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Sample records for clinical prediction rule

  1. Clinical Prediction Rule of Drug Resistant Epilepsy in Children

    OpenAIRE

    2015-01-01

    Background and Purpose: Clinical prediction rules (CPR) are clinical decision-making tools containing variables such as history, physical examination, diagnostic tests by developing scoring model from potential risk factors. This study is to establish clinical prediction scoring of drug-resistant epilepsy (DRE) in children using clinical manifestationa and only basic electroencephalography (EEG). Methods: Retrospective cohort study was conducted. A total of 308 children with diagnosed epileps...

  2. 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.

  3. Graphics and statistics for cardiology: clinical prediction rules.

    Science.gov (United States)

    Woodward, Mark; Tunstall-Pedoe, Hugh; Peters, Sanne Ae

    2017-04-01

    Graphs and tables are indispensable aids to quantitative research. When developing a clinical prediction rule that is based on a cardiovascular risk score, there are many visual displays that can assist in developing the underlying statistical model, testing the assumptions made in this model, evaluating and presenting the resultant score. All too often, researchers in this field follow formulaic recipes without exploring the issues of model selection and data presentation in a meaningful and thoughtful way. Some ideas on how to use visual displays to make wise decisions and present results that will both inform and attract the reader are given. Ideas are developed, and results tested, using subsets of the data that were used to develop the ASSIGN cardiovascular risk score, as used in Scotland.

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

    NARCIS (Netherlands)

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

    2010-01-01

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

  5. Improvement of a clinical prediction rule for clinical trials on prophylaxis for invasive candidiasis in the intensive care unit.

    Science.gov (United States)

    Ostrosky-Zeichner, Luis; Pappas, Peter G; Shoham, Shmuel; Reboli, Annette; Barron, Michelle A; Sims, Charles; Wood, Craig; Sobel, Jack D

    2011-01-01

    We created a clinical prediction rule to identify patients at risk of invasive candidiasis (IC) in the intensive care unit (ICU) (Eur J Clin Microbiol Infect Dis 2007; 26:271). The rule applies to <10% of patients in ICUs. We sought to create a more inclusive rule for clinical trials. Retrospective review of patients admitted to ICU ≥ 4 days, collecting risk factors and outcomes. Variations of the rule based on introduction of mechanical ventilation and risk factors were assessed. We reviewed 597 patients with a mean APACHE II score of 14.4, mean ICU stay of 12.5 days and mean ventilation time of 10.7 days. A variation of the rule requiring mechanical ventilation AND central venous catheter AND broad spectrum antibiotics on days 1-3 AND an additional risk factor applied to 18% of patients, maintaining the incidence of IC at 10%. Modification of our original rule resulted in a more inclusive rule for studies.

  6. Clinical prediction rules for invasive candidiasis in the ICU: ready for prime time?

    Science.gov (United States)

    Ostrosky-Zeichner, Luis

    2011-01-01

    Invasive candidiasis is a major source of morbidity and mortality in critically ill patients. The creation and validation of clinical prediction rules to identify patients at high risk has given clinicians access to advanced management strategies, such as targeted prophylaxis, pre-emptive therapy, and protocolized empirical therapy.

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

    NARCIS (Netherlands)

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

    2005-01-01

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

  8. 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

    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......-survivors (discrimination ability) was evaluated by the area under the receiver operating characteristic curve (AUC), positive predictive values (PPVs), negative predictive values (NPVs), and adjusted relative risks. Results. Median age (range) was 70 years (25-92 years), 51% of the patients were females, and 73...

  9. Diagnosing malignant melanoma in ambulatory care: a systematic review of clinical prediction rules

    Science.gov (United States)

    Harrington, Emma; Clyne, Barbara; Wesseling, Nieneke; Sandhu, Harkiran; Armstrong, Laura; Bennett, Holly; Fahey, Tom

