth-dependent soil concentrations, so we recommend to take into account the described theoretical exponential decrease model of chemical concentrations with depth in chemical fate studies. In this model the d p -values should estimated be either based on local conditions or on a fixed d p -value, which we recommend to be 10 cm for chemicals with a log K ow > 3. - Multimedia mass model predictions will improve when taking into account depth dependent soil concentrations

Connecting clinical and actuarial prediction with rule-based methods

NARCIS (Netherlands)

Fokkema, M.; Smits, N.; Kelderman, H.; Penninx, B.W.J.H.

2015-01-01

Meta-analyses comparing the accuracy of clinical versus actuarial prediction have shown actuarial methods to outperform clinical methods, on average. However, actuarial methods are still not widely used in clinical practice, and there has been a call for the development of actuarial prediction

CAsubtype: An R Package to Identify Gene Sets Predictive of Cancer Subtypes and Clinical Outcomes.

Science.gov (United States)

Kong, Hualei; Tong, Pan; Zhao, Xiaodong; Sun, Jielin; Li, Hua

2018-03-01

In the past decade, molecular classification of cancer has gained high popularity owing to its high predictive power on clinical outcomes as compared with traditional methods commonly used in clinical practice. In particular, using gene expression profiles, recent studies have successfully identified a number of gene sets for the delineation of cancer subtypes that are associated with distinct prognosis. However, identification of such gene sets remains a laborious task due to the lack of tools with flexibility, integration and ease of use. To reduce the burden, we have developed an R package, CAsubtype, to efficiently identify gene sets predictive of cancer subtypes and clinical outcomes. By integrating more than 13,000 annotated gene sets, CAsubtype provides a comprehensive repertoire of candidates for new cancer subtype identification. For easy data access, CAsubtype further includes the gene expression and clinical data of more than 2000 cancer patients from TCGA. CAsubtype first employs principal component analysis to identify gene sets (from user-provided or package-integrated ones) with robust principal components representing significantly large variation between cancer samples. Based on these principal components, CAsubtype visualizes the sample distribution in low-dimensional space for better understanding of the distinction between samples and classifies samples into subgroups with prevalent clustering algorithms. Finally, CAsubtype performs survival analysis to compare the clinical outcomes between the identified subgroups, assessing their clinical value as potentially novel cancer subtypes. In conclusion, CAsubtype is a flexible and well-integrated tool in the R environment to identify gene sets for cancer subtype identification and clinical outcome prediction. Its simple R commands and comprehensive data sets enable efficient examination of the clinical value of any given gene set, thus facilitating hypothesis generating and testing in biological and

Clinical Trials of Precision Medicine through Molecular Profiling: Focus on Breast Cancer.

Science.gov (United States)

Zardavas, Dimitrios; Piccart-Gebhart, Martine

2015-01-01

High-throughput technologies of molecular profiling in cancer, such as gene-expression profiling and next-generation sequencing, are expanding our knowledge of the molecular landscapes of several cancer types. This increasing knowledge coupled with the development of several molecularly targeted agents hold the promise for personalized cancer medicine to be fully realized. Moreover, an expanding armamentarium of targeted agents has been approved for the treatment of specific molecular cancer subgroups in different diagnoses. According to this paradigm, treatment selection should be dictated by the specific molecular aberrations found in each patient's tumor. The classical clinical trials paradigm of patients' eligibility being based on clinicopathologic parameters is being abandoned, with current clinical trials enrolling patients on the basis of specific molecular aberrations. New, innovative trial designs have been generated to better tackle the multiple challenges induced by the increasing molecular fragmentation of cancer, namely: (1) longitudinal cohort studies with or without downstream trials, (2) studies assessing the clinical utility of molecular profiling, (3) master or umbrella trials, (4) basket trials, (5) N-of-1 trials, and (6) adaptive design trials. This article provides an overview of the challenges for clinical trials in the era of molecular profiling of cancer. Subsequently, innovative trial designs with respective examples and their potential to expedite efficient clinical development of targeted anticancer agents is discussed.

ProFile Vortex and Vortex Blue Nickel-Titanium Rotary Instruments after Clinical Use.

Science.gov (United States)

Shen, Ya; Zhou, Huimin; Coil, Jeffrey M; Aljazaeri, Bassim; Buttar, Rene; Wang, Zhejun; Zheng, Yu-feng; Haapasalo, Markus

2015-06-01

The aim of this study was to analyze the incidence and mode of ProFile Vortex and Vortex Blue instrument defects after clinical use in a graduate endodontic program and to examine the impact of clinical use on the instruments' metallurgical properties. A total of 330 ProFile Vortex and 1136 Vortex Blue instruments from the graduate program were collected after each had been used in 3 teeth. The incidence and type of instrument defects were analyzed. The lateral surfaces and fracture surfaces of the fractured files were examined by using scanning electron microscopy. Unused and used instruments were examined by full and partial differential scanning calorimetry. No fractures were observed in the 330 ProFile Vortex instruments, whereas 20 (6.1%) revealed bent or blunt defects. Only 2 of the 1136 Vortex Blue files fractured during clinical use. The cause of fracture was shear stress. The fractures occurred at the tip end of the spirals. Only 1.8% (21 of 1136) of the Vortex Blue files had blunt tips. Austenite-finish temperatures were very similar for unused and used ProFile Vortex files and were all greater than 50°C. The austenite-finish temperatures of used and unused Vortex Blue files (38.5°C) were lower than those in ProFile Vortex instruments (P Vortex Blue files had an obvious 2-stage transformation, martensite-to-R phase and R-to-austenite phase. The trends of differential scanning calorimetry plots of unused Vortex Blue instruments and clinically used instruments were very similar. The risk of ProFile Vortex and Vortex Blue instrument fracture is very low when instruments are discarded after clinical use in the graduate endodontic program. The Vortex Blue files have metallurgical behavior different from ProFile Vortex instruments. Copyright © 2015 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

The clinical and anthropometric profile of undernourished children ...

African Journals Online (AJOL)

Background. Although Botswana is a middle-income country, undernutrition among children younger than 5 years of age is still seen in various parts of the country. There is little information on the clinical and anthropometric profile of undernourished children in this age group admitted to hospitals in Francistown, Botswana.

Predicting the educational performance of Isfahan University students of medical sciences based on their behaviour profile, mental health and demographic characteristic.

Science.gov (United States)

Samouei, Rahele; Fooladvand, Maryam; Janghorban, Shahla; Khorvash, Fariba

2015-01-01

The issue of students' academic failure is one of the most important educational, economic, and social issues. Cognizance of the factors related to academic downfall is so efficient in its prevention and control and leads to protecting governmental assets and labor force. In order to achieve this goal, this study intends to determine the predictive factors of the students' academic performance in Isfahan University of Medical Sciences in terms of their personality profile, mental health, and their demographic characteristics. This study was a descriptive-correlation study on 771 students who entered Isfahan University of Medical Sciences between 2005 and 2007. The information was gathered through using the students' educational and clinical files (for measuring personality characteristics and mental health) and SAMA Software (To get the mean scores). Minnesota Multiphasic Personality Inventory short form and General Health Questionnaire were used for collecting clinical data. The data were analyzed using SPSS 15 (stepwise regression coefficient, variance analysis, Student's t-test, and Spearman correlation coefficient). The results showed that the aforementioned students obtained a normal average for their personality profile and mental health indicators. Of all the reviewed variables, education, age, gender, depression, and hypochondria were the predictive factors of the students' educational performance. It could be concluded that some of the personality features, mental health indicators, and personality profile play such a significant role in the students' educational life that the disorder in any of them affects the students' educational performance and academic failure.

Profile control simulations and experiments on TCV: a controller test environment and results using a model-based predictive controller

Science.gov (United States)

Maljaars, E.; Felici, F.; Blanken, T. C.; Galperti, C.; Sauter, O.; de Baar, M. R.; Carpanese, F.; Goodman, T. P.; Kim, D.; Kim, S. H.; Kong, M.; Mavkov, B.; Merle, A.; Moret, J. M.; Nouailletas, R.; Scheffer, M.; Teplukhina, A. A.; Vu, N. M. T.; The EUROfusion MST1-team; The TCV-team

2017-12-01

The successful performance of a model predictive profile controller is demonstrated in simulations and experiments on the TCV tokamak, employing a profile controller test environment. Stable high-performance tokamak operation in hybrid and advanced plasma scenarios requires control over the safety factor profile (q-profile) and kinetic plasma parameters such as the plasma beta. This demands to establish reliable profile control routines in presently operational tokamaks. We present a model predictive profile controller that controls the q-profile and plasma beta using power requests to two clusters of gyrotrons and the plasma current request. The performance of the controller is analyzed in both simulation and TCV L-mode discharges where successful tracking of the estimated inverse q-profile as well as plasma beta is demonstrated under uncertain plasma conditions and the presence of disturbances. The controller exploits the knowledge of the time-varying actuator limits in the actuator input calculation itself such that fast transitions between targets are achieved without overshoot. A software environment is employed to prepare and test this and three other profile controllers in parallel in simulations and experiments on TCV. This set of tools includes the rapid plasma transport simulator RAPTOR and various algorithms to reconstruct the plasma equilibrium and plasma profiles by merging the available measurements with model-based predictions. In this work the estimated q-profile is merely based on RAPTOR model predictions due to the absence of internal current density measurements in TCV. These results encourage to further exploit model predictive profile control in experiments on TCV and other (future) tokamaks.

Response-predictive gene expression profiling of glioma progenitor cells in vitro.

Directory of Open Access Journals (Sweden)

Sylvia Moeckel

Full Text Available High-grade gliomas are amongst the most deadly human tumors. Treatment results are disappointing. Still, in several trials around 20% of patients respond to therapy. To date, diagnostic strategies to identify patients that will profit from a specific therapy do not exist.In this study, we used serum-free short-term treated in vitro cell cultures to predict treatment response in vitro. This approach allowed us (a to enrich specimens for brain tumor initiating cells and (b to confront cells with a therapeutic agent before expression profiling.As a proof of principle we analyzed gene expression in 18 short-term serum-free cultures of high-grade gliomas enhanced for brain tumor initiating cells (BTIC before and after in vitro treatment with the tyrosine kinase inhibitor Sunitinib. Profiles from treated progenitor cells allowed to predict therapy-induced impairment of proliferation in vitro.For the tyrosine kinase inhibitor Sunitinib used in this dataset, the approach revealed additional predictive information in comparison to the evaluation of classical signaling analysis.

Profiles of verbal working memory growth predict speech and language development in children with cochlear implants.

Science.gov (United States)

Kronenberger, William G; Pisoni, David B; Harris, Michael S; Hoen, Helena M; Xu, Huiping; Miyamoto, Richard T

2013-06-01

Verbal short-term memory (STM) and working memory (WM) skills predict speech and language outcomes in children with cochlear implants (CIs) even after conventional demographic, device, and medical factors are taken into account. However, prior research has focused on single end point outcomes as opposed to the longitudinal process of development of verbal STM/WM and speech-language skills. In this study, the authors investigated relations between profiles of verbal STM/WM development and speech-language development over time. Profiles of verbal STM/WM development were identified through the use of group-based trajectory analysis of repeated digit span measures over at least a 2-year time period in a sample of 66 children (ages 6-16 years) with CIs. Subjects also completed repeated assessments of speech and language skills during the same time period. Clusters representing different patterns of development of verbal STM (digit span forward scores) were related to the growth rate of vocabulary and language comprehension skills over time. Clusters representing different patterns of development of verbal WM (digit span backward scores) were related to the growth rate of vocabulary and spoken word recognition skills over time. Different patterns of development of verbal STM/WM capacity predict the dynamic process of development of speech and language skills in this clinical population.

Correlation of clinical predictions and surgical results in maxillary superior repositioning.

Science.gov (United States)

Tabrizi, Reza; Zamiri, Barbad; Kazemi, Hamidreza

2014-05-01

This is a prospective study to evaluate the accuracy of clinical predictions related to surgical results in subjects who underwent maxillary superior repositioning without anterior-posterior movement. Surgeons' predictions according to clinical (tooth show at rest and at the maximum smile) and cephalometric evaluation were documented for the amount of maxillary superior repositioning. Overcorrection or undercorrection was documented for every subject 1 year after the operations. Receiver operating characteristic curve test was used to find a cutoff point in prediction errors and to determine positive predictive value (PPV) and negative predictive value. Forty subjects (14 males and 26 females) were studied. Results showed a significant difference between changes in the tooth show at rest and at the maximum smile line before and after surgery. Analysis of the data demonstrated no correlation between the predictive data and the surgical results. The incidence of undercorrection (25%) was more common than overcorrection (7.5%). The cutoff point for errors in predictions was 5 mm for tooth show at rest and 15 mm at the maximum smile. When the amount of the presurgical tooth show at rest was more than 5 mm, 50.5% of clinical predictions did not match the clinical results (PPV), and 75% of clinical predictions showed the same results when the tooth show was less than 5 mm (negative predictive value). When the amount of presurgical tooth shown in the maximum smile line was more than 15 mm, 75% of clinical predictions did not match with clinical results (PPV), and 25% of the predictions had the same results because the tooth show at the maximum smile was lower than 15 mm. Clinical predictions according to the tooth show at rest and at the maximum smile have a poor correlation with clinical results in maxillary superior repositioning for vertical maxillary excess. The risk of errors in predictions increased when the amount of superior repositioning of the maxilla increased

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.

Predicting Post-Editor Profiles from the Translation Process

DEFF Research Database (Denmark)

Singla, Karan; Orrego-Carmona, David; Gonzales, Ashleigh Rhea

2014-01-01

The purpose of the current investigation is to predict post-editor profiles based on user behaviour and demographics using machine learning techniques to gain a better understanding of post-editor styles. Our study extracts process unit features from the CasMaCat LS14 database from the CRITT...... of translation process features. The classification and clustering of participants resulting from our study suggest this type of exploration could be used as a tool to develop new translation tool features or customization possibilities....

Nursing Diagnosis Risk for falls: prevalence and clinical profile of hospitalized patients.

Science.gov (United States)

Luzia, Melissa de Freitas; Victor, Marco Antonio de Goes; Lucena, Amália de Fátima

2014-01-01

to identify the prevalence of the Nursing Diagnosis (ND) Risk for falls in the hospitalizations of adult patients in clinical and surgical units, to characterize the clinical profile and to identify the risk factors of the patients with this ND. a cross-sectional study with 174 patients. The data was collected from the computerized nursing care prescriptions system and on-line hospital records, and analyzed statistically. the prevalence of the ND Risk for falls was 4%. The patients' profile indicated older adults, males (57%), those hospitalized in the clinical units (63.2%), with a median length of hospitalization of 20 (10-24) days, with neurological illnesses (26%), cardio-vascular illnesses (74.1%) and various co-morbidities (3±1.8). The prevalent risk factors were neurological alterations (43.1%), impaired mobility (35.6%) and extremes of age (10.3%). the findings contributed to evidencing the profile of the patients with a risk of falling hospitalized in clinical and surgical wards, which favors the planning of interventions for preventing this adverse event.

Changing clinical profile of acute rheumatic fever and rheumatic recurrence

International Nuclear Information System (INIS)

Sheikh, A.M.; Sadiq, M.; Rehman, A.U.

2016-01-01

Background: Clinical profile of acute rheumatic fever and rheumatic recurrence seems to have changed in countries where rheumatic fever is still endemic. The objectives of this study were to compare clinical profile and outcome of patients suffering initial and recurrent episodes of acute rheumatic fever in children. Methods: This prospective study was conducted in two tertiary care hospitals from January to June 2011. The diagnosis was based on the modified Jones criteria. Sixty children were included in the study, 15 having first episode of rheumatic fever and 45 with rheumatic recurrence. The severity of carditis was assessed by Clinical and echocardiography means. Results: Carditis was the commonest presentation in both first (80 percentage) and recurrent attacks (100 percentage). Arthritis was seen in 60 percentage of children with first episode and in 26.7 percentage with recurrence. The frequency of subcutaneous nodules, invariably associated with carditis, was very high (33.3 percentage in the first and 48.3 percentage in recurrent episodes). Carditis was generally mild during first episode (53.3 percentage) and severe with rheumatic recurrence (55.6 percentage). There was no death in either group. One patient with severe mitral regurgitation and rheumatic recurrence underwent mitral valve repair for intractable heart failure. Conclusion: Clinical profile of rheumatic recurrence and acute rheumatic fever has changed. Rheumatic recurrence is associated with severe carditis. Carditis is more common than arthritis even in the first attack. Sub-cutaneous nodules are a frequent finding invariably associated with carditis. (author)

Clinical Prediction Models for Cardiovascular Disease: Tufts Predictive Analytics and Comparative Effectiveness Clinical Prediction Model Database.

Science.gov (United States)

Wessler, Benjamin S; Lai Yh, Lana; Kramer, Whitney; Cangelosi, Michael; Raman, Gowri; Lutz, Jennifer S; Kent, David M

2015-07-01

Clinical prediction models (CPMs) estimate the probability of clinical outcomes and hold the potential to improve decision making and individualize care. For patients with cardiovascular disease, there are numerous CPMs available although the extent of this literature is not well described. We conducted a systematic review for articles containing CPMs for cardiovascular disease published between January 1990 and May 2012. Cardiovascular disease includes coronary heart disease, heart failure, arrhythmias, stroke, venous thromboembolism, and peripheral vascular disease. We created a novel database and characterized CPMs based on the stage of development, population under study, performance, covariates, and predicted outcomes. There are 796 models included in this database. The number of CPMs published each year is increasing steadily over time. Seven hundred seventeen (90%) are de novo CPMs, 21 (3%) are CPM recalibrations, and 58 (7%) are CPM adaptations. This database contains CPMs for 31 index conditions, including 215 CPMs for patients with coronary artery disease, 168 CPMs for population samples, and 79 models for patients with heart failure. There are 77 distinct index/outcome pairings. Of the de novo models in this database, 450 (63%) report a c-statistic and 259 (36%) report some information on calibration. There is an abundance of CPMs available for a wide assortment of cardiovascular disease conditions, with substantial redundancy in the literature. The comparative performance of these models, the consistency of effects and risk estimates across models and the actual and potential clinical impact of this body of literature is poorly understood. © 2015 American Heart Association, Inc.

A probabilistic model to predict clinical phenotypic traits from genome sequencing.

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Chen, Yun-Ching; Douville, Christopher; Wang, Cheng; Niknafs, Noushin; Yeo, Grace; Beleva-Guthrie, Violeta; Carter, Hannah; Stenson, Peter D; Cooper, David N; Li, Biao; Mooney, Sean; Karchin, Rachel

2014-09-01

Genetic screening is becoming possible on an unprecedented scale. However, its utility remains controversial. Although most variant genotypes cannot be easily interpreted, many individuals nevertheless attempt to interpret their genetic information. Initiatives such as the Personal Genome Project (PGP) and Illumina's Understand Your Genome are sequencing thousands of adults, collecting phenotypic information and developing computational pipelines to identify the most important variant genotypes harbored by each individual. These pipelines consider database and allele frequency annotations and bioinformatics classifications. We propose that the next step will be to integrate these different sources of information to estimate the probability that a given individual has specific phenotypes of clinical interest. To this end, we have designed a Bayesian probabilistic model to predict the probability of dichotomous phenotypes. When applied to a cohort from PGP, predictions of Gilbert syndrome, Graves' disease, non-Hodgkin lymphoma, and various blood groups were accurate, as individuals manifesting the phenotype in question exhibited the highest, or among the highest, predicted probabilities. Thirty-eight PGP phenotypes (26%) were predicted with area-under-the-ROC curve (AUC)>0.7, and 23 (15.8%) of these were statistically significant, based on permutation tests. Moreover, in a Critical Assessment of Genome Interpretation (CAGI) blinded prediction experiment, the models were used to match 77 PGP genomes to phenotypic profiles, generating the most accurate prediction of 16 submissions, according to an independent assessor. Although the models are currently insufficiently accurate for diagnostic utility, we expect their performance to improve with growth of publicly available genomics data and model refinement by domain experts.

Clinical and pulmonary functions profiling of patients with chronic obstructive pulmonary disease experiencing frequent acute exacerbations

Directory of Open Access Journals (Sweden)

Prem Parkash Gupta

2018-01-01

Full Text Available Purpose: The present study aimed at clinical and pulmonary functions profiling of patients with chronic obstructive pulmonary disease (COPD to anticipate future exacerbations. Methods: The study included 80 COPD patients; 40 patients had ≥2 acute exacerbations during preceding 1 year (frequent exacerbation [FECOPD] group and 40 patients had <2 acute exacerbations during preceding 1 year (infrequent exacerbation [I-FECOPD] group. Clinical profile, sputum microbiology, blood gas analysis, spirometric indices, and diffusion capacity (transfer test variables were assessed. Groups' comparison was performed using an independent t-test for numeric scale parameters and Chi-square test for nominal parameters. Pearson's and Spearman's correlation coefficients were derived for numeric scale parameters and numeric nominal parameters, respectively. Multinomial logistic regression analysis was done using SPSS software. Results: FECOPD group contained younger patients than in I-FECOPD group although the difference was not statistically significant. There was no significant difference between two groups regarding smoking pack-years and duration of illness. FECOPD group had significantly more expectoration score and Modified Medical Research Council dyspnea scores. Cough score and wheeze score did not differ significantly between two groups. More patients in FECOPD group (12/40 vs. 4/40 had lower airway bacterial colonization. Arterial blood gas parameters were more deranged in FECOPD group. Spirometric indices (forced expiratory volume during 1st s as well as transfer test (both diffusing capacity for carbon monoxide and transfer coefficient of the lung values were significantly reduced in FECOPD group. Conclusions: The patients in FECOPD group had clinical, spirometric, and transfer test profiling suggestive of a severe COPD phenotype, the recognition will help in predicting future exacerbations and a better management.

TargetNet: a web service for predicting potential drug-target interaction profiling via multi-target SAR models

Science.gov (United States)

Yao, Zhi-Jiang; Dong, Jie; Che, Yu-Jing; Zhu, Min-Feng; Wen, Ming; Wang, Ning-Ning; Wang, Shan; Lu, Ai-Ping; Cao, Dong-Sheng

2016-05-01

Drug-target interactions (DTIs) are central to current drug discovery processes and public health fields. Analyzing the DTI profiling of the drugs helps to infer drug indications, adverse drug reactions, drug-drug interactions, and drug mode of actions. Therefore, it is of high importance to reliably and fast predict DTI profiling of the drugs on a genome-scale level. Here, we develop the TargetNet server, which can make real-time DTI predictions based only on molecular structures, following the spirit of multi-target SAR methodology. Naïve Bayes models together with various molecular fingerprints were employed to construct prediction models. Ensemble learning from these fingerprints was also provided to improve the prediction ability. When the user submits a molecule, the server will predict the activity of the user's molecule across 623 human proteins by the established high quality SAR model, thus generating a DTI profiling that can be used as a feature vector of chemicals for wide applications. The 623 SAR models related to 623 human proteins were strictly evaluated and validated by several model validation strategies, resulting in the AUC scores of 75-100 %. We applied the generated DTI profiling to successfully predict potential targets, toxicity classification, drug-drug interactions, and drug mode of action, which sufficiently demonstrated the wide application value of the potential DTI profiling. The TargetNet webserver is designed based on the Django framework in Python, and is freely accessible at http://targetnet.scbdd.com.

TargetNet: a web service for predicting potential drug-target interaction profiling via multi-target SAR models.

Science.gov (United States)

Yao, Zhi-Jiang; Dong, Jie; Che, Yu-Jing; Zhu, Min-Feng; Wen, Ming; Wang, Ning-Ning; Wang, Shan; Lu, Ai-Ping; Cao, Dong-Sheng

2016-05-01

Drug-target interactions (DTIs) are central to current drug discovery processes and public health fields. Analyzing the DTI profiling of the drugs helps to infer drug indications, adverse drug reactions, drug-drug interactions, and drug mode of actions. Therefore, it is of high importance to reliably and fast predict DTI profiling of the drugs on a genome-scale level. Here, we develop the TargetNet server, which can make real-time DTI predictions based only on molecular structures, following the spirit of multi-target SAR methodology. Naïve Bayes models together with various molecular fingerprints were employed to construct prediction models. Ensemble learning from these fingerprints was also provided to improve the prediction ability. When the user submits a molecule, the server will predict the activity of the user's molecule across 623 human proteins by the established high quality SAR model, thus generating a DTI profiling that can be used as a feature vector of chemicals for wide applications. The 623 SAR models related to 623 human proteins were strictly evaluated and validated by several model validation strategies, resulting in the AUC scores of 75-100 %. We applied the generated DTI profiling to successfully predict potential targets, toxicity classification, drug-drug interactions, and drug mode of action, which sufficiently demonstrated the wide application value of the potential DTI profiling. The TargetNet webserver is designed based on the Django framework in Python, and is freely accessible at http://targetnet.scbdd.com .

The clinical utility of lipid profile and positive troponin in predicting future cardiac events

Directory of Open Access Journals (Sweden)

Arun Kumar

2012-02-01

Full Text Available Objective: To study the usefulness of traditional lipid profile levels in screening subjects who had developed chest pain due to cardiac event as indicated by a positive troponin I (TnI test. Methods: In this retrospective study data of the 740 patients presented to the emergency department with symptoms of cardiac ischemia that underwent both troponin and lipid profiles tests were compared with the lipid profiles of 411 normal healthy subjects (controls. The troponin was detected qualitatively when a specimen contains TnI above the 99th percentile (TnI >0.5 ng/ mL. The total cholesterol (TC, high density lipoproteins (HDL, very low density lipoproteins (VLDL, and triacyl glycerol (TG levels were also analyzed and low density lipoprotein level (LDL was calculated using Friedewald ’s formula. Results: Patients with chest pain and positive troponin test (with confirmed cardiac event were found to have significantly elevated levels of TC, TG, LDL and significantly reduced HDL levels when compared to the patients who experienced only chest pain (negative troponin and healthy controls. Conclusions: Traditional lipid profile levels still can be used in screening populations to identify the subjects with high risk of developing cardiac event which is identified by highly sensitive and specific positive troponin test.

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. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

A predictable Java profile

DEFF Research Database (Denmark)

Bøgholm, Thomas; Hansen, Rene Rydhof; Ravn, Anders Peter

2009-01-01

A Java profile suitable for development of high integrity embedded systems is presented. It is based on event handlers which are grouped in missions and equipped with respectively private handler memory and shared mission memory. This is a result of our previous work on developing a Java profile......, and is directly inspired by interactions with the Open Group on their on-going work on a safety critical Java profile (JSR-302). The main contribution is an arrangement of the class hierarchy such that the proposal is a generalization of Real-Time Specification for Java (RTSJ). A further contribution...

Prospective Genomic Profiling of Prostate Cancer Across Disease States Reveals Germline and Somatic Alterations That May Affect Clinical Decision Making.

Science.gov (United States)

Abida, Wassim; Armenia, Joshua; Gopalan, Anuradha; Brennan, Ryan; Walsh, Michael; Barron, David; Danila, Daniel; Rathkopf, Dana; Morris, Michael; Slovin, Susan; McLaughlin, Brigit; Curtis, Kristen; Hyman, David M; Durack, Jeremy C; Solomon, Stephen B; Arcila, Maria E; Zehir, Ahmet; Syed, Aijazuddin; Gao, Jianjiong; Chakravarty, Debyani; Vargas, Hebert Alberto; Robson, Mark E; Joseph, Vijai; Offit, Kenneth; Donoghue, Mark T A; Abeshouse, Adam A; Kundra, Ritika; Heins, Zachary J; Penson, Alexander V; Harris, Christopher; Taylor, Barry S; Ladanyi, Marc; Mandelker, Diana; Zhang, Liying; Reuter, Victor E; Kantoff, Philip W; Solit, David B; Berger, Michael F; Sawyers, Charles L; Schultz, Nikolaus; Scher, Howard I

2017-07-01

A long natural history and a predominant osseous pattern of metastatic spread are impediments to the adoption of precision medicine in patients with prostate cancer. To establish the feasibility of clinical genomic profiling in the disease, we performed targeted deep sequencing of tumor and normal DNA from patients with locoregional, metastatic non-castrate, and metastatic castration-resistant prostate cancer (CRPC). Patients consented to genomic analysis of their tumor and germline DNA. A hybridization capture-based clinical assay was employed to identify single nucleotide variations, small insertions and deletions, copy number alterations and structural rearrangements in over 300 cancer-related genes in tumors and matched normal blood. We successfully sequenced 504 tumors from 451 patients with prostate cancer. Potentially actionable alterations were identified in DNA damage repair (DDR), PI3K, and MAP kinase pathways. 27% of patients harbored a germline or a somatic alteration in a DDR gene that may predict for response to PARP inhibition. Profiling of matched tumors from individual patients revealed that somatic TP53 and BRCA2 alterations arose early in tumors from patients who eventually developed metastatic disease. In contrast, comparative analysis across disease states revealed that APC alterations were enriched in metastatic tumors, while ATM alterations were specifically enriched in CRPC. Through genomic profiling of prostate tumors representing the disease clinical spectrum, we identified a high frequency of potentially actionable alterations and possible drivers of disease initiation, metastasis and castration-resistance. Our findings support the routine use of tumor and germline DNA profiling for patients with advanced prostate cancer, for the purpose of guiding enrollment in targeted clinical trials and counseling families at increased risk of malignancy.

Considerations for automated machine learning in clinical metabolic profiling: Altered homocysteine plasma concentration associated with metformin exposure.

Science.gov (United States)

Orlenko, Alena; Moore, Jason H; Orzechowski, Patryk; Olson, Randal S; Cairns, Junmei; Caraballo, Pedro J; Weinshilboum, Richard M; Wang, Liewei; Breitenstein, Matthew K

2018-01-01

With the maturation of metabolomics science and proliferation of biobanks, clinical metabolic profiling is an increasingly opportunistic frontier for advancing translational clinical research. Automated Machine Learning (AutoML) approaches provide exciting opportunity to guide feature selection in agnostic metabolic profiling endeavors, where potentially thousands of independent data points must be evaluated. In previous research, AutoML using high-dimensional data of varying types has been demonstrably robust, outperforming traditional approaches. However, considerations for application in clinical metabolic profiling remain to be evaluated. Particularly, regarding the robustness of AutoML to identify and adjust for common clinical confounders. In this study, we present a focused case study regarding AutoML considerations for using the Tree-Based Optimization Tool (TPOT) in metabolic profiling of exposure to metformin in a biobank cohort. First, we propose a tandem rank-accuracy measure to guide agnostic feature selection and corresponding threshold determination in clinical metabolic profiling endeavors. Second, while AutoML, using default parameters, demonstrated potential to lack sensitivity to low-effect confounding clinical covariates, we demonstrated residual training and adjustment of metabolite features as an easily applicable approach to ensure AutoML adjustment for potential confounding characteristics. Finally, we present increased homocysteine with long-term exposure to metformin as a potentially novel, non-replicated metabolite association suggested by TPOT; an association not identified in parallel clinical metabolic profiling endeavors. While warranting independent replication, our tandem rank-accuracy measure suggests homocysteine to be the metabolite feature with largest effect, and corresponding priority for further translational clinical research. Residual training and adjustment for a potential confounding effect by BMI only slightly modified

Metabolic profile of clinically severe obese patients.

Science.gov (United States)

Faria, Silvia Leite; Faria, Orlando Pereira; Menezes, Caroline Soares; de Gouvêa, Heloisa Rodrigues; de Almeida Cardeal, Mariane

2012-08-01

Since low basal metabolic rate (BMR) is a risk factor for weight regain, it is important to measure BMR before bariatric surgery. We aimed to evaluate the BMR among clinically severe obese patients preoperatively. We compared it with that of the control group, with predictive formulas and correlated it with body composition. We used indirect calorimetry (IC) to collect BMR data and multifrequency bioelectrical impedance to collect body composition data. Our sample population consisted of 193 patients of whom 130 were clinically severe obese and 63 were normal/overweight individuals. BMR results were compared with the following predictive formulas: Harris-Benedict (HBE), Bobbioni-Harsch (BH), Cunningham (CUN), Mifflin-St. Jeor (MSJE), and Horie-Waitzberg & Gonzalez (HW & G). This study was approved by the Ethics Committee for Research of the University of Brasilia. Statistical analysis was used to compare and correlate variables. Clinically severe obese patients had higher absolute BMR values and lower adjusted BMR values (p BMR were found in both groups. Among the clinically severe obese patients, the formulas of HW & G and HBE overestimated BMR values (p = 0.0002 and p = 0.0193, respectively), while the BH and CUN underestimated this value; only the MSJE formulas showed similar results to those of IC. The clinically severe obese patients showed low BMR levels when adjusted per kilogram per body weight. Body composition may influence BMR. The use of the MSJE formula may be helpful in those cases where it is impossible to use IC.

Prediction of Process-Induced Distortions in L-Shaped Composite Profiles Using Path-Dependent Constitutive Law

Science.gov (United States)

Ding, Anxin; Li, Shuxin; Wang, Jihui; Ni, Aiqing; Sun, Liangliang; Chang, Lei

2016-10-01

In this paper, the corner spring-in angles of AS4/8552 L-shaped composite profiles with different thicknesses are predicted using path-dependent constitutive law with the consideration of material properties variation due to phase change during curing. The prediction accuracy mainly depends on the properties in the rubbery and glassy states obtained by homogenization method rather than experimental measurements. Both analytical and finite element (FE) homogenization methods are applied to predict the overall properties of AS4/8552 composite. The effect of fiber volume fraction on the properties is investigated for both rubbery and glassy states using both methods. And the predicted results are compared with experimental measurements for the glassy state. Good agreement is achieved between the predicted results and available experimental data, showing the reliability of the homogenization method. Furthermore, the corner spring-in angles of L-shaped composite profiles are measured experimentally and the reliability of path-dependent constitutive law is validated as well as the properties prediction by FE homogenization method.

Predicting adverse drug reaction profiles by integrating protein interaction networks with drug structures.

Science.gov (United States)

Huang, Liang-Chin; Wu, Xiaogang; Chen, Jake Y

2013-01-01

The prediction of adverse drug reactions (ADRs) has become increasingly important, due to the rising concern on serious ADRs that can cause drugs to fail to reach or stay in the market. We proposed a framework for predicting ADR profiles by integrating protein-protein interaction (PPI) networks with drug structures. We compared ADR prediction performances over 18 ADR categories through four feature groups-only drug targets, drug targets with PPI networks, drug structures, and drug targets with PPI networks plus drug structures. The results showed that the integration of PPI networks and drug structures can significantly improve the ADR prediction performance. The median AUC values for the four groups were 0.59, 0.61, 0.65, and 0.70. We used the protein features in the best two models, "Cardiac disorders" (median-AUC: 0.82) and "Psychiatric disorders" (median-AUC: 0.76), to build ADR-specific PPI networks with literature supports. For validation, we examined 30 drugs withdrawn from the U.S. market to see if our approach can predict their ADR profiles and explain why they were withdrawn. Except for three drugs having ADRs in the categories we did not predict, 25 out of 27 withdrawn drugs (92.6%) having severe ADRs were successfully predicted by our approach. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Gene Expression Profile of BRCAness That Predicts for Responsiveness to Platinum and PARP Inhibitors

Science.gov (United States)

2017-02-01

affecting the function of Fanconi Anemia (FA) genes ( FANCA /B/C/D2/E/F/G/I/J/L/M, PALB2) or DNA damage response genes involved in HR 5 (ATM, ATR...Award Number: W81XWH-10-1-0585 TITLE: A Gene Expression Profile of BRCAness That Predicts for Responsiveness to Platinum and PARP Inhibitors...To) 15 July 2010 – 2 Nov.2016 4. TITLE AND SUBTITLE A Gene Expression Profile of BRCAness That Predicts for Responsiveness to Platinum and PARP

Plasma metabolic profiling of dairy cows affected with clinical ketosis using LC/MS technology.

Science.gov (United States)

Li, Y; Xu, C; Xia, C; Zhang, Hy; Sun, Lw; Gao, Y

2014-01-01

Ketosis in dairy cattle is an important metabolic disorder. Currently, the plasma metabolic profile of ketosis as determined using liquid chromatography-mass spectrometry (LC/MS) has not been reported. To investigate plasma metabolic profiles from cows with clinical ketosis in comparison to control cows. Twenty Holstein dairy cows were divided into two groups based on clinical signs and plasma β-hydroxybutyric acid and glucose concentrations 7-21 days postpartum: clinical ketosis and control cows. Plasma metabolic profiles were analyzed using LC/MS. Data were processed using principal component analysis and orthogonal partial least-squares discriminant analysis. Compared to control cows, the levels of valine, glycine, glycocholic, tetradecenoic acid, and palmitoleic acid increased significantly in clinical ketosis. On the other hand, the levels of arginine, aminobutyric acid, leucine/isoleucine, tryptophan, creatinine, lysine, norcotinine, and undecanoic acid decreased markedly. Our results showed that the metabolic changes in cows with clinical ketosis involve complex metabolic networks and signal transduction. These results are important for future studies elucidating the pathogenesis, diagnosis, and prevention of clinical ketosis in dairy cows.

Metabolite Profiles of Diabetes Risk

OpenAIRE

Gerszten, Robert E.

2013-01-01

Metabolic diseases present particular difficulty for clinicians because they are often present for years before becoming clinically apparent. We investigated whether metabolite profiles can predict the development of diabetes in the Framingham Heart Study. Five branched-chain and aromatic amino acids had highly-significant associations with future diabetes, while a combination of three amino acids strongly predicted future diabetes by up to 12 years (>5-fold increased risk for individuals in ...

(1)H-Nuclear magnetic resonance-based plasma metabolic profiling of dairy cows with clinical and subclinical ketosis.

Science.gov (United States)

Sun, L W; Zhang, H Y; Wu, L; Shu, S; Xia, C; Xu, C; Zheng, J S

2014-03-01

The purpose of this study was to assess the metabolic profile of plasma samples from cows with clinical and subclinical ketosis. According to clinical signs and 3-hydroxybutyrate plasma levels, 81 multiparous Holstein cows were selected from a dairy farm 7 to 21 d after calving. The cows were divided into 3 groups: cows with clinical ketosis, cows with subclinical ketosis, and healthy control cows. (1)H-Nuclear magnetic resonance-based metabolomics was used to assess the plasma metabolic profiles of the 3 groups. The data were analyzed by principal component analysis, partial least squares discriminant analysis, and orthogonal partial least-squares discriminant analysis. The differences in metabolites among the 3 groups were assessed. The orthogonal partial least-squares discriminant analysis model differentiated the 3 groups of plasma samples. The model predicted clinical ketosis with a sensitivity of 100% and a specificity of 100%. In the case of subclinical ketosis, the model had a sensitivity of 97.0% and specificity of 95.7%. Twenty-five metabolites, including acetoacetate, acetone, lactate, glucose, choline, glutamic acid, and glutamine, were different among the 3 groups. Among the 25 metabolites, 4 were upregulated, 7 were downregulated, and 14 were both upregulated and downregulated. The results indicated that plasma (1)H-nuclear magnetic resonance-based metabolomics, coupled with pattern recognition analytical methods, not only has the sensitivity and specificity to distinguish cows with clinical and subclinical ketosis from healthy controls, but also has the potential to be developed into a clinically useful diagnostic tool that could contribute to a further understanding of the disease mechanisms. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Sleep-wake profiles predict longitudinal changes in manic symptoms and memory in young people with mood disorders.

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Robillard, Rébecca; Hermens, Daniel F; Lee, Rico S C; Jones, Andrew; Carpenter, Joanne S; White, Django; Naismith, Sharon L; Southan, James; Whitwell, Bradley; Scott, Elizabeth M; Hickie, Ian B

2016-10-01

Mood disorders are characterized by disabling symptoms and cognitive difficulties which may vary in intensity throughout the course of the illness. Sleep-wake cycles and circadian rhythms influence emotional regulation and cognitive functions. However, the relationships between the sleep-wake disturbances experienced commonly by people with mood disorders and the longitudinal changes in their clinical and cognitive profile are not well characterized. This study investigated associations between initial sleep-wake patterns and longitudinal changes in mood symptoms and cognitive functions in 50 young people (aged 13-33 years) with depression or bipolar disorder. Data were based on actigraphy monitoring conducted over approximately 2 weeks and clinical and neuropsychological assessment. As part of a longitudinal cohort study, these assessments were repeated after a mean follow-up interval of 18.9 months. No significant differences in longitudinal clinical changes were found between the participants with depression and those with bipolar disorder. Lower sleep efficiency was predictive of longitudinal worsening in manic symptoms (P = 0.007). Shorter total sleep time (P = 0.043) and poorer circadian rhythmicity (P = 0.045) were predictive of worsening in verbal memory. These findings suggest that some sleep-wake and circadian disturbances in young people with mood disorders may be associated with less favourable longitudinal outcomes, notably for subsequent manic symptoms and memory difficulties. © 2016 European Sleep Research Society.

Childhood vitiligo: Clinical epidemiological profile

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Asmae Lahlou

2017-07-01

Full Text Available Objective: To study the clinical and the epidemiologic profiles of childhood vitiligo. Patients and Methods: We prospectively analyzed the clinical data of children with vitiligo presented to the dermatology derpartement at University Hospital – Fès for 5 years from May 2011 to May 2016. This study included 31 patients. All patients were assessed for the natural history, clinical characteristics, family history, and associated abnormalities of vitiligo. Results: Of the 31 children with vitiligo 9 (29,03% were boys and 21 (67.74% were girls. The mean age of onset of the vitiligo was 10 years. The mean duration of the disease was 38,9 weeks. The most common type of vitiligo was vitiligo vulgaris (49.5% followed by focal vitiligo (39%, acrofacial vitiligo (32%, and segmental vitiligo (16% The most frequent site of onset was the extremities followed by the head and the neck, then the trunk and the genitalia. Of the 31 children with vitiligo, 39% had a family history and 4 % had an antecedent of autoimmune diesease like le diabète, une thyroïdite, l’anémie et le psoriasis, retrouvé. Conclusion: Our children have a strong family history of vitiligo and they are developing the disease at a slightly older age compared with those of other studies; however, other epidemiologic features appear to be similar to those reported in the previously published studies.

Nursing Diagnosis Risk for falls: prevalence and clinical profile of hospitalized patients1

Science.gov (United States)

Luzia, Melissa de Freitas; Victor, Marco Antonio de Goes; Lucena, Amália de Fátima

2014-01-01

Objectives to identify the prevalence of the Nursing Diagnosis (ND) Risk for falls in the hospitalizations of adult patients in clinical and surgical units, to characterize the clinical profile and to identify the risk factors of the patients with this ND. Method a cross-sectional study with 174 patients. The data was collected from the computerized nursing care prescriptions system and on-line hospital records, and analyzed statistically. Results the prevalence of the ND Risk for falls was 4%. The patients' profile indicated older adults, males (57%), those hospitalized in the clinical units (63.2%), with a median length of hospitalization of 20 (10-24) days, with neurological illnesses (26%), cardio-vascular illnesses (74.1%) and various co-morbidities (3±1.8). The prevalent risk factors were neurological alterations (43.1%), impaired mobility (35.6%) and extremes of age (10.3%). Conclusion the findings contributed to evidencing the profile of the patients with a risk of falling hospitalized in clinical and surgical wards, which favors the planning of interventions for preventing this adverse event. PMID:26107834

Clinical profile and warning sign finding in children with severe dengue and non-severe dengue

Science.gov (United States)

Adam, A. S.; Pasaribu, S.; Wijaya, H.; Pasaribu, A. P.

2018-03-01

Dengue fever is one of the most important emerging vector-borne viral diseases. Approximately 500,000 out of 100 million cases develop to severe dengue infection. Patient with severe dengue (SD) can be predicted by clinical profile, laboratory and warning sign which could be saved by early interventions.This was a retrospective descriptive-analytic study to investigate clinical manifestations, laboratory and warning signs ofchildren with dengue infection in Haji Adam Malik hospital during January 2014–May 2016. Through medical records, we had selected 140 cases which fulfilled research criteria.Cases were classified as SD (n=28) and NSD (n=112). Most common clinical manifestations for NSD were abdominal pain (39.3%), myalgia (39.3%), headache (37.1%), mucosal bleeding (36.4%) while for SD were shock (15.7%), mucosal bleeding (15.7%), clinical fluid accumulation (15%), shortness of breath (14.3%). SGPT >1000IU/L (5 cases), SGOT >1000IU/L (9 cases), PT (10 cases) and aPTT (16 cases) were abnormal in SD. Severe dengue was frequently found in the range of white cell count 1000-4000/L and platelet count 20,000-50,000mm/uL. Clinical manifestations, warning sign, and laboratoryfinding, were different between SD and NSD.

De novo sequencing of circulating miRNAs identifies novel markers predicting clinical outcome of locally advanced breast cancer

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Wu Xiwei

2012-03-01

Full Text Available Abstract Background MicroRNAs (miRNAs have been recently detected in the circulation of cancer patients, where they are associated with clinical parameters. Discovery profiling of circulating small RNAs has not been reported in breast cancer (BC, and was carried out in this study to identify blood-based small RNA markers of BC clinical outcome. Methods The pre-treatment sera of 42 stage II-III locally advanced and inflammatory BC patients who received neoadjuvant chemotherapy (NCT followed by surgical tumor resection were analyzed for marker identification by deep sequencing all circulating small RNAs. An independent validation cohort of 26 stage II-III BC patients was used to assess the power of identified miRNA markers. Results More than 800 miRNA species were detected in the circulation, and observed patterns showed association with histopathological profiles of BC. Groups of circulating miRNAs differentially associated with ER/PR/HER2 status and inflammatory BC were identified. The relative levels of selected miRNAs measured by PCR showed consistency with their abundance determined by deep sequencing. Two circulating miRNAs, miR-375 and miR-122, exhibited strong correlations with clinical outcomes, including NCT response and relapse with metastatic disease. In the validation cohort, higher levels of circulating miR-122 specifically predicted metastatic recurrence in stage II-III BC patients. Conclusions Our study indicates that certain miRNAs can serve as potential blood-based biomarkers for NCT response, and that miR-122 prevalence in the circulation predicts BC metastasis in early-stage patients. These results may allow optimized chemotherapy treatments and preventive anti-metastasis interventions in future clinical applications.

Behavioral Profile Predicts Dominance Status in Mountain Chickadees.

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Fox, Rebecca A; Ladage, Lara D; Roth, Timothy C; Pravosudov, Vladimir V

2009-06-01

Individual variation in stable behavioral traits may explain variation in ecologically-relevant behaviors such as foraging, dispersal, anti-predator behavior, and dominance. We investigated behavioral variation in mountain chickadees (Poecile gambeli), a North American parid that lives in dominance-structured winter flocks, using two common measures of behavioral profile: exploration of a novel room and novel object exploration. We related those behavioral traits to dominance status in male chickadees following brief, pair-wise encounters. Low-exploring birds (birds that visited less than four locations in the novel room) were significantly more likely to become dominant in brief, pairwise encounters with high-exploring birds (i.e., birds that visited all perching locations within a novel room). On the other hand, there was no relationship between novel object exploration and dominance. Interestingly, novel room exploration was also not correlated with novel object exploration. These results suggest that behavioral profile may predict the social status of group-living individuals. Moreover, our results contradict the idea that novel object exploration and novel room exploration are always interchangeable measures of individuals' sensitivity to environmental novelty.

Longitudinal prediction and concurrent functioning of adolescent girls demonstrating various profiles of dating violence and victimization.

Science.gov (United States)

Chiodo, Debbie; Crooks, Claire V; Wolfe, David A; McIsaac, Caroline; Hughes, Ray; Jaffe, Peter G

2012-08-01

Adolescent girls are involved in physical dating violence as both perpetrators and victims, and there are negative consequences associated with each of these behaviors. This article used a prospective design with 519 girls dating in grade 9 to predict profiles of dating violence in grade 11 based on relationships with families of origin (child maltreatment experiences, harsh parenting), and peers (harassment, delinquency, relational aggression). In addition, dating violence profiles were compared on numerous indices of adjustment (school connectedness, grades, self-efficacy and community connectedness) and maladjustment (suicide attempts, distress, delinquency, sexual behavior) for descriptive purposes. The most common profile was no dating violence (n = 367) followed by mutual violence (n = 81). Smaller numbers of girls reported victimization or perpetration only (ns = 39 and 32, respectively). Predicting grade 11 dating violence profile membership from grade 9 relationships was limited, although delinquency, parental rejection, and sexual harassment perpetration predicted membership to the mutually violent group, and delinquency predicted the perpetrator-only group. Compared to the non-violent group, the mutually violent girls in grade 11 had lower grades, poorer self-efficacy, and lower school connectedness and community involvement. Furthermore, they had higher rates of peer aggression and delinquency, were less likely to use condoms and were much more likely to have considered suicide. There were fewer differences among the profiles for girls involved with dating violence. In addition, the victims-only group reported higher rates of sexual intercourse, comparable to the mutually violent group and those involved in nonviolent relationships. Implications for prevention and intervention are highlighted.

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

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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.

Enhanced clinical pharmacy service targeting tools: risk-predictive algorithms.

Science.gov (United States)

El Hajji, Feras W D; Scullin, Claire; Scott, Michael G; McElnay, James C

2015-04-01

This study aimed to determine the value of using a mix of clinical pharmacy data and routine hospital admission spell data in the development of predictive algorithms. Exploration of risk factors in hospitalized patients, together with the targeting strategies devised, will enable the prioritization of clinical pharmacy services to optimize patient outcomes. Predictive algorithms were developed using a number of detailed steps using a 75% sample of integrated medicines management (IMM) patients, and validated using the remaining 25%. IMM patients receive targeted clinical pharmacy input throughout their hospital stay. The algorithms were applied to the validation sample, and predicted risk probability was generated for each patient from the coefficients. Risk threshold for the algorithms were determined by identifying the cut-off points of risk scores at which the algorithm would have the highest discriminative performance. Clinical pharmacy staffing levels were obtained from the pharmacy department staffing database. Numbers of previous emergency admissions and admission medicines together with age-adjusted co-morbidity and diuretic receipt formed a 12-month post-discharge and/or readmission risk algorithm. Age-adjusted co-morbidity proved to be the best index to predict mortality. Increased numbers of clinical pharmacy staff at ward level was correlated with a reduction in risk-adjusted mortality index (RAMI). Algorithms created were valid in predicting risk of in-hospital and post-discharge mortality and risk of hospital readmission 3, 6 and 12 months post-discharge. The provision of ward-based clinical pharmacy services is a key component to reducing RAMI and enabling the full benefits of pharmacy input to patient care to be realized. © 2014 John Wiley & Sons, Ltd.

Are traditional cognitive tests useful in predicting clinical success?

Science.gov (United States)

Gray, Sarah A; Deem, Lisa P; Straja, Sorin R

2002-11-01

The purpose of this research was to determine the predictive value of the Dental Admission Test (DAT) for clinical success using Ackerman's theory of ability determinants of skilled performance. The Ackerman theory is a valid, reliable schema in the applied psychology literature used to predict complex skill acquisition. Inconsistent stimulus-response skill acquisition depends primarily on determinants of cognitive ability. Consistent information-processing tasks have been described as "automatic," in which stimuli and responses are mapped in a manner that allows for complete certainty once the relationships have been learned. It is theorized that the skills necessary for success in the clinical component of dental schools involve a significant amount of automatic processing demands and, as such, student performance in the clinics should begin to converge as task practice is realized and tasks become more consistent. Subtest scores of the DAT of four classes were correlated with final grades in nine clinical courses. Results showed that the DAT subtest scores played virtually no role with regard to the final clinical grades. Based on this information, the DAT scores were determined to be of no predictive value in clinical achievement.

Clinical pharmacology profile of care in Hepatology clinic

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Talita Rocha Passos

Full Text Available Summary Since 2010, the Clinical Gastroenterology and Hepatology Division of the Central Institute of Hospital das Clínicas of the University of São Paulo Medical School (HC-FMUSP, in the Portuguese acronym has been developing specialized electives assistance activities in the Outpatient Specialty Clinic, Secondary Level, in São Paulo NGA-63 Várzea do Carmo. The objective of this study was to analyze the pharmacotherapeutic profile of patients. This is a cross-sectional and retrospective study in which patients were seen at the Hepatology sector and the results were submitted to descriptive statistics. During the study period, 492 patients were treated at the clinic, with a mean age of 58.9 years and frequency of 61.2% female and 74.8% living in São Paulo. This population was served by various other medical specialties (cardiology and endocrine among others and the major liver diagnoses were: chronic hepatitis B and C and fatty liver. Comorbidities were also identified, such as diabetes, hypertension and dyslipidemia. Most patients took their medication in the Basic Health Units. We found that 30% of patients use of more than five medications and the most prescribed were omeprazole 208 (42.3%, metformin 132 (26.8% and losartan 80 (16.3%. Because it is an adult/elderly population, with several comorbidities and polymedication, it is important to be aware of the rational use of medication. The multidisciplinary team is important in applying correct conducts for the safe use of medicines, to reduce the burden on health spending and improving the quality of life of patients.