    2017-01-01

    Objectives Malignant melanoma has high morbidity and mortality rates. Early diagnosis improves prognosis. Clinical prediction rules (CPRs) can be used to stratify patients with symptoms of suspected malignant melanoma to improve early diagnosis. We conducted a systematic review of CPRs for melanoma diagnosis in ambulatory care. Design Systematic review. Data sources A comprehensive search of PubMed, EMBASE, PROSPERO, CINAHL, the Cochrane Library and SCOPUS was conducted in May 2015, using combinations of keywords and medical subject headings (MeSH) terms. Study selection and data extraction Studies deriving and validating, validating or assessing the impact of a CPR for predicting melanoma diagnosis in ambulatory care were included. Data extraction and methodological quality assessment were guided by the CHARMS checklist. Results From 16 334 studies reviewed, 51 were included, validating the performance of 24 unique CPRs. Three impact analysis studies were identified. Five studies were set in primary care. The most commonly evaluated CPRs were the ABCD, more than one or uneven distribution of Colour, or a large (greater than 6 mm) Diameter (ABCD) dermoscopy rule (at a cut-point of >4.75; 8 studies; pooled sensitivity 0.85, 95% CI 0.73 to 0.93, specificity 0.72, 95% CI 0.65 to 0.78) and the 7-point dermoscopy checklist (at a cut-point of ≥1 recommending ruling in melanoma; 11 studies; pooled sensitivity 0.77, 95% CI 0.61 to 0.88, specificity 0.80, 95% CI 0.59 to 0.92). The methodological quality of studies varied. Conclusions At their recommended cut-points, the ABCD dermoscopy rule is more useful for ruling out melanoma than the 7-point dermoscopy checklist. A focus on impact analysis will help translate melanoma risk prediction rules into useful tools for clinical practice. PMID:28264830

  10. Development and validation of a clinical prediction rule for chest wall syndrome in primary care

    Directory of Open Access Journals (Sweden)

    Ronga Alexandre

    2012-08-01

    Full Text Available Abstract Background Chest wall syndrome (CWS, the main cause of chest pain in primary care practice, is most often an exclusion diagnosis. We developed and evaluated a clinical prediction rule for CWS. Methods Data from a multicenter clinical cohort of consecutive primary care patients with chest pain were used (59 general practitioners, 672 patients. A final diagnosis was determined after 12 months of follow-up. We used the literature and bivariate analyses to identify candidate predictors, and multivariate logistic regression was used to develop a clinical prediction rule for CWS. We used data from a German cohort (n = 1212 for external validation. Results From bivariate analyses, we identified six variables characterizing CWS: thoracic pain (neither retrosternal nor oppressive, stabbing, well localized pain, no history of coronary heart disease, absence of general practitioner’s concern, and pain reproducible by palpation. This last variable accounted for 2 points in the clinical prediction rule, the others for 1 point each; the total score ranged from 0 to 7 points. The area under the receiver operating characteristic (ROC curve was 0.80 (95% confidence interval 0.76-0.83 in the derivation cohort (specificity: 89%; sensitivity: 45%; cut-off set at 6 points. Among all patients presenting CWS (n = 284, 71% (n = 201 had a pain reproducible by palpation and 45% (n = 127 were correctly diagnosed. For a subset (n = 43 of these correctly classified CWS patients, 65 additional investigations (30 electrocardiograms, 16 thoracic radiographies, 10 laboratory tests, eight specialist referrals, one thoracic computed tomography had been performed to achieve diagnosis. False positives (n = 41 included three patients with stable angina (1.8% of all positives. External validation revealed the ROC curve to be 0.76 (95% confidence interval 0.73-0.79 with a sensitivity of 22% and a specificity of 93%. Conclusions This CWS score offers

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

    Directory of Open Access Journals (Sweden)

    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.

  12. Ruling out coronary heart disease in primary care patients with chest pain: a clinical prediction score

    Directory of Open Access Journals (Sweden)

    Burnand Bernard

    2010-01-01

    Full Text Available Abstract Background Chest pain raises concern for the possibility of coronary heart disease. Scoring methods have been developed to identify coronary heart disease in emergency settings, but not in primary care. Methods Data were collected from a multicenter Swiss clinical cohort study including 672 consecutive patients with chest pain, who had visited one of 59 family practitioners' offices. Using delayed diagnosis we derived a prediction rule to rule out coronary heart disease by means of a logistic regression model. Known cardiovascular risk factors, pain characteristics, and physical signs associated with coronary heart disease were explored to develop a clinical score. Patients diagnosed with angina or acute myocardial infarction within the year following their initial visit comprised the coronary heart disease group. Results The coronary heart disease score was derived from eight variables: age, gender, duration of chest pain from 1 to 60 minutes, substernal chest pain location, pain increasing with exertion, absence of tenderness point at palpation, cardiovascular risks factors, and personal history of cardiovascular disease. Area under the receiver operating characteristics curve was of 0.95 with a 95% confidence interval of 0.92; 0.97. From this score, 413 patients were considered as low risk for values of percentile 5 of the coronary heart disease patients. Internal validity was confirmed by bootstrapping. External validation using data from a German cohort (Marburg, n = 774 revealed a receiver operating characteristics curve of 0.75 (95% confidence interval, 0.72; 0.81 with a sensitivity of 85.6% and a specificity of 47.2%. Conclusions This score, based only on history and physical examination, is a complementary tool for ruling out coronary heart disease in primary care patients complaining of chest pain.