Non-invasive metabolomic profiling of embryo culture media and morphology grading to predict implantation outcome in frozen-thawed embryo transfer cycles.

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Li, Xiong; Xu, Yan; Fu, Jing; Zhang, Wen-Bi; Liu, Su-Ying; Sun, Xiao-Xi

2015-11-01

Assessment of embryo viability is a crucial component of in vitro fertilization and currently relies largely on embryo morphology and cleavage rate. Because morphological assessment remains highly subjective, it can be unreliable in predicting embryo viability. This study investigated the metabolomic profiling of embryo culture media using near-infrared (NIR) spectroscopy for predicting the implantation potential of human embryos in frozen-thawed embryo transfer (FET) cycles. Spent embryo culture media was collected on day 4 after thawed embryo transfer (n = 621) and analysed using NIR spectroscopy. Viability scores were calculated using a predictive multivariate algorithm of fresh embryos with known pregnancy outcomes. The mean viability indices of embryos resulting in clinical pregnancy following FET were significantly higher than those of non-implanted embryos and differed between the 0, 50, and 100 % implantation groups. Notably, the 0 % group index was significantly lower than the 100 % implantation group index (-0.787 ± 0.382 vs. 1.064 ± 0.331, P  0.05). NIR metabolomic profiling of thawed embryo culture media is independent of morphology and correlates with embryo implantation potential in FET cycles. The viability score alone or in conjunction with morphologic grading is a more objective marker for implantation outcome in FET cycles than morphology alone.

Predictive genomics: A cancer hallmark network framework for predicting tumor clinical phenotypes using genome sequencing data

OpenAIRE

Wang, Edwin; Zaman, Naif; Mcgee, Shauna; Milanese, Jean-Sébastien; Masoudi-Nejad, Ali; O'Connor, Maureen

2014-01-01

We discuss a cancer hallmark network framework for modelling genome-sequencing data to predict cancer clonal evolution and associated clinical phenotypes. Strategies of using this framework in conjunction with genome sequencing data in an attempt to predict personalized drug targets, drug resistance, and metastasis for a cancer patient, as well as cancer risks for a healthy individual are discussed. Accurate prediction of cancer clonal evolution and clinical phenotypes will have substantial i...

Predicting lower third molar eruption on panoramic radiographs after cephalometric comparison of profile and panoramic radiographs

DEFF Research Database (Denmark)

Begtrup, Anders; Grønastøð, Halldis Á; Christensen, Ib Jarle

2012-01-01

and to find a simple and reliable method for predicting the eruption of the mandibular third molar by measurements on panoramic radiographs. The material consisted of profile and panoramic radiographs, taken before orthodontic treatment, of 30 males and 23 females (median age 22, range 18-48 years......Previous studies have suggested methods for predicting third molar tooth eruption radiographically. Still, this prediction is associated with uncertainty. The aim of the present study was to elucidate the association between cephalometric measurements on profile and panoramic radiographs...... the length from the ramus to the incisors (olr-id) showed a statistically significant correlation. By combining this length with the mesiodistal width of the lower second molar, the prediction of eruption of the lower third molar was strengthened. A new formula for calculating the probability of eruption...

The clinical profile of idiopathic Parkinson's disease in a South ...

African Journals Online (AJOL)

The clinical profile of idiopathic Parkinson's disease in a South African hospital complex - the influence of ethnicity and gender. Marcelle Smith, Girish Modi. Abstract. Background Idiopathic Parkinson's Disease (IPD) has not been well studied in Black African populations. Data on the demographics, phenotype differences ...

Slurry discharge management-beach profile prediction

Energy Technology Data Exchange (ETDEWEB)

Bravo, R.; Nawrot, J.R. [Southern Illinois University at Carbondale, Carbondale, IL (United States). Dept. of Civil Engineering

1996-11-01

Mine tailings dams are embankments used by the mining industry to retain the tailings products after the mineral preparation process. Based on the acid-waste stereotype that all coal slurry is acid producing, current reclamation requires a four foot soil cover for inactive slurry disposal areas. Compliance with this requirement is both difficult and costly and in some case unnecessary, as not all the slurry, or portions of slurry impoundments are acid producing. Reduced costs and recent popularity of wetland development has prompted many operators to request reclamation variances for slurry impoundments. Waiting to address slurry reclamation until after the impoundment is full, limits the flexibility of reclamation opportunities. This paper outlines a general methodology to predict the formation of the beach profile for mine tailings dams, by the discharge volume and location of the slurry into the impoundment. The review is presented under the perspective of geotechnical engineering and waste disposal management emphasizing the importance of pre-planning slurry disposal land reclamation. 4 refs., 5 figs.

Body composition indices and predicted cardiovascular disease risk profile among urban dwellers in Malaysia.

Science.gov (United States)

Su, Tin Tin; Amiri, Mohammadreza; Mohd Hairi, Farizah; Thangiah, Nithiah; Dahlui, Maznah; Majid, Hazreen Abdul

2015-01-01

This study aims to compare various body composition indices and their association with a predicted cardiovascular disease (CVD) risk profile in an urban population in Kuala Lumpur, Malaysia. A cross-sectional survey was conducted in metropolitan Kuala Lumpur, Malaysia, in 2012. Households were selected using a simple random-sampling method, and adult members were invited for medical screening. The Framingham Risk Scoring algorithm was used to predict CVD risk, which was then analyzed in association with body composition measurements, including waist circumference, waist-hip ratio, waist-height ratio, body fat percentage, and body mass index. Altogether, 882 individuals were included in our analyses. Indices that included waist-related measurements had the strongest association with CVD risk in both genders. After adjusting for demographic and socioeconomic variables, waist-related measurements retained the strongest correlations with predicted CVD risk in males. However, body mass index, waist-height ratio, and waist circumference had the strongest correlation with CVD risk in females. The waist-related indicators of abdominal obesity are important components of CVD risk profiles. As waist-related parameters can quickly and easily be measured, they should be routinely obtained in primary care settings and population health screens in order to assess future CVD risk profiles and design appropriate interventions.

Body Composition Indices and Predicted Cardiovascular Disease Risk Profile among Urban Dwellers in Malaysia

Directory of Open Access Journals (Sweden)

Tin Tin Su

2015-01-01

Full Text Available Objectives. This study aims to compare various body composition indices and their association with a predicted cardiovascular disease (CVD risk profile in an urban population in Kuala Lumpur, Malaysia. Methods. A cross-sectional survey was conducted in metropolitan Kuala Lumpur, Malaysia, in 2012. Households were selected using a simple random-sampling method, and adult members were invited for medical screening. The Framingham Risk Scoring algorithm was used to predict CVD risk, which was then analyzed in association with body composition measurements, including waist circumference, waist-hip ratio, waist-height ratio, body fat percentage, and body mass index. Results. Altogether, 882 individuals were included in our analyses. Indices that included waist-related measurements had the strongest association with CVD risk in both genders. After adjusting for demographic and socioeconomic variables, waist-related measurements retained the strongest correlations with predicted CVD risk in males. However, body mass index, waist-height ratio, and waist circumference had the strongest correlation with CVD risk in females. Conclusions. The waist-related indicators of abdominal obesity are important components of CVD risk profiles. As waist-related parameters can quickly and easily be measured, they should be routinely obtained in primary care settings and population health screens in order to assess future CVD risk profiles and design appropriate interventions.

Clinical and medication profiles stratified by household income in patients referred for diabetes care

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Svenson Lawrence W

2007-03-01

Full Text Available Abstract Background Low income individuals with diabetes are at particularly high risk for poor health outcomes. While specialized diabetes care may help reduce this risk, it is not currently known whether there are significant clinical differences across income groups at the time of referral. The objective of this study is to determine if the clinical profiles and medication use of patients referred for diabetes care differ across income quintiles. Methods This cross-sectional study was conducted using a Canadian, urban, Diabetes Education Centre (DEC database. Clinical information on the 4687 patients referred to the DEC from May 2000 – January 2002 was examined. These data were merged with 2001 Canadian census data on income. Potential differences in continuous clinical parameters across income quintiles were examined using regression models. Differences in medication use were examined using Chi square analyses. Results Multivariate regression analysis indicated that income was negatively associated with BMI (p Conclusion Our findings demonstrate that low income patients present to diabetes clinic older, heavier and with a more atherogenic lipid profile than do high income patients. Overall medication use was higher among the lower income group suggesting that differences in clinical profiles are not the result of under-treatment, thus invoking lifestyle factors as potential contributors to these findings.

The Clinical Prediction of Dangerousness.

Science.gov (United States)

1985-05-01

8217 8 ings. Szasz (1963) has argued persuasively that clinical predictions of future dangerous behavior are unfairly focused on the mentally ill...Persons labeled paranoid, Szasz states, are readily commitable, while highly dangerous drunken drivers are not. Indeed, dangerousness such as that...Psychology, 31, 492-494. Szasz , T. (1963). Law, liberty and psychiatry. New York: Macmillan. Taft, R. (1955). The ability to judge people. Psychological

Prediction of Metastasis and Recurrence in Colorectal Cancer Based on Gene Expression Analysis: Ready for the Clinic?

Energy Technology Data Exchange (ETDEWEB)

Shibayama, Masaki [Sysmex Corporation, Central Research Laboratories, Kobe 651-2271 (Japan); Maak, Matthias; Nitsche, Ulrich [Chirurgische Klinik, Klinikum Rechts der Isar der TUM, München 81657 (Germany); Gotoh, Kengo [Sysmex Corporation, Central Research Laboratories, Kobe 651-2271 (Japan); Rosenberg, Robert; Janssen, Klaus-Peter, E-mail: klaus-peter.janssen@lrz.tum.de [Chirurgische Klinik, Klinikum Rechts der Isar der TUM, München 81657 (Germany)

2011-07-07

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.

Prediction of Metastasis and Recurrence in Colorectal Cancer Based on Gene Expression Analysis: Ready for the Clinic?

International Nuclear Information System (INIS)

Shibayama, Masaki; Maak, Matthias; Nitsche, Ulrich; Gotoh, Kengo; Rosenberg, Robert; Janssen, Klaus-Peter

2011-01-01

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

Cerebrospinal fluid cytokine profiles predict risk of early mortality and immune reconstitution inflammatory syndrome in HIV-associated cryptococcal meningitis.

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Joseph N Jarvis

2015-04-01

Full Text Available Understanding the host immune response during cryptococcal meningitis (CM is of critical importance for the development of immunomodulatory therapies. We profiled the cerebrospinal fluid (CSF immune-response in ninety patients with HIV-associated CM, and examined associations between immune phenotype and clinical outcome. CSF cytokine, chemokine, and macrophage activation marker concentrations were assayed at disease presentation, and associations between these parameters and microbiological and clinical outcomes were examined using principal component analysis (PCA. PCA demonstrated a co-correlated CSF cytokine and chemokine response consisting primarily of Th1, Th2, and Th17-type cytokines. The presence of this CSF cytokine response was associated with evidence of increased macrophage activation, more rapid clearance of Cryptococci from CSF, and survival at 2 weeks. The key components of this protective immune-response were interleukin (IL-6 and interferon-γ, IL-4, IL-10 and IL-17 levels also made a modest positive contribution to the PC1 score. A second component of co-correlated chemokines was identified by PCA, consisting primarily of monocyte chemotactic protein-1 (MCP-1 and macrophage inflammatory protein-1α (MIP-1α. High CSF chemokine concentrations were associated with low peripheral CD4 cell counts and CSF lymphocyte counts and were predictive of immune reconstitution inflammatory syndrome (IRIS. In conclusion CSF cytokine and chemokine profiles predict risk of early mortality and IRIS in HIV-associated CM. We speculate that the presence of even minimal Cryptococcus-specific Th1-type CD4+ T-cell responses lead to increased recruitment of circulating lymphocytes and monocytes into the central nervous system (CNS, more effective activation of CNS macrophages and microglial cells, and faster organism clearance; while high CNS chemokine levels may predispose to over recruitment or inappropriate recruitment of immune cells to the CNS and

Validity of a Manual Soft Tissue Profile Prediction Method Following Mandibular Setback Osteotomy

OpenAIRE

Kolokitha, Olga-Elpis

2007-01-01

Objectives The aim of this study was to determine the validity of a manual cephalometric method used for predicting the post-operative soft tissue profiles of patients who underwent mandibular setback surgery and compare it to a computerized cephalometric prediction method (Dentofacial Planner). Lateral cephalograms of 18 adults with mandibular prognathism taken at the end of pre-surgical orthodontics and approximately one year after surgery were used. Methods To test the validity of the manu...

Coagulation profile of children with sickle cell anemia in steady state ...

African Journals Online (AJOL)

Background: Sickle cell anemia is associated with a hypercoagulable state that may lead to alterations in a coagulation profile. Measurements of coagulation factors are known to have some predictive value for clinical outcome. Objectives: To determine the coagulation profile of children with SCA in steady state and crisis ...

A predictive approach to selecting the size of a clinical trial, based on subjective clinical opinion.

Science.gov (United States)

Spiegelhalter, D J; Freedman, L S

1986-01-01

The 'textbook' approach to determining sample size in a clinical trial has some fundamental weaknesses which we discuss. We describe a new predictive method which takes account of prior clinical opinion about the treatment difference. The method adopts the point of clinical equivalence (determined by interviewing the clinical participants) as the null hypothesis. Decision rules at the end of the study are based on whether the interval estimate of the treatment difference (classical or Bayesian) includes the null hypothesis. The prior distribution is used to predict the probabilities of making the decisions to use one or other treatment or to reserve final judgement. It is recommended that sample size be chosen to control the predicted probability of the last of these decisions. An example is given from a multi-centre trial of superficial bladder cancer.

Predicting the disease of Alzheimer with SNP biomarkers and clinical data using data mining classification approach: decision tree.

Science.gov (United States)

Erdoğan, Onur; Aydin Son, Yeşim

2014-01-01

Single Nucleotide Polymorphisms (SNPs) are the most common genomic variations where only a single nucleotide differs between individuals. Individual SNPs and SNP profiles associated with diseases can be utilized as biological markers. But there is a need to determine the SNP subsets and patients' clinical data which is informative for the diagnosis. Data mining approaches have the highest potential for extracting the knowledge from genomic datasets and selecting the representative SNPs as well as most effective and informative clinical features for the clinical diagnosis of the diseases. In this study, we have applied one of the widely used data mining classification methodology: "decision tree" for associating the SNP biomarkers and significant clinical data with the Alzheimer's disease (AD), which is the most common form of "dementia". Different tree construction parameters have been compared for the optimization, and the most accurate tree for predicting the AD is presented.

Effects of DTM resolution on slope steepness and soil loss prediction on hillslope profiles

Science.gov (United States)

Eder Paulo Moreira; William J. Elliot; Andrew T. Hudak

2011-01-01

Topographic attributes play a critical role in predicting erosion in models such as the Water Erosion Prediction Project (WEPP). The effects of four different high resolution hillslope profiles were studied using four different DTM resolutions: 1-m, 3-m, 5-m and 10-m. The WEPP model used a common scenario encountered in the forest environment and the selected hillslope...

Connecting clinical and actuarial prediction with rule-based methods.

Science.gov (United States)

Fokkema, Marjolein; Smits, Niels; Kelderman, Henk; Penninx, Brenda W J H

2015-06-01

Meta-analyses comparing the accuracy of clinical versus actuarial prediction have shown actuarial methods to outperform clinical methods, on average. However, actuarial methods are still not widely used in clinical practice, and there has been a call for the development of actuarial prediction methods for clinical practice. We argue that rule-based methods may be more useful than the linear main effect models usually employed in prediction studies, from a data and decision analytic as well as a practical perspective. In addition, decision rules derived with rule-based methods can be represented as fast and frugal trees, which, unlike main effects models, can be used in a sequential fashion, reducing the number of cues that have to be evaluated before making a prediction. We illustrate the usability of rule-based methods by applying RuleFit, an algorithm for deriving decision rules for classification and regression problems, to a dataset on prediction of the course of depressive and anxiety disorders from Penninx et al. (2011). The RuleFit algorithm provided a model consisting of 2 simple decision rules, requiring evaluation of only 2 to 4 cues. Predictive accuracy of the 2-rule model was very similar to that of a logistic regression model incorporating 20 predictor variables, originally applied to the dataset. In addition, the 2-rule model required, on average, evaluation of only 3 cues. Therefore, the RuleFit algorithm appears to be a promising method for creating decision tools that are less time consuming and easier to apply in psychological practice, and with accuracy comparable to traditional actuarial methods. (c) 2015 APA, all rights reserved).

Clinical Predictive Modeling Development and Deployment through FHIR Web Services.

Science.gov (United States)

Khalilia, Mohammed; Choi, Myung; Henderson, Amelia; Iyengar, Sneha; Braunstein, Mark; Sun, Jimeng

2015-01-01

Clinical predictive modeling involves two challenging tasks: model development and model deployment. In this paper we demonstrate a software architecture for developing and deploying clinical predictive models using web services via the Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) standard. The services enable model development using electronic health records (EHRs) stored in OMOP CDM databases and model deployment for scoring individual patients through FHIR resources. The MIMIC2 ICU dataset and a synthetic outpatient dataset were transformed into OMOP CDM databases for predictive model development. The resulting predictive models are deployed as FHIR resources, which receive requests of patient information, perform prediction against the deployed predictive model and respond with prediction scores. To assess the practicality of this approach we evaluated the response and prediction time of the FHIR modeling web services. We found the system to be reasonably fast with one second total response time per patient prediction.

Clinical time series prediction: Toward a hierarchical dynamical system framework.

Science.gov (United States)

Liu, Zitao; Hauskrecht, Milos

2015-09-01

Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventions and clinical decision making. In this work, we propose and develop a novel hierarchical framework for modeling clinical time series data of varied length and with irregularly sampled observations. Our hierarchical dynamical system framework for modeling clinical time series combines advantages of the two temporal modeling approaches: the linear dynamical system and the Gaussian process. We model the irregularly sampled clinical time series by using multiple Gaussian process sequences in the lower level of our hierarchical framework and capture the transitions between Gaussian processes by utilizing the linear dynamical system. The experiments are conducted on the complete blood count (CBC) panel data of 1000 post-surgical cardiac patients during their hospitalization. Our framework is evaluated and compared to multiple baseline approaches in terms of the mean absolute prediction error and the absolute percentage error. We tested our framework by first learning the time series model from data for the patients in the training set, and then using it to predict future time series values for the patients in the test set. We show that our model outperforms multiple existing models in terms of its predictive accuracy. Our method achieved a 3.13% average prediction accuracy improvement on ten CBC lab time series when it was compared against the best performing baseline. A 5.25% average accuracy improvement was observed when only short-term predictions were considered. A new hierarchical dynamical system framework that lets us model irregularly sampled time series data is a promising new direction for modeling clinical time series and for improving their predictive performance. Copyright © 2014 Elsevier B.V. All rights reserved.

Clinical time series prediction: towards a hierarchical dynamical system framework

Science.gov (United States)

Liu, Zitao; Hauskrecht, Milos

2014-01-01

Objective Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventions and clinical decision making. In this work, we propose and develop a novel hierarchical framework for modeling clinical time series data of varied length and with irregularly sampled observations. Materials and methods Our hierarchical dynamical system framework for modeling clinical time series combines advantages of the two temporal modeling approaches: the linear dynamical system and the Gaussian process. We model the irregularly sampled clinical time series by using multiple Gaussian process sequences in the lower level of our hierarchical framework and capture the transitions between Gaussian processes by utilizing the linear dynamical system. The experiments are conducted on the complete blood count (CBC) panel data of 1000 post-surgical cardiac patients during their hospitalization. Our framework is evaluated and compared to multiple baseline approaches in terms of the mean absolute prediction error and the absolute percentage error. Results We tested our framework by first learning the time series model from data for the patient in the training set, and then applying the model in order to predict future time series values on the patients in the test set. We show that our model outperforms multiple existing models in terms of its predictive accuracy. Our method achieved a 3.13% average prediction accuracy improvement on ten CBC lab time series when it was compared against the best performing baseline. A 5.25% average accuracy improvement was observed when only short-term predictions were considered. Conclusion A new hierarchical dynamical system framework that lets us model irregularly sampled time series data is a promising new direction for modeling clinical time series and for improving their predictive

Omics AnalySIs System for PRecision Oncology (OASISPRO): A Web-based Omics Analysis Tool for Clinical Phenotype Prediction.

Science.gov (United States)

Yu, Kun-Hsing; Fitzpatrick, Michael R; Pappas, Luke; Chan, Warren; Kung, Jessica; Snyder, Michael

2017-09-12

Precision oncology is an approach that accounts for individual differences to guide cancer management. Omics signatures have been shown to predict clinical traits for cancer patients. However, the vast amount of omics information poses an informatics challenge in systematically identifying patterns associated with health outcomes, and no general-purpose data-mining tool exists for physicians, medical researchers, and citizen scientists without significant training in programming and bioinformatics. To bridge this gap, we built the Omics AnalySIs System for PRecision Oncology (OASISPRO), a web-based system to mine the quantitative omics information from The Cancer Genome Atlas (TCGA). This system effectively visualizes patients' clinical profiles, executes machine-learning algorithms of choice on the omics data, and evaluates the prediction performance using held-out test sets. With this tool, we successfully identified genes strongly associated with tumor stage, and accurately predicted patients' survival outcomes in many cancer types, including mesothelioma and adrenocortical carcinoma. By identifying the links between omics and clinical phenotypes, this system will facilitate omics studies on precision cancer medicine and contribute to establishing personalized cancer treatment plans. This web-based tool is available at http://tinyurl.com/oasispro ;source codes are available at http://tinyurl.com/oasisproSourceCode . © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Antimicrobial sensitivity profile of Staphylococcus spp. Isolated from clinical mastitis

Directory of Open Access Journals (Sweden)

Thamires Martins

2012-12-01

Full Text Available Inflammation of the mammary gland, which is also known as mastitis, occupies a prominent place among the diseases that affect dairy cattle, having a great economic importance in the dairy sector. Mastitis may have different origins, however, infectious mastitis is the most frequent and represents a risk to public health due to the propagation of microorganisms through milk. Staphylococcus spp. are considered the microorganisms that cause the greatest losses in milk production, being that Staphylococcus aureus is the pathogen of major importance because they present high resistence to antimicrobials. Empirical treatment, without prior identification of the pathogens and their resistance profile, may contribute to the emergence of multidrug-resistant strains and risk the efficiency of the antimicrobial. In that scenery, the study aimed to evaluate the resistance profile of Staphylococcus spp. against some antimicrobials used in the treatment of cows with clinical mastitis. The study was conducted on a property in the state of São Paulo from January 2011 to June 2012. We evaluated 29 lactating cows that present clinical mastitis in, at least, one mammary quarter. The diagnosis of clinical mastitis was performed by evaluating the clinical signs and also by Tamis test. Samples of milk from mammary quarters were collected aseptically in sterile tubes for microbiological evaluation. Microorganisms were isolated on sheep blood agar 5% and Sabouraud agar with chloramphenicol. The sensitivity profile of Staphylococcus spp. to the antibiotics ampicillin, cephalexin, ceftiofur, cefaclor, gentamicin, kanamycin, neomycin, penicillin G and oxacillin, was tested by disk diffusion test on Mueller-Hinton agar. From a total of 106 samples of milk analyzed, 64 (60.38% presented microbiological growth, being observed isolation of Streptococcus spp. 29 (34.52%, Staphylococcus spp. 28 (33.33%, Corynebacterium spp. 17 (20.24%, filamentous fungi 4 (4.76%, yeast 4 (4

Through-Thickness Residual Stress Profiles in Austenitic Stainless Steel Welds: A Combined Experimental and Prediction Study

Science.gov (United States)

Mathew, J.; Moat, R. J.; Paddea, S.; Francis, J. A.; Fitzpatrick, M. E.; Bouchard, P. J.

2017-12-01

Economic and safe management of nuclear plant components relies on accurate prediction of welding-induced residual stresses. In this study, the distribution of residual stress through the thickness of austenitic stainless steel welds has been measured using neutron diffraction and the contour method. The measured data are used to validate residual stress profiles predicted by an artificial neural network approach (ANN) as a function of welding heat input and geometry. Maximum tensile stresses with magnitude close to the yield strength of the material were observed near the weld cap in both axial and hoop direction of the welds. Significant scatter of more than 200 MPa was found within the residual stress measurements at the weld center line and are associated with the geometry and welding conditions of individual weld passes. The ANN prediction is developed in an attempt to effectively quantify this phenomenon of `innate scatter' and to learn the non-linear patterns in the weld residual stress profiles. Furthermore, the efficacy of the ANN method for defining through-thickness residual stress profiles in welds for application in structural integrity assessments is evaluated.

Physiotherapy clinical educators' perceptions and experiences of clinical prediction rules.

Science.gov (United States)

Knox, Grahame M; Snodgrass, Suzanne J; Rivett, Darren A

2015-12-01

Clinical prediction rules (CPRs) are widely used in medicine, but their application to physiotherapy practice is more recent and less widespread, and their implementation in physiotherapy clinical education has not been investigated. This study aimed to determine the experiences and perceptions of physiotherapy clinical educators regarding CPRs, and whether they are teaching CPRs to students on clinical placement. Cross-sectional observational survey using a modified Dillman method. Clinical educators (n=211, response rate 81%) supervising physiotherapy students from 10 universities across 5 states and territories in Australia. Half (48%) of respondents had never heard of CPRs, and a further 25% had never used CPRs. Only 27% reported using CPRs, and of these half (51%) were rarely if ever teaching CPRs to students in the clinical setting. However most respondents (81%) believed CPRs assisted in the development of clinical reasoning skills and few (9%) were opposed to teaching CPRs to students. Users of CPRs were more likely to be male (pphysiotherapy (pStudents are unlikely to be learning about CPRs on clinical placement, as few clinical educators use them. Clinical educators will require training in CPRs and assistance in teaching them if students are to better learn about implementing CPRs in physiotherapy clinical practice. Copyright © 2015 Chartered Society of Physiotherapy. Published by Elsevier Ltd. All rights reserved.

Protein Profile study of clinical samples using Laser Induced Fluorescence as the detection method

DEFF Research Database (Denmark)

Karemore, Gopal Raghunath; Raja, Sujatha N.; Rai, Lavanya

2009-01-01

  Protein profiles of tissue homogenates were recorded using HPLC separation and LIF detection method. The samples were collected from volunteers with clinically normal or cervical cancer conditions. It is shown that the protein profile can be classified as belonging to malignant or normal state ...

Imbalanced target prediction with pattern discovery on clinical data repositories.

Science.gov (United States)

Chan, Tak-Ming; Li, Yuxi; Chiau, Choo-Chiap; Zhu, Jane; Jiang, Jie; Huo, Yong

2017-04-20

Clinical data repositories (CDR) have great potential to improve outcome prediction and risk modeling. However, most clinical studies require careful study design, dedicated data collection efforts, and sophisticated modeling techniques before a hypothesis can be tested. We aim to bridge this gap, so that clinical domain users can perform first-hand prediction on existing repository data without complicated handling, and obtain insightful patterns of imbalanced targets for a formal study before it is conducted. We specifically target for interpretability for domain users where the model can be conveniently explained and applied in clinical practice. We propose an interpretable pattern model which is noise (missing) tolerant for practice data. To address the challenge of imbalanced targets of interest in clinical research, e.g., deaths less than a few percent, the geometric mean of sensitivity and specificity (G-mean) optimization criterion is employed, with which a simple but effective heuristic algorithm is developed. We compared pattern discovery to clinically interpretable methods on two retrospective clinical datasets. They contain 14.9% deaths in 1 year in the thoracic dataset and 9.1% deaths in the cardiac dataset, respectively. In spite of the imbalance challenge shown on other methods, pattern discovery consistently shows competitive cross-validated prediction performance. Compared to logistic regression, Naïve Bayes, and decision tree, pattern discovery achieves statistically significant (p-values repositories with imbalance and noise. The prediction results and interpretable patterns can provide insights in an agile and inexpensive way for the potential formal studies.

Pattern Of Altered Lipid Profile In Patients With Subclinical And Clinical Hypothyroidism And Its Correlation With Body Mass Index

International Nuclear Information System (INIS)

Humerah, S.; Siddiqui, A.; Khan, H. F.

2016-01-01

Objective: To compare the lipid profile of the subclinical and clinical hypothyroid patients and to evaluate the correlation between body mass index (BMI) and lipid profile in hypothyroidism. Study Design: Cross-sectional study. Place and Duration of Study: Islamic International Medical College, Riphah International University, Islamabad, and Citi Laboratory, Rawalpindi, from January to December 2013. Methodology: The subjects were selected through non-probability, purposive sampling. On the basis of thyroid profile, the subjects were divided into 3 groups: euthyroids (n=20), subclinical hypothyroids (n=50), and clinical hypothyroids (n=30). The blood of these subjects was then analyzed for lipid profile. Data was analyzed using SPSS version 18 statistical software. Result: Both hypothyroid groups showed altered lipid profile which was observed to be significantly raised when compared with the euthyroid subjects. Comparison of lipid profile in euthyroid, subclinical, and clinical hypothyroid groups showed significant differences by non-parametric tests (p < 0.05). An assessment of correlation of lipid profile with the BMI was found to be significant (p < 0.01). Conclusion: Hypothyroidism causes alteration of lipid profile. Clinical and subclinical hypothyroid patients have altered lipid profile as compared to euthyroids. Thyroid status monitoring is very important, since it can induce changes in lipid profile. Such dyslipidemic status is significant not only for the management of thyroid disorders but also for common diseases like obesity and coronary atherosclerosis in the population. (author)

Health profiles of foreigners attending primary care clinics in Malaysia.

Science.gov (United States)

Ab Rahman, Norazida; Sivasampu, Sheamini; Mohamad Noh, Kamaliah; Khoo, Ee Ming

2016-06-14

The world population has become more globalised with increasing number of people residing in another country for work or other reasons. Little is known about the health profiles of foreign population in Malaysia. The aim of this study was to provide a detailed description of the health problems presented by foreigners attending primary care clinics in Malaysia. Data were derived from the 2012 National Medical Care Survey (NMCS), a cross sectional survey of primary care encounters from public and private primary care clinics sampled from five regions in Malaysia. Patients with foreign nationality were identified and analysed for demographic profiles, reasons for encounter (RFEs), diagnosis, and provision of care. Foreigners accounted for 7.7 % (10,830) of all patient encounters from NMCS. Most encounters were from private clinics (90.2 %). Median age was 28 years (IQR: 24.0, 34.8) and 69.9 % were male. Most visits to the primary care clinics were for symptom-based complaints (69.5 %), followed by procedures (23.0 %) and follow-up visit (7.4 %). The commonest diagnosis in public clinics was antenatal care (21.8 %), followed by high risk pregnancies (7.5 %) and upper respiratory tract infection (URTI) (6.8 %). Private clinics had more cases for general medical examination (13.5 %), URTI (13.1 %) and fever (3.9 %). Medications were prescribed to 76.5 % of these encounters. More foreigners were seeking primary medical care from private clinics and the encounters were for general medical examinations and acute minor ailments. Those who sought care from public clinics were for obstetric problems and chronic diseases. Medications were prescribed to two-thirds of the encounters while other interventions: laboratory investigations, medical procedures and follow-up appointment had lower rates in private clinics. Foreigners are generally of young working group and are expected to have mandatory medical checks. The preponderance of obstetrics seen in public

What predicts performance during clinical psychology training?

OpenAIRE

Scior, Katrina; Bradley, Caroline E; Potts, Henry W W; Woolf, Katherine; de C Williams, Amanda C

2013-01-01

Objectives While the question of who is likely to be selected for clinical psychology training has been studied, evidence on performance during training is scant. This study explored data from seven consecutive intakes of the UK's largest clinical psychology training course, aiming to identify what factors predict better or poorer outcomes. Design Longitudinal cross-sectional study using prospective and retrospective data. Method Characteristics at application were analysed in relation to a r...

Chemical Profiling of Primary Mesothelioma Cultures Defines Subtypes with Different Expression Profiles and Clinical Responses.

Science.gov (United States)

Schunselaar, Laurel M; Quispel-Janssen, Josine M M F; Kim, Yongsoo; Alifrangis, Constantine; Zwart, Wilbert; Baas, Paul; Neefjes, Jacques

2018-04-01

Purpose: Finding new treatment options for patients with malignant pleural mesothelioma is challenging due to the rarity and heterogeneity of this cancer type. The absence of druggable targets further complicates the development of new therapies. Current treatment options are therefore limited, and prognosis remains poor. Experimental Design: We performed drug screening on primary mesothelioma cultures to guide treatment decisions of corresponding patients that were progressive after first- or second-line treatment. Results: We observed a high concordance between in vitro results and clinical outcomes. We defined three subgroups responding differently to the anticancer drugs tested. In addition, gene expression profiling yielded distinct signatures that segregated the differently responding subgroups. These genes signatures involved various pathways, most prominently the fibroblast growth factor pathway. Conclusions: Our primary mesothelioma culture system has proved to be suitable to test novel drugs. Chemical profiling of primary mesothelioma cultures allows personalizing treatment for a group of patients with a rare tumor type where clinical trials are notoriously difficult. This personalized treatment strategy is expected to improve the poor prospects of patients with mesothelioma. Clin Cancer Res; 24(7); 1761-70. ©2017 AACR See related commentary by John and Chia, p. 1513 . ©2017 American Association for Cancer Research.

Leading-Edge Noise Prediction of General Airfoil Profiles with Spanwise-Varying Inflow Conditions

NARCIS (Netherlands)

Miotto, Renato Fuzaro; Wolf, William Roberto; De Santana, Leandro Dantas

2018-01-01

This paper presents a study of the leading-edge noise radiated by an airfoil undergoing a turbulent inflow. The noise prediction of generic airfoil profiles subjected to spanwise-varying inflow conditions is performed with the support of Amiet’s theory and the inverse strip technique. In the

Leading-Edge Noise Prediction of General Airfoil Profiles with Spanwise-Varying Inflow Conditions

NARCIS (Netherlands)

Miotto, Renato Fuzaro; Wolf, William Roberto; De Santana, Leandro Dantas

This paper presents a study of the leading-edge noise radiated by an airfoil undergoing a turbulent inflow. The noise prediction of generic airfoil profiles subjected to spanwise-varying inflow conditions is performed with the support of Amiet’s theory and the inverse strip technique. In the

Clinical features and endocrine profile of Laron syndrome in Indian children.

Science.gov (United States)

Phanse-Gupte, Supriya R; Khadilkar, Vaman V; Khadilkar, Anuradha V

2014-11-01

Patients with growth hormone (GH) insensitivity (also known as Laron syndome) have been reported from the Mediterranean region and Southern Eucador, with few case reports from India. We present here the clinical and endocrine profile of 9 children with Laron syndrome from India. Nine children diagnosed with Laron syndrome based on clinical features of GH deficiency and biochemical profile suggestive of GH resistance were studied over a period of 5 years from January 2008 to January 2013. Age of presentation was between 2.5-11.5 years. All children were considerably short on contemporary Indian charts with mean (SD) height Z score -5.2 (1.6). However, they were within ± 2 SD on Laron charts. No child was overweight [mean (SD) BMI Z score 0.92 (1.1)]. All children had characteristic facies of GH deficiency with an added feature of prominent eyes. Three boys had micropenis and 1 had unilateral undescended testis. All children had low IGF-1 (Laron syndrome should be suspected in children with clinical features of GH deficiency, high GH levels and low IGF-1/IGFBP-3. These children are in a state of GH resistance and need IGF-1 therapy.

Clinical profile of children with developmental delay and microcephaly

Science.gov (United States)

Aggarwal, Anju; Mittal, Hema; Patil, Rahul; Debnath, Sanjib; Rai, Anuradha

2013-01-01

Aim: To study the profile of children with developmental delay and microcephaly. Materials and Methods: Children attending child development clinic with developmental delay were evaluated as per protocol. Z scores of head circumference were calculated using WHO charts. Clinical, radiological and etiological profile of those with microcephaly and those without was compared. Results: Of the 414 children with developmental delay 231 had microcephaly (z score ≤ -3). Mean age of children with microcephaly was 35.1 ± 27.9 months (range 4-184), males (72.7%). Comorbidities were epilepsy (42.9%), visual abnormality (26.4%), hearing abnormality (16.9%). Mean DQ was 29.75 + 17.8 in those with microcephaly was significantly lower compared to the rest (P = 0.002). Secondary microcephaly was associated with cerebral palsy in 69.7%. Other causes were congenital infections (4), inborn error of metabolism (3), post-meningoencephalitis (5), malformations (12), and syndromic (13). Neuroimaging was done in 118 (51.1%) cases of which 104 (88.1%) were abnormal. On comparison children with microcephaly had more epilepsy, lower developmental quotient, vision abnormalities findings as compared to normocephalic children with developmental delay (P > 0.05). Conclusion: Microcephaly was associated with lower, DQ, higher comorbidities in children with developmental delay. Spastic CP is commonly associated with microcephaly. PMID:24250161

Comparison of percentage body fat and body mass index for the prediction of inflammatory and atherogenic lipid risk profiles in elderly women.

Science.gov (United States)

Funghetto, Silvana Schwerz; Silva, Alessandro de Oliveira; de Sousa, Nuno Manuel Frade; Stival, Marina Morato; Tibana, Ramires Alsamir; Pereira, Leonardo Costa; Antunes, Marja Letícia Chaves; de Lima, Luciano Ramos; Prestes, Jonato; Oliveira, Ricardo Jacó; Dutra, Maurílio Tiradentes; Souza, Vinícius Carolino; Nascimento, Dahan da Cunha; Karnikowski, Margô Gomes de Oliveira

2015-01-01

To compare the clinical classification of the body mass index (BMI) and percentage body fat (PBF) for the prediction of inflammatory and atherogenic lipid profile risk in older women. Cross-sectional analytical study with 277 elderly women from a local community in the Federal District, Brazil. PBF and fat-free mass (FFM) were determined by dual energy X-ray absorptiometry. The investigated inflammatory parameters were interleukin 6 and C-reactive protein. Twenty-five percent of the elderly women were classified as normal weight, 50% overweight, and 25% obese by the BMI. The obese group had higher levels of triglycerides and very low-density lipoproteins than did the normal weight group (P≤0.05) and lower levels of high-density lipoproteins (HDL) than did the overweight group (P≤0.05). According to the PBF, 49% of the elderly women were classified as eutrophic, 28% overweight, and 23% obese. In the binomial logistic regression analyses including age, FFM, and lipid profile, only FFM (odds ratio [OR]=0.809, 95% confidence interval [CI]: 0.739-0.886; Pprofile is key to assessing the risk of cardiometabolic diseases. Classification based on dual energy X-ray absorptiometry measures, along with biochemical and inflammatory parameters, seems to have a great clinical importance, since it allows the lipid profile eutrophic distinction in elderly overweight women.

Modeling and prediction of extraction profile for microwave-assisted extraction based on absorbed microwave energy.

Science.gov (United States)

Chan, Chung-Hung; Yusoff, Rozita; Ngoh, Gek-Cheng

2013-09-01

A modeling technique based on absorbed microwave energy was proposed to model microwave-assisted extraction (MAE) of antioxidant compounds from cocoa (Theobroma cacao L.) leaves. By adapting suitable extraction model at the basis of microwave energy absorbed during extraction, the model can be developed to predict extraction profile of MAE at various microwave irradiation power (100-600 W) and solvent loading (100-300 ml). Verification with experimental data confirmed that the prediction was accurate in capturing the extraction profile of MAE (R-square value greater than 0.87). Besides, the predicted yields from the model showed good agreement with the experimental results with less than 10% deviation observed. Furthermore, suitable extraction times to ensure high extraction yield at various MAE conditions can be estimated based on absorbed microwave energy. The estimation is feasible as more than 85% of active compounds can be extracted when compared with the conventional extraction technique. Copyright © 2013 Elsevier Ltd. All rights reserved.

The Impact of Mission Profile Models on the Predicted Lifetime of IGBT Modules in the Modular Multilevel Converter

DEFF Research Database (Denmark)

Zhang, Yi; Wang, Huai; Wang, Zhongxu

2017-01-01

and electrical power modeling methods on the estimated lifetime of IGBT modules in an MMC for offshore wind power application. In a 30 MW MMC case study, an annual wind speed profile with a resolution of 1 s/data, 10 minute/data, and 1 hour/data are considered, respectively. A method to re-generate higher......The reliability aspect study of Modular Multilevel Converter (MMC) is of great interest in industry applications, such as offshore wind. Lifetime prediction of key components is an important tool to design MMC with fulfilled reliability specifications. While many efforts have been made...... to the lifetime prediction of IGBT modules in renewable energy applications by considering long-term varying operation conditions (i.e., mission profile), the justifications of using the associated mission profiles are still missed. This paper investigates the impact of mission profile data resolutions...

Human In Silico Drug Trials Demonstrate Higher Accuracy than Animal Models in Predicting Clinical Pro-Arrhythmic Cardiotoxicity.

Science.gov (United States)

Passini, Elisa; Britton, Oliver J; Lu, Hua Rong; Rohrbacher, Jutta; Hermans, An N; Gallacher, David J; Greig, Robert J H; Bueno-Orovio, Alfonso; Rodriguez, Blanca

2017-01-01

Early prediction of cardiotoxicity is critical for drug development. Current animal models raise ethical and translational questions, and have limited accuracy in clinical risk prediction. Human-based computer models constitute a fast, cheap and potentially effective alternative to experimental assays, also facilitating translation to human. Key challenges include consideration of inter-cellular variability in drug responses and integration of computational and experimental methods in safety pharmacology. Our aim is to evaluate the ability of in silico drug trials in populations of human action potential (AP) models to predict clinical risk of drug-induced arrhythmias based on ion channel information, and to compare simulation results against experimental assays commonly used for drug testing. A control population of 1,213 human ventricular AP models in agreement with experimental recordings was constructed. In silico drug trials were performed for 62 reference compounds at multiple concentrations, using pore-block drug models (IC 50 /Hill coefficient). Drug-induced changes in AP biomarkers were quantified, together with occurrence of repolarization/depolarization abnormalities. Simulation results were used to predict clinical risk based on reports of Torsade de Pointes arrhythmias, and further evaluated in a subset of compounds through comparison with electrocardiograms from rabbit wedge preparations and Ca 2+ -transient recordings in human induced pluripotent stem cell-derived cardiomyocytes (hiPS-CMs). Drug-induced changes in silico vary in magnitude depending on the specific ionic profile of each model in the population, thus allowing to identify cell sub-populations at higher risk of developing abnormal AP phenotypes. Models with low repolarization reserve (increased Ca 2+ /late Na + currents and Na + /Ca 2+ -exchanger, reduced Na + /K + -pump) are highly vulnerable to drug-induced repolarization abnormalities, while those with reduced inward current density

Human In Silico Drug Trials Demonstrate Higher Accuracy than Animal Models in Predicting Clinical Pro-Arrhythmic Cardiotoxicity

Directory of Open Access Journals (Sweden)

Elisa Passini

2017-09-01

Full Text Available Early prediction of cardiotoxicity is critical for drug development. Current animal models raise ethical and translational questions, and have limited accuracy in clinical risk prediction. Human-based computer models constitute a fast, cheap and potentially effective alternative to experimental assays, also facilitating translation to human. Key challenges include consideration of inter-cellular variability in drug responses and integration of computational and experimental methods in safety pharmacology. Our aim is to evaluate the ability of in silico drug trials in populations of human action potential (AP models to predict clinical risk of drug-induced arrhythmias based on ion channel information, and to compare simulation results against experimental assays commonly used for drug testing. A control population of 1,213 human ventricular AP models in agreement with experimental recordings was constructed. In silico drug trials were performed for 62 reference compounds at multiple concentrations, using pore-block drug models (IC50/Hill coefficient. Drug-induced changes in AP biomarkers were quantified, together with occurrence of repolarization/depolarization abnormalities. Simulation results were used to predict clinical risk based on reports of Torsade de Pointes arrhythmias, and further evaluated in a subset of compounds through comparison with electrocardiograms from rabbit wedge preparations and Ca2+-transient recordings in human induced pluripotent stem cell-derived cardiomyocytes (hiPS-CMs. Drug-induced changes in silico vary in magnitude depending on the specific ionic profile of each model in the population, thus allowing to identify cell sub-populations at higher risk of developing abnormal AP phenotypes. Models with low repolarization reserve (increased Ca2+/late Na+ currents and Na+/Ca2+-exchanger, reduced Na+/K+-pump are highly vulnerable to drug-induced repolarization abnormalities, while those with reduced inward current density

Neonatal Pulmonary MRI of Bronchopulmonary Dysplasia Predicts Short-term Clinical Outcomes.

Science.gov (United States)

Higano, Nara S; Spielberg, David R; Fleck, Robert J; Schapiro, Andrew H; Walkup, Laura L; Hahn, Andrew D; Tkach, Jean A; Kingma, Paul S; Merhar, Stephanie L; Fain, Sean B; Woods, Jason C

2018-05-23

Bronchopulmonary dysplasia (BPD) is a serious neonatal pulmonary condition associated with premature birth, but the underlying parenchymal disease and trajectory are poorly characterized. The current NICHD/NHLBI definition of BPD severity is based on degree of prematurity and extent of oxygen requirement. However, no clear link exists between initial diagnosis and clinical outcomes. We hypothesized that magnetic resonance imaging (MRI) of structural parenchymal abnormalities will correlate with NICHD-defined BPD disease severity and predict short-term respiratory outcomes. Forty-two neonates (20 severe BPD, 6 moderate, 7 mild, 9 non-BPD controls; 40±3 weeks post-menstrual age) underwent quiet-breathing structural pulmonary MRI (ultrashort echo-time and gradient echo) in a NICU-sited, neonatal-sized 1.5T scanner, without sedation or respiratory support unless already clinically prescribed. Disease severity was scored independently by two radiologists. Mean scores were compared to clinical severity and short-term respiratory outcomes. Outcomes were predicted using univariate and multivariable models including clinical data and scores. MRI scores significantly correlated with severities and predicted respiratory support at NICU discharge (P<0.0001). In multivariable models, MRI scores were by far the strongest predictor of respiratory support duration over clinical data, including birth weight and gestational age. Notably, NICHD severity level was not predictive of discharge support. Quiet-breathing neonatal pulmonary MRI can independently assess structural abnormalities of BPD, describe disease severity, and predict short-term outcomes more accurately than any individual standard clinical measure. Importantly, this non-ionizing technique can be implemented to phenotype disease and has potential to serially assess efficacy of individualized therapies.

Sociodemographic and clinical profile of patients in voluntary and involuntary psychiatric hospitalizations

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Carlos Robson Bezerra de Medeiros

2011-12-01

Full Text Available Objective: To assess the sociodemographic and clinical profile of patients in psychiatric hospitalizations of voluntary inpatients (IPV and involuntary (IPI, in psychiatric hospitals of Fortaleza-CE, Brazil, under contract with the Unified Health System (SUS. Methods: A quantitative study, descriptive, cross-sectional and analytical. The sample comprised 393 patients, distributed among 253 IPV and 140 IPI, submitted to Psychiatry specialtytreatment, in the year 2007. Results: For both patients, IPV and IPI, most were male: 185 (73.1% and 82 (58.6%; single: 181 (46.7% and 103 (26.5%; living in Fortaleza: 181 (71.5% and 95 (67.9%, respectively, and aged 20 to 60 years (mean age of 37 years. Weobserved significant difference between the type of hospital and patient gender (p = 0.003, which did not occur with marital status (p = 0.688 and origin (p = 0.95. The main symptom profiles which justified the clinical admission of these patients were the use of alcohol or drugs 70 (27.6%, changes in critical judgments 40 (28.6% and psychological distress 68 (26.9%. Family members were the main responsible for conducting these patients to the hospital. Conclusion: The results showed that patients on IPV and IPI, which joined in the study, had a socio-demographic and clinical profile characterized by: prevalence of male patients, from the capital Fortaleza, single, mean age of 37 years, having been brought tohospital by a relative, mainly due to alcohol use or drugs.

Systematic review of the global epidemiology, clinical and laboratory profile of enteric fever

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Asma Azmatullah

2015-12-01

Full Text Available Children suffer the highest burden of enteric fever among populations in South Asian countries. The clinical features are non–specific, vary in populations, and are often difficult to distinguish clinically from other febrile illnesses, leading to delayed or inappropriate diagnosis and treatment. We undertook a systematic review to assess the clinical profile and laboratory features of enteric fever across age groups, economic regions, level of care and antibiotic susceptibility patterns.

Prediction of fracture profile using digital image correlation

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Chaitanya, G. M. S. K.; Sasi, B.; Kumar, Anish; Babu Rao, C.; Purnachandra Rao, B.; Jayakumar, T.

2015-04-01

Digital Image Correlation (DIC) based full field strain mapping methodology is used for mapping strain on an aluminum sample subjected to tensile deformation. The local strains on the surface of the specimen are calculated at different strain intervals. Early localization of strain is observed at a total strain of 0.050ɛ; itself, whereas a visually apparent localization of strain is observed at a total strain of 0.088ɛ;. Orientation of the line of fracture (12.0°) is very close to the orientation of locus of strain maxima (11.6°) computed from the strain mapping at 0.063ɛ itself. These results show the efficacy of the DIC based method to predict the location as well as the profile of the fracture, at an early stage.

A Report of Six Clinical Cases of Lowered Blood Cholesterol Profile ...

African Journals Online (AJOL)

Purpose: To assess six patients with Diabegard® supplementation with reference to cholesterol profiles. Methods: We report the clinical courses of six individuals taking Diabegard® supplementation at 60 and 120 mg/day for 8 weeks. Results: Patients had a maximum of 52.13 % reduction in low-density lipoprotein (LDL) ...

Clinical & biochemical profile of trichinellosis outbreak in north India

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Rahul K Sharma

2014-01-01

Full Text Available Background & objectives: Trichinellosis is a parasitic infection caused by Trichinella nematodes, acquired from consumption of raw meat. However, data from Indian subcontinent are limited. The aim of this study was to investigate the clinical and biochemical profile of a suspected trichinellosis outbreak in a village in Tehri Garhwal district of Uttarakhand state in north India. Methods: Three index cases presenting as acute febrile myalgia syndrome with eosinophilia, after consumption of uncooked pork in a common feast, were confirmed as trichinellosis on muscle biopsy. A detailed epidemiological survey was carried out in the affected community and all the people who participated in the feast were investigated for clinical and biochemical profile. Results: A total of 54 patients were evaluated in the study. The type of pork consumed included uncooked in 24 per cent (n=13, open fire roasted in 39 per cent (n=21 and fried in 37 per cent (n=20. Clinical symptoms were found in those who consumed pork in uncooked or open fire roasted form (n=34. These included fever with chills and myalgia (100%, periorbital oedema (67%, dyspnoea (9%, and dysphagia (3%. Laboratory parameters studied in both symptomatic and asymptomatic patients showed eosinophilia in 90 per cent (n=41, raised ESR in 98 per cent (n=45, and an elevated creatinine phosphokinase (CPK level in 85 per cent (n=39. All symptomatic patients were treated with a short course of oral steroids and albendazole therapy. Conclusions: Trichinella infection is not uncommon in India, and should be suspected in case of acute febrile myalgia especially in areas, where habits of consumption of raw meat is more prevalent.

Tumor microenvironment in head and neck squamous cell carcinomas: predictive value and clinical relevance of hypoxic markers. A review.

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Hoogsteen, Ilse J; Marres, Henri A M; Bussink, Johan; van der Kogel, Albert J; Kaanders, Johannes H A M

2007-06-01

Hypoxia and tumor cell proliferation are important factors determining the treatment response of squamous cell carcinomas of the head and neck. Successful approaches have been developed to counteract these resistance mechanisms although usually at the cost of increased short- and long-term side effects. To provide the best attainable quality of life for individual patients and the head and neck cancer patient population as a whole, it is of increasing importance that tools be developed that allow a better selection of patients for these intensified treatments. A literature review was performed with special focus on the predictive value and clinical relevance of endogenous hypoxia-related markers. New methods for qualitative and quantitative assessment of functional microenvironmental parameters such as hypoxia, proliferation, and vasculature have identified several candidate markers for future use in predictive assays. Hypoxia-related markers include hypoxia inducible factor (HIF)-1alpha, carbonic anhydrase IX, glucose transporters, erythropoietin receptor, osteopontin, and others. Although several of these markers and combinations of markers are associated with treatment outcome, their clinical value as predictive factors remains to be established. A number of markers and marker profiles have emerged that may have potential as a predictive assay. Validation of these candidate assays requires testing in prospective trials comparing standard treatment against experimental treatments targeting the related microregional constituent. (c) 2007 Wiley Periodicals, Inc. Head Neck, 2007.

Conversational assessment in memory clinic encounters: interactional profiling for differentiating dementia from functional memory disorders.

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Jones, Danielle; Drew, Paul; Elsey, Christopher; Blackburn, Daniel; Wakefield, Sarah; Harkness, Kirsty; Reuber, Markus

2016-01-01

In the UK dementia is under-diagnosed, there is limited access to specialist memory clinics, and many of the patients referred to such clinics are ultimately found to have functional (non-progressive) memory disorders (FMD), rather than a neurodegenerative disorder. Government initiatives on 'timely diagnosis' aim to improve the rate and quality of diagnosis for those with dementia. This study seeks to improve the screening and diagnostic process by analysing communication between clinicians and patients during initial specialist clinic visits. Establishing differential conversational profiles could help the timely differential diagnosis of memory complaints. This study is based on video- and audio recordings of 25 initial consultations between neurologists and patients referred to a UK memory clinic. Conversation analysis was used to explore recurrent communicative practices associated with each diagnostic group. Two discrete conversational profiles began to emerge, to help differentiate between patients with dementia and functional memory complaints, based on (1) whether the patient is able to answer questions about personal information; (2) whether they can display working memory in interaction; (3) whether they are able to respond to compound questions; (4) the time taken to respond to questions; and (5) the level of detail they offer when providing an account of their memory failure experiences. The distinctive conversational profiles observed in patients with functional memory complaints on the one hand and neurodegenerative memory conditions on the other suggest that conversational profiling can support the differential diagnosis of functional and neurodegenerative memory disorders.

Immunological monitoring for prediction of clinical response to antitumor vaccine therapy.

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Mikhaylova, Irina N; Shubina, Irina Zh; Chkadua, George Z; Petenko, Natalia N; Morozova, Lidia F; Burova, Olga S; Beabelashvili, Robert Sh; Parsunkova, Kermen A; Balatskaya, Natalia V; Chebanov, Dmitrii K; Pospelov, Vadim I; Nazarova, Valeria V; Vihrova, Anastasia S; Cheremushkin, Evgeny A; Molodyk, Alvina A; Kiselevsky, Mikhail V; Demidov, Lev V

2018-05-11

Immunotherapy has shown promising results in a variety of cancers, including melanoma. However, the responses to therapy are usually heterogeneous, and understanding the factors affecting clinical outcome is still not achieved. Here, we show that immunological monitoring of the vaccine therapy for melanoma patients may help to predict the clinical course of the disease. We studied cytokine profile of cellular Th1 (IL-2, IL-12, IFN-γ) and humoral Th2 (IL-4, IL-10) immune response, vascular endothelial growth factor (VEGFA), transforming growth factor-β 2 (TGF-β 2), S100 protein (S100A1B and S100BB), adhesion molecule CD44 and serum cytokines β2-microglobulin to analyze different peripheral blood mononuclear cell subpopuations of patients treated with dendritic vaccines and/or cyclophosphamide in melanoma patients in the course of adjuvant treatment. The obtained data indicate predominance of cellular immunity in the first adjuvant group of patients with durable time to progression and shift to humoral with low cellular immunity in patients with short-term period to progression (increased levels of IL-4 and IL- 10). Beta-2 microglobulin was differentially expressed in adjuvant subgroups: its higher levels correlated with shorter progression-free survival and the total follow-up time. Immunoregulatory index was overall higher in patients with disease progression compared to the group of patients with no signs of disease progression.

The Meta-Analysis of Clinical Judgment Project: Fifty-Six Years of Accumulated Research on Clinical Versus Statistical Prediction

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Aegisdottir, Stefania; White, Michael J.; Spengler, Paul M.; Maugherman, Alan S.; Anderson, Linda A.; Cook, Robert S.; Nichols, Cassandra N.; Lampropoulos, Georgios K.; Walker, Blain S.; Cohen, Genna; Rush, Jeffrey D.

2006-01-01

Clinical predictions made by mental health practitioners are compared with those using statistical approaches. Sixty-seven studies were identified from a comprehensive search of 56 years of research; 92 effect sizes were derived from these studies. The overall effect of clinical versus statistical prediction showed a somewhat greater accuracy for…

Clinical chemistry in higher dimensions: Machine-learning and enhanced prediction from routine clinical chemistry data.

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Richardson, Alice; Signor, Ben M; Lidbury, Brett A; Badrick, Tony

2016-11-01

Big Data is having an impact on many areas of research, not the least of which is biomedical science. In this review paper, big data and machine learning are defined in terms accessible to the clinical chemistry community. Seven myths associated with machine learning and big data are then presented, with the aim of managing expectation of machine learning amongst clinical chemists. The myths are illustrated with four examples investigating the relationship between biomarkers in liver function tests, enhanced laboratory prediction of hepatitis virus infection, the relationship between bilirubin and white cell count, and the relationship between red cell distribution width and laboratory prediction of anaemia. Copyright © 2016 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

Bayesian Nonparametric Estimation of Targeted Agent Effects on Biomarker Change to Predict Clinical Outcome

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Graziani, Rebecca; Guindani, Michele; Thall, Peter F.

2015-01-01

Summary The effect of a targeted agent on a cancer patient's clinical outcome putatively is mediated through the agent's effect on one or more early biological events. This is motivated by pre-clinical experiments with cells or animals that identify such events, represented by binary or quantitative biomarkers. When evaluating targeted agents in humans, central questions are whether the distribution of a targeted biomarker changes following treatment, the nature and magnitude of this change, and whether it is associated with clinical outcome. Major difficulties in estimating these effects are that a biomarker's distribution may be complex, vary substantially between patients, and have complicated relationships with clinical outcomes. We present a probabilistically coherent framework for modeling and estimation in this setting, including a hierarchical Bayesian nonparametric mixture model for biomarkers that we use to define a functional profile of pre-versus-post treatment biomarker distribution change. The functional is similar to the receiver operating characteristic used in diagnostic testing. The hierarchical model yields clusters of individual patient biomarker profile functionals, and we use the profile as a covariate in a regression model for clinical outcome. The methodology is illustrated by analysis of a dataset from a clinical trial in prostate cancer using imatinib to target platelet-derived growth factor, with the clinical aim to improve progression-free survival time. PMID:25319212

TP53, STK11 and EGFR Mutations Predict Tumor Immune Profile and the Response to anti-PD-1 in Lung Adenocarcinoma.

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Biton, Jerome; Mansuet-Lupo, Audrey; Pécuchet, Nicolas; Alifano, Marco; Ouakrim, Hanane; Arrondeau, Jennifer; Boudou-Rouquette, Pascaline; Goldwasser, Francois; Leroy, Karen; Goc, Jeremy; Wislez, Marie; Germain, Claire; Laurent-Puig, Pierre; Dieu-Nosjean, Marie-Caroline; Cremer, Isabelle; Herbst, Ronald; Blons, Hélène F; Damotte, Diane

2018-05-15

By unlocking anti-tumor immunity, antibodies targeting programmed cell death 1 (PD-1) exhibit impressive clinical results in non-small cell lung cancer, underlining the strong interactions between tumor and immune cells. However, factors that can robustly predict long-lasting responses are still needed. We performed in depth immune profiling of lung adenocarcinoma using an integrative analysis based on immunohistochemistry, flow-cytometry and transcriptomic data. Tumor mutational status was investigated using next-generation sequencing. The response to PD-1 blockers was analyzed from a prospective cohort according to tumor mutational profiles and to PD-L1 expression, and a public clinical database was used to validate the results obtained. We showed that distinct combinations of STK11 , EGFR and TP53 mutations, were major determinants of the tumor immune profile (TIP) and of the expression of PD-L1 by malignant cells. Indeed, the presence of TP53 mutations without co-occurring STK11 or EGFR alterations ( TP53 -mut/ STK11 - EGFR -WT), independently of KRAS mutations, identified the group of tumors with the highest CD8 T cell density and PD-L1 expression. In this tumor subtype, pathways related to T cell chemotaxis, immune cell cytotoxicity, and antigen processing were up-regulated. Finally, a prolonged progression-free survival (PFS: HR=0.32; 95% CI, 0.16-0.63, p <0.001) was observed in anti-PD-1 treated patients harboring TP53 -mut/ STK11 - EGFR -WT tumors. This clinical benefit was even more remarkable in patients with associated strong PD-L1 expression. Our study reveals that different combinations of TP53 , EGFR and STK11 mutations , together with PD-L1 expression by tumor cells, represent robust parameters to identify best responders to PD-1 blockade. Copyright ©2018, American Association for Cancer Research.

Elderly fall risk prediction based on a physiological profile approach using artificial neural networks.

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Razmara, Jafar; Zaboli, Mohammad Hassan; Hassankhani, Hadi

2016-11-01

Falls play a critical role in older people's life as it is an important source of morbidity and mortality in elders. In this article, elders fall risk is predicted based on a physiological profile approach using a multilayer neural network with back-propagation learning algorithm. The personal physiological profile of 200 elders was collected through a questionnaire and used as the experimental data for learning and testing the neural network. The profile contains a series of simple factors putting elders at risk for falls such as vision abilities, muscle forces, and some other daily activities and grouped into two sets: psychological factors and public factors. The experimental data were investigated to select factors with high impact using principal component analysis. The experimental results show an accuracy of ≈90 percent and ≈87.5 percent for fall prediction among the psychological and public factors, respectively. Furthermore, combining these two datasets yield an accuracy of ≈91 percent that is better than the accuracy of single datasets. The proposed method suggests a set of valid and reliable measurements that can be employed in a range of health care systems and physical therapy to distinguish people who are at risk for falls.

The Hampstead Clinic at work. Discussions in the Diagnostic Profile Research Group.

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Koch, Ehud

2012-01-01

Minutes of the Hampstead Clinic's Diagnostic Profile Research Group during a fifteen-month period (1964-1965) are reviewed and discussed. A wide range of topics were considered and discussed, with a special focus on the affective life, object relations, and ego function of atypical children in comparison to the early ego functions and differentiation of normal and neurotic children. These lively clinical and theoretical discussions and their implications for therapeutic work with a wide range of children, demonstrate the multifaceted leadership and contributions of Anna Freud as teacher, clinician, and thinker, and of the Hampstead Clinic as a major center for psychoanalytic studies.

Acylcarnitines profile best predicts survival in horses with atypical myopathy.

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François Boemer

Full Text Available Equine atypical myopathy (AM is caused by hypoglycin A intoxication and is characterized by a high fatality rate. Predictive estimation of survival in AM horses is necessary to prevent unnecessary suffering of animals that are unlikely to survive and to focus supportive therapy on horses with a possible favourable prognosis of survival. We hypothesized that outcome may be predicted early in the course of disease based on the assumption that the acylcarnitine profile reflects the derangement of muscle energetics. We developed a statistical model to prognosticate the risk of death of diseased animals and found that estimation of outcome may be drawn from three acylcarnitines (C2, C10:2 and C18 -carnitines with a high sensitivity and specificity. The calculation of the prognosis of survival makes it possible to distinguish the horses that will survive from those that will die despite severe signs of acute rhabdomyolysis in both groups.

Acylcarnitines profile best predicts survival in horses with atypical myopathy

Science.gov (United States)

Detilleux, Johann; Cello, Christophe; Amory, Hélène; Marcillaud-Pitel, Christel; Richard, Eric; van Galen, Gaby; van Loon, Gunther; Lefère, Laurence; Votion, Dominique-Marie

2017-01-01

Equine atypical myopathy (AM) is caused by hypoglycin A intoxication and is characterized by a high fatality rate. Predictive estimation of survival in AM horses is necessary to prevent unnecessary suffering of animals that are unlikely to survive and to focus supportive therapy on horses with a possible favourable prognosis of survival. We hypothesized that outcome may be predicted early in the course of disease based on the assumption that the acylcarnitine profile reflects the derangement of muscle energetics. We developed a statistical model to prognosticate the risk of death of diseased animals and found that estimation of outcome may be drawn from three acylcarnitines (C2, C10:2 and C18 -carnitines) with a high sensitivity and specificity. The calculation of the prognosis of survival makes it possible to distinguish the horses that will survive from those that will die despite severe signs of acute rhabdomyolysis in both groups. PMID:28846683

Profile control simulations and experiments on TCV : A controller test environment and results using a model-based predictive controller

NARCIS (Netherlands)

Maljaars, E.; Felici, F.; Blanken, T.C.; Galperti, C.; Sauter, O.; de Baar, M.R.; Carpanese, F.; Goodman, T.P.; Kim, D.; Kim, S.H.; Kong, M.G.; Mavkov, B.; Merle, A.; Moret, J.M.; Nouailletas, R.; Scheffer, M.; Teplukhina, A.A.; Vu, N.M.T.

2017-01-01

The successful performance of a model predictive profile controller is demonstrated in simulations and experiments on the TCV tokamak, employing a profile controller test environment. Stable high-performance tokamak operation in hybrid and advanced plasma scenarios requires control over the safety

Profile control simulations and experiments on TCV: a controller test environment and results using a model-based predictive controller

NARCIS (Netherlands)

Maljaars, B.; Felici, F.; Blanken, T. C.; Galperti, C.; Sauter, O.; de Baar, M. R.; Carpanese, F.; Goodman, T. P.; Kim, D.; Kim, S. H.; Kong, M.; Mavkov, B.; Merle, A.; Moret, J.; Nouailletas, R.; Scheffer, M.; Teplukhina, A.; Vu, T.

2017-01-01

The successful performance of a model predictive profile controller is demonstrated in simulations and experiments on the TCV tokamak, employing a profile controller test environment. Stable high-performance tokamak operation in hybrid and advanced plasma scenarios requires control over the safety

[Clinical and psychopathological profile of women victims of psychological partner violence].

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Lamy, C; Dubois, F; Jaafari, N; Carl, T; Gaillard, P; Camus, V; El Hage, W

2009-08-01

Partner violence is a serious public health problem, due to their potential short-, medium- or long-term physical and psychological consequences. Violence is unbearable when it occurs between family members, and often remains unrevealed, invisible, hidden and repeated. The woman possibly feels trapped in a relationship of imprisonment. International studies have well-explored the psychopathological aspects of physical and sexual abuse within couples, but few explored the clinical profile of women victims of psychological violence or moral harassment. This study aims to define the clinical and psychopathological profile of women who are victims of psychological intimate partner violence. We contacted 628 women who consulted consecutively at the emergency ward of a university hospital covering a 300,000 catchment area. The telephone screening of psychological violence was therefore carried out using the Women's Experience with Battering (WEB) questionnaire (N=226). An optional clinical interview was given to the women declaring themselves as victims of psychological intimate partner violence (N=56) to evaluate the life events and the psychiatric disorders according to the DSM-IV. Finally, 43 participants (77%) gave their opinion on the qualitative aspects of the WEB questionnaire and their level of ease with this report. In 63% (N=35) of the cases, the victims and their partners had a rather high socioprofessional level. Women refer to emergency ward mostly for complaint of vague idiopathic pain (49%) or for psychiatric disorders (52%) with predominance of anxiety (28%) or addictive disorders (19%). The prevalence of potentially traumatic life events was found to be high in this group (83%). The traumatic psychological intimate partner violence was associated with a heightened prevalence of psychiatric comorbidities, like anxiety (72%), depression (100%), posttraumatic stress disorder (100%), and addiction to alcohol (100%) or another psychoactive substance (50

Clinical predictive score of intracranial hemorrhage in mild traumatic brain injury

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Yuksen C

2018-02-01

Full Text Available Chaiyaporn Yuksen,1 Yuwares Sittichanbuncha,1 Jayanton Patumanond,2 Sombat Muengtaweepongsa,3 Kittisak Sawanyawisuth4,5 1Department of Emergency Medicine, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok, 2Clinical Epidemiology Unit and Clinical Research Center, Faculty of Medicine, Thammasat University, Pathum Thani, 3Department of Medicine, Faculty of Medicine, Thammasat University, Pathum Thani, 4Department of Medicine, Faculty of Medicine, Khon Kaen University, Khon Kaen, 5Sleep Apnea Research Group, Research Center in Back, Neck, Other Joint Pain and Human Performance (BNOJPH, and Research and Training Center for Enhancing Quality of Life of Working Age People, Khon Kaen University, Khon Kaen, Thailand Background: Mild traumatic brain injury (TBI is a common condition at the Emergency Medicine Department. Head computer tomography (CT scans in mild TBI patients must be properly justified in order to avoid unnecessary exposure to X-rays and to reduce the hospital/transfer costs. This study aimed to evaluate which clinical factors are associated with intracranial hemorrhage in Asian population and to develop a user-friendly predictive model.Methods: The study was conducted retrospectively at the Emergency Medicine Department in Ramathibodi Hospital, a university-affiliated super tertiary care hospital in Bangkok, Thailand. The study period was between September 2013 and August 2016. The inclusion criteria were age >15 years and having received a head CT scan after presenting with mild TBI. Those patients with mild TBI and no symptoms/deterioration after 24 h of clinical observation were excluded. The predictive model and prediction score for intracranial hemorrhage was developed by multivariate logistic regression analysis.Results: During the study period, there were 708 patients who met the study criteria. Of those, 100 patients (14.12% had positive head CT scan results. There were seven independent factors that were

Predicting reattendance at a high-risk breast cancer clinic.

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Ormseth, Sarah R; Wellisch, David K; Aréchiga, Adam E; Draper, Taylor L

2015-10-01

The research about follow-up patterns of women attending high-risk breast-cancer clinics is sparse. This study sought to profile daughters of breast-cancer patients who are likely to return versus those unlikely to return for follow-up care in a high-risk clinic. Our investigation included 131 patients attending the UCLA Revlon Breast Center High Risk Clinic. Predictor variables included age, computed breast-cancer risk, participants' perceived personal risk, clinically significant depressive symptomatology (CES-D score ≥ 16), current level of anxiety (State-Trait Anxiety Inventory), and survival status of participants' mothers (survived or passed away from breast cancer). A greater likelihood of reattendance was associated with older age (adjusted odds ratio [AOR] = 1.07, p = 0.004), computed breast-cancer risk (AOR = 1.10, p = 0.017), absence of depressive symptomatology (AOR = 0.25, p = 0.009), past psychiatric diagnosis (AOR = 3.14, p = 0.029), and maternal loss to breast cancer (AOR = 2.59, p = 0.034). Also, an interaction was found between mother's survival and perceived risk (p = 0.019), such that reattendance was associated with higher perceived risk among participants whose mothers survived (AOR = 1.04, p = 0.002), but not those whose mothers died (AOR = 0.99, p = 0.685). Furthermore, a nonlinear inverted "U" relationship was observed between state anxiety and reattendance (p = 0.037); participants with moderate anxiety were more likely to reattend than those with low or high anxiety levels. Demographic, medical, and psychosocial factors were found to be independently associated with reattendance to a high-risk breast-cancer clinic. Explication of the profiles of women who may or may not reattend may serve to inform the development and implementation of interventions to increase the likelihood of follow-up care.

Comparative prediction of nonepileptic events using MMPI-2 clinical scales, Harris Lingoes subscales, and restructured clinical scales.

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Yamout, Karim Z; Heinrichs, Robin J; Baade, Lyle E; Soetaert, Dana K; Liow, Kore K

2017-03-01

The Minnesota Multiphasic Personality Inventory-2 (MMPI-2) is a psychological testing tool used to measure psychological and personality constructs. The MMPI-2 has proven helpful in identifying individuals with nonepileptic events/nonepileptic seizures. However, the MMPI-2 has had some updates that enhanced its original scales. The aim of this article was to test the utility of updated MMPI-2 scales in predicting the likelihood of non-epileptic seizures in individuals admitted to an EEG video monitoring unit. We compared sensitivity, specificity, and likelihood ratios of traditional MMPI-2 Clinical Scales against more homogenous MMPI-2 Harris-Lingoes subscales and the newer Restructured Clinical (RC) scales. Our results showed that the Restructured Scales did not show significant improvement over the original Clinical scales. However, one Harris-Lingoes subscale (HL4 of Clinical Scale 3) did show improved predictive utility over the original Clinical scales as well as over the newer Restructured Clinical scales. Our study suggests that the predictive utility of the MMPI-2 can be improved using already existing scales. This is particularly useful for those practitioners who are not invested in switching over to the newly developed MMPI-2 Restructured Form (MMPI-2 RF). Copyright © 2016 Elsevier Inc. All rights reserved.

Predicting multi-class customer profiles based on transactions : a case study in food sales

NARCIS (Netherlands)

Apeh, E.; Zliobaite, I.; Pechenizkiy, M.; Gabrys, B.; Bramer, M.; Petridis, M.

2012-01-01

Predicting the class of customer profiles is a key task in marketing, which enables businesses to approach the customers in a right way to satisfy the customer’s evolving needs. However, due to costs, privacy and/or data protection, only the business’ owned transactional data is typically available

Serological profile of HSV-2 in patients attending STI clinic: Evaluation of diagnostic utility of HSV-2 IgM detection

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Choudhry Shilpee

2009-07-01

Full Text Available Objective: The present study was done to evaluate the serological profile of herpes simplex virus-2 (HSV-2 among patients attending sexually transmitted infections (STI clinic and to determine the utility of detecting HSV-2 IgM antibodies in such patients. A correlation of HSV-2 infection with other STI including HIV has also been attempted. Materials and Methods: Hundred consecutive patients who attended STI clinic, with one or more of the complaints as enunciated by WHO in syndromic approach for the diagnosis of STI, were included as subjects. All subjects were screened for common STI by standard laboratory procedures/ commercially available kits. HSV-1 and HSV-2 IgM antibody was detected by commercially available enzyme immuno assay kit in all patient′s sera. Sera were also tested for other STI, namely HIV, Hepatitis B virus, Hepatitis C virus and Treponema pallidum. Antigen detection for Chlamydia trachomatis was done in genital swabs of all patients by Bio-Rad Chlamydia Microplate EIA 31189 (United States kit. Results: Thirty patients were found to have genital herpes. In 17/30 (56.6% patients, HSV-2 serology was found to correlate with the clinical diagnosis. The coexistence of other infection in HSV-2 seropositive patients was detected in 8/30 patients. None of the patients having concomitant infections were clinically diagnosed accurately. Sensitivity, specificity, positive predictive value and negative predictive value of IgM antibodies for the diagnosis of genital herpes was 73.91%, 90.91%, 70.83% and 92.91% respectively. Conclusion: HSV-2 IgM detection could only be used as a supportive test for the diagnosis of genital herpes . It needs to be emphasized that the sensitivity and positive predictive value scores are pointers for further improvement in the commercial assay systems and a large sample size may determine the broader utility of such systems.

Profiling of volatile organic compounds produced by clinical Aspergillus isolates using gas chromatography-mass spectrometry

NARCIS (Netherlands)

Gerritsen, M G; Brinkman, P; Escobar Salazar, Natalia; Bos, L D; de Heer, K; Meijer, M; Janssen, H-G; de Cock, H; Wösten, H A B; Visser, C.E.; van Oers, M H J; Sterk, P J

Volatile organic compounds (VOCs) in exhaled breath may identify the presence of invasive pulmonary aspergillosis. We aimed to detect VOC profiles emitted by in vitro cultured, clinical Aspergillus isolates using gas chromatography-mass spectrometry (GC-MS). Three clinical Aspergillus isolates and a

Profiling of volatile organic compounds produced by clinical Aspergillus isolates using gas chromatography-mass spectrometry

NARCIS (Netherlands)

Gerritsen, M. G.; Brinkman, P.; Escobar, N.; Bos, L. D.; de Heer, K.; Meijer, M.; Janssen, H.-G.; de Cock, H.; Wösten, H. A. B.; Visser, C. E.; van Oers, M. H. J.; Sterk, P. J.

2018-01-01

Volatile organic compounds (VOCs) in exhaled breath may identify the presence of invasive pulmonary aspergillosis. We aimed to detect VOC profiles emitted by in vitro cultured, clinical Aspergillus isolates using gas chromatography-mass spectrometry (GC-MS). Three clinical Aspergillus isolates and a

Relationship between the prognostic and predictive value of the intrinsic subtypes and a validated gene profile predictive of loco-regional control and benefit from post-mastectomy radiotherapy in patients with high-risk breast cancer

DEFF Research Database (Denmark)

Tramm, Trine; Kyndi, Marianne; Myhre, Simen

2014-01-01

, and has shown prognostic impact in terms of loco-regional failure and predictive impact for PMRT. Reports have also shown predictive value in terms of benefit of PMRT from intrinsic subtypes and derived approximations. The aim of this study was to examine: 1) the agreement between various methods...... for determining the intrinsic subtypes; and 2) the relationship between the prognostic and predictive impact of the DBCG-RT profile and the intrinsic subtypes. MATERIAL AND METHODS: Intrinsic subtypes and the DBCG-RT profile was determined from microarray analysis based on fresh frozen tissue from 191 patients...... and predictive information obtained from the DBCG-RT profile cannot be substituted by any approximation of the tumors intrinsic subtype. The predictive value of the intrinsic subtypes in terms of PMRT was influenced by the method used for assignment to the intrinsic subtypes....

Long‐Term Post‐CABG Survival: Performance of Clinical Risk Models Versus Actuarial Predictions

Science.gov (United States)

Carr, Brendan M.; Romeiser, Jamie; Ruan, Joyce; Gupta, Sandeep; Seifert, Frank C.; Zhu, Wei

2015-01-01

Abstract Background/aim Clinical risk models are commonly used to predict short‐term coronary artery bypass grafting (CABG) mortality but are less commonly used to predict long‐term mortality. The added value of long‐term mortality clinical risk models over traditional actuarial models has not been evaluated. To address this, the predictive performance of a long‐term clinical risk model was compared with that of an actuarial model to identify the clinical variable(s) most responsible for any differences observed. Methods Long‐term mortality for 1028 CABG patients was estimated using the Hannan New York State clinical risk model and an actuarial model (based on age, gender, and race/ethnicity). Vital status was assessed using the Social Security Death Index. Observed/expected (O/E) ratios were calculated, and the models' predictive performances were compared using a nested c‐index approach. Linear regression analyses identified the subgroup of risk factors driving the differences observed. Results Mortality rates were 3%, 9%, and 17% at one‐, three‐, and five years, respectively (median follow‐up: five years). The clinical risk model provided more accurate predictions. Greater divergence between model estimates occurred with increasing long‐term mortality risk, with baseline renal dysfunction identified as a particularly important driver of these differences. Conclusions Long‐term mortality clinical risk models provide enhanced predictive power compared to actuarial models. Using the Hannan risk model, a patient's long‐term mortality risk can be accurately assessed and subgroups of higher‐risk patients can be identified for enhanced follow‐up care. More research appears warranted to refine long‐term CABG clinical risk models. doi: 10.1111/jocs.12665 (J Card Surg 2016;31:23–30) PMID:26543019

ABC gene expression profiles have clinical importance and possibly form a new hallmark of cancer.

Science.gov (United States)

Dvorak, Pavel; Pesta, Martin; Soucek, Pavel

2017-05-01

Adenosine triphosphate-binding cassette proteins constitute a large family of active transporters through extracellular and intracellular membranes. Increased drug efflux based on adenosine triphosphate-binding cassette protein activity is related to the development of cancer cell chemoresistance. Several articles have focused on adenosine triphosphate-binding cassette gene expression profiles (signatures), based on the expression of all 49 human adenosine triphosphate-binding cassette genes, in individual tumor types and reported connections to established clinicopathological features. The aim of this study was to test our theory about the existence of adenosine triphosphate-binding cassette gene expression profiles common to multiple types of tumors, which may modify tumor progression and provide clinically relevant information. Such general adenosine triphosphate-binding cassette profiles could constitute a new attribute of carcinogenesis. Our combined cohort consisted of tissues from 151 cancer patients-breast, colorectal, and pancreatic carcinomas. Standard protocols for RNA isolation and quantitative real-time polymerase chain reaction were followed. Gene expression data from individual tumor types as well as a merged tumor dataset were analyzed by bioinformatics tools. Several general adenosine triphosphate-binding cassette profiles, with differences in gene functions, were established and shown to have significant relations to clinicopathological features such as tumor size, histological grade, or clinical stage. Genes ABCC7, A3, A8, A12, and C8 prevailed among the most upregulated or downregulated ones. In conclusion, the results supported our theory about general adenosine triphosphate-binding cassette gene expression profiles and their importance for cancer on clinical as well as research levels. The presence of ABCC7 (official symbol CFTR) among the genes with key roles in the profiles supports the emerging evidence about its crucial role in various

Clinical profile of high-risk febrile neutropenia in a tertiary care hospital

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Mohan V Bhojaraja

2016-06-01

Full Text Available Background Infection in the immunocompromised host has been a reason of concern in the clinical setting and a topic of debate for decades. In this study, the aim was to analyse the clinical profile of high-risk febrile neutropenic patients. Aims To study the clinical profile of high risk febrile neutropenia patients with the objective of identifying the most common associated malignancy, most common associated pathogen, the source of infection, to correlate the treatment and management with that of the Infectious Diseases Society of America (IDSA 2010 guidelines and to assess the clinical outcome. Methods A cross-sectional time bound study was carried out and a total of 80 episodes of high-risk febrile neutropenia were recorded among patients with malignancies from September 2011 to July 2013 with each episode being taken as a new case. Results Non-Hodgkin’s lymphoma (30 per cent was the most common malignancy associated, commonest source of infection was due to central venous catheters, the commonest pathogens were gram negative (52 per cent the treatment and management of each episode of high risk febrile neutropenia correlated with that of IDSA 2010 guidelines and the mortality rate was 13.75 per cent. Conclusion Febrile neutropenia is one of the major complications and cause of mortality in patients with malignancy and hence understanding its entire spectrum can help us reduce morbidity and mortality.

Study Of Clinical Profile of Allergic Contact Dermatitis In Pune

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Sayal S K

1999-01-01

Full Text Available One hundred and twenty five cases of clinically diagnosed allergic contact dermatitis were studied. All patients were subjected to patch test with standard test allergens and also with suspected test allergens based on history and clinical profile. Allergic contact dermatitis due to Parthenium hysterophorus was commonest and found in 64% cases, followed by wearing apparel and jewellery in 16.8%, topical medicaments in 8% and cosmetics and occupational contactants in 5.6% cases each. The common individual allergens other than parthenium, were nickel in 8.8%, leather, hair dye and cement in 3.2% each, nitrofurazone and petrol, oil, lubricant (POL in 2.4% each. Patch test with suspected allergens was positive in 72% of cases.

CLINICAL PROFILE AND COMMON CAUSES OF HAEMOLYTIC ANAEMIA IN A TERTIARY CARE HOSPITAL, NORTHERN KERALA

OpenAIRE

Jog Antony; Reeta J; Sreelakshmi S; Rohit Mathew4; Adarsh Surendran

2016-01-01

BACKGROUND Haemolytic anaemia is a well-recognised clinical problem. This study looks into the clinical profile of haemolytic anaemia and also attempts to find out the common underlying causative disease. It also tries to group the patients according to the clinical manifestations and underlying causes. MATERIALS AND METHODS This is a hospital-based observational study conducted in a tertiary care centre in Northern Kerala. Forty-four adult patients with clinical manifestati...

In-flight measurements and RCS-predictions: A comparison on broad-side radar range profiles of a Boeing 737

NARCIS (Netherlands)

Heiden, R. van der; Ewijk, L.J. van; Groen, F.C.A.

1997-01-01

The validation of Radar Cross Section (RCS) prediction techniques against real measurements is crucial to acquire confidence in predictions when measurements are not available. In this paper we present the first results of a comparison on one dimensional images, i.e., radar range profiles. The

Statistical model based gender prediction for targeted NGS clinical panels

Directory of Open Access Journals (Sweden)

Palani Kannan Kandavel

2017-12-01

The reference test dataset are being used to test the model. The sensitivity on predicting the gender has been increased from the current “genotype composition in ChrX” based approach. In addition, the prediction score given by the model can be used to evaluate the quality of clinical dataset. The higher prediction score towards its respective gender indicates the higher quality of sequenced data.

The prediction of concentration profiles for a NIMCIX column absorbing uranium from aqueous solution

International Nuclear Information System (INIS)

Wright, R.S.

1979-01-01

A procedure is proposed for the prediction of concentration profiles for a countercurrent ion-exchange absorption column, use being made of equilibrium and kinetic data derived from small-scale batch tests. A comparison is presented between the predictions and the measured performance of a column (2,5 m in diameter) absorbing uranium from solution. The method is shown to be adequate for design purposes provided that the data used are from tests in which the solution and resin conditions approximate those for which the plant is being designed [af

PIGE - Resonance profiling applied to a clinical test of flouride varnishes

Science.gov (United States)

Zschau, H. E.; Plier, F.; Otto, G.; Wyrwich, C.; Treide, A.

1992-03-01

A clinical in-vivo experiment had been carried out to compare two caries preventing fluorine varnishes. The fluorine depth profiles in the near surface region of tooth enamel were measured using the 935 keV resonance of the nuclear reaction 19F( p, p' γ) 19F. The results can be understood by studying the flourine anamnese of the patients.

A statistical approach for predicting thermal diffusivity profiles in fusion plasmas as a transport model

International Nuclear Information System (INIS)

Yokoyama, Masayuki

2014-01-01

A statistical approach is proposed to predict thermal diffusivity profiles as a transport “model” in fusion plasmas. It can provide regression expressions for the ion and electron heat diffusivities (χ i and χ e ), separately, to construct their radial profiles. An approach that this letter is proposing outstrips the conventional scaling laws for the global confinement time (τ E ) since it also deals with profiles (temperature, density, heating depositions etc.). This approach has become possible with the analysis database accumulated by the extensive application of the integrated transport analysis suite to experiment data. In this letter, TASK3D-a analysis database for high-ion-temperature (high-T i ) plasmas in the LHD (Large Helical Device) is used as an example to describe an approach. (author)

Stepped approach for prediction of syndrome Z in patients attending sleep clinic: a north Indian hospital-based study.

Science.gov (United States)

Agrawal, Swastik; Sharma, Surendra Kumar; Sreenivas, Vishnubhatla; Lakshmy, Ramakrishnan; Mishra, Hemant K

2012-09-01

Syndrome Z is the occurrence of metabolic syndrome (MS) with obstructive sleep apnea. Knowledge of its risk factors is useful to screen patients requiring further evaluation for syndrome Z. Consecutive patients referred from sleep clinic undergoing polysomnography in the Sleep Laboratory of AIIMS Hospital, New Delhi were screened between June 2008 and May 2010, and 227 patients were recruited. Anthropometry, body composition analysis, blood pressure, fasting blood sugar, and lipid profile were measured. MS was defined using the National Cholesterol Education Program (adult treatment panel III) criteria, with Asian cutoff values for abdominal obesity. Prevalence of MS and syndrome Z was 74% and 65%, respectively. Age, percent body fat, excessive daytime sleepiness (EDS), and ΔSaO(2) (defined as difference between baseline and minimum SaO(2) during polysomnography) were independently associated with syndrome Z. Using a cutoff of 15% for level of desaturation, the stepped predictive score using these risk factors had sensitivity, specificity, positive predictive value, and negative predictive value of 75%, 73%, 84%, and 61%, respectively for the diagnosis of syndrome Z. It correctly characterized presence of syndrome Z 75% of the time and obviated need for detailed evaluation in 42% of the screened subjects. A large proportion of patients presenting to sleep clinics have MS and syndrome Z. Age, percent body fat, EDS, and ΔSaO(2) are independent risk factors for syndrome Z. A stepped predictive score using these parameters is cost-effective and useful in diagnosing syndrome Z in resource-limited settings.

Neuro-Fuzzy Prediction of Cooperation Interaction Profile of Flexible Road Train Based on Hybrid Automaton Modeling

Directory of Open Access Journals (Sweden)

Banjanovic-Mehmedovic Lejla

2016-01-01

Full Text Available Accurate prediction of traffic information is important in many applications in relation to Intelligent Transport systems (ITS, since it reduces the uncertainty of future traffic states and improves traffic mobility. There is a lot of research done in the field of traffic information predictions such as speed, flow and travel time. The most important research was done in the domain of cooperative intelligent transport system (C-ITS. The goal of this paper is to introduce the novel cooperation behaviour profile prediction through the example of flexible Road Trains useful road cooperation parameter, which contributes to the improvement of traffic mobility in Intelligent Transportation Systems. This paper presents an approach towards the control and cooperation behaviour modelling of vehicles in the flexible Road Train based on hybrid automaton and neuro-fuzzy (ANFIS prediction of cooperation profile of the flexible Road Train. Hybrid automaton takes into account complex dynamics of each vehicle as well as discrete cooperation approach. The ANFIS is a particular class of the ANN family with attractive estimation and learning potentials. In order to provide statistical analysis, RMSE (root mean square error, coefficient of determination (R2 and Pearson coefficient (r, were utilized. The study results suggest that ANFIS would be an efficient soft computing methodology, which could offer precise predictions of cooperative interactions between vehicles in Road Train, which is useful for prediction mobility in Intelligent Transport systems.

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

Abstract Objective. The aim of the present study was to compare the ability of four clinical prediction rules to predict adverse outcome in perforated peptic ulcer (PPU): the Boey score, the American Society of Anesthesiologists (ASA) score, the Acute Physiology and Chronic Health Evaluation...... and breastfeeding women, non-surgically treated patients, patients with malignant ulcers, and patients with perforation of other organs were excluded. Primary outcome measure: 30-day mortality rate. Statistical analysis: the ability of four clinical prediction rules to distinguish survivors from non...

Progression to dementia in memory clinic patients without dementia: a latent profile analysis

NARCIS (Netherlands)

Kohler, S.; Hamel, R.; Sistermans, N.; Koene, T.; Pijnenburg, Y.A.L.; van der Flier, W.M.; Scheltens, P.; Visser, P.J.; Aalten, P.; Verhey, F. R. J.; Ramakers, I.

2013-01-01

Objective: To identify the existence of discrete cognitive subtypes among memory clinic patients without dementia and test their prognostic values. Methods: In a retrospective cohort study of 635 patients without dementia visiting the Alzheimer centers in Maastricht or Amsterdam, latent profile

The Success Factor Profile for clinical computer innovation.

Science.gov (United States)

Lorenzi, Nancy M; Smith, Janis B; Conner, Susan R; Campion, Thomas R

2004-01-01

Fifty to seventy percent of information system projects fail. Most of the failures are not the victims of flawed technology, but rather organizational and people related issues. When Vanderbilt University Medical Center began an intensive electronic health record (EHR) effort, a process was carefully designed to select the clinical areas where new tools could be developed and pilot tested. The Success Factor Profile was created to guide the selection of sites most likely to have innovation success. This paper describes both the tools and the processes used to select clinical sites for new computer tools development and pilot implementation. Early results demonstrated that the tools provided structure for the decision making process, permitting side-by-side comparison of "apples and oranges." Selecting the site most likely to succeed with computer application innovation and early implementation has broad applicability in healthcare informatics. Failure to succeed with early system users is not only costly, but also discourages users and developers alike, and may damage the reputation of the tools and systems across the institution.

Magnetic resonance spectroscopy metabolite profiles predict survival in paediatric brain tumours.

Science.gov (United States)

Wilson, Martin; Cummins, Carole L; Macpherson, Lesley; Sun, Yu; Natarajan, Kal; Grundy, Richard G; Arvanitis, Theodoros N; Kauppinen, Risto A; Peet, Andrew C

2013-01-01

Brain tumours cause the highest mortality and morbidity rate of all childhood tumour groups and new methods are required to improve clinical management. (1)H magnetic resonance spectroscopy (MRS) allows non-invasive concentration measurements of small molecules present in tumour tissue, providing clinically useful imaging biomarkers. The primary aim of this study was to investigate whether MRS detectable molecules can predict the survival of paediatric brain tumour patients. Short echo time (30ms) single voxel (1)H MRS was performed on children attending Birmingham Children's Hospital with a suspected brain tumour and 115 patients were included in the survival analysis. Patients were followed-up for a median period of 35 months and Cox-Regression was used to establish the prognostic value of individual MRS detectable molecules. A multivariate model of survival was also investigated to improve prognostic power. Lipids and scyllo-inositol predicted poor survival whilst glutamine and N-acetyl aspartate predicted improved survival (pmodel of survival based on three MRS biomarkers predicted survival with a similar accuracy to histologic grading (p5e-5). A negative correlation between lipids and glutamine was found, suggesting a functional link between these molecules. MRS detectable biomolecules have been identified that predict survival of paediatric brain tumour patients across a range of tumour types. The evaluation of these biomarkers in large prospective studies of specific tumour types should be undertaken. The correlation between lipids and glutamine provides new insight into paediatric brain tumour metabolism that may present novel targets for therapy. Copyright © 2012 Elsevier Ltd. All rights reserved.

Clinical relevance of copy number profiling in oral and oropharyngeal squamous cell carcinoma

Science.gov (United States)

van Kempen, Pauline M W; Noorlag, Rob; Braunius, Weibel W; Moelans, Cathy B; Rifi, Widad; Savola, Suvi; Koole, Ronald; Grolman, Wilko; van Es, Robert J J; Willems, Stefan M

2015-01-01

Current conventional treatment modalities in head and neck squamous cell carcinoma (HNSCC) are nonselective and have shown to cause serious side effects. Unraveling the molecular profiles of head and neck cancer may enable promising clinical applications that pave the road for personalized cancer treatment. We examined copy number status in 36 common oncogenes and tumor suppressor genes in a cohort of 191 oropharyngeal squamous cell carcinomas (OPSCC) and 164 oral cavity squamous cell carcinomas (OSCC) using multiplex ligation probe amplification. Copy number status was correlated with human papillomavirus (HPV) status in OPSCC, with occult lymph node status in OSCC and with patient survival. The 11q13 region showed gain or amplifications in 59% of HPV-negative OPSCC, whereas this amplification was almost absent in HPV-positive OPSCC. Additionally, in clinically lymph node-negative OSCC (Stage I–II), gain of the 11q13 region was significantly correlated with occult lymph node metastases with a negative predictive value of 81%. Multivariate survival analysis revealed a significantly decreased disease-free survival in both HPV-negative and HPV-positive OPSCC with a gain of Wnt-induced secreted protein-1. Gain of CCND1 showed to be an independent predictor for worse survival in OSCC. These results show that copy number aberrations, mainly of the 11q13 region, may be important predictors and prognosticators which allow for stratifying patients for personalized treatment of HNSCC. PMID:26194878

Clinical relevance of copy number profiling in oral and oropharyngeal squamous cell carcinoma

International Nuclear Information System (INIS)

Kempen, Pauline M W van; Noorlag, Rob; Braunius, Weibel W; Moelans, Cathy B; Rifi, Widad; Savola, Suvi; Koole, Ronald; Grolman, Wilko; Es, Robert J J van; Willems, Stefan M

2015-01-01

Current conventional treatment modalities in head and neck squamous cell carcinoma (HNSCC) are nonselective and have shown to cause serious side effects. Unraveling the molecular profiles of head and neck cancer may enable promising clinical applications that pave the road for personalized cancer treatment. We examined copy number status in 36 common oncogenes and tumor suppressor genes in a cohort of 191 oropharyngeal squamous cell carcinomas (OPSCC) and 164 oral cavity squamous cell carcinomas (OSCC) using multiplex ligation probe amplification. Copy number status was correlated with human papillomavirus (HPV) status in OPSCC, with occult lymph node status in OSCC and with patient survival. The 11q13 region showed gain or amplifications in 59% of HPV-negative OPSCC, whereas this amplification was almost absent in HPV-positive OPSCC. Additionally, in clinically lymph node-negative OSCC (Stage I–II), gain of the 11q13 region was significantly correlated with occult lymph node metastases with a negative predictive value of 81%. Multivariate survival analysis revealed a significantly decreased disease-free survival in both HPV-negative and HPV-positive OPSCC with a gain of Wnt-induced secreted protein-1. Gain of CCND1 showed to be an independent predictor for worse survival in OSCC. These results show that copy number aberrations, mainly of the 11q13 region, may be important predictors and prognosticators which allow for stratifying patients for personalized treatment of HNSCC

ORION: a web server for protein fold recognition and structure prediction using evolutionary hybrid profiles.

Science.gov (United States)

Ghouzam, Yassine; Postic, Guillaume; Guerin, Pierre-Edouard; de Brevern, Alexandre G; Gelly, Jean-Christophe

2016-06-20

Protein structure prediction based on comparative modeling is the most efficient way to produce structural models when it can be performed. ORION is a dedicated webserver based on a new strategy that performs this task. The identification by ORION of suitable templates is performed using an original profile-profile approach that combines sequence and structure evolution information. Structure evolution information is encoded into profiles using structural features, such as solvent accessibility and local conformation -with Protein Blocks-, which give an accurate description of the local protein structure. ORION has recently been improved, increasing by 5% the quality of its results. The ORION web server accepts a single protein sequence as input and searches homologous protein structures within minutes. Various databases such as PDB, SCOP and HOMSTRAD can be mined to find an appropriate structural template. For the modeling step, a protein 3D structure can be directly obtained from the selected template by MODELLER and displayed with global and local quality model estimation measures. The sequence and the predicted structure of 4 examples from the CAMEO server and a recent CASP11 target from the 'Hard' category (T0818-D1) are shown as pertinent examples. Our web server is accessible at http://www.dsimb.inserm.fr/ORION/.

A study of the clinical profile and outcome of spina bifida

Directory of Open Access Journals (Sweden)

Theophilus Nikita Kumar

2016-02-01

Full Text Available Neural tube defects (NTDs are a group of congenital anomalies characterized by defects in dorsal midline structures, including neural tissue, dura, muscle, bone and/or skin. The clinical presentations and the follow-up of these patients requires attention to various end organs besides the nervous system. To evaluate the clinical profile and surgical outcome of children with spina bifida. Out of a total of 74 patients treated at our institute for spina bifida between June 2013 to august 2015, 74 cases of spina bifida were analyzed retrospectively and prospectively. The clinical profile, radiological findings and urodynamic studies were recorded. Craniospinal MRI was done in patients to screen for Arnold Chiari malformations and monitoring of hydrocephalus was done as a management protocol at our institute for these children. All these patients except two underwent surgery for correction and closure of the spinal defect. Associated anomalies were treated accordingly. They were clinically assessed over a mean follow up period of 1.3years, ranging from 2months to 2½ years. 73% of the patients presented in the neonatal age group. Of which, 72% presented with a visible sac over the back.72% of the cases were Myelomeningocoeles. 79% of the defects were in the lumbosacral region.30% presented with sensorimotor loss or bladder bowel incontinence. Sensorimotor improvement was seen in 12.5% after repairing the defect with the help of physiotherapy and braces. 30% of the patients were diagnosed to have hydrocephalus, of which 33% required a CSF diversion procedure. The postoperative course of spina bifida repair was found to be uneventful in 90% of the patients

Predicting fiber refractive index from a measured preform index profile

Science.gov (United States)

Kiiveri, P.; Koponen, J.; Harra, J.; Novotny, S.; Husu, H.; Ihalainen, H.; Kokki, T.; Aallos, V.; Kimmelma, O.; Paul, J.

2018-02-01

When producing fiber lasers and amplifiers, silica glass compositions consisting of three to six different materials are needed. Due to the varying needs of different applications, substantial number of different glass compositions are used in the active fiber structures. Often it is not possible to find material parameters for theoretical models to estimate thermal and mechanical properties of those glass compositions. This makes it challenging to predict accurately fiber core refractive index values, even if the preform index profile is measured. Usually the desired fiber refractive index value is achieved experimentally, which is expensive. To overcome this problem, we analyzed statistically the changes between the measured preform and fiber index values. We searched for correlations that would help to predict the Δn-value change from preform to fiber in a situation where we don't know the values of the glass material parameters that define the change. Our index change models were built using the data collected from preforms and fibers made by the Direct Nanoparticle Deposition (DND) technology.

Impact of INTERMACS Profile on Clinical Outcomes for Patients Supported With the Total Artificial Heart.

Science.gov (United States)

Shah, Keyur B; Thanavaro, Kristin L; Tang, Daniel G; Quader, Mohammed A; Mankad, Anit K; Tchoukina, Inna; Thacker, Leroy R; Smallfield, Melissa C; Katlaps, Gundars; Hess, Michael L; Cooke, Richard H; Kasirajan, Vigneshwar

2016-11-01

Insufficient data delineate outcomes for Interagency Registry for Mechanically Assisted Circulatory Support (INTERMACS) profile 1 patients with the total artificial heart (TAH). We studied 66 consecutive patients implanted with the TAH at our institution from 2006 through 2012 and compared outcome by INTERMACS profile. INTERMACS profiles were adjudicated retrospectively by a reviewer blinded to clinical outcomes. Survival after TAH implantation at 6 and 12 months was 76% and 71%, respectively. INTERMACS profile 1 patients had decreased 6-month survival on the device compared with those in profiles 2-4 (74% vs 95%, log rank: P = .015). For the 50 patients surviving to heart transplantation, the 1-year posttransplant survival was 82%. There was no difference in 1-year survival when comparing patients in the INTERMACS 1 profile with less severe profiles (79% vs 84%; log rank test P = .7; hazard ratio [confidence interval] 1.3 [0.3-4.8]). Patients implanted with the TAH as INTERMACS profile 1 had reduced survival to transplantation compared with less sick profiles. INTERMACS profile at the time of TAH implantation did not affect 1-year survival after heart transplantation. Copyright © 2016 Elsevier Inc. All rights reserved.

Classification of breast cancer patients using somatic mutation profiles and machine learning approaches.

Science.gov (United States)

Vural, Suleyman; Wang, Xiaosheng; Guda, Chittibabu

2016-08-26

The high degree of heterogeneity observed in breast cancers makes it very difficult to classify the cancer patients into distinct clinical subgroups and consequently limits the ability to devise effective therapeutic strategies. Several classification strategies based on ER/PR/HER2 expression or the expression profiles of a panel of genes have helped, but such methods often produce misleading results due to their dynamic nature. In contrast, somatic DNA mutations are relatively stable and lead to initiation and progression of many sporadic cancers. Hence in this study, we explore the use of gene mutation profiles to classify, characterize and predict the subgroups of breast cancers. We analyzed the whole exome sequencing data from 358 ethnically similar breast cancer patients in The Cancer Genome Atlas (TCGA) project. Somatic and non-synonymous single nucleotide variants identified from each patient were assigned a quantitative score (C-score) that represents the extent of negative impact on the gene function. Using these scores with non-negative matrix factorization method, we clustered the patients into three subgroups. By comparing the clinical stage of patients, we identified an early-stage-enriched and a late-stage-enriched subgroup. Comparison of the mutation scores of early and late-stage-enriched subgroups identified 358 genes that carry significantly higher mutations rates in the late stage subgroup. Functional characterization of these genes revealed important functional gene families that carry a heavy mutational load in the late state rich subgroup of patients. Finally, using the identified subgroups, we also developed a supervised classification model to predict the stage of the patients. This study demonstrates that gene mutation profiles can be effectively used with unsupervised machine-learning methods to identify clinically distinguishable breast cancer subgroups. The classification model developed in this method could provide a reasonable

Clinical gestalt and the prediction of massive transfusion after trauma.

Science.gov (United States)

Pommerening, Matthew J; Goodman, Michael D; Holcomb, John B; Wade, Charles E; Fox, Erin E; Del Junco, Deborah J; Brasel, Karen J; Bulger, Eileen M; Cohen, Mitch J; Alarcon, Louis H; Schreiber, Martin A; Myers, John G; Phelan, Herb A; Muskat, Peter; Rahbar, Mohammad; Cotton, Bryan A

2015-05-01

Early recognition and treatment of trauma patients requiring massive transfusion (MT) has been shown to reduce mortality. While many risk factors predicting MT have been demonstrated, there is no universally accepted method or algorithm to identify these patients. We hypothesised that even among experienced trauma surgeons, the clinical gestalt of identifying patients who will require MT is unreliable. Transfusion and mortality outcomes after trauma were observed at 10 U.S. Level-1 trauma centres in patients who survived ≥ 30 min after admission and received ≥ 1 unit of RBC within 6h of arrival. Subjects who received ≥ 10 units within 24h of admission were classified as MT patients. Trauma surgeons were asked the clinical gestalt question "Is the patient likely to be massively transfused?" 10 min after the patients arrival. The performance of clinical gestalt to predict MT was assessed using chi-square tests and ROC analysis to compare gestalt to previously described scoring systems. Of the 1245 patients enrolled, 966 met inclusion criteria and 221 (23%) patients received MT. 415 (43%) were predicted to have a MT and 551(57%) were predicted to not have MT. Patients predicted to have MT were younger, more often sustained penetrating trauma, had higher ISS scores, higher heart rates, and lower systolic blood pressures (all pGestalt sensitivity was 65.6% and specificity was 63.8%. PPV and NPV were 34.9% and 86.2% respectively. Data from this large multicenter trial demonstrates that predicting the need for MT continues to be a challenge. Because of the increased mortality associated with delayed therapy, a more reliable algorithm is needed to identify and treat these severely injured patients earlier. Copyright © 2015 Elsevier Ltd. All rights reserved.