  13. A clinical prediction rule for ambulation outcomes after traumatic spinal cord injury: a longitudinal cohort study

    NARCIS (Netherlands)

    Middendorp, J.J. van; Hosman, A.J.F.; Donders, A.R.T.; Pouw, M.H.; Ditunno Jr., J.F.; Curt, A.; Geurts, A.C.H.; Meent, H. van de

    2011-01-01

    BACKGROUND: Traumatic spinal cord injury is a serious disorder in which early prediction of ambulation is important to counsel patients and to plan rehabilitation. We developed a reliable, validated prediction rule to assess a patient's chances of walking independently after such injury. METHODS: We

  14. Framework for the impact analysis and implementation of Clinical Prediction Rules (CPRs)

    LENUS (Irish Health Repository)

    Wallace, Emma

    2011-10-14

    Abstract Clinical Prediction Rules (CPRs) are tools that quantify the contribution of symptoms, clinical signs and available diagnostic tests, and in doing so stratify patients according to the probability of having a target outcome or need for a specified treatment. Most focus on the derivation stage with only a minority progressing to validation and very few undergoing impact analysis. Impact analysis studies remain the most efficient way of assessing whether incorporating CPRs into a decision making process improves patient care. However there is a lack of clear methodology for the design of high quality impact analysis studies. We have developed a sequential four-phased framework based on the literature and the collective experience of our international working group to help researchers identify and overcome the specific challenges in designing and conducting an impact analysis of a CPR. There is a need to shift emphasis from deriving new CPRs to validating and implementing existing CPRs. The proposed framework provides a structured approach to this topical and complex area of research.

  15. Framework for the impact analysis and implementation of Clinical Prediction Rules (CPRs

    Directory of Open Access Journals (Sweden)

    Verbakel Jan

    2011-10-01

    Full Text Available Abstract Clinical Prediction Rules (CPRs are tools that quantify the contribution of symptoms, clinical signs and available diagnostic tests, and in doing so stratify patients according to the probability of having a target outcome or need for a specified treatment. Most focus on the derivation stage with only a minority progressing to validation and very few undergoing impact analysis. Impact analysis studies remain the most efficient way of assessing whether incorporating CPRs into a decision making process improves patient care. However there is a lack of clear methodology for the design of high quality impact analysis studies. We have developed a sequential four-phased framework based on the literature and the collective experience of our international working group to help researchers identify and overcome the specific challenges in designing and conducting an impact analysis of a CPR. There is a need to shift emphasis from deriving new CPRs to validating and implementing existing CPRs. The proposed framework provides a structured approach to this topical and complex area of research.

  16. Diagnostic accuracy of the STRATIFY clinical prediction rule for falls: A systematic review and meta-analysis

    LENUS (Irish Health Repository)

    Billington, Jennifer

    2012-08-07

    AbstractBackgroundThe STRATIFY score is a clinical prediction rule (CPR) derived to assist clinicians to identify patients at risk of falling. The purpose of this systematic review and meta-analysis is to determine the overall diagnostic accuracy of the STRATIFY rule across a variety of clinical settings.MethodsA literature search was performed to identify all studies that validated the STRATIFY rule. The methodological quality of the studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies tool. A STRATIFY score of ≥2 points was used to identify individuals at higher risk of falling. All included studies were combined using a bivariate random effects model to generate pooled sensitivity and specificity of STRATIFY at ≥2 points. Heterogeneity was assessed using the variance of logit transformed sensitivity and specificity.ResultsSeventeen studies were included in our meta-analysis, incorporating 11,378 patients. At a score ≥2 points, the STRATIFY rule is more useful at ruling out falls in those classified as low risk, with a greater pooled sensitivity estimate (0.67, 95% CI 0.52–0.80) than specificity (0.57, 95% CI 0.45 – 0.69). The sensitivity analysis which examined the performance of the rule in different settings and subgroups also showed broadly comparable results, indicating that the STRATIFY rule performs in a similar manner across a variety of different ‘at risk’ patient groups in different clinical settings.ConclusionThis systematic review shows that the diagnostic accuracy of the STRATIFY rule is limited and should not be used in isolation for identifying individuals at high risk of falls in clinical practice.