Clinical presentation and biochemical profile of horses during induction and treatment of hypocalcemia

OpenAIRE

Barrêto-Júnior, Raimundo A.; Minervino, Antonio H.; Rodrigues, Federico A.; Meira Júnior, Enoch B.; Lima, Alessandra; Sousa, Rejane; Mori, Clara; Araújo, Carolina A.; R.Fernandes, Wilson; Ortolani, Enrico

2017-01-01

ABSTRACT: The aim of this study was to examine the clinical presentation, biochemical profile and response to treatment among horses with experimentally-induced hypocalcemia. Twelve adult, mixed breed mares were used. A 5% ethylenediaminetetraacetic acid disodium (Na2EDTA) solution was infused into all the mares until the animals presented clinical signs of hypocalcemia, at which point they were divided into a control group (n = 5) and a treatment group (n = 7). The treated group received an ...

Clinical profile of patients with myasthenia gravis followed at the University Hospital, Federal University of Minas Gerais

Directory of Open Access Journals (Sweden)

Aline Mansueto Mourão

2015-04-01

Full Text Available Summary Objective: to determine the clinical profile of patients with myasthenia gravis (MG; followed at the Neuromuscular Diseases Clinic of the University Hospital, Federal University of Minas Gerais, Brazil, and to compare it with other Brazilian case series. Methods: sociodemographic and clinical data were collected from patients, and a systematic literature review performed, focusing on national studies on the clinical profile of MG patients. Results: sixty nine patients were enrolled in the study. Fifty five (91% subjects were female and the mean age (SD was 37.6 (±11.4 years. The mean disease duration was 14.1 years. Regarding treatment, prednisone was the most used strategy (64%, followed by the use of azathioprine (43%. There was no difference between thymectomized (42 and non-thymectomized (27 patients regarding disease severity and medication use. Conclusion: clinical and socio-demographic features of this MG sample from a University-based clinic resemble those reported in other Brazilian series and in the international literature.

Prediction of lymphatic metastasis based on gene expression profile analysis after brachytherapy for early-stage oral tongue carcinoma

International Nuclear Information System (INIS)

Watanabe, Hiroshi; Mogushi, Kaoru; Miura, Masahiko; Yoshimura, Ryo-ichi; Kurabayashi, Tohru; Shibuya, Hitoshi; Tanaka, Hiroshi; Noda, Shuhei; Iwakawa, Mayumi; Imai, Takashi

2008-01-01

Background and purpose: The management of lymphatic metastasis of early-stage oral tongue carcinoma patients is crucial for its prognosis. The purpose of this study was to evaluate the predictive ability of lymphatic metastasis after brachytherapy (BRT) for early-stage tongue carcinoma based on gene expression profiling. Patients and methods: Pre-therapeutic biopsies from 39 patients with T1 or T2 tongue cancer were analyzed for gene expression signatures using Codelink Uniset Human 20K Bioarray. All patients were treated with low dose-rate BRT for their primary lesions and underwent strict follow-up under a wait-and-see policy for cervical lymphatic metastasis. Candidate genes were selected for predicting lymph-node status in the reference group by the permutation test. Predictive accuracy was further evaluated by the prediction strength (PS) scoring system using an independent validation group. Results: We selected a set of 19 genes whose expression differed significantly between classes with or without lymphatic metastasis in the reference group. The lymph-node status in the validation group was predicted by the PS scoring system with an accuracy of 76%. Conclusions: Gene expression profiling using 19 genes in primary tumor tissues may allow prediction of lymphatic metastasis after BRT for early-stage oral tongue carcinoma

Predicting the profile of nutrients available for absorption: from nutrient requirement to animal response and environmental impact.

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Dijkstra, J; Kebreab, E; Mills, J A N; Pellikaan, W F; López, S; Bannink, A; France, J

2007-02-01

Current feed evaluation systems for dairy cattle aim to match nutrient requirements with nutrient intake at pre-defined production levels. These systems were not developed to address, and are not suitable to predict, the responses to dietary changes in terms of production level and product composition, excretion of nutrients to the environment, and nutrition related disorders. The change from a requirement to a response system to meet the needs of various stakeholders requires prediction of the profile of absorbed nutrients and its subsequent utilisation for various purposes. This contribution examines the challenges to predicting the profile of nutrients available for absorption in dairy cattle and provides guidelines for further improved prediction with regard to animal production responses and environmental pollution.The profile of nutrients available for absorption comprises volatile fatty acids, long-chain fatty acids, amino acids and glucose. Thus the importance of processes in the reticulo-rumen is obvious. Much research into rumen fermentation is aimed at determination of substrate degradation rates. Quantitative knowledge on rates of passage of nutrients out of the rumen is rather limited compared with that on degradation rates, and thus should be an important theme in future research. Current systems largely ignore microbial metabolic variation, and extant mechanistic models of rumen fermentation give only limited attention to explicit representation of microbial metabolic activity. Recent molecular techniques indicate that knowledge on the presence and activity of various microbial species is far from complete. Such techniques may give a wealth of information, but to include such findings in systems predicting the nutrient profile requires close collaboration between molecular scientists and mathematical modellers on interpreting and evaluating quantitative data. Protozoal metabolism is of particular interest here given the paucity of quantitative data

Prospective molecular profiling of canine cancers provides a clinically relevant comparative model for evaluating personalized medicine (PMed trials.

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Melissa Paoloni

Full Text Available Molecularly-guided trials (i.e. PMed now seek to aid clinical decision-making by matching cancer targets with therapeutic options. Progress has been hampered by the lack of cancer models that account for individual-to-individual heterogeneity within and across cancer types. Naturally occurring cancers in pet animals are heterogeneous and thus provide an opportunity to answer questions about these PMed strategies and optimize translation to human patients. In order to realize this opportunity, it is now necessary to demonstrate the feasibility of conducting molecularly-guided analysis of tumors from dogs with naturally occurring cancer in a clinically relevant setting.A proof-of-concept study was conducted by the Comparative Oncology Trials Consortium (COTC to determine if tumor collection, prospective molecular profiling, and PMed report generation within 1 week was feasible in dogs. Thirty-one dogs with cancers of varying histologies were enrolled. Twenty-four of 31 samples (77% successfully met all predefined QA/QC criteria and were analyzed via Affymetrix gene expression profiling. A subsequent bioinformatics workflow transformed genomic data into a personalized drug report. Average turnaround from biopsy to report generation was 116 hours (4.8 days. Unsupervised clustering of canine tumor expression data clustered by cancer type, but supervised clustering of tumors based on the personalized drug report clustered by drug class rather than cancer type.Collection and turnaround of high quality canine tumor samples, centralized pathology, analyte generation, array hybridization, and bioinformatic analyses matching gene expression to therapeutic options is achievable in a practical clinical window (<1 week. Clustering data show robust signatures by cancer type but also showed patient-to-patient heterogeneity in drug predictions. This lends further support to the inclusion of a heterogeneous population of dogs with cancer into the preclinical

Predicting pneumococcal community-acquired pneumonia in the emergency department: evaluation of clinical parameters.

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Huijts, S M; Boersma, W G; Grobbee, D E; Gruber, W C; Jansen, K U; Kluytmans, J A J W; Kuipers, B A F; Palmen, F; Pride, M W; Webber, C; Bonten, M J M

2014-12-01

The aim of this study was to quantify the value of clinical predictors available in the emergency department (ED) in predicting Streptococcus pneumoniae as the cause of community-acquired pneumonia (CAP). A prospective, observational, cohort study of patients with CAP presenting in the ED was performed. Pneumococcal aetiology of CAP was based on either bacteraemia, or S. pneumoniae being cultured from sputum, or urinary immunochromatographic assay positivity, or positivity of a novel serotype-specific urinary antigen detection test. Multivariate logistic regression was used to identify independent predictors and various cut-off values of probability scores were used to evaluate the usefulness of the model. Three hundred and twenty-eight (31.0%) of 1057 patients with CAP had pneumococcal CAP. Nine independent predictors for pneumococcal pneumonia were identified, but the clinical utility of this prediction model was disappointing, because of low positive predictive values or a small yield. Clinical criteria have insufficient diagnostic capacity to predict pneumococcal CAP. Rapid antigen detection tests are needed to diagnose S. pneumoniae at the time of hospital admission. © 2014 The Authors Clinical Microbiology and Infection © 2014 European Society of Clinical Microbiology and Infectious Diseases.

Insights into an original pocket-ligand pair classification: a promising tool for ligand profile prediction.

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Stéphanie Pérot

Full Text Available Pockets are today at the cornerstones of modern drug discovery projects and at the crossroad of several research fields, from structural biology to mathematical modeling. Being able to predict if a small molecule could bind to one or more protein targets or if a protein could bind to some given ligands is very useful for drug discovery endeavors, anticipation of binding to off- and anti-targets. To date, several studies explore such questions from chemogenomic approach to reverse docking methods. Most of these studies have been performed either from the viewpoint of ligands or targets. However it seems valuable to use information from both ligands and target binding pockets. Hence, we present a multivariate approach relating ligand properties with protein pocket properties from the analysis of known ligand-protein interactions. We explored and optimized the pocket-ligand pair space by combining pocket and ligand descriptors using Principal Component Analysis and developed a classification engine on this paired space, revealing five main clusters of pocket-ligand pairs sharing specific and similar structural or physico-chemical properties. These pocket-ligand pair clusters highlight correspondences between pocket and ligand topological and physico-chemical properties and capture relevant information with respect to protein-ligand interactions. Based on these pocket-ligand correspondences, a protocol of prediction of clusters sharing similarity in terms of recognition characteristics is developed for a given pocket-ligand complex and gives high performances. It is then extended to cluster prediction for a given pocket in order to acquire knowledge about its expected ligand profile or to cluster prediction for a given ligand in order to acquire knowledge about its expected pocket profile. This prediction approach shows promising results and could contribute to predict some ligand properties critical for binding to a given pocket, and conversely

Insights into an original pocket-ligand pair classification: a promising tool for ligand profile prediction.

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Pérot, Stéphanie; Regad, Leslie; Reynès, Christelle; Spérandio, Olivier; Miteva, Maria A; Villoutreix, Bruno O; Camproux, Anne-Claude

2013-01-01

Pockets are today at the cornerstones of modern drug discovery projects and at the crossroad of several research fields, from structural biology to mathematical modeling. Being able to predict if a small molecule could bind to one or more protein targets or if a protein could bind to some given ligands is very useful for drug discovery endeavors, anticipation of binding to off- and anti-targets. To date, several studies explore such questions from chemogenomic approach to reverse docking methods. Most of these studies have been performed either from the viewpoint of ligands or targets. However it seems valuable to use information from both ligands and target binding pockets. Hence, we present a multivariate approach relating ligand properties with protein pocket properties from the analysis of known ligand-protein interactions. We explored and optimized the pocket-ligand pair space by combining pocket and ligand descriptors using Principal Component Analysis and developed a classification engine on this paired space, revealing five main clusters of pocket-ligand pairs sharing specific and similar structural or physico-chemical properties. These pocket-ligand pair clusters highlight correspondences between pocket and ligand topological and physico-chemical properties and capture relevant information with respect to protein-ligand interactions. Based on these pocket-ligand correspondences, a protocol of prediction of clusters sharing similarity in terms of recognition characteristics is developed for a given pocket-ligand complex and gives high performances. It is then extended to cluster prediction for a given pocket in order to acquire knowledge about its expected ligand profile or to cluster prediction for a given ligand in order to acquire knowledge about its expected pocket profile. This prediction approach shows promising results and could contribute to predict some ligand properties critical for binding to a given pocket, and conversely, some key pocket

Temperament and Character Profiles of Sasang Typology in an Adult Clinical Sample

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Soo Hyun Park

2011-01-01

Full Text Available The purpose of this study was to examine the biopsychological personality profiles of traditional Korean Sasang typology based on the Temperament and Character Inventory (TCI in a Korean adult clinical sample. A total of 97 adults completed the Korean version of the TCI. The participants were classified as one of three traditional Korean Sasang types (31 So-Yang, 41 Tae-Eum, 25 So-Eum by three specialists in Sasang typology. The seven dimensions of TCI were compared between the different Sasang types using analysis of variance (ANOVA and profile analysis. There were no significant differences in age, gender and education across the Sasang types. The TCI profile for each of the Sasang types was significantly different (profile analysis, df = 5.038, F = 3.546, P = .004. There were significant differences in the temperament dimensions of Novelty Seeking (F = 3.43, P = .036 and Harm Avoidance (F = 5.43, P = .006 among the Sasang types. The Novelty Seeking score of the So-Yang type (31.90 ± 9.87 was higher than that of the So-Eum type (25.24 ± 9.21; P = .019 while the So-Eum type (44.64 ± 8.47 scored higher on the Harm Avoidance score compared to the So-Yang type (35.16 ± 11.50; P = .003. There were no significant differences in the temperament dimension of Reward Dependence and Persistence, and the three character dimensions of Self-Directedness, Cooperativeness and Self-Transcendence. Results demonstrated distinct temperament traits associated with traditional Korean Sasang types using an objective biopsychological personality inventory. With further study, the Sasang typology may lead to enhanced clinical safety and efficacy as part of personalized medicine with traditional medicine.

Prediction of the Inlet Nozzle Velocity Profiles for the CANDU-6 Moderator Analysis

International Nuclear Information System (INIS)

Yoon, Churl; Park, Joo Hwan

2006-01-01

For the moderator analysis of the CANDU reactors in Korea, predicting local moderator subcooling in the Calandria vessels is one of the main concerns for the estimation of heat sink capability of moderator under LOCA transients. The moderator circulation pattern is determined by the combined forces of the inlet jet momentum and the buoyancy flow. Even though the inlet boundary condition plays an important role in determining the moderator circulations, no measured data of detailed inlet velocity profiles is available. The purpose of this study is to produce the velocity profiles at the inlet nozzles by a CFD simulation. To produce the velocity vector fields at the inlet nozzle surfaces, the internal flows in the nozzle assembly were simulated by using a commercial CFD code, CFX-5.7. In the reference, the analytical capability of CFX-5.7 had been estimated by a validation of the CFD code against available experimental data for separate flow phenomena. Various turbulence models and grid spacing had been also tested. In the following section, the interface treatment between the computational domains would be explained. In section 3, the inlet nozzle flow through the CANDU moderator nozzle assembly was predicted by using the obtained technology of the CFD simulation

Predicting Mental Imagery-Based BCI Performance from Personality, Cognitive Profile and Neurophysiological Patterns.

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Camille Jeunet

Full Text Available Mental-Imagery based Brain-Computer Interfaces (MI-BCIs allow their users to send commands to a computer using their brain-activity alone (typically measured by ElectroEncephaloGraphy-EEG, which is processed while they perform specific mental tasks. While very promising, MI-BCIs remain barely used outside laboratories because of the difficulty encountered by users to control them. Indeed, although some users obtain good control performances after training, a substantial proportion remains unable to reliably control an MI-BCI. This huge variability in user-performance led the community to look for predictors of MI-BCI control ability. However, these predictors were only explored for motor-imagery based BCIs, and mostly for a single training session per subject. In this study, 18 participants were instructed to learn to control an EEG-based MI-BCI by performing 3 MI-tasks, 2 of which were non-motor tasks, across 6 training sessions, on 6 different days. Relationships between the participants' BCI control performances and their personality, cognitive profile and neurophysiological markers were explored. While no relevant relationships with neurophysiological markers were found, strong correlations between MI-BCI performances and mental-rotation scores (reflecting spatial abilities were revealed. Also, a predictive model of MI-BCI performance based on psychometric questionnaire scores was proposed. A leave-one-subject-out cross validation process revealed the stability and reliability of this model: it enabled to predict participants' performance with a mean error of less than 3 points. This study determined how users' profiles impact their MI-BCI control ability and thus clears the way for designing novel MI-BCI training protocols, adapted to the profile of each user.

Prediction of incidence and stability of alcohol use disorders by latent internalizing psychopathology risk profiles in adolescence and young adulthood.

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Behrendt, Silke; Bühringer, Gerhard; Höfler, Michael; Lieb, Roselind; Beesdo-Baum, Katja

2017-10-01

Comorbid internalizing mental disorders in alcohol use disorders (AUD) can be understood as putative independent risk factors for AUD or as expressions of underlying shared psychopathology vulnerabilities. However, it remains unclear whether: 1) specific latent internalizing psychopathology risk-profiles predict AUD-incidence and 2) specific latent internalizing comorbidity-profiles in AUD predict AUD-stability. To investigate baseline latent internalizing psychopathology risk profiles as predictors of subsequent AUD-incidence and -stability in adolescents and young adults. Data from the prospective-longitudinal EDSP study (baseline age 14-24 years) were used. The study-design included up to three follow-up assessments in up to ten years. DSM-IV mental disorders were assessed with the DIA-X/M-CIDI. To investigate risk-profiles and their associations with AUD-outcomes, latent class analysis with auxiliary outcome variables was applied. AUD-incidence: a 4-class model (N=1683) was identified (classes: normative-male [45.9%], normative-female [44.2%], internalizing [5.3%], nicotine dependence [4.5%]). Compared to the normative-female class, all other classes were associated with a higher risk of subsequent incident alcohol dependence (p<0.05). AUD-stability: a 3-class model (N=1940) was identified with only one class (11.6%) with high probabilities for baseline AUD. This class was further characterized by elevated substance use disorder (SUD) probabilities and predicted any subsequent AUD (OR 8.5, 95% CI 5.4-13.3). An internalizing vulnerability may constitute a pathway to AUD incidence in adolescence and young adulthood. In contrast, no indication for a role of internalizing comorbidity profiles in AUD-stability was found, which may indicate a limited importance of such profiles - in contrast to SUD-related profiles - in AUD stability. Copyright © 2017 Elsevier B.V. All rights reserved.

TEMA and Dot Enumeration Profiles Predict Mental Addition Problem Solving Speed Longitudinally.

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Major, Clare S; Paul, Jacob M; Reeve, Robert A

2017-01-01

Different math indices can be used to assess math potential at school entry. We evaluated whether standardized math achievement (TEMA-2 performance), core number abilities (dot enumeration, symbolic magnitude comparison), non-verbal intelligence (NVIQ) and visuo-spatial working memory (VSWM), in combination or separately, predicted mental addition problem solving speed over time. We assessed 267 children's TEMA-2, magnitude comparison, dot enumeration, and VSWM abilities at school entry (5 years) and NVIQ at 8 years. Mental addition problem solving speed was assessed at 6, 8, and 10 years. Longitudinal path analysis supported a model in which dot enumeration performance ability profiles and previous mental addition speed predicted future mental addition speed on all occasions, supporting a componential account of math ability. Standardized math achievement and NVIQ predicted mental addition speed at specific time points, while VSWM and symbolic magnitude comparison did not contribute unique variance to the model. The implications of using standardized math achievement and dot enumeration ability to index math learning potential at school entry are discussed.

Pretreatment data is highly predictive of liver chemistry signals in clinical trials.

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Cai, Zhaohui; Bresell, Anders; Steinberg, Mark H; Silberg, Debra G; Furlong, Stephen T

2012-01-01

The goal of this retrospective analysis was to assess how well predictive models could determine which patients would develop liver chemistry signals during clinical trials based on their pretreatment (baseline) information. Based on data from 24 late-stage clinical trials, classification models were developed to predict liver chemistry outcomes using baseline information, which included demographics, medical history, concomitant medications, and baseline laboratory results. Predictive models using baseline data predicted which patients would develop liver signals during the trials with average validation accuracy around 80%. Baseline levels of individual liver chemistry tests were most important for predicting their own elevations during the trials. High bilirubin levels at baseline were not uncommon and were associated with a high risk of developing biochemical Hy's law cases. Baseline γ-glutamyltransferase (GGT) level appeared to have some predictive value, but did not increase predictability beyond using established liver chemistry tests. It is possible to predict which patients are at a higher risk of developing liver chemistry signals using pretreatment (baseline) data. Derived knowledge from such predictions may allow proactive and targeted risk management, and the type of analysis described here could help determine whether new biomarkers offer improved performance over established ones.

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

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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.

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

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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

Profiling inflammatory biomarkers in cervico-vaginal mucus (CVM) postpartum: Potential early indicators of bovine clinical endometritis?

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Adnane, Mounir; Chapwanya, Aspinas; Kaidi, Rachid; Meade, Kieran G; O'Farrelly, Cliona

2017-11-01

Endometritis significantly impacts fertility and milk yield, thus reducing profitability of the dairy production. In cows that develop endometritis, normal postpartum endometrial inflammation is dysregulated. Here, we propose that endometrial inflammation is reflected in cervico-vaginal mucus (CVM) which could therefore be used as a prognostic tool. CVM was collected from 20 dairy cows (10 with clinical endometritis and 10 healthy) 7 and 21 days postpartum (DPP). Polymorphonuclear (PMN), mononuclear leukocyte and epithelial cells were counted, total protein levels were estimated and levels of IL-1β, IL-6, IL-8, serum amyloid A (SAA), haptoglobin (Hp) and C5b were analyzed by ELISA in CVM. PMN were consistently high in CVM from 7 to 21 DPP, but were higher in CVM from cows with clinical endometritis 21 DPP compared with healthy cows. In contrast, there were more epithelial cells in healthy cows 21 DPP than in clinical endometritis animals. Total protein levels decreased significantly in CVM from healthy cows between days 7 and 21 postpartum. All inflammatory biomarkers except C5b, remained high in cows with clinical endometritis from 7 to 21 DPP, indicating sustained and chronic endometrial inflammation. IL1, IL-6, IL-8 and Hp levels were higher in CVM from cows with clinical endometritis compared to healthy cows 21 DPP. Interestingly IL-1β levels were raised in CVM from clinical endometritis but not in healthy cows 7 DPP suggesting that early measurement of IL-1β levels might provide a useful predictive marker of clinical endometritis. In contrast, SAA and C5b levels were increased in healthy cows 21 DPP, compared to cows with clinical endometritis suggesting that these acute phase proteins might have an anti-inflammatory role. Our results show that CVM is convenient for profiling disease-associated changes in key inflammatory molecules postpartum and reaffirms that sustained inflammation is a key feature of clinical endometritis in the dairy cow. Copyright �

Association of Immunological Cell Profiles with Specific Clinical Phenotypes of Scleroderma Disease

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Calzada, David; Mayayo, Teodoro; González-Rodríguez, María Luisa; Rabasco, Antonio María; Lahoz, Carlos

2014-01-01

This study aimed to search the correlation among immunological profiles and clinical phenotypes of scleroderma in well-characterized groups of scleroderma patients, comparing forty-nine scleroderma patients stratified according to specific clinical phenotypes with forty-nine healthy controls. Five immunological cell subpopulations (B, CD4+ and CD8+ T-cells, NK, and monocytes) and their respective stages of apoptosis and activation were analyzed by flow cytometry, in samples of peripheral blood mononuclear cells (PBMCs). Analyses of results were stratified according to disease stage, time since the diagnosis, and visceral damage (pulmonary fibrosis, pulmonary hypertension, and cardiac affliction) and by time of treatment with corticosteroids. An increase in the percentages of monocytes and a decrease in the B cells were mainly related to the disease progression. A general apoptosis decrease was found in all phenotypes studied, except in localized scleroderma. An increase of B and NK cells activation was found in patients diagnosed more than 10 years ago. Specific cell populations like monocytes, NK, and B cells were associated with the type of affected organ. This study shows how, in a heterogeneous disease, proper patient's stratification according to clinical phenotypes allows finding specific cellular profiles. Our data may lead to improvements in the knowledge of prognosis factors and to aid in the analysis of future specific therapies. PMID:24818126

Automated interpretable computational biology in the clinic: a framework to predict disease severity and stratify patients from clinical data

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Soumya Banerjee

2017-10-01

Full Text Available We outline an automated computational and machine learning framework that predicts disease severity and stratifies patients. We apply our framework to available clinical data. Our algorithm automatically generates insights and predicts disease severity with minimal operator intervention. The computational framework presented here can be used to stratify patients, predict disease severity and propose novel biomarkers for disease. Insights from machine learning algorithms coupled with clinical data may help guide therapy, personalize treatment and help clinicians understand the change in disease over time. Computational techniques like these can be used in translational medicine in close collaboration with clinicians and healthcare providers. Our models are also interpretable, allowing clinicians with minimal machine learning experience to engage in model building. This work is a step towards automated machine learning in the clinic.

Some uses of predictive probability of success in clinical drug development

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Mauro Gasparini

2013-03-01

Full Text Available Predictive probability of success is a (subjective Bayesian evaluation of the prob- ability of a future successful event in a given state of information. In the context of pharmaceutical clinical drug development, successful events relate to the accrual of positive evidence on the therapy which is being developed, like demonstration of su- perior efficacy or ascertainment of safety. Positive evidence will usually be obtained via standard frequentist tools, according to the regulations imposed in the world of pharmaceutical development.Within a single trial, predictive probability of success can be identified with expected power, i.e. the evaluation of the success probability of the trial. Success means, for example, obtaining a significant result of a standard superiority test.Across trials, predictive probability of success can be the probability of a successful completion of an entire part of clinical development, for example a successful phase III development in the presence of phase II data.Calculations of predictive probability of success in the presence of normal data with known variance will be illustrated, both for within-trial and across-trial predictions.

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

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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

Clinical features and endocrine profile of Laron syndrome in Indian children

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Supriya R Phanse-Gupte

2014-01-01

Full Text Available Introduction: Patients with growth hormone (GH insensitivity (also known as Laron syndome have been reported from the Mediterranean region and Southern Eucador, with few case reports from India. We present here the clinical and endocrine profile of 9 children with Laron syndrome from India. Material and Methods: Nine children diagnosed with Laron syndrome based on clinical features of GH deficiency and biochemical profile suggestive of GH resistance were studied over a period of 5 years from January 2008 to January 2013. Results and Discussion: Age of presentation was between 2.5-11.5 years. All children were considerably short on contemporary Indian charts with mean (SD height Z score -5.2 (1.6. However, they were within ± 2 SD on Laron charts. No child was overweight [mean (SD BMI Z score 0.92 (1.1]. All children had characteristic facies of GH deficiency with an added feature of prominent eyes. Three boys had micropenis and 1 had unilateral undescended testis. All children had low IGF-1 (<5 percentile and IGFP-3 (<0.1 percentile with high basal and stimulated GH [Basal GH mean (SD = 13.78 (12.75 ng/ml, 1-h stimulated GH mean (SD = 46.29 (25.68 ng/ml]. All children showed poor response to IGF generation test. Conclusion: Laron syndrome should be suspected in children with clinical features of GH deficiency, high GH levels and low IGF-1/IGFBP-3. These children are in a state of GH resistance and need IGF-1 therapy.

Clinical and functional criteria for predicting asthma in infants

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Yu. L. Mizemitskiy

2015-01-01

Full Text Available Objective: to determine clinical and functional criteria for predicting asthma in children who have sustained acute obstructive bronchitis in infancy. Subjects and methods. A total of 125 infants aged 2 to 36 months who had experienced 1 -2 episodes of acute obstructive bronchitis and treated at hospital were examined when bronchial obstruction syndrome was being relieved. In addition to physical examination, functional studies (computerized bronchophonography and heart rate variability assessment were used. Immunological examination included determination of the serum levels of immunoglobulin E and interleuMn-17A. The infants who had sustained acute obstructive bronchitis were followed up for 12-36 months. Results. The infants who had sustained acute obstructive bronchitis in the presence of mild perinatal CNS damage caused by hypoxia were typified by high respiratory morbidity; early-onset bronchial obstruction; long-term bronchial obstruction relief; high incidence of grade 2 respiratory failure in acute obstructive bronchitis. These patients developed asthma more often than twice and repeated episodes of bronchial obstruction. ROC analysis was used to elaborate clinical and functional criteria for predicting the development of asthma in infants. Conclusion. The proposed additional clinical and functional criteria characterizing external respiratory dysfunction and autonomic homeostatic changes contribute to the early diagnosis of asthma and substantially increase the validity of prediction of its development in children younger than 3 years, which is of great importance for goal-oriented preventive measures.

Predicting inpatient clinical order patterns with probabilistic topic models vs conventional order sets.

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Chen, Jonathan H; Goldstein, Mary K; Asch, Steven M; Mackey, Lester; Altman, Russ B

2017-05-01

Build probabilistic topic model representations of hospital admissions processes and compare the ability of such models to predict clinical order patterns as compared to preconstructed order sets. The authors evaluated the first 24 hours of structured electronic health record data for > 10 K inpatients. Drawing an analogy between structured items (e.g., clinical orders) to words in a text document, the authors performed latent Dirichlet allocation probabilistic topic modeling. These topic models use initial clinical information to predict clinical orders for a separate validation set of > 4 K patients. The authors evaluated these topic model-based predictions vs existing human-authored order sets by area under the receiver operating characteristic curve, precision, and recall for subsequent clinical orders. Existing order sets predict clinical orders used within 24 hours with area under the receiver operating characteristic curve 0.81, precision 16%, and recall 35%. This can be improved to 0.90, 24%, and 47% ( P  sets tend to provide nonspecific, process-oriented aid, with usability limitations impairing more precise, patient-focused support. Algorithmic summarization has the potential to breach this usability barrier by automatically inferring patient context, but with potential tradeoffs in interpretability. Probabilistic topic modeling provides an automated approach to detect thematic trends in patient care and generate decision support content. A potential use case finds related clinical orders for decision support. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association.

Determining clinical benefits of drug-eluting coronary stents according to the population risk profile: a meta-regression from 31 randomized trials.

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Moreno, Raul; Martin-Reyes, Roberto; Jimenez-Valero, Santiago; Sanchez-Recalde, Angel; Galeote, Guillermo; Calvo, Luis; Plaza, Ignacio; Lopez-Sendon, Jose-Luis

2011-04-01

The use of drug-eluting stents (DES) in unfavourable patients has been associated with higher rates of clinical complications and stent thrombosis, and because of that concerns about the use of DES in high-risk settings have been raised. This study sought to demonstrate that the clinical benefit of DES increases as the risk profile of the patients increases. A meta-regression analysis from 31 randomized trials that compared DES and bare-metal stents, including overall 12,035 patients, was performed. The relationship between the clinical benefit of using DES (number of patients to treat [NNT] to prevent one episode of target lesion revascularization [TLR]), and the risk profile of the population (rate of TLR in patients allocated to bare-metal stents) in each trial was evaluated. The clinical benefit of DES increased as the risk profile of each study population increased: NNT for TLR=31.1-1.2 (TLR for bare-metal stents); prisk profile of each study population, since the effect of DES in mortality, myocardial infarction, and stent thrombosis, was not adversely affected by the risk profile of each study population (95% confidence interval for β value 0.09 to 0.11, -0.12 to 0.19, and -0.03 to-0.15 for mortality, myocardial infarction, and stent thrombosis, respectively). The clinical benefit of DES increases as the risk profile of the patients increases, without affecting safety. Copyright © 2009 Elsevier Ireland Ltd. All rights reserved.

Technical player profiles related to the physical fitness of young female volleyball players predict team performance.

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Dávila-Romero, C; Hernández-Mocholí, M A; García-Hermoso, A

2015-03-01

This study is divided into three sequential stages: identification of fitness and game performance profiles (individual player performance), an assessment of the relationship between these profiles, and an assessment of the relationship between individual player profiles and team performance during play (in championship performance). The overall study sample comprised 525 (19 teams) female volleyball players aged 12-16 years and a subsample (N.=43) used to examine study aims one and two was selected from overall sample. Anthropometric, fitness and individual player performance (actual game) data were collected in the subsample. These data were analyzed through clustering methods, ANOVA and independence chi-square test. Then, we investigated whether the proportion of players with the highest individual player performance profile might predict a team's results in the championship. Cluster analysis identified three volleyball fitness profiles (high, medium, and low) and two individual player performance profiles (high and low). The results showed a relationship between both types of profile (fitness and individual player performance). Then, linear regression revealed a moderate relationship between the number of players with a high volleyball fitness profile and a team's results in the championship (R2=0.23). The current study findings may enable coaches and trainers to manage training programs more efficiently in order to obtain tailor-made training, identify volleyball-specific physical fitness training requirements and reach better results during competitions.

A rat retinal damage model predicts for potential clinical visual disturbances induced by Hsp90 inhibitors

International Nuclear Information System (INIS)

Zhou, Dan; Liu, Yuan; Ye, Josephine; Ying, Weiwen; Ogawa, Luisa Shin; Inoue, Takayo; Tatsuta, Noriaki; Wada, Yumiko; Koya, Keizo; Huang, Qin; Bates, Richard C.; Sonderfan, Andrew J.

2013-01-01

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

Prediction of the hardness profile of an AISI 4340 steel cylinder heat-treated by laser - 3D and artificial neural networks modelling and experimental validation

Energy Technology Data Exchange (ETDEWEB)

Hadhri, Mahdi; Ouafi, Abderazzak El; Barka, Noureddine [University of Quebec, Rimouski (Canada)

2017-02-15

This paper presents a comprehensive approach developed to design an effective prediction model for hardness profile in laser surface transformation hardening process. Based on finite element method and Artificial neural networks, the proposed approach is built progressively by (i) examining the laser hardening parameters and conditions known to have an influence on the hardened surface attributes through a structured experimental investigation, (ii) investigating the laser hardening parameters effects on the hardness profile through extensive 3D modeling and simulation efforts and (ii) integrating the hardening process parameters via neural network model for hardness profile prediction. The experimental validation conducted on AISI4340 steel using a commercial 3 kW Nd:Yag laser, confirm the feasibility and efficiency of the proposed approach leading to an accurate and reliable hardness profile prediction model. With a maximum relative error of about 10 % under various practical conditions, the predictive model can be considered as effective especially in the case of a relatively complex system such as laser surface transformation hardening process.

Prediction of the hardness profile of an AISI 4340 steel cylinder heat-treated by laser - 3D and artificial neural networks modelling and experimental validation

International Nuclear Information System (INIS)

Hadhri, Mahdi; Ouafi, Abderazzak El; Barka, Noureddine

2017-01-01

This paper presents a comprehensive approach developed to design an effective prediction model for hardness profile in laser surface transformation hardening process. Based on finite element method and Artificial neural networks, the proposed approach is built progressively by (i) examining the laser hardening parameters and conditions known to have an influence on the hardened surface attributes through a structured experimental investigation, (ii) investigating the laser hardening parameters effects on the hardness profile through extensive 3D modeling and simulation efforts and (ii) integrating the hardening process parameters via neural network model for hardness profile prediction. The experimental validation conducted on AISI4340 steel using a commercial 3 kW Nd:Yag laser, confirm the feasibility and efficiency of the proposed approach leading to an accurate and reliable hardness profile prediction model. With a maximum relative error of about 10 % under various practical conditions, the predictive model can be considered as effective especially in the case of a relatively complex system such as laser surface transformation hardening process

A predictable Java profile - rationale and implementations

DEFF Research Database (Denmark)

Søndergaard, Hans; Bøgholm, Thomas; Hansen, Rene Rydhof

A Java profile suitable for development of high integrity embedded systems is presented. It is based on event handlers which are grouped in missions and equipped with respectively private handler memory and shared mission memory. This is a result of our previous work on developing a Java profile......, and is directly inspired by interactions with the Open Group on their on-going work on a safety critical Java profile (JSR-302). The main contribution is an arrangement of the class hierarchy such that the proposal is a generalization of Real-Time Specification for Java (RTSJ). A further contribution...

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

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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…

Oligonucleotide-based pharmaceuticals: Non-clinical and clinical safety signals and non-clinical testing strategies.

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Mustonen, Enni-Kaisa; Palomäki, Tiina; Pasanen, Markku

2017-11-01

Antisense oligonucleotides, short interfering RNAs (siRNAs) and aptamers are oligonucleotide-based pharmaceuticals with a promising role in targeted therapies. Currently, five oligonucleotide-based pharmaceuticals have achieved marketing authorization in Europe or USA and many more are undergoing clinical testing. However, several safety concerns have been raised in non-clinical and clinical studies. Oligonucleotides share properties with both chemical and biological pharmaceuticals and therefore they pose challenges also from the regulatory point of view. We have analyzed the safety data of oligonucleotides and evaluated the applicability of current non-clinical toxicological guidelines for assessing the safety of oligonucleotide-based pharmaceuticals. Oligonucleotide-based pharmaceuticals display a similar toxicological profile, exerting adverse effects on liver and kidney, evoking hematological alterations, as well as causing immunostimulation and prolonging the coagulation time. It is possible to extrapolate some of these effects from non-clinical studies to humans. However, evaluation strategies for genotoxicity testing of "non-natural" oligonucleotides should be revised. Additionally, the selective use of surrogates and prediction of clinical endpoints for non-clinically observed immunostimulation is complicated by its multiple potential manifestations, demanding improvements in the testing strategies. Utilizing more relevant and mechanistic-based approaches and taking better account of species differences, could possibly improve the prediction of relevant immunological/proinflammatory effects in humans. Copyright © 2017 Elsevier Inc. All rights reserved.

Predicting Recurrence and Progression of Noninvasive Papillary Bladder Cancer at Initial Presentation Based on Quantitative Gene Expression Profiles

DEFF Research Database (Denmark)

Birkhahn, M.; Mitra, A.P.; Williams, Johan

2010-01-01

% specificity. Since this is a small retrospective study using medium-throughput profiling, larger confirmatory studies are needed. Conclusions: Gene expression profiling across relevant cancer pathways appears to be a promising approach for Ta bladder tumor outcome prediction at initial diagnosis......Background: Currently, tumor grade is the best predictor of outcome at first presentation of noninvasive papillary (Ta) bladder cancer. However, reliable predictors of Ta tumor recurrence and progression for individual patients, which could optimize treatment and follow-up schedules based...... on specific tumor biology, are yet to be identified. Objective: To identify genes predictive for recurrence and progression in Ta bladder cancer at first presentation using a quantitative, pathway-specific approach. Design, setting, and participants: Retrospective study of patients with Ta G2/3 bladder tumors...

Glycogen storage disease type I: clinical and laboratory profile

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Berenice L. Santos

2014-12-01

Full Text Available OBJECTIVES: To characterize the clinical, laboratory, and anthropometric profile of a sample of Brazilian patients with glycogen storage disease type I managed at an outpatient referral clinic for inborn errors of metabolism. METHODS: This was a cross-sectional outpatient study based on a convenience sampling strategy. Data on diagnosis, management, anthropometric parameters, and follow-up were assessed. RESULTS: Twenty-one patients were included (median age 10 years, range 1-25 years, all using uncooked cornstarch therapy. Median age at diagnosis was 7 months (range, 1-132 months, and 19 patients underwent liver biopsy for diagnostic confirmation. Overweight, short stature, hepatomegaly, and liver nodules were present in 16 of 21, four of 21, nine of 14, and three of 14 patients, respectively. A correlation was found between height-for-age and BMI-for-age Z-scores (r = 0.561; p = 0.008. CONCLUSIONS: Diagnosis of glycogen storage disease type I is delayed in Brazil. Most patients undergo liver biopsy for diagnostic confirmation, even though the combination of a characteristic clinical presentation and molecular methods can provide a definitive diagnosis in a less invasive manner. Obesity is a side effect of cornstarch therapy, and appears to be associated with growth in these patients.

Reproducibility of mass spectrometry based protein profiles for diagnosis of breast cancer across clinical studies

DEFF Research Database (Denmark)

Callesen, Anne Kjærgaard; Vach, Werner; Jørgensen, Per E

2008-01-01

Serum protein profiling by mass spectrometry has achieved attention as a promising technology in oncoproteomics. We performed a systematic review of published reports on protein profiling as a diagnostic tool for breast cancer. The MEDLINE, EMBASE, and COCHRANE databases were searched for original...... studies reporting discriminatory protein peaks for breast cancer as either protein identity or as m/ z values in the period from January 1995 to October 2006. To address the important aspect of reproducibility of mass spectrometry data across different clinical studies, we compared the published lists...... of potential discriminatory peaks with those peaks detected in an original MALDI MS protein profiling study performed by our own research group. A total of 20 protein/peptide profiling studies were eligible for inclusion in the systematic review. Only 3 reports included information on protein identity...

Prediction of polycystic ovarian syndrome based on ultrasound findings and clinical parameters.

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Moschos, Elysia; Twickler, Diane M

2015-03-01

To determine the accuracy of sonographic-diagnosed polycystic ovaries and clinical parameters in predicting polycystic ovarian syndrome. Medical records and ultrasounds of 151 women with sonographically diagnosed polycystic ovaries were reviewed. Sonographic criteria for polycystic ovaries were based on 2003 Rotterdam European Society of Human Reproduction and Embryology/American Society for Reproductive Medicine guidelines: at least one ovary with 12 or more follicles measuring 2-9 mm and/or increased ovarian volume >10 cm(3) . Clinical variables of age, gravidity, ethnicity, body mass index, and sonographic indication were collected. One hundred thirty-five patients had final outcomes (presence/absence of polycystic ovarian syndrome). Polycystic ovarian syndrome was diagnosed if a patient had at least one other of the following two criteria: oligo/chronic anovulation and/or clinical/biochemical hyperandrogenism. A logistic regression model was constructed using stepwise selection to identify variables significantly associated with polycystic ovarian syndrome (p polycystic ovaries and 115 (89.8%) had polycystic ovarian syndrome (p = .009). Lower gravidity, abnormal bleeding, and body mass index >33 were significant in predicting polycystic ovarian syndrome (receiver operating characteristics curve, c = 0.86). Pain decreased the likelihood of polycystic ovarian syndrome. Polycystic ovaries on ultrasound were sensitive in predicting polycystic ovarian syndrome. Ultrasound, combined with clinical parameters, can be used to generate a predictive index for polycystic ovarian syndrome. © 2014 Wiley Periodicals, Inc.

Electromyographic Patterns during Golf Swing: Activation Sequence Profiling and Prediction of Shot Effectiveness.

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Verikas, Antanas; Vaiciukynas, Evaldas; Gelzinis, Adas; Parker, James; Olsson, M Charlotte

2016-04-23

This study analyzes muscle activity, recorded in an eight-channel electromyographic (EMG) signal stream, during the golf swing using a 7-iron club and exploits information extracted from EMG dynamics to predict the success of the resulting shot. Muscles of the arm and shoulder on both the left and right sides, namely flexor carpi radialis, extensor digitorum communis, rhomboideus and trapezius, are considered for 15 golf players (∼5 shots each). The method using Gaussian filtering is outlined for EMG onset time estimation in each channel and activation sequence profiling. Shots of each player revealed a persistent pattern of muscle activation. Profiles were plotted and insights with respect to player effectiveness were provided. Inspection of EMG dynamics revealed a pair of highest peaks in each channel as the hallmark of golf swing, and a custom application of peak detection for automatic extraction of swing segment was introduced. Various EMG features, encompassing 22 feature sets, were constructed. Feature sets were used individually and also in decision-level fusion for the prediction of shot effectiveness. The prediction of the target attribute, such as club head speed or ball carry distance, was investigated using random forest as the learner in detection and regression tasks. Detection evaluates the personal effectiveness of a shot with respect to the player-specific average, whereas regression estimates the value of target attribute, using EMG features as predictors. Fusion after decision optimization provided the best results: the equal error rate in detection was 24.3% for the speed and 31.7% for the distance; the mean absolute percentage error in regression was 3.2% for the speed and 6.4% for the distance. Proposed EMG feature sets were found to be useful, especially when used in combination. Rankings of feature sets indicated statistics for muscle activity in both the left and right body sides, correlation-based analysis of EMG dynamics and features

Electromyographic Patterns during Golf Swing: Activation Sequence Profiling and Prediction of Shot Effectiveness

Directory of Open Access Journals (Sweden)

Antanas Verikas

2016-04-01

Full Text Available This study analyzes muscle activity, recorded in an eight-channel electromyographic (EMG signal stream, during the golf swing using a 7-iron club and exploits information extracted from EMG dynamics to predict the success of the resulting shot. Muscles of the arm and shoulder on both the left and right sides, namely flexor carpi radialis, extensor digitorum communis, rhomboideus and trapezius, are considered for 15 golf players (∼5 shots each. The method using Gaussian filtering is outlined for EMG onset time estimation in each channel and activation sequence profiling. Shots of each player revealed a persistent pattern of muscle activation. Profiles were plotted and insights with respect to player effectiveness were provided. Inspection of EMG dynamics revealed a pair of highest peaks in each channel as the hallmark of golf swing, and a custom application of peak detection for automatic extraction of swing segment was introduced. Various EMG features, encompassing 22 feature sets, were constructed. Feature sets were used individually and also in decision-level fusion for the prediction of shot effectiveness. The prediction of the target attribute, such as club head speed or ball carry distance, was investigated using random forest as the learner in detection and regression tasks. Detection evaluates the personal effectiveness of a shot with respect to the player-specific average, whereas regression estimates the value of target attribute, using EMG features as predictors. Fusion after decision optimization provided the best results: the equal error rate in detection was 24.3% for the speed and 31.7% for the distance; the mean absolute percentage error in regression was 3.2% for the speed and 6.4% for the distance. Proposed EMG feature sets were found to be useful, especially when used in combination. Rankings of feature sets indicated statistics for muscle activity in both the left and right body sides, correlation-based analysis of EMG

Childhood-onset systemic lupus erythematosus in Singapore: clinical phenotypes, disease activity, damage, and autoantibody profiles.

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Tan, J H T; Hoh, S F; Win, M T M; Chan, Y H; Das, L; Arkachaisri, T

2015-08-01

Childhood-onset systemic lupus erythematosus (cSLE) is a multisystem autoimmune disease characterized by immune dysregulation affecting patients less than 18 years old. One-fifth of SLE cases are diagnosed during childhood. cSLE presents differently from adults and has a more severe and aggressive course. We describe the clinical and antibody profiles in our cSLE Singapore cohort. All cSLE patients who satisfied the 1997 American College of Rheumatology diagnostic criteria were captured in our lupus registry from January 2009 to January 2014. Data including demographic, cumulative clinical, serologic data, and damage indices were collected. Adjusted mean SLEDAI-2K (AMS) was used to summarize disease activity over multiple visits. Cluster analysis using non-hierarchical K-means procedure was performed on eight selected antibodies. The 64 patients (female:male ratio 5:1; Chinese 45.3%, Malay 28.1%, Indian 9.4%, and other races 17.2%) had a mean onset age of 11.5 years (range 2.1-16.7) and mean age at diagnosis was 11.9 years (range 2.6-18.0). Our study demonstrated differences in clinical manifestations for which hematologic involvement was the most common manifestation with less renal disease and uncommon neurologic manifestation as compared to other cSLE cohorts reported in our region. Antibody clusters were identified in our cohort but their clinical association/discrimination and outcome prediction required further validation study. Outcomes of our cohort in regard to disease activity after therapy and organ damages were comparable if not better to other cSLE cohorts elsewhere. Steroid-related damage, including symptomatic multifocal avascular necrosis and cataract, were not uncommon locally. Infection remains the major cause of death for the continent. Nevertheless, the five year survival rate of our cohort (98.4%) was high. © The Author(s) 2015.

Clinical Implications of Cluster Analysis-Based Classification of Acute Decompensated Heart Failure and Correlation with Bedside Hemodynamic Profiles.

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Tariq Ahmad

Full Text Available Classification of acute decompensated heart failure (ADHF is based on subjective criteria that crudely capture disease heterogeneity. Improved phenotyping of the syndrome may help improve therapeutic strategies.To derive cluster analysis-based groupings for patients hospitalized with ADHF, and compare their prognostic performance to hemodynamic classifications derived at the bedside.We performed a cluster analysis on baseline clinical variables and PAC measurements of 172 ADHF patients from the ESCAPE trial. Employing regression techniques, we examined associations between clusters and clinically determined hemodynamic profiles (warm/cold/wet/dry. We assessed association with clinical outcomes using Cox proportional hazards models. Likelihood ratio tests were used to compare the prognostic value of cluster data to that of hemodynamic data.We identified four advanced HF clusters: 1 male Caucasians with ischemic cardiomyopathy, multiple comorbidities, lowest B-type natriuretic peptide (BNP levels; 2 females with non-ischemic cardiomyopathy, few comorbidities, most favorable hemodynamics; 3 young African American males with non-ischemic cardiomyopathy, most adverse hemodynamics, advanced disease; and 4 older Caucasians with ischemic cardiomyopathy, concomitant renal insufficiency, highest BNP levels. There was no association between clusters and bedside-derived hemodynamic profiles (p = 0.70. For all adverse clinical outcomes, Cluster 4 had the highest risk, and Cluster 2, the lowest. Compared to Cluster 4, Clusters 1-3 had 45-70% lower risk of all-cause mortality. Clusters were significantly associated with clinical outcomes, whereas hemodynamic profiles were not.By clustering patients with similar objective variables, we identified four clinically relevant phenotypes of ADHF patients, with no discernable relationship to hemodynamic profiles, but distinct associations with adverse outcomes. Our analysis suggests that ADHF classification using

Biologic and clinical significance of molecular profiling in Chronic Lymphocytic Leukemia.

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Butler, Tom; Gribben, J G

2010-05-01

CLL is extremely heterogeneous in its clinical course, with some patients living decades with no need for treatment whilst others have a rapidly aggressive clinical course. A major focus of research has been to try to identify those biological factors that influence this heterogeneity. The goal of therapy has been to maintain the best quality of life and treat only when patients become symptomatic from their disease. For the majority of patients this means following a "watch and wait" approach to determine the rate of progression of the disease and assess for development of symptoms. Any alteration to this approach will require identification of criteria that define patients sufficiently "high-risk" that they gain benefit by introduction of early therapy. The use of molecular profiling to suggest particular therapies is currently appropriate only in defining the treatment of the minority of patients with 17p deletions or p53 mutations and in all other circumstances remains a clinical trial question. Copyright 2010 Elsevier Ltd. All rights reserved.

Prognostic Gene Expression Profiles in Breast Cancer

DEFF Research Database (Denmark)

Sørensen, Kristina Pilekær

Each year approximately 4,800 Danish women are diagnosed with breast cancer. Several clinical and pathological factors are used as prognostic and predictive markers to categorize the patients into groups of high or low risk. Around 90% of all patients are allocated to the high risk group...... clinical courses, and they may be useful as novel prognostic biomarkers in breast cancer. The aim of the present project was to predict the development of metastasis in lymph node negative breast cancer patients by RNA profiling. We collected and analyzed 82 primary breast tumors from patients who...... and the time of event. Previous findings have shown that high expression of the lncRNA HOTAIR is correlated with poor survival in breast cancer. We validated this finding by demonstrating that high HOTAIR expression in our primary tumors was significantly associated with worse prognosis independent...

Comparing 2 Whiplash Grading Systems to Predict Clinical Outcomes.

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Croft, Arthur C; Bagherian, Alireza; Mickelsen, Patrick K; Wagner, Stephen

2016-06-01

Two whiplash severity grading systems have been developed: Quebec Task Force on Whiplash-Associated Disorders (QTF-WAD) and the Croft grading system. The majority of clinical studies to date have used the modified grading system published by the QTF-WAD in 1995 and have demonstrated some ability to predict outcome. But most studies include only injuries of lower severity (grades 1 and 2), preventing a broader interpretation. The purpose of this study was assess the ability of these grading systems to predict clinical outcome within the context of a broader injury spectrum. This study evaluated both grading systems for their ability to predict the bivalent outcome, recovery, within a sample of 118 whiplash patients who were part of a previous case-control designed study. Of these, 36% (controls) had recovered, and 64% (cases) had not recovered. The discrete bivariate distribution between recovery status and whiplash grade was analyzed using the 2-tailed cross-tabulation statistics. Applying the criteria of the original 1993 Croft grading system, the subset comprised 1 grade 1 injury, 32 grade 2 injuries, 53 grade 3 injuries, and 32 grade 4 injuries. Applying the criteria of the modified (QTF-WAD) grading system, there were 1 grade 1 injury, 89 grade 2 injuries, and 28 grade 3 injuries. Both whiplash grading systems correlated negatively with recovery; that is, higher severity grades predicted a lower probability of recovery, and statistically significant correlations were observed in both, but the Croft grading system substantially outperformed the QTF-WAD system on this measure. The Croft grading system for whiplash injury severity showed a better predictive measure for recovery status from whiplash injuries as compared with the QTF-WAD grading system.