  17. A clinical prediction rule for urinary tract infections in patients with type 2 diabetes mellitus in primary care

    NARCIS (Netherlands)

    Venmans, L M A J; Gorter, K J; Rutten, G E H M; Schellevis, F G; Hoepelman, A I M; Hak, E

    2009-01-01

    We aimed to develop a prediction rule for urinary tract infections (UTIs) in patients with type 2 diabetes mellitus (DM2). A 12-month prospective cohort study was conducted in patients with DM2 aged > or = 45 years to predict the occurrence of recurrent UTIs in women and lower UTIs in men. Predictor

  18. A clinical prediction rule for urinary tract infections in patients with type 2 diabetes mellitus in primary care.

    NARCIS (Netherlands)

    Venmans, L.M.A.J.; Gorter, K.J.; Rutten, G.E.H.M.; Schellevis, F.G.; Hoepelman, A.I.M.; Hak, E.

    2009-01-01

    We aimed to develop a prediction rule for urinary tract infections (UTIs) in patients with type 2 diabetes mellitus (DM2). A 12-month prospective cohort study was conducted in patients with DM2 aged > or = 45 years to predict the occurrence of recurrent UTIs in women and lower UTIs in men. Predictor

  19. A clinical prediction rule for classifying patients with low back pain who demonstrate short-term improvement with mechanical lumbar traction

    OpenAIRE

    Cai, Congcong; Pua, Yong Hao; Lim, Kian Chong

    2009-01-01

    The objective of the study was to develop a clinical prediction rule for identifying patients with low back pain, who improved with mechanical lumbar traction. A prospective, cohort study was conducted in a physiotherapy clinic at a local hospital. Patients with low back pain, referred to physiotherapy were included in the study. The intervention was a standardized mechanical lumbar traction program, which comprised three sessions provided within 9 days. Patient demographic information, stand...

  20. Predictors of non-use of prostheses by people with lower limb amputation after discharge from rehabilitation: development and validation of clinical prediction rules

    Directory of Open Access Journals (Sweden)

    Caroline E Roffman

    2014-12-01

    Full Text Available Questions: Can rules be developed to predict the risk of non-use of prostheses by people with lower limb amputation following discharge from rehabilitation? Are these clinical prediction rules valid? Design: Retrospective and prospective cohort study designs. Participants: Consecutive tertiary rehabilitation patients: 135 retrospective (103 males, mean age = 56 years, SD 15 and 66 prospective (58 males, mean age = 54 years, SD 16. Method: Medical records were audited for potential predictor variables. Retrospective participants were interviewed at a median of 1.9 years after discharge (IQR 1.4 to 2.5 and prospective participants at a median of 1.3 years (IQR 1.1 to 1.4. Results: Clinical prediction rules were identified at 4, 8 and 12 months after discharge, and validated. Amputation levels above transtibial and mobility-aid use were common predictors for all three time frames. At 4 months, if four out of five predictor variables were present (LR+ = 43.9, 95% CI 2.73 to 999+, the probability of non-use increased from 12 to 86% (p < 0.001. At 8 months, if all three predictor variables were present (LR+ = 33.9, 95% CI 2.1 to 999+, the probability of non-use increased from 15 to 86% (p < 0.001. At 12 months, if two out of three predictor variables were present (LR+ = 2.8, 95% CI 0.9 to 6.6, the probability of non-use increased from 17 to 36% (p < 0.031. Conclusions: These validated clinical prediction rules have implications for rehabilitation and service model development. [Roffman CE, Buchanan J, Allison GT (2014 Predictors of non-use of prostheses by people with lower limb amputation after discharge from rehabilitation: development and validation of clinical prediction rules. Journal of Physiotherapy 60: 224–231

  1. Multicenter retrospective development and validation of a clinical prediction rule for nosocomial invasive candidiasis in the intensive care setting.