Efficacy and predictive value of clinical stage in non-surgical patients with esophageal cancer

International Nuclear Information System (INIS)

Liu Xiao; Wang Guiqi; He Shun

2014-01-01

Objective: To investigate the efficacy and predictive value of clinical stage in non-surgical patients with esophageal cancer (EC). Methods: A retrospective study was conducted in 358 EC patients who underwent radical surgery in our hospital from April 2003 to October 2010 and who had preoperative work-up including endoscopic esophageal ultrasound (EUS), esophagoscopy, thoracic CT scans,and contrast esophagography and had detailed information on postoperative pathological stages. The predictive value of preoperative clinical T/N stage based on EUS + CT for postoperative pathological stage was analyzed. The disease free survival (DFS) and overall survival (OS) were analyzed according to the UICC TNM classification (2002/ 2009) and the clinical stage based on imaging findings. Results: The median follow-up was 47 months.A total of 305 (85.2%) of all patients were analyzed by clinical stage based on EUS + CT.Among them, the predictive value of clinical T stage for pathological T stage was 0-88.6%, highest (88.6%) for T1 stage and lowest for T4 stage. The predictive value of clinical N stage (N 0 /N1) was 62.5-100%. The significant differences in OS and DFS rates based on both 2002 and 2009 UICC TNM classifications were noted (P=0.000 and 0.000). There were significant differences in OS between stage groups, except the comparison between two stage Ⅳ patients and other groups, according to 2002 UICC TNM classification. There were usually insignificant differences in OS between stage groups, according to 2009 UICC TNM classification. For the 305 patients staged clinically based on EUS and CT according to 2002 UICC TNM classification, significant differences in OS and DFS rates were noted (P=0.000 and 0.000). Conclusions: Imaging modalities show good predictive value for N stage (N0/N1),even though they cannot accurately provide the number of metastatic lymph nodes. The clinical stage based on EUS + CT can effectively predict the prognosis of non-surgical EC patients

Identifying and Predicting Profiles of Medical Noncompliance: Pediatric Caregivers' Antibiotic Stewardship.

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Smith, Rachel A; Kim, Youllee; M'Ikanatha, Nkuchia M

2018-05-14

Sometimes compliance with medical recommendations is problematic. We investigated pediatric caregivers' (N = 606) patterns of noncompliance with antibiotic stewardship based on the obstacle hypothesis. We tested predictors of noncompliance framed by the obstacle hypothesis, dissonance theory, and psychological reactance. The results revealed four profiles of caregivers' stewardship: one marked by compliance (Stewards) and three marked by types of noncompliance (Stockers, Persuaders, and Dissenters). The covariate analysis showed that, although psychological reactance predicted being noncompliant, it was types of obstacles and discrepant experiences that predicted caregivers' patterns of noncompliance with antibiotic stewardship. Campaign planning often focuses on identifying the belief most associated with the targeted outcome, such as compliance. Noncompliance research, however, points out that persuaders may be successful to the extent to which they anticipate obstacles to compliance and address them in their influence attempts. A shift from medical noncompliance to patient engagement also affords an opportunity to consider how some recommendations create obstacles for others and to find positive ways to embrace conflicting needs, tensions, and reasons for refusal in order to promote collective goals.

Prediction potential of candidate biomarker sets identified and validated on gene expression data from multiple datasets

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Karacali Bilge

2007-10-01

Full Text Available Abstract Background Independently derived expression profiles of the same biological condition often have few genes in common. In this study, we created populations of expression profiles from publicly available microarray datasets of cancer (breast, lymphoma and renal samples linked to clinical information with an iterative machine learning algorithm. ROC curves were used to assess the prediction error of each profile for classification. We compared the prediction error of profiles correlated with molecular phenotype against profiles correlated with relapse-free status. Prediction error of profiles identified with supervised univariate feature selection algorithms were compared to profiles selected randomly from a all genes on the microarray platform and b a list of known disease-related genes (a priori selection. We also determined the relevance of expression profiles on test arrays from independent datasets, measured on either the same or different microarray platforms. Results Highly discriminative expression profiles were produced on both simulated gene expression data and expression data from breast cancer and lymphoma datasets on the basis of ER and BCL-6 expression, respectively. Use of relapse-free status to identify profiles for prognosis prediction resulted in poorly discriminative decision rules. Supervised feature selection resulted in more accurate classifications than random or a priori selection, however, the difference in prediction error decreased as the number of features increased. These results held when decision rules were applied across-datasets to samples profiled on the same microarray platform. Conclusion Our results show that many gene sets predict molecular phenotypes accurately. Given this, expression profiles identified using different training datasets should be expected to show little agreement. In addition, we demonstrate the difficulty in predicting relapse directly from microarray data using supervised machine

Prognostic impact of clinical course-specific mRNA expression profiles in the serum of perioperative patients with esophageal cancer in the ICU: a case control study

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Oshima Yoshiaki

2010-10-01

Full Text Available Abstract Background We previously reported that measuring circulating serum mRNAs using quantitative one-step real-time RT-PCR was clinically useful for detecting malignancies and determining prognosis. The aim of our study was to find crucial serum mRNA biomarkers in esophageal cancer that would provide prognostic information for post-esophagectomy patients in the critical care setting. Methods We measured serum mRNA levels of 11 inflammatory-related genes in 27 post-esophagectomy patients admitted to the intensive care unit (ICU. We tracked these levels chronologically, perioperatively and postoperatively, until the two-week mark, investigating their clinical and prognostic significance as compared with clinical parameters. Furthermore, we investigated whether gene expression can accurately predict clinical outcome and prognosis. Results Circulating mRNAs in postoperative esophagectomy patients had gene-specific expression profiles that varied with the clinical phase of their treatment. Multivariate regression analysis showed that upregulation of IL-6, VWF and TGF-β1 mRNA in the intraoperative phase (p = 0.016, 0.0021 and 0.009 and NAMPT and MUC1 mRNA on postoperative day 3 (p ®, Ono Pharmaceutical Co., Ltd. significantly correlated with MUC1 and NAMPT mRNA expression (p = 0.048 and 0.045. IL-6 mRNA correlated with hypercytokinemia and recovery from hypercytokinemia (sensitivity 80.9% and was a significant biomarker in predicting the onset of severe inflammatory diseases. Conclusion Chronological tracking of postoperative mRNA levels of inflammatory-related genes in esophageal cancer patients may facilitate early institution of pharamacologic therapy, prediction of treatment response, and prognostication during ICU management in the perioperative period.

Predictive probability methods for interim monitoring in clinical trials with longitudinal outcomes.

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Zhou, Ming; Tang, Qi; Lang, Lixin; Xing, Jun; Tatsuoka, Kay

2018-04-17

In clinical research and development, interim monitoring is critical for better decision-making and minimizing the risk of exposing patients to possible ineffective therapies. For interim futility or efficacy monitoring, predictive probability methods are widely adopted in practice. Those methods have been well studied for univariate variables. However, for longitudinal studies, predictive probability methods using univariate information from only completers may not be most efficient, and data from on-going subjects can be utilized to improve efficiency. On the other hand, leveraging information from on-going subjects could allow an interim analysis to be potentially conducted once a sufficient number of subjects reach an earlier time point. For longitudinal outcomes, we derive closed-form formulas for predictive probabilities, including Bayesian predictive probability, predictive power, and conditional power and also give closed-form solutions for predictive probability of success in a future trial and the predictive probability of success of the best dose. When predictive probabilities are used for interim monitoring, we study their distributions and discuss their analytical cutoff values or stopping boundaries that have desired operating characteristics. We show that predictive probabilities utilizing all longitudinal information are more efficient for interim monitoring than that using information from completers only. To illustrate their practical application for longitudinal data, we analyze 2 real data examples from clinical trials. Copyright © 2018 John Wiley & Sons, Ltd.

Usefulness of Clinical Prediction Rules, D-dimer, and Arterial Blood Gas Analysis to Predict Pulmonary Embolism in Cancer Patients

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Shazia Awan

2017-03-01

Full Text Available Objectives: Pulmonary embolism (PE is seven times more common in cancer patients than non-cancer patients. Since the existing clinical prediction rules (CPRs were validated predominantly in a non-cancer population, we decided to look at the utility of arterial blood gas (ABG analysis and D-dimer in predicting PE in cancer patients. Methods: Electronic medical records were reviewed between December 2005 and November 2010. A total of 177 computed tomography pulmonary angiograms (CTPAs were performed. We selected 104 individuals based on completeness of laboratory and clinical data. Patients were divided into two groups, CTPA positive (patients with PE and CTPA negative (PE excluded. Wells score, Geneva score, and modified Geneva score were calculated for each patient. Primary outcomes of interest were the sensitivities, specificities, positive, and negative predictive values for all three CPRs. Results: Of the total of 104 individuals who had CTPAs, 33 (31.7% were positive for PE and 71 (68.3% were negative. There was no difference in basic demographics between the two groups. Laboratory parameters were compared and partial pressure of oxygen was significantly lower in patients with PE (68.1 mmHg vs. 71 mmHg, p = 0.030. Clinical prediction rules showed good sensitivities (88−100% and negative predictive values (93−100%. An alveolar-arterial (A-a gradient > 20 had 100% sensitivity and negative predictive values. Conclusions: CPRs and a low A-a gradient were useful in excluding PE in cancer patients. There is a need for prospective trials to validate these results.

Prevalence and clinical profile of celiac disease in children with type 1 diabetes mellitus

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Rajesh Joshi

2015-01-01

Full Text Available Objective: To determine the prevalence of celiac disease (CD in children with type 1 diabetes mellitus (TIDM in follow-up in a Tertiary Care Referral Centre in Western India and to describe the clinical features indicative of CD in screened patients of TIDM. Study Design: In this single center observational cross-sectional study, 71 children who were diagnosed with TIDM were subjected to screening for CD with tissue transglutaminase antibody testing. Those who tested positive were offered intestinal biopsy for the confirmation of diagnosis. Clinical profiles of both groups of patients were compared and manifestations of CD were delineated. Results: The study revealed the prevalence of CD (based on serology in children with Type 1 diabetes as 15.49%. The prevalence of biopsy-confirmed CD was 7.04%. Of the diagnosed CD patients, one-third were symptomatic at the time of screening while the majority was asymptomatic. The major clinical features indicative of CD were intestinal symptoms, anemia, rickets, and short stature. Autoimmune thyroid disease was prevalent in 29.6% of the patients with TIDM followed by CD. Conclusions: The high prevalence of CD in children with Type 1 diabetes emphasizes the need for routine screening programs to be in place for these high-risk populations. The clinical profile of patients with CD further elaborates the indicators of CD and the need to screen for them.

[Usefulness of clinical prediction rules for ruling out deep vein thrombosis in a hospital emergency department].

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Rosa-Jiménez, Francisco; Rosa-Jiménez, Ascensión; Lozano-Rodríguez, Aquiles; Santoro-Martínez, María Del Carmen; Duro-López, María Del Carmen; Carreras-Álvarez de Cienfuegos, Amelia

2015-01-01

To compare the efficacy of the most familiar clinical prediction rules in combination with D-dimer testing to rule out a diagnosis of deep vein thrombosis (DVT) in a hospital emergency department. Retrospective cross-sectional analysis of the case records of all patients attending a hospital emergency department with suspected lower-limb DVT between 1998 and 2002. Ten clinical prediction scores were calculated and D-dimer levels were available for all patients. The gold standard was ultrasound diagnosis of DVT by an independent radiologist who was blinded to clinical records. For each prediction rule, we analyzed the effectiveness of the prediction strategy defined by "low clinical probability and negative D-dimer level" against the ultrasound diagnosis. A total of 861 case records were reviewed and 577 cases were selected; the mean (SD) age was 66.7 (14.2) years. DVT was diagnosed in 145 patients (25.1%). Only the Wells clinical prediction rule and 4 other models had a false negative rate under 2%. The Wells criteria and the score published by Johanning and colleagues identified higher percentages of cases (15.6% and 11.6%, respectively). This study shows that several clinical prediction rules can be safely used in the emergency department, although none of them have proven more effective than the Wells criteria.

How good are publicly available web services that predict bioactivity profiles for drug repurposing?

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Murtazalieva, K A; Druzhilovskiy, D S; Goel, R K; Sastry, G N; Poroikov, V V

2017-10-01

Drug repurposing provides a non-laborious and less expensive way for finding new human medicines. Computational assessment of bioactivity profiles shed light on the hidden pharmacological potential of the launched drugs. Currently, several freely available computational tools are available via the Internet, which predict multitarget profiles of drug-like compounds. They are based on chemical similarity assessment (ChemProt, SuperPred, SEA, SwissTargetPrediction and TargetHunter) or machine learning methods (ChemProt and PASS). To compare their performance, this study has created two evaluation sets, consisting of (1) 50 well-known repositioned drugs and (2) 12 drugs recently patented for new indications. In the first set, sensitivity values varied from 0.64 (TarPred) to 1.00 (PASS Online) for the initial indications and from 0.64 (TarPred) to 0.98 (PASS Online) for the repurposed indications. In the second set, sensitivity values varied from 0.08 (SuperPred) to 1.00 (PASS Online) for the initial indications and from 0.00 (SuperPred) to 1.00 (PASS Online) for the repurposed indications. Thus, this analysis demonstrated that the performance of machine learning methods surpassed those of chemical similarity assessments, particularly in the case of novel repurposed indications.

A clinical profile of compulsive exercise in adolescent inpatients with anorexia nervosa

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Noetel, Melissa; Miskovic-Wheatley, Jane; Crosby, Ross D.; Hay, Phillipa; Madden, Sloane; Touyz, Stephen

2016-01-01

Background The aim of the current study was to contribute to the development of a clinical profile of compulsive exercise in adolescents with Anorexia Nervosa (AN), by examining associations between compulsive exercise and eating and general psychopathology. Method A sample of 60 female adolescent inpatients with AN completed a self-report measure of compulsive exercise and a series of standardized self-report questionnaires assessing eating and general psychopathology. Results Higher levels ...

Violence risk prediction. Clinical and actuarial measures and the role of the Psychopathy Checklist.

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Dolan, M; Doyle, M

2000-10-01

Violence risk prediction is a priority issue for clinicians working with mentally disordered offenders. To review the current status of violence risk prediction research. Literature search (Medline). Key words: violence, risk prediction, mental disorder. Systematic/structured risk assessment approaches may enhance the accuracy of clinical prediction of violent outcomes. Data on the predictive validity of available clinical risk assessment tools are based largely on American and North American studies and further validation is required in British samples. The Psychopathy Checklist appears to be a key predictor of violent recidivism in a variety of settings. Violence risk prediction is an inexact science and as such will continue to provoke debate. Clinicians clearly need to be able to demonstrate the rationale behind their decisions on violence risk and much can be learned from recent developments in research on violence risk prediction.

Clinical profile of parkinson's disease: Experience of niger

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Hamid Assadeck

2018-01-01

Full Text Available Background: Parkinson's disease (PD is a chronic neurodegenerative pathology with unknown etiology. It is characterized clinically by the classic triad that associated tremors, bradykinesia, and rigidity. In Niger, there are no data on PD. Aims: We aimed to provide the demographic and clinical profile of PD in patients from Niger to create a database on PD in Niger. Patients and Methods: We conducted a retrospective study at the Neurology Outpatient Clinic of the Hôpital National de Niamey (HNN, Niger over a period of 4.42 years from February 2009 to July 2013 collecting all cases of PD. The demographic and clinical features of all patients were collected and analyzed. Results: During the period of the study, 1695 patients consulted at the Neurology Outpatient Clinic of the HNN, among which 76 patients (4.48% had secondary parkinsonism and 25 patients (1.47% had features compatible with PD. Only patients with PD were included in this study. The mean age at onset of symptoms was 58 years (range: 42–74 years. The male sex was predominant (60% with a sex ratio of 1.5. The mean time interval from the onset of symptoms to diagnosis of PD was 1.8 years (range: 1–5 years. The tremor was the most common symptom (84%. Bradykinesia represented 64% of the symptoms and rigidity 20%. At the time of the diagnosis of PD, 8 patients (32% were in Stage I of the classification of Hoehn and Yahr, 16 patients (64% in Stage II, and 1 patient (4% in Stage III. The levodopa/carbidopa combination was the most used antiparkinsonian drug in our patients (88%. The mean time of follow-up of the patients was 2.5 years (range: 1–4.42 years. During the course of the disease, 9 patients (36% were in Stage II of the classification of Hoehn and Yahr, 13 patients (52% in Stage III, and 3 patients (12% in Stage IV. Conclusion: Our study provides demographic and clinical data of PD in patients from Niger and shows that the hospital frequency of this disease is low (1

Multigene expression profile for predicting efficacy of cisplatin and vinorelbine in non-small cell lung cancer

DEFF Research Database (Denmark)

Buhl, I. K.; Christensen, I. J.; Santoni-Rugiu, E.

2016-01-01

Background: There is a need for biomarkers to predict efficacy of adjuvant chemotherapy in resected non-small cell lung cancer (NSCLC). Presented is a combined cisplatin and vinorelbine marker from a previously validated model system [1] tested in two cohorts. Methods: The profiles consist...... and vinorelbine (ACT) and 62 patients who had no adjuvant treatment (OBS) [2] and 2) 95 stage Ib-IIIb completely resected NSCLC patients who all received adjuvant cisplatin and vinorelbine [3]. Endpoint is cancer specific survival. Results: The combined cisplatin and vinorelbine profiles scored as a continuous...... of correlated in vitro cytotoxicity of cisplatin and vinorelbine and mRNA expressions. Then each profile is correlated to mRNA expression of 3500 tumors. The cohorts are 1) a publically available dataset with 133 completely resected stage Ib-II NSCLC patients, 71 of whom received adjuvant cisplatin...

Prediction of higher cost of antiretroviral therapy (ART) according to clinical complexity. A validated clinical index.

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Velasco, Cesar; Pérez, Inaki; Podzamczer, Daniel; Llibre, Josep Maria; Domingo, Pere; González-García, Juan; Puig, Inma; Ayala, Pilar; Martín, Mayte; Trilla, Antoni; Lázaro, Pablo; Gatell, Josep Maria

2016-03-01

The financing of antiretroviral therapy (ART) is generally determined by the cost incurred in the previous year, the number of patients on treatment, and the evidence-based recommendations, but not the clinical characteristics of the population. To establish a score relating the cost of ART and patient clinical complexity in order to understand the costing differences between hospitals in the region that could be explained by the clinical complexity of their population. Retrospective analysis of patients receiving ART in a tertiary hospital between 2009 and 2011. Factors potentially associated with a higher cost of ART were assessed by bivariate and multivariate analysis. Two predictive models of "high-cost" were developed. The normalized estimated (adjusted for the complexity scores) costs were calculated and compared with the normalized real costs. In the Hospital Index, 631 (16.8%) of the 3758 patients receiving ART were responsible for a "high-cost" subgroup, defined as the highest 25% of spending on ART. Baseline variables that were significant predictors of high cost in the Clinic-B model in the multivariate analysis were: route of transmission of HIV, AIDS criteria, Spanish nationality, year of initiation of ART, CD4+ lymphocyte count nadir, and number of hospital admissions. The Clinic-B score ranged from 0 to 13, and the mean value (5.97) was lower than the overall mean value of the four hospitals (6.16). The clinical complexity of the HIV patient influences the cost of ART. The Clinic-B and Clinic-BF scores predicted patients with high cost of ART and could be used to compare and allocate costs corrected for the patient clinical complexity. Copyright © 2015 Elsevier España, S.L.U. y Sociedad Española de Enfermedades Infecciosas y Microbiología Clínica. All rights reserved.

CRISPR-Cas9-mediated saturated mutagenesis screen predicts clinical drug resistance with improved accuracy.

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Ma, Leyuan; Boucher, Jeffrey I; Paulsen, Janet; Matuszewski, Sebastian; Eide, Christopher A; Ou, Jianhong; Eickelberg, Garrett; Press, Richard D; Zhu, Lihua Julie; Druker, Brian J; Branford, Susan; Wolfe, Scot A; Jensen, Jeffrey D; Schiffer, Celia A; Green, Michael R; Bolon, Daniel N

2017-10-31

Developing tools to accurately predict the clinical prevalence of drug-resistant mutations is a key step toward generating more effective therapeutics. Here we describe a high-throughput CRISPR-Cas9-based saturated mutagenesis approach to generate comprehensive libraries of point mutations at a defined genomic location and systematically study their effect on cell growth. As proof of concept, we mutagenized a selected region within the leukemic oncogene BCR-ABL1 Using bulk competitions with a deep-sequencing readout, we analyzed hundreds of mutations under multiple drug conditions and found that the effects of mutations on growth in the presence or absence of drug were critical for predicting clinically relevant resistant mutations, many of which were cancer adaptive in the absence of drug pressure. Using this approach, we identified all clinically isolated BCR-ABL1 mutations and achieved a prediction score that correlated highly with their clinical prevalence. The strategy described here can be broadly applied to a variety of oncogenes to predict patient mutations and evaluate resistance susceptibility in the development of new therapeutics. Published under the PNAS license.

Hierarchical Status Predicts Behavioral Vulnerability and Nucleus Accumbens Metabolic Profile Following Chronic Social Defeat Stress.

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Larrieu, Thomas; Cherix, Antoine; Duque, Aranzazu; Rodrigues, João; Lei, Hongxia; Gruetter, Rolf; Sandi, Carmen

2017-07-24

Extensive data highlight the existence of major differences in individuals' susceptibility to stress [1-4]. While genetic factors [5, 6] and exposure to early life stress [7, 8] are key components for such neurobehavioral diversity, intriguing observations revealed individual differences in response to stress in inbred mice [9-12]. This raised the possibility that other factors might be critical in stress vulnerability. A key challenge in the field is to identify non-invasively risk factors for vulnerability to stress. Here, we investigated whether behavioral factors, emerging from preexisting dominance hierarchies, could predict vulnerability to chronic stress [9, 13-16]. We applied a chronic social defeat stress (CSDS) model of depression in C57BL/6J mice to investigate the predictive power of hierarchical status to pinpoint which individuals will exhibit susceptibility to CSDS. Given that the high social status of dominant mice would be the one particularly challenged by CSDS, we predicted and found that dominant individuals were the ones showing a strong susceptibility profile as indicated by strong social avoidance following CSDS, while subordinate mice were not affected. Data from 1 H-NMR spectroscopy revealed that the metabolic profile in the nucleus accumbens (NAc) relates to social status and vulnerability to stress. Under basal conditions, subordinates show lower levels of energy-related metabolites compared to dominants. In subordinates, but not dominants, levels of these metabolites were increased after exposure to CSDS. To the best of our knowledge, this is the first study that identifies non-invasively the origin of behavioral risk factors predictive of stress-induced depression-like behaviors associated with metabolic changes. Copyright © 2017 Elsevier Ltd. All rights reserved.

Behavioral Profiles of Clinically Referred Children with Intellectual Giftedness

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Fabian Guénolé

2013-01-01

Full Text Available It is common that intellectually gifted children—that is, children with an IQ ≥ 130—are referred to paediatric or child neuropsychiatry clinics for socio-emotional problems and/or school underachievement or maladjustment. These clinically-referred children with intellectual giftedness are thought to typically display internalizing problems (i.e., self-focused problems reflecting overcontrol of emotion and behavior, and to be more behaviorally impaired when “highly” gifted (IQ ≥ 145 or displaying developmental asynchrony (i.e., a heterogeneous developmental pattern, reflected in a significant verbal-performance discrepancy on IQ tests. We tested all these assumptions in 143 clinically-referred gifted children aged 8 to 12, using Wechsler’s intelligence profile and the Child Behavior Checklist. Compared to a normative sample, gifted children displayed increased behavioral problems in the whole symptomatic range. Internalizing problems did not predominate over externalizing ones (i.e., acted-out problems, reflecting undercontrol of emotion and behavior, revealing a symptomatic nature of behavioral syndromes more severe than expected. “Highly gifted” children did not display more behavioral problems than the “low gifted.” Gifted children with a significant verbal-performance discrepancy displayed more externalizing problems and mixed behavioral syndromes than gifted children without such a discrepancy. These results suggest that developmental asynchrony matters when examining emotional and behavioral problems in gifted children.

Improvement of a predictive model in ovarian cancer patients submitted to platinum-based chemotherapy: implications of a GST activity profile.

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Pereira, Deolinda; Assis, Joana; Gomes, Mónica; Nogueira, Augusto; Medeiros, Rui

2016-05-01

The success of chemotherapy in ovarian cancer (OC) is directly associated with the broad variability in platinum response, with implications in patients survival. This heterogeneous response might result from inter-individual variations in the platinum-detoxification pathway due to the expression of glutathione-S-transferase (GST) enzymes. We hypothesized that GSTM1 and GSTT1 polymorphisms might have an impact as prognostic and predictive determinants for OC. We conducted a hospital-based study in a cohort of OC patients submitted to platinum-based chemotherapy. GSTM1 and GSTT1 genotypes were determined by multiplex PCR. GSTM1-null genotype patients presented a significantly longer 5-year survival and an improved time to progression when compared with GSTM1-wt genotype patients (log-rank test, P = 0.001 and P = 0.013, respectively). Multivariate Cox regression analysis indicates that the inclusion of genetic information regarding GSTM1 polymorphism increased the predictive ability of risk of death after OC platinum-based chemotherapy (c-index from 0.712 to 0.833). Namely, residual disease (HR, 4.90; P = 0.016) and GSTM1-wt genotype emerged as more important predictors of risk of death (HR, 2.29; P = 0.039; P = 0.036 after bootstrap). No similar effect on survival was observed regarding GSTT1 polymorphism, and there were no statistically significant differences between GSTM1 and GSTT1 genotypes and the assessed patients' clinical-pathological characteristics. GSTM1 polymorphism seems to have an impact in OC prognosis as it predicts a better response to platinum-based chemotherapy and hence an improved survival. The characterization of the GSTM1 genetic profile might be a useful molecular tool and a putative genetic marker for OC clinical outcome.

Profile of tobacco users amongst treatment seekers: A comparison between clinic and community sample

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Savita Malhotra

2017-01-01

Full Text Available Background and objectives: Despite the huge burden of tobacco use or addiction, there has been a glaring scarcity of resources to tackle the problem. Although some of the tobacco users want to quit, very few have the opportunity to seek help from available treatment facilities. The study aimed to find out the profile of treatment seekers from clinic and community programs and also to compare the two groups. Method: This is a cross sectional, retrospective study of subjects enrolled in the clinic and various community outreach programs of a Tobacco Cessation Centre from the year 2002-2011. Modified intake form developed by the WHO was administered to the subjects. Results: Significant difference was found between the two groups with regard to the age of treatment seeking, education and socio economic status. Older subjects reported in greater numbers to the clinic, whereas younger subjects belonged to the community group. Community group had lower level of education, belonged to lower or upper lower socio economic status whereas clinic group had higher level of education and were from the middle or upper socio economic status. Curiosity (Z score = 3.2,P = 0.001 played a significant role in initiating the use in clinic group whereas role model (Z score = 5.1, P = <0.0001 and low self esteem (Z score = 2.0, P = 0.023 were significantly associated with community sample. Presence of medical complications (Z score = 12.5, P = <0.0001, awareness of physical harm of nicotine (Z score = 5.0, P = <0.0001 and awareness of addiction was significantly more in the clinic group. Interpretation and Conclusions: The difference in the socio-demographic and clinical profile of tobacco users in these two treatment groups is noteworthy, and is expected to offer useful information for the clinicians and as well as for the policy makers.

Molecular profiling of advanced breast cancer tumors is beneficial in assisting clinical treatment plans.

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Carter, Philip; Alifrangis, Costi; Cereser, Biancastella; Chandrasinghe, Pramodh; Del Bel Belluz, Lisa; Moderau, Nina; Poyia, Fotini; Schwartzberg, Lee S; Tabassum, Neha; Wen, Jinrui; Krell, Jonathan; Stebbing, Justin

2018-04-03

We used data obtained by Caris Life Sciences, to evaluate the benefits of tailoring treatments for a breast carcinoma cohort by using tumor molecular profiles to inform decisions. Data for 92 breast cancer patients from the commercial Caris Molecular Intelligence database was retrospectively divided into two groups, so that the first always followed treatment recommendations, whereas in the second group all patients received at least one drug after profiling that was predicted to lack benefit. The biomarker and drug associations were based on tests including fluorescent in situ hybridization and DNA sequencing, although immunohistochemistry was the main test used. Patients whose drugs matched those recommended according to their tumor profile had an average overall survival of 667 days, compared to 510 days for patients that did not (P=0.0316). In the matched treatment group, 26% of patients were deceased by the last time of monitoring, whereas this was 41% in the unmatched group (P=0.1257). We therefore confirm the ability of tumor molecular profiling to improve survival of breast cancer patients. Immunohistochemistry biomarkers for the androgen, estrogen and progesterone receptors were found to be prognostic for survival.

Expression profiling of blood samples from an SU5416 Phase III metastatic colorectal cancer clinical trial: a novel strategy for biomarker identification

International Nuclear Information System (INIS)

DePrimo, Samuel E; Wong, Lily M; Khatry, Deepak B; Nicholas, Susan L; Manning, William C; Smolich, Beverly D; O'Farrell, Anne-Marie; Cherrington, Julie M

2003-01-01

Microarray-based gene expression profiling is a powerful approach for the identification of molecular biomarkers of disease, particularly in human cancers. Utility of this approach to measure responses to therapy is less well established, in part due to challenges in obtaining serial biopsies. Identification of suitable surrogate tissues will help minimize limitations imposed by those challenges. This study describes an approach used to identify gene expression changes that might serve as surrogate biomarkers of drug activity. Expression profiling using microarrays was applied to peripheral blood mononuclear cell (PBMC) samples obtained from patients with advanced colorectal cancer participating in a Phase III clinical trial. The PBMC samples were harvested pre-treatment and at the end of the first 6-week cycle from patients receiving standard of care chemotherapy or standard of care plus SU5416, a vascular endothelial growth factor (VEGF) receptor tyrosine kinase (RTK) inhibitor. Results from matched pairs of PBMC samples from 23 patients were queried for expression changes that consistently correlated with SU5416 administration. Thirteen transcripts met this selection criterion; six were further tested by quantitative RT-PCR analysis of 62 additional samples from this trial and a second SU5416 Phase III trial of similar design. This method confirmed four of these transcripts (CD24, lactoferrin, lipocalin 2, and MMP-9) as potential biomarkers of drug treatment. Discriminant analysis showed that expression profiles of these 4 transcripts could be used to classify patients by treatment arm in a predictive fashion. These results establish a foundation for the further exploration of peripheral blood cells as a surrogate system for biomarker analyses in clinical oncology studies

Expression profiling of blood samples from an SU5416 Phase III metastatic colorectal cancer clinical trial: a novel strategy for biomarker identification

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Smolich Beverly D

2003-02-01

Full Text Available Abstract Background Microarray-based gene expression profiling is a powerful approach for the identification of molecular biomarkers of disease, particularly in human cancers. Utility of this approach to measure responses to therapy is less well established, in part due to challenges in obtaining serial biopsies. Identification of suitable surrogate tissues will help minimize limitations imposed by those challenges. This study describes an approach used to identify gene expression changes that might serve as surrogate biomarkers of drug activity. Methods Expression profiling using microarrays was applied to peripheral blood mononuclear cell (PBMC samples obtained from patients with advanced colorectal cancer participating in a Phase III clinical trial. The PBMC samples were harvested pre-treatment and at the end of the first 6-week cycle from patients receiving standard of care chemotherapy or standard of care plus SU5416, a vascular endothelial growth factor (VEGF receptor tyrosine kinase (RTK inhibitor. Results from matched pairs of PBMC samples from 23 patients were queried for expression changes that consistently correlated with SU5416 administration. Results Thirteen transcripts met this selection criterion; six were further tested by quantitative RT-PCR analysis of 62 additional samples from this trial and a second SU5416 Phase III trial of similar design. This method confirmed four of these transcripts (CD24, lactoferrin, lipocalin 2, and MMP-9 as potential biomarkers of drug treatment. Discriminant analysis showed that expression profiles of these 4 transcripts could be used to classify patients by treatment arm in a predictive fashion. Conclusions These results establish a foundation for the further exploration of peripheral blood cells as a surrogate system for biomarker analyses in clinical oncology studies.

First Trimester Urine and Serum Metabolomics for Prediction of Preeclampsia and Gestational Hypertension: A Prospective Screening Study.

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Austdal, Marie; Tangerås, Line H; Skråstad, Ragnhild B; Salvesen, Kjell; Austgulen, Rigmor; Iversen, Ann-Charlotte; Bathen, Tone F

2015-09-08

Hypertensive disorders of pregnancy, including preeclampsia, are major contributors to maternal morbidity. The goal of this study was to evaluate the potential of metabolomics to predict preeclampsia and gestational hypertension from urine and serum samples in early pregnancy, and elucidate the metabolic changes related to the diseases. Metabolic profiles were obtained by nuclear magnetic resonance spectroscopy of serum and urine samples from 599 women at medium to high risk of preeclampsia (nulliparous or previous preeclampsia/gestational hypertension). Preeclampsia developed in 26 (4.3%) and gestational hypertension in 21 (3.5%) women. Multivariate analyses of the metabolic profiles were performed to establish prediction models for the hypertensive disorders individually and combined. Urinary metabolomic profiles predicted preeclampsia and gestational hypertension at 51.3% and 40% sensitivity, respectively, at 10% false positive rate, with hippurate as the most important metabolite for the prediction. Serum metabolomic profiles predicted preeclampsia and gestational hypertension at 15% and 33% sensitivity, respectively, with increased lipid levels and an atherogenic lipid profile as most important for the prediction. Combining maternal characteristics with the urinary hippurate/creatinine level improved the prediction rates of preeclampsia in a logistic regression model. The study indicates a potential future role of clinical importance for metabolomic analysis of urine in prediction of preeclampsia.

First Trimester Urine and Serum Metabolomics for Prediction of Preeclampsia and Gestational Hypertension: A Prospective Screening Study

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Marie Austdal

2015-09-01

Full Text Available Hypertensive disorders of pregnancy, including preeclampsia, are major contributors to maternal morbidity. The goal of this study was to evaluate the potential of metabolomics to predict preeclampsia and gestational hypertension from urine and serum samples in early pregnancy, and elucidate the metabolic changes related to the diseases. Metabolic profiles were obtained by nuclear magnetic resonance spectroscopy of serum and urine samples from 599 women at medium to high risk of preeclampsia (nulliparous or previous preeclampsia/gestational hypertension. Preeclampsia developed in 26 (4.3% and gestational hypertension in 21 (3.5% women. Multivariate analyses of the metabolic profiles were performed to establish prediction models for the hypertensive disorders individually and combined. Urinary metabolomic profiles predicted preeclampsia and gestational hypertension at 51.3% and 40% sensitivity, respectively, at 10% false positive rate, with hippurate as the most important metabolite for the prediction. Serum metabolomic profiles predicted preeclampsia and gestational hypertension at 15% and 33% sensitivity, respectively, with increased lipid levels and an atherogenic lipid profile as most important for the prediction. Combining maternal characteristics with the urinary hippurate/creatinine level improved the prediction rates of preeclampsia in a logistic regression model. The study indicates a potential future role of clinical importance for metabolomic analysis of urine in prediction of preeclampsia.

The predictive value of microbiological findings on teeth, internal and external implant portions in clinical decision making.

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Canullo, Luigi; Radovanović, Sandro; Delibasic, Boris; Blaya, Juan Antonio; Penarrocha, David; Rakic, Mia

2017-05-01

The primary aim of this study was to evaluate 23 pathogens associated with peri-implantitis at inner part of implant connections, in peri-implant and periodontal pockets between patients suffering peri-implantitis and participants with healthy peri-implant tissues; the secondary aim was to estimate the predictive value of microbiological profile in patients wearing dental implants using data mining methods. Fifty participants included in the present case─control study were scheduled for collection of plaque samples from the peri-implant pockets, internal connection, and periodontal pocket. Real-time polymerase chain reaction was performed to quantify 23 pathogens. Three predictive models were developed using C4.5 decision trees to estimate the predictive value of microbiological profile between three experimental sites. The final sample included 47 patients (22 healthy controls and 25 diseased cases), 90 implants (43 with healthy peri-implant tissues and 47 affected by peri-implantitis). Total and mean pathogen counts at inner portions of the implant connection, in peri-implant and periodontal pockets were generally increased in peri-implantitis patients when compared to healthy controls. The inner portion of the implant connection, the periodontal pocket and peri-implant pocket, respectively, presented a predictive value of microbiologic profile of 82.78%, 94.31%, and 97.5% of accuracy. This study showed that microbiological profile at all three experimental sites is differently characterized between patients suffering peri-implantitis and healthy controls. Data mining analysis identified Parvimonas micra as a highly accurate predictor of peri-implantitis when present in peri-implant pocket while this method generally seems to be promising for diagnosis of such complex infections. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Prognostic Impact of Array-based Genomic Profiles in Esophageal Squamous Cell Cancer

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Carneiro, Ana; Isinger, Anna; Karlsson, Anna; Johansson, Jan; Jönsson, Göran; Bendahl, Pär-Ola; Falkenback, Dan; Halvarsson, Britta; Nilbert, Mef

2008-01-01

Esophageal squamous cell carcinoma (ESCC) is a genetically complex tumor type and a major cause of cancer related mortality. Although distinct genetic alterations have been linked to ESCC development and prognosis, the genetic alterations have not gained clinical applicability. We applied array-based comparative genomic hybridization (aCGH) to obtain a whole genome copy number profile relevant for identifying deranged pathways and clinically applicable markers. A 32 k aCGH platform was used for high resolution mapping of copy number changes in 30 stage I-IV ESCC. Potential interdependent alterations and deranged pathways were identified and copy number changes were correlated to stage, differentiation and survival. Copy number alterations affected median 19% of the genome and included recurrent gains of chromosome regions 5p, 7p, 7q, 8q, 10q, 11q, 12p, 14q, 16p, 17p, 19p, 19q, and 20q and losses of 3p, 5q, 8p, 9p and 11q. High-level amplifications were observed in 30 regions and recurrently involved 7p11 (EGFR), 11q13 (MYEOV, CCND1, FGF4, FGF3, PPFIA, FAD, TMEM16A, CTTS and SHANK2) and 11q22 (PDFG). Gain of 7p22.3 predicted nodal metastases and gains of 1p36.32 and 19p13.3 independently predicted poor survival in multivariate analysis. aCGH profiling verified genetic complexity in ESCC and herein identified imbalances of multiple central tumorigenic pathways. Distinct gains correlate with clinicopathological variables and independently predict survival, suggesting clinical applicability of genomic profiling in ESCC

CSF Hypocretin-1 Levels and Clinical Profiles in Narcolepsy and Idiopathic CNS Hypersomnia in Norway

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Heier, Mona Skard; Evsiukova, Tatiana; Vilming, Steinar; Gjerstad, Michaela D.; Schrader, Harald; Gautvik, Kaare

2007-01-01

Objective: To evaluate the relationship between CSF hypocretin-1 levels and clinical profiles in narcolepsy and CNS hypersomnia in Norwegian patients. Method: CSF hypocretin-1 was measured by a sensitive radioimmunoassay in 47 patients with narcolepsy with cataplexy, 7 with narcolepsy without cataplexy, 10 with idiopathic CNS hypersomnia, and a control group. Results: Low hypocretin-1 values were found in 72% of the HLA DQB1*0602 positive patients with narcolepsy and cataplexy. Patients with low CSF hypocretin-1 levels reported more extensive muscular involvement during cataplectic attacks than patients with normal levels. Hypnagogic hallucinations and sleep paralysis occurred more frequently in patients with cataplexy than in the other patient groups, but with no correlation to hypocretin-1 levels. Conclusion: About three quarters of the HLA DQB1*0602 positive patients with narcolepsy and cataplexy had low CSF hypocretin-1 values, and appear to form a distinct clinical entity. Narcolepsy without cataplexy could not be distinguished from idiopathic CNS hypersomnia by clinical symptoms or biochemical findings. Citation: Heier MS; Evsiukova T; Vilming S; Gjerstad MD; Schrader H; Gautvik K. CSF hypocretin-1 levels and clinical profiles in narcolepsy and idiopathic CNS hypersomnia in norway. SLEEP 2007;30(8):969-973. PMID:17702265

Molecular prediction of adjuvant cisplatin efficacy in Non-Small Cell Lung Cancer (NSCLC)—validation in two independent cohorts

DEFF Research Database (Denmark)

Buhl, Ida Kappel; Santoni Rugiu, Eric; Ravn, Jesper

2018-01-01

Introduction Effective predictive biomarkers for selection of patients benefiting from adjuvant platinum-based chemotherapy in non-small cell lung cancer (NSCLC) are needed. Based on a previously validated methodology, molecular profiles of predicted sensitivity in two patient cohorts are presented....... Methods The profiles are correlations between in vitro sensitivity to cisplatin and vinorelbine and baseline mRNA expression of the 60 cell lines in the National Cancer Institute panel. An applied clinical samples filter focused the profiles to clinically relevant genes. The profiles were tested on 1......) univariate HR of 0.37 (95% CI:0.12–1.15, p = 0.09) in the ACV cohort and 2) univariate HR of 0.14 (95% CI:0.03–0.59, p = 0.0076) to three years. Functional analysis on the cisplatin profile revealed a group of upregulated genes related to RNA splicing as a part of DNA damage repair and apoptosis. Conclusions...

Predicted Interval Plots (PIPS): A Graphical Tool for Data Monitoring of Clinical Trials.

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Li, Lingling; Evans, Scott R; Uno, Hajime; Wei, L J

2009-11-01

Group sequential designs are often used in clinical trials to evaluate efficacy and/or futility. Many methods have been developed for different types of endpoints and scenarios. However, few of these methods convey information regarding effect sizes (e.g., treatment differences) and none uses prediction to convey information regarding potential effect size estimates and associated precision, with trial continuation. To address these limitations, Evans et al. (2007) proposed to use prediction and predicted intervals as a flexible and practical tool for quantitative monitoring of clinical trials. In this article, we reaffirm the importance and usefulness of this innovative approach and introduce a graphical summary, predicted interval plots (PIPS), to display the information obtained in the prediction process in a straightforward yet comprehensive manner. We outline the construction of PIPS and apply this method in two examples. The results and the interpretations of the PIPS are discussed.

Clinical profiles of stigma experiences, self-esteem and social relationships among people with schizophrenia, depressive, and bipolar disorders.

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Oliveira, Sandra E H; Esteves, Francisco; Carvalho, Helena

2015-09-30

Some mental illnesses and certain mental health care environments can be severely stigmatizing, which seems to be related to decreased self-esteem and a deterioration of the quality of social relationships for people with mental illness. This study aims to identify clinical profiles characterized by clinical diagnoses more strongly associated with the treatment settings and related to internalized stigma, self-esteem and satisfaction with social relationships. It also aimed to analyze associations between clinical profiles and socio-demographic indicators. Multiple correspondence analysis and cluster analysis were performed on a sample of 261 individuals with schizophrenia and mood disorders, from hospital-based and community-based facilities. MCA showed four distinct clinical profiles allowing a differentiation among levels of: internalized stigma, social relationship satisfaction and self-esteem. Overall, results revealed that internalized stigma remains a pervasive problem for some people with schizophrenia and mood disorders. Particularly, internalized stigma and social relationships dissatisfaction and associated socio-demographic indicators appear to be a risk factor for social isolation for individuals with schizophrenia, which may worsen the course of the disorder. Our findings highlight the importance to develop structured interventions aimed to reduce internalized stigma, and exclusion of those who suffer the loss of their social roles and networks. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Clinical and Biochemical Profiles according to Homeostasis Model Assessment-insulin Resistance (HOMA-IR) in Korean Women with Polycystic Ovary Syndrome.

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Lee, Da Eun; Park, Soo Yeon; Park, So Yun; Lee, Sa Ra; Chung, Hye Won; Jeong, Kyungah

2014-12-01

The aim of this study was to investigate the clinical and biochemical profiles according to homeostasis model assessment of insulin resistance (HOMA-IR) in Korean polycystic ovary syndrome (PCOS) patients. In 458 PCOS patients diagnosed by the Rotterdam European Society for Human Reproduction and Embryology (ESHRE) criteria, measurements of somatometry, blood test of hormones, glucose metabolic and lipid profiles, and transvaginal or transrectal ultrasonogram were carried out. HOMA-IR was then calculated and compared with the clinical and biochemical profiles related to PCOS. The patients were divided into 4 groups by quartiles of HOMA-IR. The mean level of HOMA-IR was 2.18 ± 1.73. Among the four groups separated according to HOMA-IR, body weight, body mass index (BMI), waist-to-hip ratio (WHR), triglyceride (TG), total cholesterol, high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, lipid accumulation product (LAP) index, high-sensitivity C-reactive protein (hs-CRP), Apoprotein B, free testosterone, and sex hormone binding globulin (SHBG) were found to be significantly different. TG, LAP index, glucose metabolic profiles, and hs-CRP were positively correlated with HOMA-IR after adjustment for BMI. Our results suggest that the clinical and biochemical profiles which are applicable as cardiovascular risk factors are highly correlated with HOMA-IR in Korean women with PCOS.

Clinical and Autoimmune Profile of Scleroderma Patients from Western India

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Vandana Pradhan

2014-01-01

Full Text Available Background. Systemic sclerosis (SSc, scleroderma is a disorder characterized by fibrosis of skin and visceral organs. Pathogenesis of scleroderma is complex and is incompletely understood as yet. Autoantibodies in SSc represent a serologic hallmark which have clinical relevance, with diagnostic and prognostic potential. Objectives. To study distribution of clinical manifestations and to identify frequency of autoantibodies among subtypes of scleroderma patients from Western India. Methodology. One hundred and ten scleroderma patients were clinically classified according to the American College of Rheumatology/European League Against Rheumatism (ACR/EULAR criteria. All these patients were in active stage of disease. Clinical manifestations were recorded at the time of presentation. Autoantibodies were tested in them by indirect immunofluorescence test and ELISA. Immunoglobulin levels were estimated by nephelometer. These parameters were further correlated with clinical presentation of the disease. Results. Scleroderma patients had M : F ratio of 1 : 10 where mean age at evaluation was 34.7±10.7 years and a mean disease duration was 43.7±35 months. Clinical subtypes showed that 45 patients (40.9% had diffused cutaneous (dcSSc lesions, 32 patients (29.1% had limited cutaneous (lcSSc lesions, and 33 patients (30% had other autoimmune overlaps. The overall frequency of ANA in SSc patients studied was 85.5%. The frequency of anti-Scl70, anti-centromere, anti-endothelial cell antibodies (AECA, and anti-keratinocyte antibodies (AKA was 62.7%, 22.7%, 30%, and 40.9%, respectively. Anti-Scl70 antibodies were significantly high (75.6% versus 46.9% among dcSSc patients (P<0.0115 whereas anti-centromere antibodies were significantly high (9% versus 38% among lcSSc patients when these two subtypes were compared (P<0.0044. Conclusion. This study supports that there are geoepidemiological variations among scleroderma patients for their clinical

Vacuum-assisted breast biopsy of suspected mammographic breast diagnoses: predictive value of serum proteomic profile

International Nuclear Information System (INIS)

Schittulli, F.; Ventrella, V.

2009-01-01

The project planned a series of actions oriented to different scientific questions: to complete the prospective collection of serum samples for serum proteomic analysis according to SOPs needed for the Italy-USA program; the identification of different mammographic signs for prediction of histological diagnosis of breast lesions through mammotone; the analysis of relationship between serum proteomic profile and micro histology characteristics of breast lesions

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.

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

KAUST Repository

Xie, Qing; Wang, Su; Zhu, Jia; Zhang, Xiangliang

2016-01-01

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.

Clinical judgement in the era of big data and predictive analytics.

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Chin-Yee, Benjamin; Upshur, Ross

2017-12-13

Clinical judgement is a central and longstanding issue in the philosophy of medicine which has generated significant interest over the past few decades. In this article, we explore different approaches to clinical judgement articulated in the literature, focusing in particular on data-driven, mathematical approaches which we contrast with narrative, virtue-based approaches to clinical reasoning. We discuss the tension between these different clinical epistemologies and further explore the implications of big data and machine learning for a philosophy of clinical judgement. We argue for a pluralistic, integrative approach, and demonstrate how narrative, virtue-based clinical reasoning will remain indispensable in an era of big data and predictive analytics. © 2017 John Wiley & Sons, Ltd.

Pretreatment data is highly predictive of liver chemistry signals in clinical trials

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Cai Z

2012-11-01

Full Text Available Zhaohui Cai,1,* Anders Bresell,2,* Mark H Steinberg,1 Debra G Silberg,1 Stephen T Furlong11AstraZeneca Pharmaceuticals, Wilmington, DE, USA; 2AstraZeneca Pharmaceuticals, Södertälje, Sweden*These authors contributed equally to this workPurpose: The goal of this retrospective analysis was to assess how well predictive models could determine which patients would develop liver chemistry signals during clinical trials based on their pretreatment (baseline information.Patients and methods: Based on data from 24 late-stage clinical trials, classification models were developed to predict liver chemistry outcomes using baseline information, which included demographics, medical history, concomitant medications, and baseline laboratory results.Results: Predictive models using baseline data predicted which patients would develop liver signals during the trials with average validation accuracy around 80%. Baseline levels of individual liver chemistry tests were most important for predicting their own elevations during the trials. High bilirubin levels at baseline were not uncommon and were associated with a high risk of developing biochemical Hy’s law cases. Baseline γ-glutamyltransferase (GGT level appeared to have some predictive value, but did not increase predictability beyond using established liver chemistry tests.Conclusion: It is possible to predict which patients are at a higher risk of developing liver chemistry signals using pretreatment (baseline data. Derived knowledge from such predictions may allow proactive and targeted risk management, and the type of analysis described here could help determine whether new biomarkers offer improved performance over established ones.Keywords: bilirubin, Hy’s Law, ALT, GGT, baseline, prediction

CLINICAL PROFILE OF ACUTE LOWER RESPIRATORY TRACT INFECTIONS IN CHILDREN BETWEEN 2MONTHS TO 5 YEARS

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Amitoj Singh Chhina

2015-08-01

Full Text Available BACKGROUND : Acute respiratory infections are a leading cause of morbidity and mortality in under - five children in developing countries. Hence, the present study was undertaken to study the various risk factors, clinical profile and outcome of acute lower respiratory tract infections (ALRI in children aged 2 month to 5 years. OBJECTIVE : clinical features, laborato ry assessment and morbidity and mortality pattern associated with acute lower respiratory tract infections in children aged 2 months to 5 years. METHODS: 100 ALRI cases fulfilling WHO criteria for pneumonia, in the age group of 2 month to 5 years were evaluated for clinical profile as per a predesigned proforma in a rural medical college. RESULTS : Of cases 61% were infants and remaining 39%12 - 60 months age group, males outnumbered females with sex ratio of 1.3;1. Elevated total leukocyte counts for age were observed in only 22% of cases, of these 3% were having pneumonia, 9% severe pneumonia and 10% very severe pneumonia. Significant association was found between leukocytosis and ALRI severity (p= 0.0001 Positive blood culture was obtained in 8% of cases and was significantly associated with ALRI severity (p=. 0.027. Among the ALRI cases, 84% required oxygen supplementation at any time during the hospital stay and 8% required mechanical ventilation. The mortality rate was 1%; with 99% of cases recovering and getting discharged uneventfully. CONCLUSION : Among the clinical variables, the signs and symptoms of ALRI as per the WHO ARI Control Programme were found in almost all cases. Regarding the laboratory profile, leukocytosis and blood culture positivity w ere observed in a small percentage, but significant association with ALRI severity was observed for both. Thus, clinical signs, and not invasive blood tests are a better diagnostic tools, though the latter may provide additional therapeutic and prognostic information in severe disease

Predicting clinical decline in progressive agrammatic aphasia and apraxia of speech.

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Whitwell, Jennifer L; Weigand, Stephen D; Duffy, Joseph R; Clark, Heather M; Strand, Edythe A; Machulda, Mary M; Spychalla, Anthony J; Senjem, Matthew L; Jack, Clifford R; Josephs, Keith A

2017-11-28

To determine whether baseline clinical and MRI features predict rate of clinical decline in patients with progressive apraxia of speech (AOS). Thirty-four patients with progressive AOS, with AOS either in isolation or in the presence of agrammatic aphasia, were followed up longitudinally for up to 4 visits, with clinical testing and MRI at each visit. Linear mixed-effects regression models including all visits (n = 94) were used to assess baseline clinical and MRI variables that predict rate of worsening of aphasia, motor speech, parkinsonism, and behavior. Clinical predictors included baseline severity and AOS type. MRI predictors included baseline frontal, premotor, motor, and striatal gray matter volumes. More severe parkinsonism at baseline was associated with faster rate of decline in parkinsonism. Patients with predominant sound distortions (AOS type 1) showed faster rates of decline in aphasia and motor speech, while patients with segmented speech (AOS type 2) showed faster rates of decline in parkinsonism. On MRI, we observed trends for fastest rates of decline in aphasia in patients with relatively small left, but preserved right, Broca area and precentral cortex. Bilateral reductions in lateral premotor cortex were associated with faster rates of decline of behavior. No associations were observed between volumes and decline in motor speech or parkinsonism. Rate of decline of each of the 4 clinical features assessed was associated with different baseline clinical and regional MRI predictors. Our findings could help improve prognostic estimates for these patients. © 2017 American Academy of Neurology.

A clinical prediction rule for detecting major depressive disorder in primary care : the PREDICT-NL study

NARCIS (Netherlands)

Zuithoff, Nicolaas P A; Vergouwe, Yvonne; King, Michael; Nazareth, Irwin; Hak, Eelko; Moons, Karel G M; Geerlings, Mirjam I

BACKGROUND: Major depressive disorder often remains unrecognized in primary care. OBJECTIVE: Development of a clinical prediction rule using easily obtainable predictors for major depressive disorder in primary care patients. METHODS: A total of 1046 subjects, aged 18-65 years, were included from

Ethnic variations regarding clinical profiles and symptom representation in prisoners with psychotic disorders.

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Denzel, A Dorina; Harte, Joke M; van den Bergh, Mattis; Scherder, Erik J A

2018-01-01

Black and minority ethnic (BME) groups are known to have higher prevalences of psychotic disorders and are over-represented in western penitentiaries and forensic psychiatric institutions. Research from regular mental healthcare settings suggests that they could show different and more severe psychotic symptoms. Aims To explore ethnic variations in severity of symptomatology of BME and non-BME detainees with psychotic disorders. In this study, 824 patients with psychotic disorders from seven different ethnic groups, imprisoned in a penitentiary psychiatric centre in the Netherlands, were compared on symptom severity and symptom representation using the BPRS-E clinical interview. Data were analysed by means of a multilevel analysis. BME patients with psychotic disorders are over-represented in forensic psychiatry, and symptom profiles of prisoners with psychotic disorders vary by ethnicity. Additionally, severity levels of overall psychopathology differ between ethnic groups: patients with an ethnic majority status show more severe levels of psychopathology compared with BME patients. There are differences in symptom severity and symptom profiles between BME patients and non-BME patients. Disregarding these differences could have an adverse effect on the outcome of the treatment. Possible explanations and clinical impact are discussed. Declaration of interest None.

Cannabis use in children with individualized risk profiles: Predicting the effect of universal prevention intervention.

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Miovský, Michal; Vonkova, Hana; Čablová, Lenka; Gabrhelík, Roman

2015-11-01

To study the effect of a universal prevention intervention targeting cannabis use in individual children with different risk profiles. A school-based randomized controlled prevention trial was conducted over a period of 33 months (n=1874 sixth-graders, baseline mean age 11.82). We used a two-level random intercept logistic model for panel data to predict the probabilities of cannabis use for each child. Specifically, we used eight risk/protective factors to characterize each child and then predicted two probabilities of cannabis use for each child if the child had the intervention or not. Using the two probabilities, we calculated the absolute and relative effect of the intervention for each child. According to the two probabilities, we also divided the sample into a low-risk group (the quarter of the children with the lowest probabilities), a moderate-risk group, and a high-risk group (the quarter of the children with the highest probabilities) and showed the average effect of the intervention on these groups. The differences between the intervention group and the control group were statistically significant in each risk group. The average predicted probabilities of cannabis use for a child from the low-risk group were 4.3% if the child had the intervention and 6.53% if no intervention was provided. The corresponding probabilities for a child from the moderate-risk group were 10.91% and 15.34% and for a child from the high-risk group 25.51% and 32.61%. School grades, thoughts of hurting oneself, and breaking the rules were the three most important factors distinguishing high-risk and low-risk children. We predicted the effect of the intervention on individual children, characterized by their risk/protective factors. The predicted absolute effect and relative effect of any intervention for any selected risk/protective profile of a given child may be utilized in both prevention practice and research. Copyright © 2015 Elsevier Ltd. All rights reserved.

Lipoprotein metabolism indicators improve cardiovascular risk prediction.

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Daniël B van Schalkwijk

Full Text Available BACKGROUND: Cardiovascular disease risk increases when lipoprotein metabolism is dysfunctional. We have developed a computational model able to derive indicators of lipoprotein production, lipolysis, and uptake processes from a single lipoprotein profile measurement. This is the first study to investigate whether lipoprotein metabolism indicators can improve cardiovascular risk prediction and therapy management. METHODS AND RESULTS: We calculated lipoprotein metabolism indicators for 1981 subjects (145 cases, 1836 controls from the Framingham Heart Study offspring cohort in which NMR lipoprotein profiles were measured. We applied a statistical learning algorithm using a support vector machine to select conventional risk factors and lipoprotein metabolism indicators that contributed to predicting risk for general cardiovascular disease. Risk prediction was quantified by the change in the Area-Under-the-ROC-Curve (ΔAUC and by risk reclassification (Net Reclassification Improvement (NRI and Integrated Discrimination Improvement (IDI. Two VLDL lipoprotein metabolism indicators (VLDLE and VLDLH improved cardiovascular risk prediction. We added these indicators to a multivariate model with the best performing conventional risk markers. Our method significantly improved both CVD prediction and risk reclassification. CONCLUSIONS: Two calculated VLDL metabolism indicators significantly improved cardiovascular risk prediction. These indicators may help to reduce prescription of unnecessary cholesterol-lowering medication, reducing costs and possible side-effects. For clinical application, further validation is required.

Molecular profiling in the treatment of colorectal cancer: focus on regorafenib

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Yan Y

2015-10-01

Full Text Available Yiyi Yan, Axel Grothey Department of Medical Oncology, Mayo Clinic, Rochester, MN, USA Abstract: Metastatic colorectal cancer (mCRC is a highly heterogeneous disease. Its treatment outcome has been significantly improved over the last decade with the incorporation of biological targeted therapies, including anti-EGFR antibodies, cetuximab and panitumumab, and VEGF inhibitors, bevacizumab, ramucirumab, and aflibercept. The identification of predictive biomarkers has further improved the survival by accurately selecting patients who are most likely to benefit from these treatments, such as RAS mutation profiling for EGFR antibodies. Regorafenib is a multikinase inhibitor currently used as late line therapy for mCRC. The molecular and genetic markers associated with regorafenib treatment response are yet to be characterized. Here, we review currently available clinical evidence of mCRC molecular profiling, such as RAS, BRAF, and MMR testing, and its role in targeted therapies with special focus on regorafenib treatment. Keywords: metastatic colon cancer, targeted therapy, molecular profiling, regorafenib 

Development of Castration Resistant Prostate Cancer can be Predicted by a DNA Hypermethylation Profile.

Science.gov (United States)

Angulo, Javier C; Andrés, Guillermo; Ashour, Nadia; Sánchez-Chapado, Manuel; López, Jose I; Ropero, Santiago

2016-03-01

Detection of DNA hypermethylation has emerged as a novel molecular biomarker for prostate cancer diagnosis and evaluation of prognosis. We sought to define whether a hypermethylation profile of patients with prostate cancer on androgen deprivation would predict castrate resistant prostate cancer. Genome-wide methylation analysis was performed using a methylation cancer panel in 10 normal prostates and 45 tumor samples from patients placed on androgen deprivation who were followed until castrate resistant disease developed. Castrate resistant disease was defined according to EAU (European Association of Urology) guideline criteria. Two pathologists reviewed the Gleason score, Ki-67 index and neuroendocrine differentiation. Hierarchical clustering analysis was performed and relationships with outcome were investigated by Cox regression and log rank analysis. We found 61 genes that were significantly hypermethylated in greater than 20% of tumors analyzed. Three clusters of patients were characterized by a DNA methylation profile, including 1 at risk for earlier castrate resistant disease (log rank p = 0.019) and specific mortality (log rank p = 0.002). Hypermethylation of ETV1 (HR 3.75) and ZNF215 (HR 2.89) predicted disease progression despite androgen deprivation. Hypermethylation of IRAK3 (HR 13.72), ZNF215 (HR 4.81) and SEPT9 (HR 7.64) were independent markers of prognosis. Prostate specific antigen greater than 25 ng/ml, Gleason pattern 5, Ki-67 index greater than 12% and metastasis at diagnosis also predicted a negative response to androgen deprivation. Study limitations included the retrospective design and limited number of cases. Epigenetic silencing of the mentioned genes could be novel molecular markers for the prognosis of advanced prostate cancer. It might predict castrate resistance during hormone deprivation and, thus, disease specific mortality. Gene hypermethylation is associated with disease progression in patients who receive hormone therapy. It

Latent profiles of nonresidential father engagement six years after divorce predict long-term offspring outcomes.

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Modecki, Kathryn Lynn; Hagan, Melissa J; Sandler, Irwin; Wolchik, Sharlene A

2015-01-01

This study examined profiles of nonresidential father engagement (i.e., support to the adolescent, contact frequency, remarriage, relocation, and interparental conflict) with their adolescent children (N = 156) 6 to 8 years following divorce and the prospective relation between these profiles and the psychosocial functioning of their offspring, 9 years later. Parental divorce occurred during late childhood to early adolescence; indicators of nonresidential father engagement were assessed during adolescence, and mental health problems and academic achievement of offspring were assessed 9 years later in young adulthood. Three profiles of father engagement were identified in our sample of mainly White, non-Hispanic divorced fathers: Moderate Involvement/Low Conflict, Low Involvement/Moderate Conflict, and High Involvement/High Conflict. Profiles differentially predicted offspring outcomes 9 years later when they were young adults, controlling for quality of the mother-adolescent relationship, mother's remarriage, mother's income, and gender, age, and offspring mental health problems in adolescence. Offspring of fathers characterized as Moderate Involvement/Low Conflict had the highest academic achievement and the lowest number of externalizing problems 9 years later compared to offspring whose fathers had profiles indicating either the highest or lowest levels of involvement but higher levels of conflict. Results indicate that greater paternal psychosocial support and more frequent father-adolescent contact do not outweigh the negative impact of interparental conflict on youth outcomes in the long term. Implications of findings for policy and intervention are discussed.

Clinical presentation at first heart failure hospitalization does not predict recurrent heart failure admission.

Science.gov (United States)

Kosztin, Annamaria; Costa, Jason; Moss, Arthur J; Biton, Yitschak; Nagy, Vivien Klaudia; Solomon, Scott D; Geller, Laszlo; McNitt, Scott; Polonsky, Bronislava; Merkely, Bela; Kutyifa, Valentina

2017-11-01

There are limited data on whether clinical presentation at first heart failure (HF) hospitalization predicts recurrent HF events. We aimed to assess predictors of recurrent HF hospitalizations in mild HF patients with an implantable cardioverter defibrillator or cardiac resynchronization therapy with defibrillator. Data on HF hospitalizations were prospectively collected for patients enrolled in MADIT-CRT. Predictors of recurrent HF hospitalization (HF2) after the first HF hospitalization were assessed using Cox proportional hazards regression models including baseline covariates and clinical presentation or management at first HF hospitalization. There were 193 patients with first HF hospitalization, and 156 patients with recurrent HF events. Recurrent HF rate after the first HF hospitalization was 43% at 1 year, 52% at 2 years, and 55% at 2.5 years. Clinical signs and symptoms, medical treatment, or clinical management of HF at first HF admission was not predictive for HF2. Baseline covariates predicting recurrent HF hospitalization included prior HF hospitalization (HR = 1.59, 95% CI: 1.15-2.20, P = 0.005), digitalis therapy (HR = 1.58, 95% CI: 1.13-2.20, P = 0.008), and left ventricular end-diastolic volume >240 mL (HR = 1.62, 95% CI: 1.17-2.25, P = 0.004). Recurrent HF events are frequent following the first HF hospitalization in patients with implanted implantable cardioverter defibrillator or cardiac resynchronization therapy with defibrillator. Neither clinical presentation nor clinical management during first HF admission was predictive of recurrent HF. Prior HF hospitalization, digitalis therapy, and left ventricular end-diastolic volume at enrolment predicted recurrent HF hospitalization, and these covariates could be used as surrogate markers for identifying a high-risk cohort. © 2017 The Authors. ESC Heart Failure published by John Wiley & Sons Ltd on behalf of the European Society of Cardiology.

Chronic Liver Diseases in Children: Clinical Profile and Histology.

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Dhole, Sachin Devidas; Kher, Archana S; Ghildiyal, Radha G; Tambse, Manjusha P

2015-07-01

The main aim of the study is to study the clinical profile of disorders of the liver and hepatobiliary system in paediatric patients and to correlate the histopathology findings of liver biopsy in chronic liver disease. Another aim being to assess the prognosis and to know the outcome and the effects of treatment in chronic liver diseases in paediatric age group. It was a prospective study, included the clinical profile of Chronic Liver Diseases (CLD) in children and the histopathological correlation. A total of 55 children were thoroughly investigated by doing relevant investigations and liver biopsy. A male predominance (60%) was noted with maximum incidence in the age group of 6-12 years. The incidence of CLD was 1.1% of total admissions. The most common presenting complaint was jaundice and abdominal distension. Hepatic encephalopathy was noted in 29% patients. Hepatomegaly was seen in 63% patients and spleenomegaly was seen in 60% patients. The incidence of cirrhosis on liver biopsy was 42% (23cases) in CLD patients. The most common diagnosis on histopathology was Wilson's disease (22%), followed by hepatitis and autoimmune hepatitis. The predominant spectrum of CLD was metabolic liver disease and also the predominant cause of death. As the incidence of CLD is quite low, a very high index of suspicion is required for its diagnosis. Some uncommon causes of CLD in children were seen in our study like neutral lipid storage disease, α1-Antitrypsin deficiency disease, lupus hepatitis, Alagille syndrome and Budd-Chiari syndrome. A patient of CLD with jaundice and hepatomegaly should be treated aggressively as those are the poor prognostic indicators of the disease. Hepatic encephalopathy and cirrhosis are also associated with poor outcome in patients with CLD. Liver biopsy histopathology by an expert and its correlation with laboratory investigations plays an important role in the diagnosis of CLD. The major cause of deaths in patients with CLD is due to end stage

A study of clinical and endoscopic profile of acute upper, gastrointestinal bleeding.

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Dewan, K R; Patowary, B S; Bhattarai, S

2014-01-01

Acute Upper Gastrointestinal Bleeding is a common medical emergency with a hospital mortality of approximately 10 percent. Higher mortality rate is associated with rebleeding. Rockall scoring system identifies patients at higher risk of rebleed and mortality. To study the clinical and endoscopic profile of acute upper gastrointestinal bleed to know the etiology, clinical presentation, severity of bleeding and outcome. This is a prospective, descriptive hospital based study conducted in Gastroenterology unit of College of Medical Sciences and Teaching Hospital, Bharatpur, Nepal from January 2012 to January 2013. It included 120 patients at random presenting with manifestations of upper gastrointestinal bleed. Their clinical and endoscopic profiles were studied. Rockall scoring system was used to assess their prognosis. Males were predominant (75%). Age ranged from 14 to 88 years, mean being 48.76+17.19. At presentation 86 patients (71.7%) had both hematemesis and malena, 24 patients (20%) had only malena and 10 patients (8.3%) had only hematemesis. Shock was detected in 21.7%, severe anemia and high blood urea were found in 34.2% and 38.3% respectively. Upper Gastrointestinal Bleeding endoscopy revealed esophageal varices (47.5%), peptic ulcer disease (33.3%), erosive mucosal disease (11.6%), Mallory Weiss tear (4.1%) and malignancy (3.3%). Median hospital stay was 7.28+3.18 days. Comorbidities were present in 43.3%. Eighty six patients (71.7%) had Rockall score 6. Five patients (4.2%) expired. Risk factors for death being massive rebleeeding, comorbidities and Rockall score >6. Acute Upper Gastrointestinal bleeding is a medical emergency. Mortality is associated with massive bleeding, comorbidities and Rockall score >6. Urgent, appropriate hospital management definitely helps to reduce morbidity and mortality.

Proteomic profiling in multiple sclerosis clinical courses reveals potential biomarkers of neurodegeneration.

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Maria Liguori

Full Text Available The aim of our project was to perform an exploratory analysis of the cerebrospinal fluid (CSF proteomic profiles of Multiple Sclerosis (MS patients, collected in different phases of their clinical course, in order to investigate the existence of peculiar profiles characterizing the different MS phenotypes. The study was carried out on 24 Clinically Isolated Syndrome (CIS, 16 Relapsing Remitting (RR MS, 11 Progressive (Pr MS patients. The CSF samples were analysed using the Matrix Assisted Laser Desorption Ionisation Time Of Flight (MALDI-TOF mass spectrometer in linear mode geometry and in delayed extraction mode (m/z range: 1000-25000 Da. Peak lists were imported for normalization and statistical analysis. CSF data were correlated with demographic, clinical and MRI parameters. The evaluation of MALDI-TOF spectra revealed 348 peak signals with relative intensity ≥ 1% in the study range. The peak intensity of the signals corresponding to Secretogranin II and Protein 7B2 were significantly upregulated in RRMS patients compared to PrMS (p<0.05, whereas the signals of Fibrinogen and Fibrinopeptide A were significantly downregulated in CIS compared to PrMS patients (p<0.04. Additionally, the intensity of the Tymosin β4 peak was the only signal to be significantly discriminated between the CIS and RRMS patients (p = 0.013. Although with caution due to the relatively small size of the study populations, and considering that not all the findings remained significant after adjustment for multiple comparisons, in our opinion this mass spectrometry evaluation confirms that this technique may provide useful and important information to improve our understanding of the complex pathogenesis of MS.

Gas chromatography/mass spectrometry based component profiling and quality prediction for Japanese sake.

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Mimura, Natsuki; Isogai, Atsuko; Iwashita, Kazuhiro; Bamba, Takeshi; Fukusaki, Eiichiro

2014-10-01

Sake is a Japanese traditional alcoholic beverage, which is produced by simultaneous saccharification and alcohol fermentation of polished and steamed rice by Aspergillus oryzae and Saccharomyces cerevisiae. About 300 compounds have been identified in sake, and the contribution of individual components to the sake flavor has been examined at the same time. However, only a few compounds could explain the characteristics alone and most of the attributes still remain unclear. The purpose of this study was to examine the relationship between the component profile and the attributes of sake. Gas chromatography coupled with mass spectrometry (GC/MS)-based non-targeted analysis was employed to obtain the low molecular weight component profile of Japanese sake including both nonvolatile and volatile compounds. Sake attributes and overall quality were assessed by analytical descriptive sensory test and the prediction model of the sensory score from the component profile was constructed by means of orthogonal projections to latent structures (OPLS) regression analysis. Our results showed that 12 sake attributes [ginjo-ka (aroma of premium ginjo sake), grassy/aldehydic odor, sweet aroma/caramel/burnt odor, sulfury odor, sour taste, umami, bitter taste, body, amakara (dryness), aftertaste, pungent/smoothness and appearance] and overall quality were accurately explained by component profiles. In addition, we were able to select statistically significant components according to variable importance on projection (VIP). Our methodology clarified the correlation between sake attribute and 200 low molecular components and presented the importance of each component thus, providing new insights to the flavor study of sake. Copyright © 2014 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Reduced model prediction of electron temperature profiles in microtearing-dominated National Spherical Torus eXperiment plasmas

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Kaye, S. M., E-mail: skaye@pppl.gov; Guttenfelder, W.; Bell, R. E.; Gerhardt, S. P.; LeBlanc, B. P.; Maingi, R. [Princeton Plasma Physics Laboratory, Princeton University, Princeton, New Jersey 08543 (United States)

2014-08-15

A representative H-mode discharge from the National Spherical Torus eXperiment is studied in detail to utilize it as a basis for a time-evolving prediction of the electron temperature profile using an appropriate reduced transport model. The time evolution of characteristic plasma variables such as β{sub e}, ν{sub e}{sup ∗}, the MHD α parameter, and the gradient scale lengths of T{sub e}, T{sub i}, and n{sub e} were examined as a prelude to performing linear gyrokinetic calculations to determine the fastest growing micro instability at various times and locations throughout the discharge. The inferences from the parameter evolutions and the linear stability calculations were consistent. Early in the discharge, when β{sub e} and ν{sub e}{sup ∗} were relatively low, ballooning parity modes were dominant. As time progressed and both β{sub e} and ν{sub e}{sup ∗} increased, microtearing became the dominant low-k{sub θ} mode, especially in the outer half of the plasma. There are instances in time and radius, however, where other modes, at higher-k{sub θ}, may, in addition to microtearing, be important for driving electron transport. Given these results, the Rebut-Lallia-Watkins (RLW) electron thermal diffusivity model, which is based on microtearing-induced transport, was used to predict the time-evolving electron temperature across most of the profile. The results indicate that RLW does a good job of predicting T{sub e} for times and locations where microtearing was determined to be important, but not as well when microtearing was predicted to be stable or subdominant.

Role of Transition Zone Index in the Prediction of Clinical Benign Prostatic Hyperplasia

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Muhammet Güzelsoy

2016-12-01

Full Text Available Objective The objective of this study was to determine the role of the transition zone (TZ index (TZI in the prediction of clinical benign prostatic hyperplasia (BPH in patients who underwent transurethral prostatectomy (TUR-P and to analyze the correlation between the amount of resected tissue and TZ volume (TZV. Materials and Methods Twenty-six male clinical BPH patients with obstructive complaints and 17 male benign prostate enlargement (BPE patients without any complaints were included in the study. Both the groups were over the age of 50. Clinical BPH patients underwent complete TUR-P. Statistical analysis was done with SPSS. Sensitivity, specificity, positive and negative predictive values of TZI-as a method of assessing clinical BPH-were measured. Results There was a statistically significant difference in prostate volume, uroflowmetry patterns, prostate-specific antigen (PSA, International prostate symptom score (IPSS, TZV and TZI between the two groups. There was a correlation between TZV and the amount of resected tissue (r=0.97; p0.40 has a high level of sensitivity and specificity in the prediction of clinical BPH among patients who undergo TUR-P due to obstructive symptoms and reported as BPH. There is a strong correlation between the amount of resected tissue and TZV. TZI is a valuable tool in diagnosis, and TZV gives valuable information about the patient to the surgeon.

Professional choice self-efficacy: predicting traits and personality profiles in high school students

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Rodolfo Augusto Matteo Ambiel

2016-01-01

Full Text Available Abstract This study aimed to verify the predictive capacity of the Big Five personality factors related to professional choice self-efficacy, as well as to draw a personality profile of people with diverse self-efficacy levels. There were 308 high school students participating, from three different grades (57.5 % women, from public and private schools, average 26.64 years of age. Students completed two instruments, Escala de Autoeficácia para Escolha Profissional (Professional Choice Self-efficacy Scale and Bateria Fatorial de Personalidade (Factorial Personality Battery. Results were obtained using multiple regression analysis, analysis of variance with repeated measures profile and Cohen’s d to estimate the effect size of differences. Results showed that Extraversion, Agreeableness and Conscientiousness were the main predictors of self-efficacy. Differences from medium to large were observed between extreme groups, and Extraversion and Conscientiousness were the personality factors that better distinguish people with low and high levels of self-efficacy. Theses results partially corroborate with the hypothesis. Results were discussed based on literature and on the practical implications of the results. New studies are proposed.

Epidemiological profile of colombian patients with rheumatoid arthritis in a specialized care clinic.

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Bautista-Molano, Wilson; Fernández-Avila, Daniel; Jiménez, Ruth; Cardozo, Rosa; Marín, Andrés; Soler, María Del Pilar; Gómez, Olga; Ruiz, Oscar

Few studies report the epidemiological profile of RA patients attending clinics for comprehensive care. We describe the clinical, socio-demographic characteristics and comorbidities of a cohort of patients with RA. Cross-sectional study in a cohort of patients according to ACR criteria/EULAR 2010 classification who have entered to the AR clinic since October 2012 until May 2014, referred from primary care. Frequencies for socio-demographic, comorbidity, state of disease activity, functional status, biomarkers and therapeutic modalities variables are described. In total, 1652 patients were included with a mean age of 58 years and a duration of 9 years. Rheumatoid factor was positive in 80% and anti-citrullinated peptide antibody in 63% of patients. In total, 43.6% of patients had comorbidities: Hypertension (20.4%), osteoporosis (17.3%) and Sjögren's syndrome (10.4%). Fifty percent of the patients had moderate and high disease activity level measured by DAS-28 score, and the mean HAQ score was 0.64 (DS 1.12). Seventy three percent of patients were treated with oral disease modified anti rheumatic treatment and 63.6% of them were with methotrexate. 42.4% of the patients were treated with glucocorticoids (mean dose 6.3mg). The epidemiological behavior of a group of RA patients is reported. The presence of comorbidities is significant affecting the risk of morbidity and mortality in these patients. The definition of the epidemiological profile of this population will allow the design of research questions to resolve outstanding problems in the clinical context of this pathology. Copyright © 2015 Elsevier España, S.L.U. and Sociedad Española de Reumatología y Colegio Mexicano de Reumatología. All rights reserved.

Mathematical model to predict temperature profile and air–fuel equivalence ratio of a downdraft gasification process

International Nuclear Information System (INIS)

Jaojaruek, Kitipong

2014-01-01

Highlights: • A mathematical model based on finite computation analysis was developed. • Model covers all zones of gasification process which will be useful to improve gasifier design. • Model can predict temperature profile, feedstock consumption rate and reaction equivalent ratio (ϕ). • Model-predicted parameters fitted well with experimental values. - Abstract: A mathematical model for the entire length of a downdraft gasifier was developed using thermochemical principles to derive energy and mass conversion equations. Analysis of heat transfer (conduction, convection and radiation) and chemical kinetic technique were applied to predict the temperature profile, feedstock consumption rate (FCR) and reaction equivalence ratio (RER). The model will be useful for designing gasifiers, estimating output gas composition and gas production rate (GPR). Implicit finite difference method solved the equations on the considered reactor length (50 cm) and diameter (20 cm). Conversion criteria for calculation of temperature and feedstock consumption rate were 1 × 10 −6 °C and 1 × 10 −6 kg/h, respectively. Experimental validation showed that model outputs fitted well with experimental data. Maximum deviation between model and experimental data of temperature, FCR and RER were 52 °C at combustion temperature 663 °C, 0.7 kg/h at the rate 8.1 kg/h and 0.03 at the RER 0.42, respectively. Experimental uncertainty of temperature, FCR and RER were 24.4 °C, 0.71 kg/h and 0.04, respectively, on confidence level of 95%

Extracting the normal lung dose–response curve from clinical DVH data: a possible role for low dose hyper-radiosensitivity, increased radioresistance

International Nuclear Information System (INIS)

Gordon, J J; Snyder, K; Zhong, H; Barton, K; Sun, Z; Chetty, I J; Matuszak, M; Ten Haken, R K

2015-01-01

In conventionally fractionated radiation therapy for lung cancer, radiation pneumonitis’ (RP) dependence on the normal lung dose-volume histogram (DVH) is not well understood. Complication models alternatively make RP a function of a summary statistic, such as mean lung dose (MLD). This work searches over damage profiles, which quantify sub-volume damage as a function of dose. Profiles that achieve best RP predictive accuracy on a clinical dataset are hypothesized to approximate DVH dependence.Step function damage rate profiles R(D) are generated, having discrete steps at several dose points. A range of profiles is sampled by varying the step heights and dose point locations. Normal lung damage is the integral of R(D) with the cumulative DVH. Each profile is used in conjunction with a damage cutoff to predict grade 2 plus (G2+) RP for DVHs from a University of Michigan clinical trial dataset consisting of 89 CFRT patients, of which 17 were diagnosed with G2+ RP.Optimal profiles achieve a modest increase in predictive accuracy—erroneous RP predictions are reduced from 11 (using MLD) to 8. A novel result is that optimal profiles have a similar distinctive shape: enhanced damage contribution from low doses (<20 Gy), a flat contribution from doses in the range ∼20–40 Gy, then a further enhanced contribution from doses above 40 Gy. These features resemble the hyper-radiosensitivity / increased radioresistance (HRS/IRR) observed in some cell survival curves, which can be modeled using Joiner’s induced repair model.A novel search strategy is employed, which has the potential to estimate RP dependence on the normal lung DVH. When applied to a clinical dataset, identified profiles share a characteristic shape, which resembles HRS/IRR. This suggests that normal lung may have enhanced sensitivity to low doses, and that this sensitivity can affect RP risk. (paper)

External validation of a biomarker and clinical prediction model for hospital mortality in acute respiratory distress syndrome.

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Zhao, Zhiguo; Wickersham, Nancy; Kangelaris, Kirsten N; May, Addison K; Bernard, Gordon R; Matthay, Michael A; Calfee, Carolyn S; Koyama, Tatsuki; Ware, Lorraine B

2017-08-01

Mortality prediction in ARDS is important for prognostication and risk stratification. However, no prediction models have been independently validated. A combination of two biomarkers with age and APACHE III was superior in predicting mortality in the NHLBI ARDSNet ALVEOLI trial. We validated this prediction tool in two clinical trials and an observational cohort. The validation cohorts included 849 patients from the NHLBI ARDSNet Fluid and Catheter Treatment Trial (FACTT), 144 patients from a clinical trial of sivelestat for ARDS (STRIVE), and 545 ARDS patients from the VALID observational cohort study. To evaluate the performance of the prediction model, the area under the receiver operating characteristic curve (AUC), model discrimination, and calibration were assessed, and recalibration methods were applied. The biomarker/clinical prediction model performed well in all cohorts. Performance was better in the clinical trials with an AUC of 0.74 (95% CI 0.70-0.79) in FACTT, compared to 0.72 (95% CI 0.67-0.77) in VALID, a more heterogeneous observational cohort. The AUC was 0.73 (95% CI 0.70-0.76) when FACTT and VALID were combined. We validated a mortality prediction model for ARDS that includes age, APACHE III, surfactant protein D, and interleukin-8 in a variety of clinical settings. Although the model performance as measured by AUC was lower than in the original model derivation cohort, the biomarker/clinical model still performed well and may be useful for risk assessment for clinical trial enrollment, an issue of increasing importance as ARDS mortality declines, and better methods are needed for selection of the most severely ill patients for inclusion.

The Predictive Value of Ultrasound Learning Curves Across Simulated and Clinical Settings

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Madsen, Mette E; Nørgaard, Lone N; Tabor, Ann

2017-01-01

OBJECTIVES: The aim of the study was to explore whether learning curves on a virtual-reality (VR) sonographic simulator can be used to predict subsequent learning curves on a physical mannequin and learning curves during clinical training. METHODS: Twenty midwives completed a simulation-based tra......OBJECTIVES: The aim of the study was to explore whether learning curves on a virtual-reality (VR) sonographic simulator can be used to predict subsequent learning curves on a physical mannequin and learning curves during clinical training. METHODS: Twenty midwives completed a simulation......-based training program in transvaginal sonography. The training was conducted on a VR simulator as well as on a physical mannequin. A subgroup of 6 participants underwent subsequent clinical training. During each of the 3 steps, the participants' performance was assessed using instruments with established...... settings. RESULTS: A good correlation was found between time needed to achieve predefined performance levels on the VR simulator and the physical mannequin (Pearson correlation coefficient .78; P VR simulator correlated well to the clinical performance scores (Pearson...

Polymorphism in clinical immunology – From HLA typing to immunogenetic profiling

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Wang Ena

2003-11-01

Full Text Available Abstract The pathology of humans, in contrast to that of inbred laboratory animals faces the challenge of diversity addressed in genetic terms as polymorphism. Thus, unsurprisingly, treatment modalities that successfully can be applied to carefully-selected pre-clinical models only sporadically succeed in the clinical arena. Indeed, pre-fabricated experimental models purposefully avoid the basic essence of human pathology: the uncontrollable complexity of disease heterogeneity and the intrinsic diversity of human beings. Far from pontificating on this obvious point, this review presents emerging evidence that the study of complex system such as the cytokine network is further complicated by inter-individual differences dictated by increasingly recognized polymorphisms. Polymorphism appears widespread among genes of the immune system possibly resulting from an evolutionary adaptation of the organism facing an ever evolving environment. We will refer to this high variability of immune-related genes as immune polymorphism. In this review we will briefly highlight the possible clinical relevance of immune polymorphism and suggest a change in the approach to the study of human pathology, from the targeted study of individual systems to a broader view of the organism as a whole through immunogenetic profiling.

Correlation between MRI and clinical profiles of periventricular leukomalacia in children

International Nuclear Information System (INIS)

Fan Xiaoying; Xiao Jiangxi; Jiang Xuexiang; Tang Guangjian

2003-01-01

Objective: To study the relationship between MRI and clinical profiles of periventricular leukomalacia (PVL) in children. Methods: The clinical and MRI findings in 34 cases with PVL were retrospectively analyzed. Results: (1) Periventricular hyperintensity on T 2 WI was more prominent in the preterm-group than that in the term-group, and P value was 0.000; (2) Cortical lesion and subcortical leukomalacia was seen in 9 of 19 cases in the children with PVL born at term, but detected in only 1/15 in the preterm-group. P value was 0.020; (3) Seizure was common in term children. P value was 0.036; (4) The degree of reduction of periventricular white matter correlated with motor impairment and mental retardation in all children, and P values were 0.002 and 0.000, respectively. The thinning of the corpus callosum also correlated with mental retardation and P value was 0.012. The degree of reduction of periventricular white matter correlated with visual impairment in preterm-group. Conclusion: The end-stage PVL can been clearly displayed by MRI, and gestational age and clinical manifestation were closely related to the findings of MRI

Molecular markers predicting radiotherapy response: Report and recommendations from an International Atomic Energy Agency technical meeting

International Nuclear Information System (INIS)

West, Catharine M.L.; McKay, Michael J.; Hoelscher, Tobias; Baumann, Michael; Stratford, Ian J.; Bristow, Robert G.; Iwakawa, Mayumi; Imai, Takashi; Zingde, Surekha M.; Anscher, Mitchell S.; Bourhis, Jean; Begg, Adrian C.; Haustermans, Karin; Bentzen, Soren M.; Hendry, Jolyon H.

2005-01-01

Purpose: There is increasing interest in radiogenomics and the characterization of molecular profiles that predict normal tissue and tumor radioresponse. A meeting in Amsterdam was organized by the International Atomic Energy Agency to discuss this topic on an international basis. Methods and Materials: This report is not completely exhaustive, but highlights some of the ongoing studies and new initiatives being carried out worldwide in the banking of tumor and normal tissue samples underpinning the development of molecular marker profiles for predicting patient response to radiotherapy. It is generally considered that these profiles will more accurately define individual or group radiosensitivities compared with the nondefinitive findings from the previous era of cellular-based techniques. However, so far there are only a few robust reports of molecular markers predicting normal tissue or tumor response. Results: Many centers in different countries have initiated tissue and tumor banks to store samples from clinical trials for future molecular profiling analysis, to identify profiles that predict for radiotherapy response. The European Society for Therapeutic Radiology and Oncology GENEtic pathways for the Prediction of the effects of Irradiation (GENEPI) project, to store, document, and analyze sample characteristics vs. response, is the most comprehensive in this regard. Conclusions: The next 5-10 years are likely to see the results of these and other correlative studies, and promising associations of profiles with response should be validated in larger definitive trials

Semi-empirical procedures for correcting detector size effect on clinical MV x-ray beam profiles

International Nuclear Information System (INIS)

Sahoo, Narayan; Kazi, Abdul M.; Hoffman, Mark

2008-01-01

profiles of clinical high-energy x-ray beams.

Blood antioxidant profile and lipid peroxides in dairy cows with clinical mastitis

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Rajesh Rathore

2013-10-01

Full Text Available Aim: To evaluate blood antioxidant profile and lipid peroxides in dairy cows with clinical mastitis. Materials and Methods: Twelve cases of clinical mastitis in cross-bred cows were selected based on physical examination of udder and milk, California Mastitis Test (CMT, Somatic Cell Count (SCC and confirmation by bacteriological examination of milk and requisite biochemical tests. Twelve lactating cows showing negative CMT reaction and SCC <2x105 cells/ml were considered as healthy control. Antioxidant parameters measured in blood were superoxide dismutase (SOD, catalase activities and reduced glutathione (GSH concentration. Erythrocytic lipid peroxidation (LPO was measured in terms of malondialdehyde (MDA production. Results: Significant (P<0.05 decrease in blood SOD and catalase activities, GSH concentration and an increase in erythrocytic lipid peroxides was observed in cows with clinical mastitis. Conclusion: It is concluded that there is a compromise in antioxidant defense of the body in dairy cows with clinical mastitis resulting in oxidative damage, therefore, necessitate the use of antioxidants and other protective compounds along with conventional therapy for mastitis control. [Vet World 2013; 6(5.000: 271-273

Optimized high-throughput microRNA expression profiling provides novel biomarker assessment of clinical prostate and breast cancer biopsies

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Fedele Vita

2006-06-01

Full Text Available Abstract Background Recent studies indicate that microRNAs (miRNAs are mechanistically involved in the development of various human malignancies, suggesting that they represent a promising new class of cancer biomarkers. However, previously reported methods for measuring miRNA expression consume large amounts of tissue, prohibiting high-throughput miRNA profiling from typically small clinical samples such as excision or core needle biopsies of breast or prostate cancer. Here we describe a novel combination of linear amplification and labeling of miRNA for highly sensitive expression microarray profiling requiring only picogram quantities of purified microRNA. Results Comparison of microarray and qRT-PCR measured miRNA levels from two different prostate cancer cell lines showed concordance between the two platforms (Pearson correlation R2 = 0.81; and extension of the amplification, labeling and microarray platform was successfully demonstrated using clinical core and excision biopsy samples from breast and prostate cancer patients. Unsupervised clustering analysis of the prostate biopsy microarrays separated advanced and metastatic prostate cancers from pooled normal prostatic samples and from a non-malignant precursor lesion. Unsupervised clustering of the breast cancer microarrays significantly distinguished ErbB2-positive/ER-negative, ErbB2-positive/ER-positive, and ErbB2-negative/ER-positive breast cancer phenotypes (Fisher exact test, p = 0.03; as well, supervised analysis of these microarray profiles identified distinct miRNA subsets distinguishing ErbB2-positive from ErbB2-negative and ER-positive from ER-negative breast cancers, independent of other clinically important parameters (patient age; tumor size, node status and proliferation index. Conclusion In sum, these findings demonstrate that optimized high-throughput microRNA expression profiling offers novel biomarker identification from typically small clinical samples such as breast

Can we rely on predicted basal metabolic rate in chronic pancreatitis outpatients?

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Olesen, Søren Schou; Holst, Mette; Køhler, Marianne; Drewes, Asbjørn Mohr; Rasmussen, Henrik Højgaard

2015-04-01

Malnutrition is a common complication to chronic pancreatitis (CP) and many patients need nutritional support. An accurate estimation of the basal metabolic rate (BMR) is essential when appropriate nutritional support is to be initiated, but in the clinical settings BMR is cumbersome to measure. We therefore investigated whether BMR can be reliable predicted from a standard formula (the Harris-Benedict equation) in CP outpatients. Twenty-eight patients with clinical stable CP and no current alcohol abuse were enrolled. Patients were stratified according to nutritional risk using the Nutrition Risk Screening 2002 system. Body composition was estimated using bioelectrical impedance. BMR was measured using indirect calorimetry and predicted using the Harris-Benedict equation based on anthropometric data. The average predicted BMR was 1371 ± 216 kcal/day compared to an average measured BMR of 1399 ± 231 kcal/day (P = 0.4). The corresponding limits of agreement were -347 to 290 kcal/day. Twenty-two patients (79%) had a measured BMR between 85 and 115% of the predicted BMR. When analysing patients stratified according to nutritional risk profiles, no differences between predicted and measured BMR were evident for any of the risk profile subgroups (all P > 0.2). The BMR was correlated to fat free mass determined by bioelectrical impedance (rho = 0.55; P = 0.003), while no effect modification was seen from nutritional risk stratification in a linear regression analysis (P = 0.4). The Harris-Benedict equation reliable predicts the measured BMR in four out of five clinical stable CP outpatients with no current alcohol abuse. Copyright © 2015 European Society for Clinical Nutrition and Metabolism. Published by Elsevier Ltd. All rights reserved.

In silico modeling predicts drug sensitivity of patient-derived cancer cells.

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Pingle, Sandeep C; Sultana, Zeba; Pastorino, Sandra; Jiang, Pengfei; Mukthavaram, Rajesh; Chao, Ying; Bharati, Ila Sri; Nomura, Natsuko; Makale, Milan; Abbasi, Taher; Kapoor, Shweta; Kumar, Ansu; Usmani, Shahabuddin; Agrawal, Ashish; Vali, Shireen; Kesari, Santosh

2014-05-21

Glioblastoma (GBM) is an aggressive disease associated with poor survival. It is essential to account for the complexity of GBM biology to improve diagnostic and therapeutic strategies. This complexity is best represented by the increasing amounts of profiling ("omics") data available due to advances in biotechnology. The challenge of integrating these vast genomic and proteomic data can be addressed by a comprehensive systems modeling approach. Here, we present an in silico model, where we simulate GBM tumor cells using genomic profiling data. We use this in silico tumor model to predict responses of cancer cells to targeted drugs. Initially, we probed the results from a recent hypothesis-independent, empirical study by Garnett and co-workers that analyzed the sensitivity of hundreds of profiled cancer cell lines to 130 different anticancer agents. We then used the tumor model to predict sensitivity of patient-derived GBM cell lines to different targeted therapeutic agents. Among the drug-mutation associations reported in the Garnett study, our in silico model accurately predicted ~85% of the associations. While testing the model in a prospective manner using simulations of patient-derived GBM cell lines, we compared our simulation predictions with experimental data using the same cells in vitro. This analysis yielded a ~75% agreement of in silico drug sensitivity with in vitro experimental findings. These results demonstrate a strong predictability of our simulation approach using the in silico tumor model presented here. Our ultimate goal is to use this model to stratify patients for clinical trials. By accurately predicting responses of cancer cells to targeted agents a priori, this in silico tumor model provides an innovative approach to personalizing therapy and promises to improve clinical management of cancer.

Clinical prediction models for bronchopulmonary dysplasia: a systematic review and external validation study

NARCIS (Netherlands)

Onland, Wes; Debray, Thomas P.; Laughon, Matthew M.; Miedema, Martijn; Cools, Filip; Askie, Lisa M.; Asselin, Jeanette M.; Calvert, Sandra A.; Courtney, Sherry E.; Dani, Carlo; Durand, David J.; Marlow, Neil; Peacock, Janet L.; Pillow, J. Jane; Soll, Roger F.; Thome, Ulrich H.; Truffert, Patrick; Schreiber, Michael D.; van Reempts, Patrick; Vendettuoli, Valentina; Vento, Giovanni; van Kaam, Anton H.; Moons, Karel G.; Offringa, Martin

2013-01-01

Bronchopulmonary dysplasia (BPD) is a common complication of preterm birth. Very different models using clinical parameters at an early postnatal age to predict BPD have been developed with little extensive quantitative validation. The objective of this study is to review and validate clinical

Evaluating Integrative Cancer Clinics With the Claim Assessment Profile: An Example With the InspireHealth Clinic.

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Hilton, Lara; Elfenbaum, Pamela; Jain, Shamini; Sprengel, Meredith; Jonas, Wayne B

2018-03-01

The evaluation of freestanding integrative cancer clinical programs is challenging and is rarely done. We have developed an approach called the Claim Assessment Profile (CAP) to identify whether evaluation of a practice is justified, feasible, and likely to provide useful information. A CAP was performed in order to (1) clarify the healing claims at InspireHealth, an integrative oncology treatment program, by defining the most important impacts on its clients; (2) gather information about current research capacity at the clinic; and (3) create a program theory and path model for use in prospective research. This case study design incorporates methods from a variety of rapid assessment approaches. Procedures included site visits to observe the program, structured qualitative interviews with 26 providers and staff, surveys to capture descriptive data about the program, and observational data on program implementation. The InspireHealth program is a well-established, multi-site, thriving integrative oncology clinical practice that focuses on patient support, motivation, and health behavior engagement. It delivers patient-centered care via a standardized treatment protocol. There arehigh levels of research interest from staff and resources by which to conduct research. This analysis provides the primary descriptive and claims clarification of an integrative oncology treatment program, an evaluation readiness report, a detailed logic model explicating program theory, and a clinical outcomes path model for conducting prospective research. Prospective evaluation of this program would be feasible and valuable, adding to our knowledge base of integrative cancer therapies.

Prediction consistency and clinical presentations of breast cancer molecular subtypes for Han Chinese population

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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

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.

Prediction of Driving Safety in Individuals with Homonymous Hemianopia and Quadrantanopia from Clinical Neuroimaging

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Michael S. Vaphiades

2014-01-01

Full Text Available Background. This study aimed to determine whether it is possible to predict driving safety of individuals with homonymous hemianopia or quadrantanopia based upon a clinical review of neuroimages that are routinely available in clinical practice. Methods. Two experienced neuroophthalmologists viewed a summary report of the CT/MRI scans of 16 participants with homonymous hemianopic or quadrantanopic field defects which indicated the site and extent of the lesion and they made predictions regarding whether participants would be safe/unsafe to drive. Driving safety was independently defined at the time of the study using state-recorded motor vehicle crashes (all crashes and at-fault for the previous 5 years and ratings of driving safety determined through a standardized on-road driving assessment by a certified driving rehabilitation specialist. Results. The ability to predict driving safety was highly variable regardless of the driving safety measure, ranging from 31% to 63% (kappa levels ranged from −0.29 to 0.04. The level of agreement between the neuroophthalmologists was only fair (kappa = 0.28. Conclusions. Clinical evaluation of summary reports of currently available neuroimages by neuroophthalmologists is not predictive of driving safety. Future research should be directed at identifying and/or developing alternative tests or strategies to better enable clinicians to make these predictions.

Prediction of driving safety in individuals with homonymous hemianopia and quadrantanopia from clinical neuroimaging.

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Vaphiades, Michael S; Kline, Lanning B; McGwin, Gerald; Owsley, Cynthia; Shah, Ritu; Wood, Joanne M

2014-01-01

Background. This study aimed to determine whether it is possible to predict driving safety of individuals with homonymous hemianopia or quadrantanopia based upon a clinical review of neuroimages that are routinely available in clinical practice. Methods. Two experienced neuroophthalmologists viewed a summary report of the CT/MRI scans of 16 participants with homonymous hemianopic or quadrantanopic field defects which indicated the site and extent of the lesion and they made predictions regarding whether participants would be safe/unsafe to drive. Driving safety was independently defined at the time of the study using state-recorded motor vehicle crashes (all crashes and at-fault) for the previous 5 years and ratings of driving safety determined through a standardized on-road driving assessment by a certified driving rehabilitation specialist. Results. The ability to predict driving safety was highly variable regardless of the driving safety measure, ranging from 31% to 63% (kappa levels ranged from -0.29 to 0.04). The level of agreement between the neuroophthalmologists was only fair (kappa = 0.28). Conclusions. Clinical evaluation of summary reports of currently available neuroimages by neuroophthalmologists is not predictive of driving safety. Future research should be directed at identifying and/or developing alternative tests or strategies to better enable clinicians to make these predictions.

Islet oxygen consumption rate (OCR) dose predicts insulin independence for first clinical islet allotransplants

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Kitzmann, JP; O’Gorman, D; Kin, T; Gruessner, AC; Senior, P; Imes, S; Gruessner, RW; Shapiro, AMJ; Papas, KK

2014-01-01

Human islet allotransplant (ITx) for the treatment of type 1 diabetes is in phase III clinical registration trials in the US and standard of care in several other countries. Current islet product release criteria include viability based on cell membrane integrity stains, glucose stimulated insulin release (GSIR), and islet equivalent (IE) dose based on counts. However, only a fraction of patients transplanted with islets that meet or exceed these release criteria become insulin independent following one transplant. Measurements of islet oxygen consumption rate (OCR) have been reported as highly predictive of transplant outcome in many models. In this paper we report on the assessment of clinical islet allograft preparations using islet oxygen consumption rate (OCR) dose (or viable IE dose) and current product release assays in a series of 13 first transplant recipients. The predictive capability of each assay was examined and successful graft function was defined as 100% insulin independence within 45 days post-transplant. Results showed that OCR dose was most predictive of CTO. IE dose was also highly predictive, while GSIR and membrane integrity stains were not. In conclusion, OCR dose can predict CTO with high specificity and sensitivity and is a useful tool for evaluating islet preparations prior to clinical ITx. PMID:25131089

Kozeny-Carman permeability relationship with disintegration process predicted from early dissolution profiles of immediate release tablets.

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Kumari, Parveen; Rathi, Pooja; Kumar, Virender; Lal, Jatin; Kaur, Harmeet; Singh, Jasbir

2017-07-01

This study was oriented toward the disintegration profiling of the diclofenac sodium (DS) immediate-release (IR) tablets and development of its relationship with medium permeability k perm based on Kozeny-Carman equation. Batches (L1-L9) of DS IR tablets with different porosities and specific surface area were prepared at different compression forces and evaluated for porosity, in vitro dissolution and particle-size analysis of the disintegrated mass. The k perm was calculated from porosities and specific surface area, and disintegration profiles were predicted from the dissolution profiles of IR tablets by stripping/residual method. The disintegration profiles were subjected to exponential regression to find out the respective disintegration equations and rate constants k d . Batches L1 and L2 showed the fastest disintegration rates as evident from their bi-exponential equations while the rest of the batches L3-L9 exhibited the first order or mono-exponential disintegration kinetics. The 95% confidence interval (CI 95% ) revealed significant differences between k d values of different batches except L4 and L6. Similar results were also spotted for dissolution profiles of IR tablets by similarity (f 2 ) test. The final relationship between k d and k perm was found to be hyperbolic, signifying the initial effect of k perm on the disintegration rate. The results showed that disintegration profiling is possible because a relationship exists between k d and k perm . The later being relatable with porosity and specific surface area can be determined by nondestructive tests.

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

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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; Loganathan, Gopalakrishnan; Colton, Clark K; Koulmanda, Maria; Weir, Gordon C; Wilhelm, Josh J; Qian, Dajun; Niland, Joyce C; Hering, Bernhard J

2015-01-01

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.

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

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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.

Magnetic resonance imaging of injuries to the ankle joint: can it predict clinical outcome?

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Zanetti, M; De Simoni, C; Wetz, H H; Zollinger, H; Hodler, J

1997-02-01

To predict clinical outcome after ankle sprains on the basis of magnetic resonance (MR) findings. Twenty-nine consecutive patients (mean age 32.9 years, range 13-60 years) were examined clinically and with MR imaging both after trauma and following standardized conservative therapy. Various MR abnormalities were related to a clinical outcome score. There was a tendency for a better clinical outcome in partial, rather than complete, tears of the anterior talofibular ligament and when there was no fluid within the peroneal tendon sheath at the initial MR examination (P = 0.092 for either abnormality). A number of other MR features did not significantly influence clinical outcome, including the presence of a calcaneofibular ligament lesion and a bone bruise of the talar dome. Clinical outcome after ankle sprain cannot consistently be predicted by MR imaging, although MR imaging may be more accurate when the anterior talofibular ligament is only partially torn and there are no signs of injury to the peroneal tendon sheath.

Does Enjoying Friendship Help or Impede Academic Achievement? Academic and Social Intrinsic Value Profiles Predict Academic Achievement

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Seo, Eunjin; Lee, You-kyung

2018-01-01

We examine the intrinsic value students placed on schoolwork (i.e. academic intrinsic value) and social relationships (i.e. social intrinsic value). We then look at how these values predict middle and high school achievement. To do this, we came up with four profiles based on cluster analyses of 6,562 South Korean middle school students. The four…

Clinical and etiological profile of refractory rickets from western India.

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Joshi, Rajesh R; Patil, Shailesh; Rao, Sudha

2013-07-01

To present clinical and etiological profile of refractory rickets from Mumbai. Case records of 36 patients presenting over 2½ y with refractory rickets were evaluated with respect to clinical presentation, biochemical, radiological features and where needed, ophthalmological examination, ultrasonography and special tests on blood and urine. Twenty three (63 %) patients had renal tubular acidosis (RTA)-distal RTA in 20 and proximal RTA in 3 patients; 5 (14 %) had vitamin D dependent rickets (VDDR I in 2 and VDDR II in 3 patients), 4 (11 %) had chronic renal failure (CRF) and 2 each (6 %) had hypophosphatemic rickets and chronic liver disease as cause of refractory rickets. A significant proportion of patients with RTA and VDDR showed skeletal changes of rickets in the first 2 y of life, while those with hypophosphatemic rickets presented later. Patients with hypophosphatemic rickets had predominant involvement of lower limbs, normal blood calcium and PTH levels and phosphorus leak in urine. All patients with RTA presented with failure to thrive, polyuria and marked rickets; blood alkaline phosphatase levels being normal in almost 50 % patients. Three (75 %) patients with rickets due to CRF had GFR rickets inspite of taking high dose of vitamin D orally. Refractory rickets is a disorder of multiple etiologies; a good history and clinical examination supplemented with appropriate investigations helps to determine its cause.