    Science.gov (United States)

    Ostrosky-Zeichner, L; Sable, C; Sobel, J; Alexander, B D; Donowitz, G; Kan, V; Kauffman, C A; Kett, D; Larsen, R A; Morrison, V; Nucci, M; Pappas, P G; Bradley, M E; Major, S; Zimmer, L; Wallace, D; Dismukes, W E; Rex, J H

    2007-04-01

    The study presented here was performed in order to create a rule that identifies subjects at high risk for invasive candidiasis in the intensive care setting. Retrospective review and statistical modelling were carried out on 2,890 patients who stayed at least 4 days in nine hospitals in the USA and Brazil; the overall incidence of invasive candidiasis in this group was 3% (88 cases). The best performing rule was as follows: Any systemic antibiotic (days 1-3) OR presence of a central venous catheter (days 1-3) AND at least TWO of the following-total parenteral nutrition (days 1-3), any dialysis (days 1-3), any major surgery (days -7-0), pancreatitis (days -7-0), any use of steroids (days -7-3), or use of other immunosuppressive agents (days -7-0). The rate of invasive candidiasis among patients meeting the rule was 9.9%, capturing 34% of cases in the units, with the following performance: relative risk 4.36, sensitivity 0.34, specificity 0.90, positive predictive value 0.01, and negative predictive value 0.97. The rule may identify patients at high risk of invasive candidiasis.

  2. Does the use of a prescriptive clinical prediction rule increase the likelihood of applying inappropriate treatments? A survey using clinical vignettes.

    Science.gov (United States)

    Learman, Kenneth; Showalter, Christopher; Cook, Chad

    2012-12-01

    Clinical prediction rules (CPR) have been promoted as a natural progression in treatment decision-making. Methodological limitations of derivation and validation studies have resulted in some researchers questioning the indiscriminate use of CPRs. The purpose of this study was to explore the influence of the lumbar spine manipulation CPR (LCPR) use on clinical decision making through a survey of practicing clinicians. A sample of 535 physiotherapists from the United States, who routinely use thrust manipulation (TM), agreed to participate in this study. Those who use and those who do not use the LCPR determined group designation. A 9-step clinical vignette progressed a fictitious patient meeting the LCPR from no medical concern to significant concern for general health. A 2 × 9 chi-square was used to analyze the progression of decision-making. APTA board certification (P = 0.04), gender (P < 0.01), and manual therapy course attendance (P = 0.04) may increase and following the McKenzie philosophy (P < 0.01) may decrease the use of the LCPR. Subjects using the LCPR were more likely to choose to manipulate the patient (P < 0.01 and P = 0.02) during the first 2 scenarios of the vignette but both groups avoided TM equally as the medical concerns progressed. The results would suggest that subjects who routinely use TM would modify their decision-making to accommodate medical complications that preclude the indication for TM, and hence a potentially harmful intervention. This propensity to modify behaviour, was seen in both groups, regardless of their initial tendency to use the LCPR.

  3. A clinical prediction rule for classifying patients with low back pain who demonstrate short-term improvement with mechanical lumbar traction.

    Science.gov (United States)

    Cai, Congcong; Pua, Yong Hao; Lim, Kian Chong

    2009-04-01

    The objective of the study was to develop a clinical prediction rule for identifying patients with low back pain, who improved with mechanical lumbar traction. A prospective, cohort study was conducted in a physiotherapy clinic at a local hospital. Patients with low back pain, referred to physiotherapy were included in the study. The intervention was a standardized mechanical lumbar traction program, which comprised three sessions provided within 9 days. Patient demographic information, standard physical examination, numeric pain scale, fear-avoidance beliefs questionnaire and Oswestry low back pain disability index (pre- and post-intervention) were recorded. A total of 129 patients participated in the study and 25 had positive response to the mechanical lumbar traction. A clinical prediction rule with four variables (non-involvement of manual work, low level fear-avoidance beliefs, no neurological deficit and age above 30 years) was identified. The presence of all four variables (positive likelihood ratio = 9.36) increased the probability of response rate with mechanical lumbar traction from 19.4 to 69.2%. It appears that patients with low back pain who were likely to respond to mechanical lumbar traction may be identified.

  4. Rationale, design, and implementation protocol of an electronic health record integrated clinical prediction rule (iCPR randomized trial in primary care

    Directory of Open Access Journals (Sweden)

    Wisnivesky Juan

    2011-09-01

    Full Text Available Abstract Background Clinical prediction rules (CPRs represent well-validated but underutilized evidence-based medicine tools at the point-of-care. To date, an inability to integrate these rules into an electronic health record (EHR has been a major limitation and we are not aware of a study demonstrating the use of CPR's in an ambulatory EHR setting. The integrated clinical prediction rule (iCPR trial integrates two CPR's in an EHR and assesses both the usability and the effect on evidence-based practice in the primary care setting. Methods A multi-disciplinary design team was assembled to develop a prototype iCPR for validated streptococcal pharyngitis and bacterial pneumonia CPRs. The iCPR tool was built as an active Clinical Decision Support (CDS tool that can be triggered by user action during typical workflow. Using the EHR CDS toolkit, the iCPR risk score calculator was linked to tailored ordered sets, documentation, and patient instructions. The team subsequently conducted two levels of 'real world' usability testing with eight providers per group. Usability data were used to refine and create a production tool. Participating primary care providers (n = 149 were randomized and intervention providers were trained in the use of the new iCPR tool. Rates of iCPR tool triggering in the intervention and control (simulated groups are monitored and subsequent use of the various components of the iCPR tool among intervention encounters is also tracked. The primary outcome is the difference in antibiotic prescribing rates (strep and pneumonia iCPR's encounters and chest x-rays (pneumonia iCPR only between intervention and control providers. Discussion Using iterative usability testing and development paired with provider training, the iCPR CDS tool leverages user-centered design principles to overcome pervasive underutilization of EBM and support evidence-based practice at the point-of-care. The ongoing trial will determine if this collaborative

  5. Development of a clinical prediction rule to identify patients with neck pain who are likely to benefit from home-based mechanical cervical traction.

    Science.gov (United States)

    Cai, Congcong; Ming, Guan; Ng, Lih Yen

    2011-06-01

    The objective of the study was to identify the population of patients with neck pain who improved with home-based mechanical cervical traction (HMCT). A prospective cohort study was conducted in a physical therapy clinic at a local hospital. Patients with neck pain referred to the clinic for physical therapy were included in the study. A HMCT program was given to participants for 2 weeks. The patient's demographic data, Numerical Pain Scale (NPS) score, Neck Disability Index (NDI) and Fear-Avoidance Beliefs Questionnaire score were collected, and standard physical examination of the cervical spine was conducted before intervention. The NPS score, NDI and a global rating of perceived improvement were collected after the intervention was completed. A total of 103 patients participated in the study and 47 had a positive response to HMCT. A clinical prediction rule with four variables (Fear-Avoidance Beliefs Work Subscale score pain intensity ≥ 7/10, positive cervical distraction test and pain below shoulder) was identified. With satisfaction of at least three out of four variables (positive likelihood ratio = 4.77), the intervention's success rate increased from 45.6% to over 80%. It appears that patients with neck pain who are likely to respond to HMCT may be identified.

  6. Clinical prediction rules combining signs, symptoms and epidemiological context to distinguish influenza from influenza-like illnesses in primary care: a cross sectional study

    Directory of Open Access Journals (Sweden)

    Van Royen Paul

    2011-02-01

    Full Text Available Abstract Background During an influenza epidemic prompt diagnosis of influenza is important. This diagnosis however is still essentially based on the interpretation of symptoms and signs by general practitioners. No single symptom is specific enough to be useful in differentiating influenza from other respiratory infections. Our objective is to formulate prediction rules for the diagnosis of influenza with the best diagnostic performance, combining symptoms, signs and context among patients with influenza-like illness. Methods During five consecutive winter periods (2002-2007 138 sentinel general practitioners sampled (naso- and oropharyngeal swabs 4597 patients with an influenza-like illness (ILI and registered their symptoms and signs, general characteristics and contextual information. The samples were analysed by a DirectigenFlu-A&B and RT-PCR tests. 4584 records were useful for further analysis. Starting from the most relevant variables in a Generalized Estimating Equations (GEE model, we calculated the area under the Receiver Operating Characteristic curve (ROC AUC, sensitivity, specificity and likelihood ratios for positive (LR+ and negative test results (LR- of single and combined signs, symptoms and context taking into account pre-test and post-test odds. Results In total 52.6% (2409/4584 of the samples were positive for influenza virus: 64% (2066/3212 during and 25% (343/1372 pre/post an influenza epidemic. During and pre/post an influenza epidemic the LR+ of 'previous flu-like contacts', 'coughing', 'expectoration on the first day of illness' and 'body temperature above 37.8°C' is 3.35 (95%CI 2.67-4.03 and 1.34 (95%CI 0.97-1.72, respectively. During and pre/post an influenza epidemic the LR- of 'coughing' and 'a body temperature above 37.8°C' is 0.34 (95%CI 0.27-0.41 and 0.07 (95%CI 0.05-0.08, respectively. Conclusions Ruling out influenza using clinical and contextual information is easier than ruling it in. Outside an influenza