Effectiveness of gene expression profiling for response prediction of rectal cancer to preoperative radiotherapy

International Nuclear Information System (INIS)

Ojima, Eiki; Inoue, Yasuhiro; Miki, Chikao; Kusunoki, Masato; Mori, Masaki

2007-01-01

Our aim was to determine whether the expression levels of specific genes could predict clinical radiosensitivity in human colorectal cancer. Radioresistant colorectal cancer cell lines were established by repeated X-ray exposure (total, 100 Gy), and the gene expressions of the parent and radioresistant cell lines were compared in a microarray analysis. To verify the microarray data, we carried out a reverse transcriptase-polymerase chain reaction analysis of identified genes in clinical samples from 30 irradiated rectal cancer patients. A comparison of the intensity data for the parent and three radioresistant cell lines revealed 17 upregulated and 142 downregulated genes in all radioresistant cell lines. Next, we focused on two upregulated genes, PTMA (prothymosin α) and EIF5a2 (eukaryotic translation initiation factor 5A), in the radioresistant cell lines. In clinical samples, the expression of PTMA was significantly higher in the minor effect group than in the major effect group (P=0.004), but there were no significant differences in EIF5a2 expression between the two groups. We identified radiation-related genes in colorectal cancer and demonstrated that PTMA may play an important role in radiosensitivity. Our findings suggest that PTMA may be a novel marker for predicting the effectiveness of radiotherapy in clinical cases. (author)

Predicting fatty acid profiles in blood based on food intake and the FADS1 rs174546 SNP.

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Hallmann, Jacqueline; Kolossa, Silvia; Gedrich, Kurt; Celis-Morales, Carlos; Forster, Hannah; O'Donovan, Clare B; Woolhead, Clara; Macready, Anna L; Fallaize, Rosalind; Marsaux, Cyril F M; Lambrinou, Christina-Paulina; Mavrogianni, Christina; Moschonis, George; Navas-Carretero, Santiago; San-Cristobal, Rodrigo; Godlewska, Magdalena; Surwiłło, Agnieszka; Mathers, John C; Gibney, Eileen R; Brennan, Lorraine; Walsh, Marianne C; Lovegrove, Julie A; Saris, Wim H M; Manios, Yannis; Martinez, Jose Alfredo; Traczyk, Iwona; Gibney, Michael J; Daniel, Hannelore

2015-12-01

A high intake of n-3 PUFA provides health benefits via changes in the n-6/n-3 ratio in blood. In addition to such dietary PUFAs, variants in the fatty acid desaturase 1 (FADS1) gene are also associated with altered PUFA profiles. We used mathematical modeling to predict levels of PUFA in whole blood, based on multiple hypothesis testing and bootstrapped LASSO selected food items, anthropometric and lifestyle factors, and the rs174546 genotypes in FADS1 from 1607 participants (Food4Me Study). The models were developed using data from the first reported time point (training set) and their predictive power was evaluated using data from the last reported time point (test set). Among other food items, fish, pizza, chicken, and cereals were identified as being associated with the PUFA profiles. Using these food items and the rs174546 genotypes as predictors, models explained 26-43% of the variability in PUFA concentrations in the training set and 22-33% in the test set. Selecting food items using multiple hypothesis testing is a valuable contribution to determine predictors, as our models' predictive power is higher compared to analogue studies. As unique feature, we additionally confirmed our models' power based on a test set. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Predicting the oral pharmacokinetic profiles of multiple-unit (pellet) dosage forms using a modeling and simulation approach coupled with biorelevant dissolution testing: case example diclofenac sodium.

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Kambayashi, Atsushi; Blume, Henning; Dressman, Jennifer B

2014-07-01

The objective of this research was to characterize the dissolution profile of a poorly soluble drug, diclofenac, from a commercially available multiple-unit enteric coated dosage form, Diclo-Puren® capsules, and to develop a predictive model for its oral pharmacokinetic profile. The paddle method was used to obtain the dissolution profiles of this dosage form in biorelevant media, with the exposure to simulated gastric conditions being varied in order to simulate the gastric emptying behavior of pellets. A modified Noyes-Whitney theory was subsequently fitted to the dissolution data. A physiologically-based pharmacokinetic (PBPK) model for multiple-unit dosage forms was designed using STELLA® software and coupled with the biorelevant dissolution profiles in order to simulate the plasma concentration profiles of diclofenac from Diclo-Puren® capsule in both the fasted and fed state in humans. Gastric emptying kinetics relevant to multiple-units pellets were incorporated into the PBPK model by setting up a virtual patient population to account for physiological variations in emptying kinetics. Using in vitro biorelevant dissolution coupled with in silico PBPK modeling and simulation it was possible to predict the plasma profile of this multiple-unit formulation of diclofenac after oral administration in both the fasted and fed state. This approach might be useful to predict variability in the plasma profiles for other drugs housed in multiple-unit dosage forms. Copyright © 2014 Elsevier B.V. All rights reserved.

Using pathology-specific laboratory profiles in Clinical Pathology to reduce inappropriate test requesting: two completed audit cycles

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2012-01-01

Background Systematic reviews have shown that, although well prepared, the Consensus Guidelines have failed to change clinical practice. In the healthcare district of Castelnovo né Monti (Reggio Emilia, Italy), it became necessary for the GPs and Clinical Pathologists to work together to jointly define laboratory profiles. Methods Observational study with two cycles of retrospective audit on test request forms, in a primary care setting. Objectives of the study were to develop pathology-specific laboratory profiles and to increase the number of provisional diagnoses on laboratory test request forms. A Multiprofessional Multidisciplinary Inter-hospital Work Team developed pathology-specific laboratory profiles for more effective test requesting. After 8 training sessions that used a combined strategy with multifaceted interventions, the 23 General Practitioners (GPs) in the trial district (Castelnovo nè Monti) tested the profiles; the 21 GPs in the Puianello district were the control group; all GPs in both districts participated in the trial. All laboratory tests for both healthcare districts are performed at the Laboratory located in the trial district. A baseline and a 1-year audit were performed in both districts on the GPs’ request forms. Results Seven pathology-specific laboratory profiles for outpatients were developed. In the year after the first audit cycle: 1) the number of tests requested in the trial district was distinctly lower than that in the previous year, with a decrease of about 5% (p < 0.001); 2) the provisional diagnosis on the request forms was 52.8% in the trial district and 42% in the control district (P < 0.001); 3) the decrease of the number of tests on each request form was much more marked in the trial district (8.73 vs. 10.77; p < 0.001). Conclusions The first audit cycle showed a significant decrease in the number of tests ordered only in the trial district. The combined strategy used in this study improved the

A STUDY ON CLINICAL PROFILE OF SERONEGATIVE SPONDYLOARTHROPATHY IN NORTH KERALA

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Vijith Kumar Kuttat

2016-08-01

Full Text Available INTRODUCTION Seronegative spondyloarthropathy is a group of chronic autoimmune disorders that share common clinical, radiological and genetic features that are clearly distinct from other inflammatory rheumatic diseases and characterised by absence of rheumatoid factor. It includes ankylosing spondylitis, reactive arthritis, psoriatic arthritis, inflammatory bowel disease, acute anterior uveitis, undifferentiated spondyloarthropathies and juvenile spondyloarthropathies. OBJECTIVES To study the clinical profile of adult patients with seronegative spondyloarthropathy and to classify the patients into specific subtypes based on standard clinical criteria. METHODOLOGY A cross-sectional study was conducted among 100 patients with seronegative spondyloarthropathy attending Internal Medicine Department of Calicut Medical College, Kerala using semi-structured questionnaire and standard clinical tests. RESULTS Males were found to be more affected with a male female ratio of 2.7:1. Undifferentiated spondyloarthropathy was the most common subtype followed by Psoriatic arthritis and reactive arthritis. Enthesopathy was noted in 88% of patients. Skin and mucosal involvement was seen in 33%. Morning stiffness and peripheral joint involvement was present in most of the cases. Symmetric polyarthritis was the most common presentation of psoriatic arthritis, seen in the study group. CONCLUSION Prevalence of Seronegative spondyloarthropathies is on the rise among people of North Kerala. Early diagnosis and appropriate treatment is necessary to prevent complications and improve the quality of life of affected persons.

MiRNA Profiles in Lymphoblastoid Cell Lines of Finnish Prostate Cancer Families.

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Daniel Fischer

Full Text Available Heritable factors are evidently involved in prostate cancer (PrCa carcinogenesis, but currently, genetic markers are not routinely used in screening or diagnostics of the disease. More precise information is needed for making treatment decisions to distinguish aggressive cases from indolent disease, for which heritable factors could be a useful tool. The genetic makeup of PrCa has only recently begun to be unravelled through large-scale genome-wide association studies (GWAS. The thus far identified Single Nucleotide Polymorphisms (SNPs explain, however, only a fraction of familial clustering. Moreover, the known risk SNPs are not associated with the clinical outcome of the disease, such as aggressive or metastasised disease, and therefore cannot be used to predict the prognosis. Annotating the SNPs with deep clinical data together with miRNA expression profiles can improve the understanding of the underlying mechanisms of different phenotypes of prostate cancer.In this study microRNA (miRNA profiles were studied as potential biomarkers to predict the disease outcome. The study subjects were from Finnish high risk prostate cancer families. To identify potential biomarkers we combined a novel non-parametrical test with an importance measure provided from a Random Forest classifier. This combination delivered a set of nine miRNAs that was able to separate cases from controls. The detected miRNA expression profiles could predict the development of the disease years before the actual PrCa diagnosis or detect the existence of other cancers in the studied individuals. Furthermore, using an expression Quantitative Trait Loci (eQTL analysis, regulatory SNPs for miRNA miR-483-3p that were also directly associated with PrCa were found.Based on our findings, we suggest that blood-based miRNA expression profiling can be used in the diagnosis and maybe even prognosis of the disease. In the future, miRNA profiling could possibly be used in targeted screening

Clinical profile of parkinsonian disorders in the tropics: Experience at Kano, northwestern Nigeria

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Owolabi Lukman Femi

2012-01-01

Full Text Available Background: No data exists on Parkinson′s disease (PD and secondary Parkinsonism in Northwestern Nigeria. This study was designed to create a database, document the clinical profile of PD in Kano, northwestern Nigerian, and compare this to prior observations within and outside Nigeria. Materials and Methods: A database was documented on prospective patients presenting consecutively to the Neurology out-patients clinic of the two tertiary health facilities in Kano northwestern Nigeria over a period of 4 years. Demographic and clinical data at presentation were documented for all patients. Cases were classified as PD or secondary Parkinsonism. The severity at presentation and at last visit was classified using the H and Y scale. Results: Over a period of 4 years, out 1153 a total of 96 patients comprising 74 males and 22 females were enrolled. Eighty (83.3% of them had clinically diagnosed PD while 16 (16.7% had clinical features compatible with secondary Parkinsonism. The mean age at onset of symptoms in the PD patients (mean 58.2 ± 6.72 yrs was more than in secondary Parkinsonism (mean 51.4 ± 10.04 and P = 0.001. There was male preponderance in both idiopathic Parkinsonism (PD (m:f = 3.2:1 and secondary Parkinsonism (m:f = 4.3:1. Out of the patients with secondary Parkinsonism, 10 (62.5% and 5 (31.3% had vascular Parkinsonism and drug-induced Parkinsonism, respectively. Duration of symptoms prior to presentation ranged between 3 months and 16 years. The mean (SD time interval from the onset of motor symptoms to diagnosis of PD was 3.6 ± 3.4 yrs and time interval for men and women (male 3.8 ± 3.7; female 2.8 ± 2.1; P = 0.249. Conclusions : Clinical profile of patients with PD and secondary Parkinsonism in Kano is similar to that from other populations within Nigeria and other developing countries. However, delayed presentation, less frequent family history, lower frequency of Young-onset PD as well as treatment challenges occasioned by

Clinical and laboratory profile of different dengue sub types in dengue virus infection

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Niloy Gan Chaudhuri; S. Vithyavathi; K. Sankar

2016-01-01

Background: Dengue infection, an arthropod-borne viral hemorrhagic fever is caused by Arbovirus of Flavivirus genus and transmitted by Aedes aegypti, Aedes albopictus. Liver involvement in dengue fever is manifested by the elevation of transaminases representing reactive hepatitis, due to direct attack of virus itself or the use of hepatotoxic drugs. The objective of the study was to investigate clinical and laboratory profile of different dengue sub type's patients admitted for dengue fever....

Clinical and epidemiological profile of patients with valvular heart disease admitted to the emergency department

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Moraes, Ricardo Casalino Sanches de [Instituto do Coração, Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP (Brazil); Katz, Marcelo [Hospital Israelita Albert Einstein, São Paulo, SP (Brazil); Tarasoutchi, Flávio [Instituto do Coração, Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP (Brazil)

2014-07-01

To evaluate the clinical and epidemiological profile of patients with valvular heart disease who arrived decompensated at the emergency department of a university hospital in Brazil. A descriptive analysis of clinical and echocardiographic data of 174 patients with severe valvular disease, who were clinically decompensated and went to the emergency department of a tertiary cardiology hospital, in the State of São Paulo, in 2009. The mean age of participants was 56±17 years and 54% were female. The main cause of valve disease was rheumatic in 60%, followed by 15% of degenerative aortic disease and mitral valve prolapse in 13%. Mitral regurgitation (27.5%) was the most common isolated valve disease, followed by aortic stenosis (23%), aortic regurgitation (13%) and mitral stenosis (11%). In echocardiographic data, the mean left atrial diameter was 48±12mm, 38±12mm for the left ventricular systolic diameter, and 54±12mm for the diastolic diameter; the mean ejection fraction was 56±13%, and the mean pulmonary artery pressure was 53±16mmHg. Approximately half of patients (44%) presented atrial fibrillation, and over one third of them (37%) had already undergone another cardiac surgery. Despite increased comorbidities and age-dependent risk factors commonly described in patients with valvular heart disease, the clinical profile of patients arriving at the emergency department represented a cohort of rheumatic patients in more advanced stages of disease. These patients require priority care in high complexity specialized hospitals.

Clinical and epidemiological profile of patients with valvular heart disease admitted to the emergency department

International Nuclear Information System (INIS)

Moraes, Ricardo Casalino Sanches de; Katz, Marcelo; Tarasoutchi, Flávio

2014-01-01

To evaluate the clinical and epidemiological profile of patients with valvular heart disease who arrived decompensated at the emergency department of a university hospital in Brazil. A descriptive analysis of clinical and echocardiographic data of 174 patients with severe valvular disease, who were clinically decompensated and went to the emergency department of a tertiary cardiology hospital, in the State of São Paulo, in 2009. The mean age of participants was 56±17 years and 54% were female. The main cause of valve disease was rheumatic in 60%, followed by 15% of degenerative aortic disease and mitral valve prolapse in 13%. Mitral regurgitation (27.5%) was the most common isolated valve disease, followed by aortic stenosis (23%), aortic regurgitation (13%) and mitral stenosis (11%). In echocardiographic data, the mean left atrial diameter was 48±12mm, 38±12mm for the left ventricular systolic diameter, and 54±12mm for the diastolic diameter; the mean ejection fraction was 56±13%, and the mean pulmonary artery pressure was 53±16mmHg. Approximately half of patients (44%) presented atrial fibrillation, and over one third of them (37%) had already undergone another cardiac surgery. Despite increased comorbidities and age-dependent risk factors commonly described in patients with valvular heart disease, the clinical profile of patients arriving at the emergency department represented a cohort of rheumatic patients in more advanced stages of disease. These patients require priority care in high complexity specialized hospitals

Clinical and academic profile of children with specific learning disorder-mixed type: An Indian study

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Anamika Sahu

2017-01-01

Full Text Available Background: Specific learning disorder (SLD in the past decade has gained recognition as a disabling condition among children by parents and teachers in India. However, there are still gaps in knowledge about its clinical presentation and understanding. Therefore, the present study was planned to evaluate the clinical and academic profile of children with SLD. Methods: The sample comprised 30 children with their age range between 7 and 12 years with a diagnosis of SLD-mixed type. All children were assessed through specifically designed structured pro forma for clinical details (i.e., nature of birth, developmental milestones, and comorbidities and academic history (i.e., history of failure, promoted in next class, repetition in the class, school change, etc. and SLD-comprehensive battery. Results: The mean age of the participants was 9.6 years (standard deviation [SD] = 1.5. 76.7% of participants were male and their mean years of education was 4.7 (SD = 1.5. Thirty percent of children had a history of delayed developmental milestones in terms of speech (16.7%, walking (6.7% and in speech and walking (6.7%, 23% of children had comorbid conditions of attention-deficit/hyperactivity disorder/attention-deficit disorder. Thirty percent of children repeated classes in their academic career. Conclusions: A significant number of children had delayed milestones and other problems. Moreover, it is important to understand the clinical and academic profile in the cultural context so that early identification and intervention can be planned.

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

International Nuclear Information System (INIS)

Bilbao, Cristina; Lara, Pedro Carlos; Ramirez, Raquel; Henriquez-Hernandez, Luis Alberto; Rodriguez, German; Falcon, Orlando; Leon, Laureano; Perucho, Manuel

2010-01-01

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.

Impact of Humidity on In Vitro Human Skin Permeation Experiments for Predicting In Vivo Permeability.

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Ishida, Masahiro; Takeuchi, Hiroyuki; Endo, Hiromi; Yamaguchi, Jun-Ichi

2015-12-01

In vitro skin permeation studies have been commonly conducted to predict in vivo permeability for the development of transdermal therapeutic systems (TTSs). We clarified the impact of humidity on in vitro human skin permeation of two TTSs having different breathability and then elucidated the predictability of in vivo permeability based on in vitro experimental data. Nicotinell(®) TTS(®) 20 and Frandol(®) tape 40mg were used as model TTSs in this study. The in vitro human skin permeation experiments were conducted under humidity levels similar to those used in clinical trials (approximately 50%) as well as under higher humidity levels (approximately 95%). The skin permeability values of drugs at 95% humidity were higher than those at 50% humidity. The time profiles of the human plasma concentrations after TTS application fitted well with the clinical data when predicted based on the in vitro permeation parameters at 50% humidity. On the other hand, those profiles predicted based on the parameters at 95% humidity were overestimated. The impact of humidity was higher for the more breathable TTS; Frandol(®) tape 40mg. These results show that in vitro human skin permeation experiments should be investigated under realistic clinical humidity levels especially for breathable TTSs. © 2015 Wiley Periodicals, Inc. and the American Pharmacists Association.

Clinical profile of breast cancer in Arab and Jewish women in the Jerusalem area.

Science.gov (United States)

Nissan, Aviram; Spira, Ram M; Hamburger, Tamar; Badrriyah, Mahmud; Prus, Diana; Cohen, Tzeela; Hubert, Ayala; Freund, Herbert R; Peretz, Tamar

2004-07-01

The clinical profile of breast cancer may vary among different ethnic groups living in the same country and therefore affect the yield of a breast cancer screening program. The present study attempts to better characterize the breast cancer clinical profile of Arab women compared with Jewish women in the greater Jerusalem area with a future aim of establishing a comprehensive and effective screening program for this population. Retrospective chart review was conducted and the following covariates were correlated with survival: ethnicity, age at diagnosis, and American Joint Committee on Cancer (TNM) stage at diagnosis. A total of 312 women were operated on for breast cancer between 1994 and 1999; 51% were Ashkenazi Jews (AJ), 26% were Sephardic Jews (SJ), 21% were Palestinian Arabs (PA), and 2% patients did not fit into those ethnic groups. The mean age at diagnosis was 51.5 years for the PA group, 53.4 +/- 1.5 for the SJ group, and 55.9 years for the AJ group (P Arab patients compared with the Jewish patients. These findings were associated with lower 5-year survival and disease-free survival of the Arab patients.

Patient profiles and clinical utility of mepolizumab in severe eosinophilic asthma

Directory of Open Access Journals (Sweden)

Haldar P

2017-06-01

Full Text Available Pranabashis Haldar Respiratory Biomedical Research Unit, Glenfield Hospital, University of Leicester, Leicester, UK Abstract: Mepolizumab (Nucala® is an effective and specific anti-eosinophil molecular therapy that has recently been approved as add-on therapy for the management of severe eosinophilic asthma by the US Food and Drug Administration (FDA, European Medicines Agency (EMA; European Union and more recently National Institute for Health and Care Excellence (NICE; UK. It is one of several molecular therapies in development for this indication and is illustrative of the strategic trajectory for pharmaceutical drug development taken over the past decade in several disease areas. Molecular therapies offer the prospect of improved specificity and effectiveness of biological effect. However, this necessitates a clear understanding of the underlying mechanistic pathways underpinning pathological processes, to inform drug development that yields novel more efficacious treatment options with a better clinical profile than existing agents. For the first time, utilization of molecular therapies in clinical trials is providing a novel in vivo model to characterize the association between specific pathways and clinical disease expression. It is increasingly recognized that asthma exhibits both clinical and pathological heterogeneity. It follows that a one-size-fits-all approach will not be appropriate and cost-effectiveness may only be achieved by identifying responder subgroups. This so-called personalized approach to therapy is being supported by the parallel development of companion biomarkers for clinical application. In this review, the author summarizes the clinical studies, their interpretation and the lessons learnt with mepolizumab that have informed our understanding of the approach to personalized molecular therapy in asthma. Keywords: IL-5, Nucala, exacerbations 

Higher schizotypy predicts better metabolic profile in unaffected siblings of patients with schizophrenia.

Science.gov (United States)

Atbasoglu, E Cem; Gumus-Akay, Guvem; Guloksuz, Sinan; Saka, Meram Can; Ucok, Alp; Alptekin, Koksal; Gullu, Sevim; van Os, Jim

2018-04-01

Type 2 diabetes (T2D) is more frequent in schizophrenia (Sz) than in the general population. This association is partly accounted for by shared susceptibility genetic variants. We tested the hypotheses that a genetic predisposition to Sz would be associated with higher likelihood of insulin resistance (IR), and that IR would be predicted by subthreshold psychosis phenotypes. Unaffected siblings of Sz patients (n = 101) were compared with a nonclinical sample (n = 305) in terms of IR, schizotypy (SzTy), and a behavioural experiment of "jumping to conclusions". The measures, respectively, were the Homeostatic Model Assessment of Insulin Resistance (HOMA-IR), Structured Interview for Schizotypy-Revised (SIS-R), and the Beads Task (BT). The likelihood of IR was examined in multiple regression models that included sociodemographic, metabolic, and cognitive parameters alongside group status, SIS-R scores, and BT performance. Insulin resistance was less frequent in siblings (31.7%) compared to controls (43.3%) (p model that examined all relevant parameters included the tSzTy tertiles, TG and HDL-C levels, and BMI, as significant predictors of IR. Lack of IR was predicted by the highest as compared to the lowest SzTy tertile [OR (95%CI): 0.43 (0.21-0.85), p = 0.015]. Higher dopaminergic activity may contribute to both schizotypal features and a favourable metabolic profile in the same individual. This is compatible with dopamine's regulatory role in glucose metabolism via indirect central actions and a direct action on pancreatic insulin secretion. The relationship between dopaminergic activity and metabolic profile in Sz must be examined in longitudinal studies with younger unaffected siblings.

[Establishment of A Clinical Prediction Model of Prolonged Air Leak 
after Anatomic Lung Resection].

Science.gov (United States)

Wu, Xianning; Xu, Shibin; Ke, Li; Fan, Jun; Wang, Jun; Xie, Mingran; Jiang, Xianliang; Xu, Meiqing

2017-12-20

Prolonged air leak (PAL) after anatomic lung resection is a common and challenging complication in thoracic surgery. No available clinical prediction model of PAL has been established in China. The aim of this study was to construct a model to identify patients at increased risk of PAL by using preoperative factors exclusively. We retrospectively reviewed clinical data and PAL occurrence of patients after anatomic lung resection, in department of thoracic surgery, Anhui Provincial Hospital Affiliated to Anhui Medical University, from January 2016 to October 2016. 359 patients were in group A, clinical data including age, body mass index (BMI), gender, smoking history, surgical methods, pulmonary function index, pleural adhesion, pathologic diagnosis, side and site of resected lung were analyzed. By using univariate and multivariate analysis, we found the independent predictors of PAL after anatomic lung resection and subsequently established a clinical prediction model. Then, another 112 patients (group B), who underwent anatomic lung resection in different time by different team, were chosen to verify the accuracy of the prediction model. Receiver-operating characteristic (ROC) curve was constructed using the prediction model. Multivariate Logistic regression analysis was used to identify six clinical characteristics [BMI, gender, smoking history, forced expiratory volume in one second to forced vital capacity ratio (FEV1%), pleural adhesion, site of resection] as independent predictors of PAL after anatomic lung resection. The area under the ROC curve for our model was 0.886 (95%CI: 0.835-0.937). The best predictive P value was 0.299 with sensitivity of 78.5% and specificity of 93.2%. Our prediction model could accurately identify occurrence risk of PAL in patients after anatomic lung resection, which might allow for more effective use of intraoperative prophylactic strategies.
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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.

Methodologic Guide for Evaluating Clinical Performance and Effect of Artificial Intelligence Technology for Medical Diagnosis and Prediction.

Science.gov (United States)

Park, Seong Ho; Han, Kyunghwa

2018-03-01

The use of artificial intelligence in medicine is currently an issue of great interest, especially with regard to the diagnostic or predictive analysis of medical images. Adoption of an artificial intelligence tool in clinical practice requires careful confirmation of its clinical utility. Herein, the authors explain key methodology points involved in a clinical evaluation of artificial intelligence technology for use in medicine, especially high-dimensional or overparameterized diagnostic or predictive models in which artificial deep neural networks are used, mainly from the standpoints of clinical epidemiology and biostatistics. First, statistical methods for assessing the discrimination and calibration performances of a diagnostic or predictive model are summarized. Next, the effects of disease manifestation spectrum and disease prevalence on the performance results are explained, followed by a discussion of the difference between evaluating the performance with use of internal and external datasets, the importance of using an adequate external dataset obtained from a well-defined clinical cohort to avoid overestimating the clinical performance as a result of overfitting in high-dimensional or overparameterized classification model and spectrum bias, and the essentials for achieving a more robust clinical evaluation. Finally, the authors review the role of clinical trials and observational outcome studies for ultimate clinical verification of diagnostic or predictive artificial intelligence tools through patient outcomes, beyond performance metrics, and how to design such studies. © RSNA, 2018.

A Personalized Predictive Framework for Multivariate Clinical Time Series via Adaptive Model Selection.

Science.gov (United States)

Liu, Zitao; Hauskrecht, Milos

2017-11-01

Building of an accurate predictive model of clinical time series for a patient is critical for understanding of the patient condition, its dynamics, and optimal patient management. Unfortunately, this process is not straightforward. First, patient-specific variations are typically large and population-based models derived or learned from many different patients are often unable to support accurate predictions for each individual patient. Moreover, time series observed for one patient at any point in time may be too short and insufficient to learn a high-quality patient-specific model just from the patient's own data. To address these problems we propose, develop and experiment with a new adaptive forecasting framework for building multivariate clinical time series models for a patient and for supporting patient-specific predictions. The framework relies on the adaptive model switching approach that at any point in time selects the most promising time series model out of the pool of many possible models, and consequently, combines advantages of the population, patient-specific and short-term individualized predictive models. We demonstrate that the adaptive model switching framework is very promising approach to support personalized time series prediction, and that it is able to outperform predictions based on pure population and patient-specific models, as well as, other patient-specific model adaptation strategies.

The clinical profile of employees with mental health problems working in social firms in the UK.

Science.gov (United States)

Milton, Alyssa; Parsons, Nicholas; Morant, Nicola; Gilbert, Eleanor; Johnson, Sonia; Fisher, Adrian; Singh, Swaran; Cunliffe, Di; Marwaha, Steven

2015-08-01

UK social firms are under-researched but are a potentially important vocational option for people with mental health problems. To describe the clinical profile, satisfaction levels and experiences of social firms employees with mental health problems. Clinical, work and service use characteristics were collected from social firms' employees with mental health problems in England and Wales. Workplace experience and satisfaction were explored qualitatively. Predominantly, social firms' employees (N = 80) report that they have a diagnosis of depression (56%) and anxiety (41%). People with schizophrenia (20%) or bipolar disorder (5%) were a minority. Respondents had low symptom and disability levels, high quality of life and job satisfaction and experienced reductions in secondary mental health service use over time. High-workplace satisfaction was related to flexibility, manager and colleague support and workplace accommodations. The clinical profile, quality of life and job satisfaction level of employees with mental health problems suggest social firms could be a useful addition to UK vocational services for some people. Current employees mainly have common mental disorders, and social firms will need to shift their focus if they are to form a substantial pathway for the vocational recovery of people currently using community mental health teams.

Latent profiles of non-residential father engagement six years after divorce predict long term offspring outcomes

Science.gov (United States)

Modecki, Kathryn Lynn; Hagan, Melissa; Sandler, Irwin; Wolchik, Sharlene

2014-01-01

This study examined profiles of non-residential father engagement (i.e., support to the adolescent, contact frequency, remarriage, relocation, and interparental conflict) with their adolescent children (N = 156) six to eight years following divorce and the prospective relation between these profiles and the psychosocial functioning of their offspring, nine years later. Parental divorce occurred during late childhood to early adolescence; indicators of non-residential father engagement were assessed during adolescence, and mental health problems and academic achievement of offspring were assessed nine years later in young adulthood. Three profiles of father engagement were identified in our sample of mainly White, non-Hispanic divorced fathers: Moderate Involvement/Low Conflict, Low Involvement/Moderate Conflict, and High Involvement/High Conflict. Profiles differentially predicted offspring outcomes nine years later when they were young adults, controlling for quality of the mother-adolescent relationship, mother’s remarriage, mother’s income, and gender, age and offspring mental health problems in adolescence. Offspring of fathers characterized as Moderate Involvement/Low Conflict had the highest academic achievement and the lowest number of externalizing problems nine years later compared to offspring whose fathers had profiles indicating either the highest or lowest levels of involvement but higher levels of conflict. Results indicate that greater paternal psychosocial support and more frequent father-adolescent contact do not outweigh the negative impact of interparental conflict on youth outcomes in the long-term. Implications of findings for policy and intervention are discussed. PMID:24484456

Psoriasis prediction from genome-wide SNP profiles

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Fang Xiangzhong

2011-01-01

Full Text Available Abstract Background With the availability of large-scale genome-wide association study (GWAS data, choosing an optimal set of SNPs for disease susceptibility prediction is a challenging task. This study aimed to use single nucleotide polymorphisms (SNPs to predict psoriasis from searching GWAS data. Methods Totally we had 2,798 samples and 451,724 SNPs. Process for searching a set of SNPs to predict susceptibility for psoriasis consisted of two steps. The first one was to search top 1,000 SNPs with high accuracy for prediction of psoriasis from GWAS dataset. The second one was to search for an optimal SNP subset for predicting psoriasis. The sequential information bottleneck (sIB method was compared with classical linear discriminant analysis(LDA for classification performance. Results The best test harmonic mean of sensitivity and specificity for predicting psoriasis by sIB was 0.674(95% CI: 0.650-0.698, while only 0.520(95% CI: 0.472-0.524 was reported for predicting disease by LDA. Our results indicate that the new classifier sIB performs better than LDA in the study. Conclusions The fact that a small set of SNPs can predict disease status with average accuracy of 68% makes it possible to use SNP data for psoriasis prediction.

Clinical Relevance of Prognostic and Predictive Molecular Markers in Gliomas.

Science.gov (United States)

Siegal, Tali

2016-01-01

Sorting and grading of glial tumors by the WHO classification provide clinicians with guidance as to the predicted course of the disease and choice of treatment. Nonetheless, histologically identical tumors may have very different outcome and response to treatment. Molecular markers that carry both diagnostic and prognostic information add useful tools to traditional classification by redefining tumor subtypes within each WHO category. Therefore, molecular markers have become an integral part of tumor assessment in modern neuro-oncology and biomarker status now guides clinical decisions in some subtypes of gliomas. The routine assessment of IDH status improves histological diagnostic accuracy by differentiating diffuse glioma from reactive gliosis. It carries a favorable prognostic implication for all glial tumors and it is predictive for chemotherapeutic response in anaplastic oligodendrogliomas with codeletion of 1p/19q chromosomes. Glial tumors that contain chromosomal codeletion of 1p/19q are defined as tumors of oligodendroglial lineage and have favorable prognosis. MGMT promoter methylation is a favorable prognostic marker in astrocytic high-grade gliomas and it is predictive for chemotherapeutic response in anaplastic gliomas with wild-type IDH1/2 and in glioblastoma of the elderly. The clinical implication of other molecular markers of gliomas like mutations of EGFR and ATRX genes and BRAF fusion or point mutation is highlighted. The potential of molecular biomarker-based classification to guide future therapeutic approach is discussed and accentuated.

Building prognostic models for breast cancer patients using clinical variables and hundreds of gene expression signatures

Directory of Open Access Journals (Sweden)

Liu Yufeng

2011-01-01

Full Text Available Abstract Background Multiple breast cancer gene expression profiles have been developed that appear to provide similar abilities to predict outcome and may outperform clinical-pathologic criteria; however, the extent to which seemingly disparate profiles provide additive prognostic information is not known, nor do we know whether prognostic profiles perform equally across clinically defined breast cancer subtypes. We evaluated whether combining the prognostic powers of standard breast cancer clinical variables with a large set of gene expression signatures could improve on our ability to predict patient outcomes. Methods Using clinical-pathological variables and a collection of 323 gene expression "modules", including 115 previously published signatures, we build multivariate Cox proportional hazards models using a dataset of 550 node-negative systemically untreated breast cancer patients. Models predictive of pathological complete response (pCR to neoadjuvant chemotherapy were also built using this approach. Results We identified statistically significant prognostic models for relapse-free survival (RFS at 7 years for the entire population, and for the subgroups of patients with ER-positive, or Luminal tumors. Furthermore, we found that combined models that included both clinical and genomic parameters improved prognostication compared with models with either clinical or genomic variables alone. Finally, we were able to build statistically significant combined models for pathological complete response (pCR predictions for the entire population. Conclusions Integration of gene expression signatures and clinical-pathological factors is an improved method over either variable type alone. Highly prognostic models could be created when using all patients, and for the subset of patients with lymph node-negative and ER-positive breast cancers. Other variables beyond gene expression and clinical-pathological variables, like gene mutation status or DNA

CLINICAL AND ETIOLOGICAL PROFILE OF PATIENTS WITH LUNG ABSCESS AT A TERTIARY CARE CENTRE

OpenAIRE

Manoj Kumar; Amit; Sanjay; Ankit

2015-01-01

BACKGROUND: Lung abscess is a type of liquefactive necrosis of the lung tissue and formation of cavities (more than 2 cm) containing necrotic debris or fluid caused by microbial infection. This pus - filled cavity is often caused by aspiration, which may occur during altered consciousness. OBJECTIVE: To study the clinical and etiological profile of lung abscess in patients admitted at a tertiary care centre. MATERIAL ...

Clinical and functional criteria for predicting asthma in infants

OpenAIRE

Yu. L. Mizemitskiy; V. A. Pavlenko; I. M. Melnikova

2015-01-01

Objective: to determine clinical and functional criteria for predicting asthma in children who have sustained acute obstructive bronchitis in infancy. Subjects and methods. A total of 125 infants aged 2 to 36 months who had experienced 1 -2 episodes of acute obstructive bronchitis and treated at hospital were examined when bronchial obstruction syndrome was being relieved. In addition to physical examination, functional studies (computerized bronchophonography and heart rate variability asses...

Assist feature printability prediction by 3-D resist profile reconstruction

Science.gov (United States)

Zheng, Xin; Huang, Jensheng; Chin, Fook; Kazarian, Aram; Kuo, Chun-Chieh

2012-06-01

properties may then be used to optimize the printability vs. efficacy of an SRAF either prior to or during an Optical Proximity Correction (OPC) run. The process models that are used during OPC have never been able to reliably predict which SRAFs will print. This appears to be due to the fact that OPC process models are generally created using data that does not include printed subresolution patterns. An enhancement to compact modeling capability to predict Assist Features (AF) printability is developed and discussed. A hypsometric map representing 3-D resist profile was built by applying a first principle approximation to estimate the "energy loss" from the resist top to bottom. Such a 3-D resist profile is an extrapolation of a well calibrated traditional OPC model without any additional information. Assist features are detected at either top of resist (dark field) or bottom of resist (bright field). Such detection can be done by just extracting top or bottom resist models from our 3-D resist model. There is no measurement of assist features needed when we build AF but it can be included if interested but focusing on resist calibration to account for both exposure dosage and focus change sensitivities. This approach significantly increases resist model's capability for predicting printed SRAF accuracy. And we don't need to calibrate an SRAF model in addition to the OPC model. Without increase in computation time, this compact model can draw assist feature contour with real placement and size at any vertical plane. The result is compared and validated with 3-D rigorous modeling as well as SEM images. Since this method does not change any form of compact modeling, it can be integrated into current MBAF solutions without any additional work.

Physiotherapy students' perceptions and experiences of clinical prediction rules.

Science.gov (United States)

Knox, Grahame M; Snodgrass, Suzanne J; Stanton, Tasha R; Kelly, David H; Vicenzino, Bill; Wand, Benedict M; Rivett, Darren A

2017-09-01

Clinical reasoning can be difficult to teach to pre-professional physiotherapy students due to their lack of clinical experience. It may be that tools such as clinical prediction rules (CPRs) could aid the process, but there has been little investigation into their use in physiotherapy clinical education. This study aimed to determine the perceptions and experiences of physiotherapy students regarding CPRs, and whether they are learning about CPRs on clinical placement. Cross-sectional survey using a paper-based questionnaire. Final year pre-professional physiotherapy students (n=371, response rate 77%) from five universities across five states of Australia. Sixty percent of respondents had not heard of CPRs, and a further 19% had not clinically used CPRs. Only 21% reported using CPRs, and of these nearly three-quarters were rarely, if ever, learning about CPRs in the clinical setting. However most of those who used CPRs (78%) believed CPRs assisted in the development of clinical reasoning skills and none (0%) was opposed to the teaching of CPRs to students. The CPRs most commonly recognised and used by students were those for determining the need for an X-ray following injuries to the ankle and foot (67%), and for identifying deep venous thrombosis (63%). The large majority of students in this sample knew little, if anything, about CPRs and few had learned about, experienced or practiced them on clinical placement. However, students who were aware of CPRs found them helpful for their clinical reasoning and were in favour of learning more about them. Copyright © 2016 Chartered Society of Physiotherapy. Published by Elsevier Ltd. All rights reserved.

Clinical profile of parkinsonism and Parkinson's disease in Lagos, Southwestern Nigeria

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Ojo Oluwadamilola O

2010-01-01

Full Text Available Abstract Background Current data on the pattern of parkinsonism and Parkinson's disease in Nigerians are sparse. This database was designed to document the clinical profile of PD in Nigerians, and compare this to prior observations. Methods A database of patients presenting to the Neurology out-patients clinic of the Lagos University Teaching Hospital was established in October 1996. Demographic and clinical data at presentation (disease stage using Hoehn and Yahr scale; 'off' state severity on the Unified Parkinson's disease Rating Scale were documented for patients diagnosed with parkinsonism between October 1996 and December 2006. Cases were classified as Parkinson's disease or secondary parkinsonism (in the presence of criteria suggestive of a secondary aetiology. Results The hospital frequency of parkinsonism (over a 2-year period, and relative to other neurologic disorders was 1.47% (i.e. 20/1360. Of the 124 patients with parkinsonism, 98 (79.0% had PD, while 26 (21.0% had secondary parkinsonism. Mean age (SD at onset of PD (61.5 (10.0 years was slightly higher than for secondary parkinsonism (57.5 (14.0 years (P = 0.10. There was a male preponderance in PD (3.3 to 1 and secondary parkinsonism (2.7 to 1, while a positive family history of parkinsonism was present in only 1.02% (1/98 of PD. There was a modestly significant difference in age at onset (SD of PD in men (60.3 (10.4 compared to women (65.2 (7.9 (T = 2.08; P = 0.04. The frequency of young onset PD (≤ 50 years was 16.3% (16/98. The mean time interval from onset of motor symptoms to diagnosis of PD was 24.6 ± 26.1 months with majority presenting at a median 12 months from onset. On the H&Y scale, severity of PD at presentation was a median 2.0 (range 1 to 4. PD disease subtype was tremor-dominant in 31 (31.6%, mixed 54 (55.1% and akinetic-rigid 14 (14.3%. Hypertension was present as a co-morbidity in 20 (20.4%, and diabetes in 6 (6.12%. Conclusions The clinical profile of PD in

Clinical and demographic profile of HIV/AIDS patients diagnosed at a tertiary care centre in Kashmir

International Nuclear Information System (INIS)

Mir, M.A.; Ahmad, P.M.; Siddeque, M.A.; Sofi, F.A.; Ahmad, S.N.; Dar, M.R.

2010-01-01

Objectives: To study the clinical and demographic profile of HIV/AIDS patients diagnosed at a tertiary care centre. Methods: The study was conducted on a group of 1141 patients suspected of having HIV/AIDS on clinical grounds. Screening was done using different Elisa's as advised by NACO and those confirmed as HIV positive were studied for their clinical spectrum and different demographic parameters. Results: Out of 1141 patients tested, 26 proved to have HIV 1 infection with no case of HIV 2 detected. Mean age of presentation was 40.04 +- 7 years, main age group affected 31-40 years and a male: female ratio of 4.2:1 was observed. More than 42% were non Kashmiris with armed forces outnumbering all other occupational classes. Heterosexual transmission was the commonest with married out numbering unmarried. Fever, asthenia and weight loss were the predominant symptoms and pulmonary tuberculosis and oropharyngeal candidiasis commonest opportunistic infections. Conclusion: The clinical and demographic profile of HIV/AIDS patients in Kashmir is largely similar to the rest of India. Kashmir no longer stands immune to the menace of HIV/AIDS. With increasing globalization, frequent travel and change in social values the state is likely to witness an alarming rise in new cases unless a multi pronged approach is undertaken to control the spread. (author)

Magnetic resonance metabolic profiling of breast cancer tissue obtained with core needle biopsy for predicting pathologic response to neoadjuvant chemotherapy.

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Ji Soo Choi

Full Text Available The purpose of this study was to determine whether metabolic profiling of core needle biopsy (CNB samples using high-resolution magic angle spinning (HR-MAS magnetic resonance spectroscopy (MRS could be used for predicting pathologic response to neoadjuvant chemotherapy (NAC in patients with locally advanced breast cancer. After institutional review board approval and informed consent were obtained, CNB tissue samples were collected from 37 malignant lesions in 37 patients before NAC treatment. The metabolic profiling of CNB samples were performed by HR-MAS MRS. Metabolic profiles were compared according to pathologic response to NAC using the Mann-Whitney test. Multivariate analysis was performed with orthogonal projections to latent structure-discriminant analysis (OPLS-DA. Various metabolites including choline-containing compounds were identified and quantified by HR-MAS MRS in all 37 breast cancer tissue samples obtained by CNB. In univariate analysis, the metabolite concentrations and metabolic ratios of CNB samples obtained with HR-MAS MRS were not significantly different between different pathologic response groups. However, there was a trend of lower levels of phosphocholine/creatine ratio and choline-containing metabolite concentrations in the pathologic complete response group compared to the non-pathologic complete response group. In multivariate analysis, the OPLS-DA models built with HR-MAS MR metabolic profiles showed visible discrimination between the pathologic response groups. This study showed OPLS-DA multivariate analysis using metabolic profiles of pretreatment CNB samples assessed by HR- MAS MRS may be used to predict pathologic response before NAC, although we did not identify the metabolite showing statistical significance in univariate analysis. Therefore, our preliminary results raise the necessity of further study on HR-MAS MR metabolic profiling of CNB samples for a large number of cancers.

[Predictive methods versus clinical titration for the initiation of lithium therapy. A systematic review].

Science.gov (United States)

Geeraerts, I; Sienaert, P

2013-01-01

When lithium is administered, the clinician needs to know when the lithium in the patient’s blood has reached a therapeutic level. At the initiation of treatment the level is usually achieved gradually through the application of the titration method. In order to increase the efficacy of this procedure several methods for dosing lithium and for predicting lithium levels have been developed. To conduct a systematic review of the publications relating to the various methods for dosing lithium or predicting lithium levels at the initiation of therapy. We searched Medline systematically for articles published in English, French or Dutch between 1966 and April 2012 which described or studied a method for dosing lithium or for predicting the lithium level reached following a specific dosage. We screened the reference lists of relevant articles in order to locate additional papers. We found 38 lithium prediction methods, in addition to the clinical titration method. These methods can be divided into two categories: the ‘a priori’ methods and the ‘test-dose’ methods, the latter requiring the administration of a test dose of lithium. The lithium prediction methods generally achieve a therapeutic blood level faster than the clinical titration method, but none of the methods achieves convincing results. On the basis of our review, we propose that the titration method should be used as the standard method in clinical practice.

Prediction of renal mass aggressiveness using clinical and radiographic features: a global, multicentre prospective study

NARCIS (Netherlands)

Golan, Shay; Eggener, Scott; Subotic, Svetozar; Barret, Eric; Cormio, Luigi; Naito, Seiji; Tefekli, Ahmet; Pilar Laguna Pes, M.

2016-01-01

To examine the ability of preoperative clinical characteristics to predict histological features of renal masses (RMs). Data from consecutive patients with clinical stage I RMs treated surgically between 2010 and 2011 in the Clinical Research Office of Endourology Society (CROES) Renal Mass Registry

Echocardiography and risk prediction in advanced heart failure: incremental value over clinical markers.

Science.gov (United States)

Agha, Syed A; Kalogeropoulos, Andreas P; Shih, Jeffrey; Georgiopoulou, Vasiliki V; Giamouzis, Grigorios; Anarado, Perry; Mangalat, Deepa; Hussain, Imad; Book, Wendy; Laskar, Sonjoy; Smith, Andrew L; Martin, Randolph; Butler, Javed

2009-09-01

Incremental value of echocardiography over clinical parameters for outcome prediction in advanced heart failure (HF) is not well established. We evaluated 223 patients with advanced HF receiving optimal therapy (91.9% angiotensin-converting enzyme inhibitor/angiotensin receptor blocker, 92.8% beta-blockers, 71.8% biventricular pacemaker, and/or defibrillator use). The Seattle Heart Failure Model (SHFM) was used as the reference clinical risk prediction scheme. The incremental value of echocardiographic parameters for event prediction (death or urgent heart transplantation) was measured by the improvement in fit and discrimination achieved by addition of standard echocardiographic parameters to the SHFM. After a median follow-up of 2.4 years, there were 38 (17.0%) events (35 deaths; 3 urgent transplants). The SHFM had likelihood ratio (LR) chi(2) 32.0 and C statistic 0.756 for event prediction. Left ventricular end-systolic volume, stroke volume, and severe tricuspid regurgitation were independent echocardiographic predictors of events. The addition of these parameters to SHFM improved LR chi(2) to 72.0 and C statistic to 0.866 (P advanced HF.

Predicting early cognitive decline in newly-diagnosed Parkinson's patients: A practical model.

Science.gov (United States)

Hogue, Olivia; Fernandez, Hubert H; Floden, Darlene P

2018-06-19

To create a multivariable model to predict early cognitive decline among de novo patients with Parkinson's disease, using brief, inexpensive assessments that are easily incorporated into clinical flow. Data for 351 drug-naïve patients diagnosed with idiopathic Parkinson's disease were obtained from the Parkinson's Progression Markers Initiative. Baseline demographic, disease history, motor, and non-motor features were considered as candidate predictors. Best subsets selection was used to determine the multivariable baseline symptom profile that most accurately predicted individual cognitive decline within three years. Eleven per cent of the sample experienced cognitive decline. The final logistic regression model predicting decline included five baseline variables: verbal memory retention, right-sided bradykinesia, years of education, subjective report of cognitive impairment, and REM behavior disorder. Model discrimination was good (optimism-adjusted concordance index = .749). The associated nomogram provides a tool to determine individual patient risk of meaningful cognitive change in the early stages of the disease. Through the consideration of easily-implemented or routinely-gathered assessments, we have identified a multidimensional baseline profile and created a convenient, inexpensive tool to predict cognitive decline in the earliest stages of Parkinson's disease. The use of this tool would generate prediction at the individual level, allowing clinicians to tailor medical management for each patient and identify at-risk patients for clinical trials aimed at disease modifying therapies. Copyright © 2018. Published by Elsevier Ltd.

An IL28B genotype-based clinical prediction model for treatment of chronic hepatitis C.

Directory of Open Access Journals (Sweden)

Thomas R O'Brien

Full Text Available Genetic variation in IL28B and other factors are associated with sustained virological response (SVR after pegylated-interferon/ribavirin treatment for chronic hepatitis C (CHC. Using data from the HALT-C Trial, we developed a model to predict a patient's probability of SVR based on IL28B genotype and clinical variables.HALT-C enrolled patients with advanced CHC who had failed previous interferon-based treatment. Subjects were re-treated with pegylated-interferon/ribavirin during trial lead-in. We used step-wise logistic regression to calculate adjusted odds ratios (aOR and create the predictive model. Leave-one-out cross-validation was used to predict a priori probabilities of SVR and determine area under the receiver operator characteristics curve (AUC.Among 646 HCV genotype 1-infected European American patients, 14.2% achieved SVR. IL28B rs12979860-CC genotype was the strongest predictor of SVR (aOR, 7.56; p10% (43.3% of subjects had an SVR rate of 27.9% and accounted for 84.8% of subjects actually achieving SVR. To verify that consideration of both IL28B genotype and clinical variables is required for treatment decisions, we calculated AUC values from published data for the IDEAL Study.A clinical prediction model based on IL28B genotype and clinical variables can yield useful individualized predictions of the probability of treatment success that could increase SVR rates and decrease the frequency of futile treatment among patients with CHC.

The predictive validity of the BioMedical Admissions Test for pre-clinical examination performance.

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Emery, Joanne L; Bell, John F

2009-06-01

Some medical courses in the UK have many more applicants than places and almost all applicants have the highest possible previous and predicted examination grades. The BioMedical Admissions Test (BMAT) was designed to assist in the student selection process specifically for a number of 'traditional' medical courses with clear pre-clinical and clinical phases and a strong focus on science teaching in the early years. It is intended to supplement the information provided by examination results, interviews and personal statements. This paper reports on the predictive validity of the BMAT and its predecessor, the Medical and Veterinary Admissions Test. Results from the earliest 4 years of the test (2000-2003) were matched to the pre-clinical examination results of those accepted onto the medical course at the University of Cambridge. Correlation and logistic regression analyses were performed for each cohort. Section 2 of the test ('Scientific Knowledge') correlated more strongly with examination marks than did Section 1 ('Aptitude and Skills'). It also had a stronger relationship with the probability of achieving the highest examination class. The BMAT and its predecessor demonstrate predictive validity for the pre-clinical years of the medical course at the University of Cambridge. The test identifies important differences in skills and knowledge between candidates, not shown by their previous attainment, which predict their examination performance. It is thus a valid source of additional admissions information for medical courses with a strong scientific emphasis when previous attainment is very high.

Readmission prediction via deep contextual embedding of clinical concepts.

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Xiao, Cao; Ma, Tengfei; Dieng, Adji B; Blei, David M; Wang, Fei

2018-01-01

Hospital readmission costs a lot of money every year. Many hospital readmissions are avoidable, and excessive hospital readmissions could also be harmful to the patients. Accurate prediction of hospital readmission can effectively help reduce the readmission risk. However, the complex relationship between readmission and potential risk factors makes readmission prediction a difficult task. The main goal of this paper is to explore deep learning models to distill such complex relationships and make accurate predictions. We propose CONTENT, a deep model that predicts hospital readmissions via learning interpretable patient representations by capturing both local and global contexts from patient Electronic Health Records (EHR) through a hybrid Topic Recurrent Neural Network (TopicRNN) model. The experiment was conducted using the EHR of a real world Congestive Heart Failure (CHF) cohort of 5,393 patients. The proposed model outperforms state-of-the-art methods in readmission prediction (e.g. 0.6103 ± 0.0130 vs. second best 0.5998 ± 0.0124 in terms of ROC-AUC). The derived patient representations were further utilized for patient phenotyping. The learned phenotypes provide more precise understanding of readmission risks. Embedding both local and global context in patient representation not only improves prediction performance, but also brings interpretable insights of understanding readmission risks for heterogeneous chronic clinical conditions. This is the first of its kind model that integrates the power of both conventional deep neural network and the probabilistic generative models for highly interpretable deep patient representation learning. Experimental results and case studies demonstrate the improved performance and interpretability of the model.

SVM-PB-Pred: SVM based protein block prediction method using sequence profiles and secondary structures.

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Suresh, V; Parthasarathy, S

2014-01-01

We developed a support vector machine based web server called SVM-PB-Pred, to predict the Protein Block for any given amino acid sequence. The input features of SVM-PB-Pred include i) sequence profiles (PSSM) and ii) actual secondary structures (SS) from DSSP method or predicted secondary structures from NPS@ and GOR4 methods. There were three combined input features PSSM+SS(DSSP), PSSM+SS(NPS@) and PSSM+SS(GOR4) used to test and train the SVM models. Similarly, four datasets RS90, DB433, LI1264 and SP1577 were used to develop the SVM models. These four SVM models developed were tested using three different benchmarking tests namely; (i) self consistency, (ii) seven fold cross validation test and (iii) independent case test. The maximum possible prediction accuracy of ~70% was observed in self consistency test for the SVM models of both LI1264 and SP1577 datasets, where PSSM+SS(DSSP) input features was used to test. The prediction accuracies were reduced to ~53% for PSSM+SS(NPS@) and ~43% for PSSM+SS(GOR4) in independent case test, for the SVM models of above two same datasets. Using our method, it is possible to predict the protein block letters for any query protein sequence with ~53% accuracy, when the SP1577 dataset and predicted secondary structure from NPS@ server were used. The SVM-PB-Pred server can be freely accessed through http://bioinfo.bdu.ac.in/~svmpbpred.

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

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Scott B Hu

Full Text Available 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.Retrospective cohort study.The hematologic malignancy unit in an academic medical center in the United States.Adult patients admitted to the hematologic malignancy unit from 2009 to 2010.None.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.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.

Immune Profiles to Predict Response to Desensitization Therapy in Highly HLA-Sensitized Kidney Transplant Candidates.

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Yabu, Julie M; Siebert, Janet C; Maecker, Holden T

2016-01-01

Kidney transplantation is the most effective treatment for end-stage kidney disease. Sensitization, the formation of human leukocyte antigen (HLA) antibodies, remains a major barrier to successful kidney transplantation. Despite the implementation of desensitization strategies, many candidates fail to respond. Current progress is hindered by the lack of biomarkers to predict response and to guide therapy. Our objective was to determine whether differences in immune and gene profiles may help identify which candidates will respond to desensitization therapy. Single-cell mass cytometry by time-of-flight (CyTOF) phenotyping, gene arrays, and phosphoepitope flow cytometry were performed in a study of 20 highly sensitized kidney transplant candidates undergoing desensitization therapy. Responders to desensitization therapy were defined as 5% or greater decrease in cumulative calculated panel reactive antibody (cPRA) levels, and non-responders had 0% decrease in cPRA. Using a decision tree analysis, we found that a combination of transitional B cell and regulatory T cell (Treg) frequencies at baseline before initiation of desensitization therapy could distinguish responders from non-responders. Using a support vector machine (SVM) and longitudinal data, TRAF3IP3 transcripts and HLA-DR-CD38+CD4+ T cells could also distinguish responders from non-responders. Combining all assays in a multivariate analysis and elastic net regression model with 72 analytes, we identified seven that were highly interrelated and eleven that predicted response to desensitization therapy. Measuring baseline and longitudinal immune and gene profiles could provide a useful strategy to distinguish responders from non-responders to desensitization therapy. This study presents the integration of novel translational studies including CyTOF immunophenotyping in a multivariate analysis model that has potential applications to predict response to desensitization, select candidates, and personalize

Scaling laws for TEXT plasma profiles

International Nuclear Information System (INIS)

McCool, S.C.; Bravenec, R.V.; Chen, J.Y.; Foster, M.S.; Li, W.L.; Ouroura, A.; Phillips, P.E.; Richards, B.; Wenzel, K.W.; Zhang, Z.M.

1994-01-01

Regression analysis has been performed on a number of measured profiles including temperature and density vs. nominal macroscopic operating parameters for TEXT tokamak (pre-upgrade) ohmic plasmas. The resulting simple empirical model has enabled the authors to quickly approximate profiles of electron temperature and density, ion temperature, and soft x-ray brightness, as well as the scalar quantities: total radiated power, q=1 radius, sawtooth period and amplitude, and energy confinement time as a power law of toroidal field, plasma current, chord average density, and fueling gas atomic weight. The model profiles are only applicable to the plasma interior, i.e. within the limiter radius. In most cases the predicted model profiles are within the experimental error bars of measured profiles and are more accurate at predicting profile variation for small operating parameter changes than the measured profiles

Characteristics and clinical implications of the pharmacokinetic profile of ibuprofen in patients with knee osteoarthritis.

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Gallelli, L; Galasso, O; Urzino, A; Saccà, S; Falcone, D; Palleria, C; Longo, P; Corigliano, A; Terracciano, R; Savino, R; Gasparini, G; De Sarro, G; Southworth, S R

2012-12-01

Ibuprofen is a non-selective cyclo-oxygenase (COX)-1/COX-2 inhibitor used to treat pain conditions and inflammation. Limited data have been published concerning the pharmacokinetic profile and clinical effects of ibuprofen in patients with osteoarthritis (OA). In this paper we compared the pharmacokinetic and clinical profile of ibuprofen (at a dosage of from 800 mg/day to 1800 mg/day) administered in patients affected by severe knee OA. Ibuprofen was administered for 7 days to patients who were scheduled to undergo knee arthroplasty due to OA. After 7 days, the ibuprofen concentration in plasma and synovial fluid was measured through both high-performance liquid chromatography (HPLC)-UV and gas chromatography-mass spectroscopy (GC/MS), while clinical effects were evaluated through both visual analogue scale (VAS) and Western Ontario and McMaster Universities (WOMAC) scores. The Naranjo scale and the WHO causality assessment scale were used for estimating the probability of adverse drug reactions (ADRs). The severity of ADRs was assessed by the modified Hartwig and Siegel scale. Ibuprofen showed a dose-dependent diffusion in both plasma and synovial fluid, which was related to the reduction of pain intensity and improvement of health status, without the development of ADRs. Ibuprofen at higher dosages can be expected to provide better control of OA symptoms as a result of higher tissue distribution.

Is the disease course predictable in inflammatory bowel diseases?

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Lakatos, Peter Laszlo; Kiss, Lajos S

2010-01-01

During the course of the disease, most patients with Crohn’s disease (CD) may eventually develop a stricturing or a perforating complication, and a significant number of patients with both CD and ulcerative colitis will undergo surgery. In recent years, research has focused on the determination of factors important in the prediction of disease course in inflammatory bowel diseases to improve stratification of patients, identify individual patient profiles, including clinical, laboratory and molecular markers, which hopefully will allow physicians to choose the most appropriate management in terms of therapy and intensity of follow-up. This review summarizes the available evidence on clinical, endoscopic variables and biomarkers in the prediction of short and long-term outcome in patients with inflammatory bowel diseases. PMID:20518079

Cell Line Derived 5-FU and Irinotecan Drug-Sensitivity Profiles Evaluated in Adjuvant Colon Cancer Trial Data

DEFF Research Database (Denmark)

Buhl, Ida Kappel; Gerster, Sarah; Delorenzi, Mauro

2016-01-01

patients who benefitted from the addition of irinotecan to 5-FU, we used gene expression profiles based on cell lines and clinical tumor material. These profiles were applied to expression data obtained from pretreatment formalin fixed paraffin embedded (FFPE) tumor tissue from 636 stage III colon cancer...... patients enrolled in the PETACC-3 prospective randomized clinical trial. A 5-FU profile developed similarly was assessed by comparing the PETACC-3 cohort with a cohort of 359 stage II colon cancer patients who underwent surgery but received no adjuvant therapy. RESULTS: There was no statistically...... to identify colon cancer patients who may benefit from 5-FU, however, any biomarker predicting benefit for adjuvant 5-FU must be rigorously evaluated in independent cohorts. Given differences between the two study cohorts, the present results should be further validated....

SPECIFICITIES OF THE SUBSET PROFILE OF PERIPHERAL BLOOD IN PATIENTS WITH GLIOBLASTOMA: PATHOGENETIC AND CLINICAL ASSESSMENTS

Directory of Open Access Journals (Sweden)

V. A. Chumakov

2006-01-01

Full Text Available Abstract. In glioblastoma (GB, it is necessary to take into consideration GB-associated secondary immunodeficiency (SID, so-called syndrome of tumor-associated SID (STASID. Cell subsets having effector and regulatory functions, play an important role in developing STASID, and their proportions in patients with different forms of GB can be of pathogenetic importance and have clinical value for treatment and rehabilitation scheduling as well. The most pathogenically and clinically important features of cell subsets profile of peripheral blood were analyzed in patients with different clinical and morphological types of GB. The patients were divided into three groups, i.e., groups I and II were formed by patients with STASID (marked and slightly marked SID, accordingly; group III – patients with SIDTAS (tumor-associated autoimmune syndrome, associated with SID. Marked suppression of cell immunity is typical of group I - imbalance in T-lymphocytes, in a number of specific subsets, and in subsets clusters, as well as disproportions in the immunoregulatory indexes. In group II, the subset profiles of blood were slightly different from the norm. In patients with SIDTAS, activation of cell immunity was evident, forming SID with signs of autoimmune syndrome, affecting effector and regulatory chains of immunity, and influencing the severity and forecast of the disease. Specific features of the immune status in patients with GB identified can be resulted from different clinicalmorphological types of the tumor; the latter are to be considered in differential diagnostics of clinical course of GB and in scheduling of clinical-immunological efficient anti-tumor pharmacotherapy in pre- and postoperative periods.

[Validation of a clinical prediction rule to distinguish bacterial from aseptic meningitis].

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Agüero, Gonzalo; Davenport, María C; Del Valle, María de la P; Gallegos, Paulina; Kannemann, Ana L; Bokser, Vivian; Ferrero, Fernando

2010-02-01

Despite most meningitis are not bacterial, antibiotics are usually administered on admission because bacterial meningitis is difficult to be rule-out. Distinguishing bacterial from aseptic meningitis on admission could avoid inappropriate antibiotic use and hospitalization. We aimed to validate a clinical prediction rule to distinguish bacterial from aseptic meningitis in children, on arriving to the emergency room. This prospective study included patients aged or = 1000 cells/mm(3), CSF protein > or = 80 mg/dl, peripheral blood absolute neutrophil count > or = 10.000/mm(3), seizure = 1 point each. Sensitivity (S), specificity (E), positive and negative predictive values (PPV and NPV), positive and negative likelihood ratios (PLR and NLR) of the BMS to predict bacterial meningitis were calculated. Seventy patients with meningitis were included (14 bacterial meningitis). When BMS was calculated, 25 patients showed a BMS= 0 points, 11 BMS= 1 point, and 34 BMS > or = 2 points. A BMS = 0 showed S: 100%, E: 44%, VPP: 31%, VPN: 100%, RVP: 1,81 RVN: 0. A BMS > or = 2 predicted bacterial meningitis with S: 100%, E: 64%, VPP: 41%, VPN: 100%, PLR: 2.8, NLR:0. Using BMS was simple, and allowed identifying children with very low risk of bacterial meningitis. It could be a useful tool to assist clinical decision making.

Draft forces prediction model for standard single tines by using principles of soil mechanics and soil profile evaluation

Directory of Open Access Journals (Sweden)

Amer Khalid Ahmed Al-Neama

2017-06-01

Full Text Available This paper explains a model to predict the draft force acting on varying standard single tines by using principles of soil mechanics and soil profile evaluation. Draft force (Fd measurements were made with four standard single tines comprising Heavy Duty, Double Heart, Double Heart with Wings and Duck Foot. Tine widths were 6.5, 13.5, 45 and 40 cm, respectively. The test was conducted in a soil bin with sandy loam soil. The effects of forward speeds and working depths on draft forces were investigated under controlled lab conditions. Results were evaluated based on a prediction model. A good correlation between measured and predicted Fd values for all tines with an average absolute variation less than 15 % was found.

Highly accurate prediction of food challenge outcome using routinely available clinical data.

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DunnGalvin, Audrey; Daly, Deirdre; Cullinane, Claire; Stenke, Emily; Keeton, Diane; Erlewyn-Lajeunesse, Mich; Roberts, Graham C; Lucas, Jane; Hourihane, Jonathan O'B

2011-03-01

Serum specific IgE or skin prick tests are less useful at levels below accepted decision points. We sought to develop and validate a model to predict food challenge outcome by using routinely collected data in a diverse sample of children considered suitable for food challenge. The proto-algorithm was generated by using a limited data set from 1 service (phase 1). We retrospectively applied, evaluated, and modified the initial model by using an extended data set in another center (phase 2). Finally, we prospectively validated the model in a blind study in a further group of children undergoing food challenge for peanut, milk, or egg in the second center (phase 3). Allergen-specific models were developed for peanut, egg, and milk. Phase 1 (N = 429) identified 5 clinical factors associated with diagnosis of food allergy by food challenge. In phase 2 (N = 289), we examined the predictive ability of 6 clinical factors: skin prick test, serum specific IgE, total IgE minus serum specific IgE, symptoms, sex, and age. In phase 3 (N = 70), 97% of cases were accurately predicted as positive and 94% as negative. Our model showed an advantage in clinical prediction compared with serum specific IgE only, skin prick test only, and serum specific IgE and skin prick test (92% accuracy vs 57%, and 81%, respectively). Our findings have implications for the improved delivery of food allergy-related health care, enhanced food allergy-related quality of life, and economized use of health service resources by decreasing the number of food challenges performed. Copyright © 2011 American Academy of Allergy, Asthma & Immunology. Published by Mosby, Inc. All rights reserved.

Radio-guided sentinel lymph node identification by lymphoscintigraphy fused with an anatomical vector profile: clinical applications.

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Niccoli Asabella, A; Antonica, F; Renna, M A; Rubini, D; Notaristefano, A; Nicoletti, A; Rubini, G

2013-12-01

To develop a method to fuse lymphoscintigraphic images with an adaptable anatomical vector profile and to evaluate its role in the clinical practice. We used Adobe Illustrator CS6 to create different vector profiles, we fused those profiles, using Adobe Photoshop CS6, with lymphoscintigraphic images of the patient. We processed 197 lymphoscintigraphies performed in patients with cutaneous melanomas, breast cancer or delayed lymph drainage. Our models can be adapted to every patient attitude or position and contain different levels of anatomical details ranging from external body profiles to the internal anatomical structures like bones, muscles, vessels, and lymph nodes. If needed, more new anatomical details can be added and embedded in the profile without redrawing them, saving a lot of time. Details can also be easily hidden, allowing the physician to view only relevant information and structures. Fusion times are about 85 s. The diagnostic confidence of the observers increased significantly. The validation process showed a slight shift (mean 4.9 mm). We have created a new, practical, inexpensive digital technique based on commercial software for fusing lymphoscintigraphic images with built-in anatomical reference profiles. It is easily reproducible and does not alter the original scintigraphic image. Our method allows a more meaningful interpretation of lymphoscintigraphies, an easier recognition of the anatomical site and better lymph node dissection planning.

Association of glucocorticoid receptor polymorphisms with clinical and metabolic profiles in polycystic ovary syndrome

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Gustavo A.Rosa Maciel

2014-03-01

Full Text Available OBJECTIVES: We aimed to investigate whether glucocorticoid receptor gene polymorphisms are associated with clinical and metabolic profiles in patients with polycystic ovary syndrome. Polycystic ovary syndrome is a complex endocrine disease that affects 5-8% of women and may be associated with metabolic syndrome, which is a risk factor for cardiovascular disease. Cortisol action and dysregulation account for metabolic syndrome development in the general population. As glucocorticoid receptor gene (NR3C1 polymorphisms regulate cortisol sensitivity, we hypothesized that variants of this gene may be involved in the adverse metabolic profiles of patients with polycystic ovary syndrome. METHOD: Clinical, metabolic and hormonal profiles were evaluated in 97 patients with polycystic ovary syndrome who were diagnosed according to the Rotterdam criteria. The alleles of the glucocorticoid gene were genotyped. Association analyses were performed using the appropriate statistical tests. RESULTS: Obesity and metabolic syndrome were observed in 42.3% and 26.8% of patients, respectively. Body mass index was positively correlated with blood pressure, triglyceride, LDL-c, total cholesterol, glucose and insulin levels as well as HOMA-IR values and inversely correlated with HDL-c and SHBG levels. The BclI and A3669G variants were found in 24.7% and 13.4% of alleles, respectively. BclI carriers presented a lower frequency of insulin resistance compared with wild-type subjects. CONCLUSION: The BclI variant is associated with a lower frequency of insulin resistance in women with polycystic ovary syndrome. Glucocorticoid gene polymorphism screening during treatment of the syndrome may be useful for identifying subgroups of at-risk patients who would benefit the most from personalized treatment.

Distinct work-related, clinical and psychological factors predict return to work following treatment in four different cancer types.

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Cooper, Alethea F; Hankins, Matthew; Rixon, Lorna; Eaton, Emma; Grunfeld, Elizabeth A

2013-03-01

Many factors influence return to work (RTW) following cancer treatment. However specific factors affecting RTW across different cancer types are unclear. This study examined the role of clinical, sociodemographic, work and psychological factors in RTW following treatment for breast, gynaecological, head and neck, and urological cancer. A 12-month prospective questionnaire study was conducted with 290 patients. Cox regression analyses were conducted to calculate hazard ratios (HR) for time to RTW. Between 89-94% of cancer survivors returned to work. Breast cancer survivors took the longest to return (median 30 weeks), and urology cancer survivors returned the soonest (median 5 weeks). Earlier return among breast cancer survivors was predicted by a greater sense of control over their cancer at work (HR 1.2; 95% CI: 1.09-1.37) and by full-time work (HR 2.1; CI: 1.24-3.4). Predictive of a longer return among gynaecological cancer survivors was a belief that cancer treatment may impair ability to work (HR 0.75; CI: 0.62-0.91). Among urological cancer survivors constipation was predictive of longer RTW (HR 0.99; CI: 0.97-1.00), whereas undertaking flexible working was predictive of returning sooner (HR 1.70; CI: 1.07-2.7). Head and neck cancer survivors who perceived greater negative consequences of their cancer took longer to return (HR 0.27; CI: 0.11-0.68). Those reporting better physical functioning returned sooner (HR1.04; CI: 1.01-1.08). A different profile of predictive factors emerged for the four cancer types. In addition to optimal symptom management and workplace adaptations, the findings suggest that eliciting and challenging specific cancer and treatment-related perceptions may facilitate RTW. Copyright © 2012 John Wiley & Sons, Ltd.

Travellers' profile, travel patterns and vaccine practices--a 10-year prospective study in a Swiss Travel Clinic.

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Boubaker, Rim; Meige, Pierrette; Mialet, Catherine; Buffat, Chantal Ngarambe; Uwanyiligira, Mediatrice; Widmer, Francine; Rochat, Jacynthe; Fossati, Annie Hérard; Souvannaraj-Blanchant, Manisinh; Payot, Sylvie; Rochat, Laurence; de Vallière, Serge; Genton, Blaise; D'Acremont, Valérie

2016-01-01

The travel clinic in Lausanne serves a catchment area of 700 000 of inhabitants and provides pre- and post-travel consultations. This study describes the profile of attendees before departure, their travel patterns and the travel clinic practices in terms of vaccination over time. We included all pre-travel first consultation data recorded between November 2002 and December 2012 by a custom-made program DIAMM/G. We analysed client profiles, travel characteristics and vaccinations prescribed over time. Sixty-five thousand and forty-six client-trips were recorded. Fifty-one percent clients were female. Mean age was 32 years. In total, 0.1% were aged travellers had pre-existing medical conditions. Forty-six percent were travelling to Africa, 35% to Asia, 20% to Latin America and 1% (each) to Oceania and Europe; 19% visited more than one country. India was the most common destination (9.6% of travellers) followed by Thailand (8.6%) and Kenya (6.4%). Seventy-three percent of travellers were planning to travel for ≤ 4 weeks. The main reasons for travel were tourism (75%) and visiting friends and relatives (18%). Sixteen percent were backpackers. Pre-travel advice were sought a median of 29 days before departure. Ninety-nine percent received vaccine(s). The most frequently administered vaccines were hepatitis A (53%), tetanus-diphtheria (46%), yellow fever (39%), poliomyelitis (38%) and typhoid fever (30%). The profile of travel clinic attendees was younger than the general Swiss population. A significant proportion of travellers received vaccinations that are recommended in the routine national programme. These findings highlight the important role of travel clinics to (i) take care of an age group that has little contact with general practitioners and (ii) update vaccination status. The most commonly prescribed travel-related vaccines were for hepatitis A and yellow fever. The question remains to know whether clients do attend travel clinics because of compulsory

Predictive modelling of grain size distributions from marine electromagnetic profiling data using end-member analysis and a radial basis function network

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Baasch, B.; M"uller, H.; von Dobeneck, T.

2018-04-01

In this work we present a new methodology to predict grain-size distributions from geophysical data. Specifically, electric conductivity and magnetic susceptibility of seafloor sediments recovered from electromagnetic profiling data are used to predict grain-size distributions along shelf-wide survey lines. Field data from the NW Iberian shelf are investigated and reveal a strong relation between the electromagnetic properties and grain-size distribution. The here presented workflow combines unsupervised and supervised machine learning techniques. Nonnegative matrix factorisation is used to determine grain-size end-members from sediment surface samples. Four end-members were found which well represent the variety of sediments in the study area. A radial-basis function network modified for prediction of compositional data is then used to estimate the abundances of these end-members from the electromagnetic properties. The end-members together with their predicted abundances are finally back transformed to grain-size distributions. A minimum spatial variation constraint is implemented in the training of the network to avoid overfitting and to respect the spatial distribution of sediment patterns. The predicted models are tested via leave-one-out cross-validation revealing high prediction accuracy with coefficients of determination (R2) between 0.76 and 0.89. The predicted grain-size distributions represent the well-known sediment facies and patterns on the NW Iberian shelf and provide new insights into their distribution, transition and dynamics. This study suggests that electromagnetic benthic profiling in combination with machine learning techniques is a powerful tool to estimate grain-size distribution of marine sediments.

Clinical implementation of dose-volume histogram predictions for organs-at-risk in IMRT planning

International Nuclear Information System (INIS)

Moore, K L; Appenzoller, L M; Tan, J; Michalski, J M; Thorstad, W L; Mutic, S

2014-01-01

True quality control (QC) of the planning process requires quantitative assessments of treatment plan quality itself, and QC in IMRT has been stymied by intra-patient anatomical variability and inherently complex three-dimensional dose distributions. In this work we describe the development of an automated system to reduce clinical IMRT planning variability and improve plan quality using mathematical models that predict achievable OAR DVHs based on individual patient anatomy. These models rely on the correlation of expected dose to the minimum distance from a voxel to the PTV surface, whereby a three-parameter probability distribution function (PDF) was used to model iso-distance OAR subvolume dose distributions. DVH models were obtained by fitting the evolution of the PDF with distance. Initial validation on clinical cohorts of 40 prostate and 24 head-and-neck plans demonstrated highly accurate model-based predictions for achievable DVHs in rectum, bladder, and parotid glands. By quantifying the integrated difference between candidate DVHs and predicted DVHs, the models correctly identified plans with under-spared OARs, validated by replanning all cases and correlating any realized improvements against the predicted gains. Clinical implementation of these predictive models was demonstrated in the PINNACLE treatment planning system by use of existing margin expansion utilities and the scripting functionality inherent to the system. To maintain independence from specific planning software, a system was developed in MATLAB to directly process DICOM-RT data. Both model training and patient-specific analyses were demonstrated with significant computational accelerations from parallelization.

Prediction of Phenotypic Antimicrobial Resistance Profiles From Whole Genome Sequences of Non-typhoidal Salmonella enterica.

Science.gov (United States)

Neuert, Saskia; Nair, Satheesh; Day, Martin R; Doumith, Michel; Ashton, Philip M; Mellor, Kate C; Jenkins, Claire; Hopkins, Katie L; Woodford, Neil; de Pinna, Elizabeth; Godbole, Gauri; Dallman, Timothy J

2018-01-01

Surveillance of antimicrobial resistance (AMR) in non-typhoidal Salmonella enterica (NTS), is essential for monitoring transmission of resistance from the food chain to humans, and for establishing effective treatment protocols. We evaluated the prediction of phenotypic resistance in NTS from genotypic profiles derived from whole genome sequencing (WGS). Genes and chromosomal mutations responsible for phenotypic resistance were sought in WGS data from 3,491 NTS isolates received by Public Health England's Gastrointestinal Bacteria Reference Unit between April 2014 and March 2015. Inferred genotypic AMR profiles were compared with phenotypic susceptibilities determined for fifteen antimicrobials using EUCAST guidelines. Discrepancies between phenotypic and genotypic profiles for one or more antimicrobials were detected for 76 isolates (2.18%) although only 88/52,365 (0.17%) isolate/antimicrobial combinations were discordant. Of the discrepant results, the largest number were associated with streptomycin (67.05%, n = 59). Pan-susceptibility was observed in 2,190 isolates (62.73%). Overall, resistance to tetracyclines was most common (26.27% of isolates, n = 917) followed by sulphonamides (23.72%, n = 828) and ampicillin (21.43%, n = 748). Multidrug resistance (MDR), i.e., resistance to three or more antimicrobial classes, was detected in 848 isolates (24.29%) with resistance to ampicillin, streptomycin, sulphonamides and tetracyclines being the most common MDR profile ( n = 231; 27.24%). For isolates with this profile, all but one were S . Typhimurium and 94.81% ( n = 219) had the resistance determinants bla TEM-1, strA-strB, sul2 and tet (A). Extended-spectrum β-lactamase genes were identified in 41 isolates (1.17%) and multiple mutations in chromosomal genes associated with ciprofloxacin resistance in 82 isolates (2.35%). This study showed that WGS is suitable as a rapid means of determining AMR patterns of NTS for public health surveillance.

Clinical and radiological profile of Hirayama disease: A flexion myelopathy due to tight cervical dural canal amenable to collar therapy

Directory of Open Access Journals (Sweden)

K M Hassan

2012-01-01

Full Text Available Background: Hirayama disease (HD is benign focal amyotrophy of the distal upper limbs, often misdiagnosed as motor neuron disease. Routine magnetic resonance imaging (MRI is often reported normal. Objective: To study the clinicoradiological profile of hand wasting in young males. Materials and Methods: Patients presenting with insidious-onset hand wasting from March 2008 to May 2011 were evaluated electrophysiologically. Cervical MRI in neutral position was done in 11 patients and flexion contrast imaging was done in 10 patients. Results: All patients were males less than 25 years of age, with median age 23 years, except one patient who was 50 years old. Duration of illness was 3 months to 3 years. All (100% had oblique amyotrophy, four (36% cold paresis, 10 (91% minipolymyoclonus and three (27% had fasciculations. Regional reflexes were variably absent. Two patients (18% had brisk reflexes of lower limbs with flexor plantars. Electromyography (EMG showed chronic denervation in the C7-T1 myotomes. Neutral position MRI showed loss of cervical lordosis in 10/11 (91%, localized lower cervical cord atrophy in 9/11 (82%, asymmetric cord flattening in 11/11 (100% and intramedullary hyperintensity in 2/11 (18%; flexion study showed loss of dural attachment, anterior displacement of dorsal dura, epidural flow voids in 9/10 (90% and enhancing epidural crescent in 10/10 (100%. Clinical profile, imaging and electrophysiological findings of the patient aged 50 years will be described in detail as presentation at this age is exceptional. Collar therapy slowed progression in most cases. Conclusion: Clinical features of HD corroborated well with electrophysiological diagnosis of anterior horn cell disease of lower cervical cord. While dynamic contrast MRI is characteristic, routine studies have a high predictive value for diagnosis. Prompt diagnosis is important to institute early collar therapy.

Clinical Profile and Response to Chemotherapeutic Agents in Non-specific Urethritis

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R K Pandhi

1984-01-01

Full Text Available The epidemiological and clinical profile of 159 patients having non-specific iiretbritis is repoed. The majority (67.39o of patients were unm and most (70.4% of the we m re in the age group of 21-30 years. The incubation period in the majority (69.2% of patients was 1-4 weeks. Almost all the (98.1% patients complained of dysuria but urethral discharge was seen only in 48.4% of patients. Out of tetracycline′s doxycline, erythromycin and cotrimoxazole tried in this study, tetracycline′s in the dosage of 2 gm/day for 3 weeks was found to give the best (90.5%′cure rate.

Predictive markers of efficacy for an angiopoietin-2 targeting therapeutic in xenograft models.

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Gallen Triana-Baltzer

Full Text Available The clinical efficacy of anti-angiogenic therapies has been difficult to predict, and biomarkers that can predict responsiveness are sorely needed in this era of personalized medicine. CVX-060 is an angiopoietin-2 (Ang2 targeting therapeutic, consisting of two peptides that bind Ang2 with high affinity and specificity, covalently fused to a scaffold antibody. In order to optimize the use of this compound in the clinic the construction of a predictive model is described, based on the efficacy of CVX-060 in 13 cell line and 2 patient-derived xenograft models. Pretreatment size tumors from each of the models were profiled for the levels of 27 protein markers of angiogenesis, SNP haplotype in 5 angiogenesis genes, and somatic mutation status for 11 genes implicated in tumor growth and/or vascularization. CVX-060 efficacy was determined as tumor growth inhibition (TGI% at termination of each study. A predictive statistical model was constructed based on the correlation of these efficacy data with the marker profiles, and the model was subsequently tested by prospective analysis in 11 additional models. The results reveal a range of CVX-060 efficacy in xenograft models of diverse tissue types (0-64% TGI, median = 27% and define a subset of 3 proteins (Ang1, EGF, Emmprin, the levels of which may be predictive of TGI by Ang2 blockade. The direction of the associations is such that better efficacy correlates with high levels of target and low levels of compensatory/antagonizing molecules. This effort has revealed a set of candidate predictive markers for CVX-060 efficacy that will be further evaluated in ongoing clinical trials.

 DNA microarray-based gene expression profiling in diagnosis, assessing prognosis and predicting response to therapy in colorectal cancer

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Przemysław Kwiatkowski

2012-06-01

Full Text Available  Colorectal cancer is the most common cancer of the gastrointestinal tract. It is considered as a biological model of a certain type of cancerogenesis process in which progression from an early to late stage adenoma and cancer is accompanied by distinct genetic alterations.Clinical and pathological parameters commonly used in clinical practice are often insufficient to determine groups of patients suitable for personalized treatment. Moreover, reliable molecular markers with high prognostic value have not yet been determined. Molecular studies using DNA-based microarrays have identified numerous genes involved in cell proliferation and differentiation during the process of cancerogenesis. Assessment of the genetic profile of colorectal cancer using the microarray technique might be a useful tool in determining the groups of patients with different clinical outcomes who would benefit from additional personalized treatment.The main objective of this study was to present the current state of knowledge on the practical application of gene profiling techniques using microarrays for determining diagnosis, prognosis and response to treatment in colorectal cancer.

Injury profile SIMulator, a Qualitative aggregative modelling framework to predict injury profile as a function of cropping practices, and abiotic and biotic environment. II. Proof of concept: design of IPSIM-wheat-eyespot.

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Robin, Marie-Hélène; Colbach, Nathalie; Lucas, Philippe; Montfort, Françoise; Cholez, Célia; Debaeke, Philippe; Aubertot, Jean-Noël

2013-01-01

IPSIM (Injury Profile SIMulator) is a generic modelling framework presented in a companion paper. It aims at predicting a crop injury profile as a function of cropping practices and abiotic and biotic environment. IPSIM's modelling approach consists of designing a model with an aggregative hierarchical tree of attributes. In order to provide a proof of concept, a model, named IPSIM-Wheat-Eyespot, has been developed with the software DEXi according to the conceptual framework of IPSIM to represent final incidence of eyespot on wheat. This paper briefly presents the pathosystem, the method used to develop IPSIM-Wheat-Eyespot using IPSIM's modelling framework, simulation examples, an evaluation of the predictive quality of the model with a large dataset (526 observed site-years) and a discussion on the benefits and limitations of the approach. IPSIM-Wheat-Eyespot proved to successfully represent the annual variability of the disease, as well as the effects of cropping practices (Efficiency = 0.51, Root Mean Square Error of Prediction = 24%; bias = 5.0%). IPSIM-Wheat-Eyespot does not aim to precisely predict the incidence of eyespot on wheat. It rather aims to rank cropping systems with regard to the risk of eyespot on wheat in a given production situation through ex ante evaluations. IPSIM-Wheat-Eyespot can also help perform diagnoses of commercial fields. Its structure is simple and permits to combine available knowledge in the scientific literature (data, models) and expertise. IPSIM-Wheat-Eyespot is now available to help design cropping systems with a low risk of eyespot on wheat in a wide range of production situations, and can help perform diagnoses of commercial fields. In addition, it provides a proof of concept with regard to the modelling approach of IPSIM. IPSIM-Wheat-Eyespot will be a sub-model of IPSIM-Wheat, a model that will predict injury profile on wheat as a function of cropping practices and the production situation.

Clinical utility of gene expression profiling data for clinical decision-making regarding adjuvant therapy in early stage, node-negative breast cancer: a case report.

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Schuster, Steven R; Pockaj, Barbara A; Bothe, Mary R; David, Paru S; Northfelt, Donald W

2012-09-10

Breast cancer is the most common malignancy among women in the United States with the second highest incidence of cancer-related death following lung cancer. The decision-making process regarding adjuvant therapy is a time intensive dialogue between the patient and her oncologist. There are multiple tools that help individualize the treatment options for a patient. Population-based analysis with Adjuvant! Online and genomic profiling with Oncotype DX are two commonly used tools in patients with early stage, node-negative breast cancer. This case report illustrates a situation in which the population-based prognostic and predictive information differed dramatically from that obtained from genomic profiling and affected the patient's decision. In light of this case, we discuss the benefits and limitations of these tools.

Profiling cancer

DEFF Research Database (Denmark)

Ciro, Marco; Bracken, Adrian P; Helin, Kristian

2003-01-01

In the past couple of years, several very exciting studies have demonstrated the enormous power of gene-expression profiling for cancer classification and prediction of patient survival. In addition to promising a more accurate classification of cancer and therefore better treatment of patients......, gene-expression profiling can result in the identification of novel potential targets for cancer therapy and a better understanding of the molecular mechanisms leading to cancer....

Artificial neural networks to predict presence of significant pathology in patients presenting to routine colorectal clinics.

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Maslekar, S; Gardiner, A B; Monson, J R T; Duthie, G S

2010-12-01

Artificial neural networks (ANNs) are computer programs used to identify complex relations within data. Routine predictions of presence of colorectal pathology based on population statistics have little meaning for individual patient. This results in large number of unnecessary lower gastrointestinal endoscopies (LGEs - colonoscopies and flexible sigmoidoscopies). We aimed to develop a neural network algorithm that can accurately predict presence of significant pathology in patients attending routine outpatient clinics for gastrointestinal symptoms. Ethics approval was obtained and the study was monitored according to International Committee on Harmonisation - Good Clinical Practice (ICH-GCP) standards. Three-hundred patients undergoing LGE prospectively completed a specifically developed questionnaire, which included 40 variables based on clinical symptoms, signs, past- and family history. Complete data sets of 100 patients were used to train the ANN; the remaining data was used for internal validation. The primary output used was positive finding on LGE, including polyps, cancer, diverticular disease or colitis. For external validation, the ANN was applied to data from 50 patients in primary care and also compared with the predictions of four clinicians. Clear correlation between actual data value and ANN predictions were found (r = 0.931; P = 0.0001). The predictive accuracy of ANN was 95% in training group and 90% (95% CI 84-96) in the internal validation set and this was significantly higher than the clinical accuracy (75%). ANN also showed high accuracy in the external validation group (89%). Artificial neural networks offer the possibility of personal prediction of outcome for individual patients presenting in clinics with colorectal symptoms, making it possible to make more appropriate requests for lower gastrointestinal endoscopy. © 2010 The Authors. Colorectal Disease © 2010 The Association of Coloproctology of Great Britain and Ireland.

Pharmacological profile of β3-adrenoceptor agonists in clinical development for the treatment of overactive bladder syndrome

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Igawa, Yasuhiko; Michel, Martin C.

2013-01-01

β(3)-Adrenoceptor agonists are an emerging drug class for the treatment of the overactive bladder syndrome, and clinical proof-of-concept data have been obtained for three representatives of this class, mirabegron, ritobegron, and solabegron. We review here the pharmacological profile of these three

Language profiles in young children with autism spectrum disorder: A community sample using multiple assessment instruments.

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Nevill, Rose; Hedley, Darren; Uljarević, Mirko; Sahin, Ensu; Zadek, Johanna; Butter, Eric; Mulick, James A

2017-11-01

This study investigated language profiles in a community-based sample of 104 children aged 1-3 years who had been diagnosed with autism spectrum disorder using Diagnostic and Statistical Manual of Mental Disorders (5th ed.) diagnostic criteria. Language was assessed with the Mullen scales, Preschool Language Scale, fifth edition, and Vineland-II parent-report. The study aimed to determine whether the receptive-to-expressive language profile is independent from the assessment instrument used, and whether nonverbal cognition, early communicative behaviors, and autism spectrum disorder symptoms predict language scores. Receptive-to-expressive language profiles differed between assessment instruments and reporters, and Preschool Language Scale, fifth edition profiles were also dependent on developmental level. Nonverbal cognition and joint attention significantly predicted receptive language scores, and nonverbal cognition and frequency of vocalizations predicted expressive language scores. These findings support the administration of multiple direct assessment and parent-report instruments when evaluating language in young children with autism spectrum disorder, for both research and in clinical settings. Results also support that joint attention is a useful intervention target for improving receptive language skills in young children with autism spectrum disorder. Future research comparing language profiles of young children with autism spectrum disorder to children with non-autism spectrum disorder developmental delays and typical development will add to our knowledge of early language development in children with autism spectrum disorder.

Profiling Fast Healthcare Interoperability Resources (FHIR) of Family Health History based on the Clinical Element Models.

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Lee, Jaehoon; Hulse, Nathan C; Wood, Grant M; Oniki, Thomas A; Huff, Stanley M

2016-01-01

In this study we developed a Fast Healthcare Interoperability Resources (FHIR) profile to support exchanging a full pedigree based family health history (FHH) information across multiple systems and applications used by clinicians, patients, and researchers. We used previously developed clinical element models (CEMs) that are capable of representing the FHH information, and derived essential data elements including attributes, constraints, and value sets. We analyzed gaps between the FHH CEM elements and existing FHIR resources. Based on the analysis, we developed a profile that consists of 1) FHIR resources for essential FHH data elements, 2) extensions for additional elements that were not covered by the resources, and 3) a structured definition to integrate patient and family member information in a FHIR message. We implemented the profile using an open-source based FHIR framework and validated it using patient-entered FHH data that was captured through a locally developed FHH tool.

The relationship, structure and profiles of schizophrenia measurements: a post-hoc analysis of the baseline measures from a randomized clinical trial

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Chen Lei

2011-12-01

Full Text Available Background To fully assess the various dimensions affected by schizophrenia, clinical trials often include multiple scales measuring various symptom profiles, cognition, quality of life, subjective well-being, and functional impairment. In this exploratory study, we characterized the relationships among six clinical, functional, cognitive, and quality-of-life measures, identifying a parsimonious set of measurements. Methods We used baseline data from a randomized, multicenter study of patients diagnosed with schizophrenia, schizoaffective disorder, or schizophreniform disorder who were experiencing an acute symptom exacerbation (n = 628 to examine the relationship among several outcome measures. These measures included the Positive and Negative Syndrome Scale (PANSS, Montgomery-Asberg Depression Rating Scale (MADRS, Brief Assessment of Cognition in Schizophrenia Symbol Coding Test, Subjective Well-being Under Neuroleptics Scale Short Form (SWN-K, Schizophrenia Objective Functioning Instrument (SOFI, and Quality of Life Scale (QLS. Three analytic approaches were used: 1 path analysis; 2 factor analysis; and 3 categorical latent variable analysis. In the optimal path model, the SWN-K was selected as the final outcome, while the SOFI mediated the effect of the exogenous variables (PANSS, MADRS on the QLS. Results The overall model explained 47% of variance in QLS and 17% of the variance in SOFI, but only 15% in SWN-K. Factor analysis suggested four factors: "Functioning," "Daily Living," "Depression," and "Psychopathology." A strong positive correlation was observed between the SOFI and QLS (r = 0.669, and both the QLS and SOFI loaded on the "Functioning" factor, suggesting redundancy between these scales. The measurement profiles from the categorical latent variable analysis showed significant variation in functioning and quality of life despite similar levels of psychopathology. Conclusions Researchers should consider collecting PANSS, SOFI, and

LipSpin: A New Bioinformatics Tool for Quantitative 1H NMR Lipid Profiling.

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Barrilero, Rubén; Gil, Miriam; Amigó, Núria; Dias, Cintia B; Wood, Lisa G; Garg, Manohar L; Ribalta, Josep; Heras, Mercedes; Vinaixa, Maria; Correig, Xavier

2018-02-06

The structural similarity among lipid species and the low sensitivity and spectral resolution of nuclear magnetic resonance (NMR) have traditionally hampered the routine use of 1 H NMR lipid profiling of complex biological samples in metabolomics, which remains mostly manual and lacks freely available bioinformatics tools. However, 1 H NMR lipid profiling provides fast quantitative screening of major lipid classes (fatty acids, glycerolipids, phospholipids, and sterols) and some individual species and has been used in several clinical and nutritional studies, leading to improved risk prediction models. In this Article, we present LipSpin, a free and open-source bioinformatics tool for quantitative 1 H NMR lipid profiling. LipSpin implements a constrained line shape fitting algorithm based on voigt profiles and spectral templates from spectra of lipid standards, which automates the analysis of severely overlapped spectral regions and lipid signals with complex coupling patterns. LipSpin provides the most detailed quantification of fatty acid families and choline phospholipids in serum lipid samples by 1 H NMR to date. Moreover, analytical and clinical results using LipSpin quantifications conform with other techniques commonly used for lipid analysis.

Comparison of percentage body fat and body mass index for the prediction of inflammatory and atherogenic lipid risk profiles in elderly women

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Funghetto SS

2015-01-01

Full Text Available Silvana Schwerz Funghetto,1 Alessandro de Oliveira Silva,2 Nuno Manuel Frade de Sousa,3 Marina Morato Stival,1 Ramires Alsamir Tibana,4 Leonardo Costa Pereira,1 Marja Letícia Chaves Antunes,1 Luciano Ramos de Lima,1 Jonato Prestes,4 Ricardo Jacó Oliveira,1 Maurílio Tiradentes Dutra,2 Vinícius Carolino Souza,1,4 Dahan da Cunha Nascimento,4 Margô Gomes de Oliveira Karnikowski1 1University of Brasília (UnB, Brasília, DF, Brazil; 2Center University of Brasilia (UNICEUB, Brasilia, DF, Brazil; 3Laboratory of Exercise Physiology, Faculty Estácio de Sá of Vitória, ES, Brazil; 4Catholic University of Brasília, Brasília, DF, Brazil Objective: To compare the clinical classification of the body mass index (BMI and percentage body fat (PBF for the prediction of inflammatory and atherogenic lipid profile risk in older women.Method: Cross-sectional analytical study with 277 elderly women from a local community in the Federal District, Brazil. PBF and fat-free mass (FFM were determined by dual energy X-ray absorptiometry. The investigated inflammatory parameters were interleukin 6 and C-reactive protein.Results: Twenty-five percent of the elderly women were classified as normal weight, 50% overweight, and 25% obese by the BMI. The obese group had higher levels of triglycerides and very low-density lipoproteins than did the normal weight group (P≤0.05 and lower levels of high-density lipoproteins (HDL than did the overweight group (P≤0.05. According to the PBF, 49% of the elderly women were classified as eutrophic, 28% overweight, and 23% obese. In the binomial logistic regression analyses including age, FFM, and lipid profile, only FFM (odds ratio [OR]=0.809, 95% confidence interval [CI]: 0.739–0.886; P<0.0005 proved to be a predictor of reaching the eutrophic state by the BMI. When the cutoff points of PBF were used for the classification, FFM (OR=0.903, CI=0.884–0.965; P=0.003 and the total cholesterol/HDL ratio (OR=0.113, CI=0.023–0

Have the Findings from Clinical Risk Prediction and Trials Any Key Messages for Safety Pharmacology?

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Jem D. Lane

2017-11-01

Full Text Available Anti-arrhythmic drugs are a mainstay in the management of symptoms related to arrhythmias, and are adjuncts in prevention and treatment of life-threatening ventricular arrhythmias. However, they also have the potential for pro-arrhythmia and thus the prediction of arrhythmia predisposition and drug response are critical issues. Clinical trials are the latter stages in the safety testing and efficacy process prior to market release, and as such serve as a critical safeguard. In this review, we look at some of the lessons to be learned from approaches to arrhythmia prediction in patients, clinical trials of drugs used in the treatment of arrhythmias, and the implications for the design of pre-clinical safety pharmacology testing.

Ovary transcriptome profiling via artificial intelligence reveals a transcriptomic fingerprint predicting egg quality in striped bass, Morone saxatilis.

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Robert W Chapman

Full Text Available Inherited gene transcripts deposited in oocytes direct early embryonic development in all vertebrates, but transcript profiles indicative of embryo developmental competence have not previously been identified. We employed artificial intelligence to model profiles of maternal ovary gene expression and their relationship to egg quality, evaluated as production of viable mid-blastula stage embryos, in the striped bass (Morone saxatilis, a farmed species with serious egg quality problems. In models developed using artificial neural networks (ANNs and supervised machine learning, collective changes in the expression of a limited suite of genes (233 representing 90% of the eventual variance in embryo survival. Egg quality related to minor changes in gene expression (<0.2-fold, with most individual transcripts making a small contribution (<1% to the overall prediction of egg quality. These findings indicate that the predictive power of the transcriptome as regards egg quality resides not in levels of individual genes, but rather in the collective, coordinated expression of a suite of transcripts constituting a transcriptomic "fingerprint". Correlation analyses of the corresponding candidate genes indicated that dysfunction of the ubiquitin-26S proteasome, COP9 signalosome, and subsequent control of the cell cycle engenders embryonic developmental incompetence. The affected gene networks are centrally involved in regulation of early development in all vertebrates, including humans. By assessing collective levels of the relevant ovarian transcripts via ANNs we were able, for the first time in any vertebrate, to accurately predict the subsequent embryo developmental potential of eggs from individual females. Our results show that the transcriptomic fingerprint evidencing developmental dysfunction is highly predictive of, and therefore likely to regulate, egg quality, a biologically complex trait crucial to reproductive fitness.

Applying geographic profiling used in the field of criminology for predicting the nest locations of bumble bees.

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Suzuki-Ohno, Yukari; Inoue, Maki N; Ohno, Kazunori

2010-07-21

We tested whether geographic profiling (GP) can predict multiple nest locations of bumble bees. GP was originally developed in the field of criminology for predicting the area where an offender most likely resides on the basis of the actual crime sites and the predefined probability of crime interaction. The predefined probability of crime interaction in the GP model depends on the distance of a site from an offender's residence. We applied GP for predicting nest locations, assuming that foraging and nest sites were the crime sites and the offenders' residences, respectively. We identified the foraging and nest sites of the invasive species Bombus terrestris in 2004, 2005, and 2006. We fitted GP model coefficients to the field data of the foraging and nest sites, and used GP with the fitting coefficients. GP succeeded in predicting about 10-30% of actual nests. Sensitivity analysis showed that the predictability of the GP model mainly depended on the coefficient value of buffer zone, the distance at the mode of the foraging probability. GP will be able to predict the nest locations of bumble bees in other area by using the fitting coefficient values measured in this study. It will be possible to further improve the predictability of the GP model by considering food site preference and nest density. (c) 2010 Elsevier Ltd. All rights reserved.

Model Predictive Control Algorithms for Pen and Pump Insulin Administration

DEFF Research Database (Denmark)

Boiroux, Dimitri

at mealtime, and the case where the insulin sensitivity increases during the night. This thesis consists of a summary report, glucose and insulin proles of the clinical studies and research papers submitted, peer-reviewed and/or published in the period September 2009 - September 2012....... of current closed-loop controllers. In this thesis, we present different control strategies based on Model Predictive Control (MPC) for an artificial pancreas. We use Nonlinear Model Predictive Control (NMPC) in order to determine the optimal insulin and blood glucose profiles. The optimal control problem...

Risk determination after an acute myocardial infarction: review of 3 clinical risk prediction tools.

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Scruth, Elizabeth Ann; Page, Karen; Cheng, Eugene; Campbell, Michelle; Worrall-Carter, Linda

2012-01-01

The objective of the study was to provide comprehensive information for the clinical nurse specialist (CNS) on commonly used clinical prediction (risk assessment) tools used to estimate risk of a secondary cardiac or noncardiac event and mortality in patients undergoing primary percutaneous coronary intervention (PCI) for ST-elevation myocardial infarction (STEMI). The evolution and widespread adoption of primary PCI represent major advances in the treatment of acute myocardial infarction, specifically STEMI. The American College of Cardiology and the American Heart Association have recommended early risk stratification for patients presenting with acute coronary syndromes using several clinical risk scores to identify patients' mortality and secondary event risk after PCI. Clinical nurse specialists are integral to any performance improvement strategy. Their knowledge and understandings of clinical prediction tools will be essential in carrying out important assessment, identifying and managing risk in patients who have sustained a STEMI, and enhancing discharge education including counseling on medications and lifestyle changes. Over the past 2 decades, risk scores have been developed from clinical trials to facilitate risk assessment. There are several risk scores that can be used to determine in-hospital and short-term survival. This article critiques the most common tools: the Thrombolytic in Myocardial Infarction risk score, the Global Registry of Acute Coronary Events risk score, and the Controlled Abciximab and Device Investigation to Lower Late Angioplasty Complications risk score. The importance of incorporating risk screening assessment tools (that are important for clinical prediction models) to guide therapeutic management of patients cannot be underestimated. The ability to forecast secondary risk after a STEMI will assist in determining which patients would require the most aggressive level of treatment and monitoring postintervention including

Tubercular meningitis in children: Clinical, pathological, and radiological profile and factors associated with mortality

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Anil V Israni

2016-01-01

Full Text Available Context: Childhood tuberculosis is a major public health problem in developing countries with tubercular meningitis being a serious complication with high mortality and morbidity. Aim: To study the clinicopathological as well as radiological profile of childhood tuberculous meningitis (TBM cases. Settings and Design: Prospective, observational study including children <14 years of age with TBM admitted in a tertiary care hospital from Western India. Subjects and Methods: TBM was diagnosed based on predefined criteria. Glassgow coma scale (GCS and intracranial pressure (ICP was recorded. Staging was done as per British Medical Council Staging System. Mantoux test, chest X-ray, cerebrospinal fluid (CSF examination, neuroimaging, and other investigations were done to confirm TB. Statistical Analysis Used: STATA software (version 9.0 was used for data analysis. Various risk factors were determined using Chi-square tests, and a P< 0.05 was considered significant. Results: Forty-seven children were included, of which 11 (24.3% died. Fever was the most common presenting symptom, and meningismus was the most common sign. Twenty-nine (62% children presented with Stage III disease. Stage III disease, low GCS, and raised ICP were predictors of mortality. Findings on neuroimaging or CSF examination did not predict mortality. Conclusions: Childhood TBM presents with nonspecific clinical features. Stage III disease, low GCS, lack of Bacillus Calmette–Gu͹rin vaccination at birth and raised ICP seem to the most important adverse prognostic factors.

A clinical tool for predicting survival in ALS.

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Knibb, Jonathan A; Keren, Noa; Kulka, Anna; Leigh, P Nigel; Martin, Sarah; Shaw, Christopher E; Tsuda, Miho; Al-Chalabi, Ammar

2016-12-01

Amyotrophic lateral sclerosis (ALS) is a progressive and usually fatal neurodegenerative disease. Survival from diagnosis varies considerably. Several prognostic factors are known, including site of onset (bulbar or limb), age at symptom onset, delay from onset to diagnosis and the use of riluzole and non-invasive ventilation (NIV). Clinicians and patients would benefit from a practical way of using these factors to provide an individualised prognosis. 575 consecutive patients with incident ALS from a population-based registry in South-East England register for ALS (SEALS) were studied. Their survival was modelled as a two-step process: the time from diagnosis to respiratory muscle involvement, followed by the time from respiratory involvement to death. The effects of predictor variables were assessed separately for each time interval. Younger age at symptom onset, longer delay from onset to diagnosis and riluzole use were associated with slower progression to respiratory involvement, and NIV use was associated with lower mortality after respiratory involvement, each with a clinically significant effect size. Riluzole may have a greater effect in younger patients and those with longer delay to diagnosis. A patient's survival time has a roughly 50% chance of falling between half and twice the predicted median. A simple and clinically applicable graphical method of predicting an individual patient's survival from diagnosis is presented. The model should be validated in an independent cohort, and extended to include other important prognostic factors. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.