  7. The Acute Asthma Severity Assessment Protocol (AASAP) Study: Objectives and Methods of a Study to Develop an Acute Asthma Clinical Prediction Rule

    OpenAIRE

    2011-01-01

    Acute asthma exacerbations are one of the most common reasons for pediatric emergency department (PED) visits and hospitalizations, and relapse frequently necessitates repeat urgent care. While care plans exist, there are no acute asthma prediction rules (APR)to assess severity and predict outcome. The primary objective of the Acute Asthma Severity Assessment Protocol (AASAP) study is to develop a multivariable APR for acute asthma exacerbations in the pediatric patient.

  8. How well do clinical prediction rules perform in identifying serious infections in acutely ill children across an international network of ambulatory care datasets?

    NARCIS (Netherlands)

    J.Y. Verbakel (Jan); A. van den Bruel (Ann); M.J. Thompson (Matthew); R. Stevens (Richard); B. Aertgeerts (Bert); R. Oostenbrink (Rianne); H.A. Moll (Henriëtte); M.Y. Berger (Marjolein); M. Lakhanpaul (Monica); D. Mant (David); F. Buntinx (Frank)

    2013-01-01

    textabstractBackground: Diagnosing serious infections in children is challenging, because of the low incidence of such infections and their non-specific presentation early in the course of illness. Prediction rules are promoted as a means to improve recognition of serious infections. A recent system

  9. How well do clinical prediction rules perform in identifying serious infections in acutely ill children across an international network of ambulatory care datasets?

    NARCIS (Netherlands)

    Verbakel, Jan Y.; Van den Bruel, Ann; Thompson, Matthew; Stevens, Richard; Aertgeerts, Bert; Oostenbrink, Rianne; Moll, Henriette A.; Berger, Marjolein Y.; Lakhanpaul, Monica; Mant, David; Buntinx, Frank

    2013-01-01

    Background: Diagnosing serious infections in children is challenging, because of the low incidence of such infections and their non-specific presentation early in the course of illness. Prediction rules are promoted as a means to improve recognition of serious infections. A recent systematic review

  10. Comparison of the effectiveness of three manual physical therapy techniques in a subgroup of patients with low back pain who satisfy a clinical prediction rule: Study protocol of a randomized clinical trial [NCT00257998

    Directory of Open Access Journals (Sweden)

    Childs John D

    2006-02-01

    Full Text Available Abstract Background Recently a clinical prediction rule (CPR has been developed and validated that accurately identifies patients with low back pain (LBP that are likely to benefit from a lumbo-pelvic thrust manipulation. The studies that developed and validated the rule used the identical manipulation procedure. However, recent evidence suggests that different manual therapy techniques may result similar outcomes. The purpose of this study is to investigate the effectiveness of three different manual therapy techniques in a subgroup of patient with low back pain that satisfy the CPR. Methods/Design Consecutive patients with LBP referred to physical therapy clinics in one of four geographical locations who satisfy the CPR will be invited to participate in this randomized clinical trial. Subjects who agree to participate will undergo a standard evaluation and complete a number of patient self-report questionnaires including the Oswestry Disability Index (OSW, which will serve as the primary outcome measure. Following the baseline examination patients will be randomly assigned to receive the lumbopelvic manipulation used in the development of the CPR, an alternative lumbar manipulation technique, or non-thrust lumbar mobilization technique for the first 2 visits. Beginning on visit 3, all 3 groups will receive an identical standard exercise program for 3 visits (visits 3,4,5. Outcomes of interest will be captured by a therapist blind to group assignment at 1 week (3rd visit, 4 weeks (6th visit and at a 6-month follow-up. The primary aim of the study will be tested with analysis of variance (ANOVA using the change in OSW score from baseline to 4-weeks (OSWBaseline – OSW4-weeks as the dependent variable. The independent variable will be treatment with three levels (lumbo-pelvic manipulation, alternative lumbar manipulation, lumbar mobilization. Discussion This trial will be the first to investigate the effectiveness of various manual therapy

  11. Evolving Decision Rules to Predict Investment Opportunities

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    This paper is motivated by the interest in finding significant movements in financial stock prices. However, when the number of profitable opportunities is scarce, the prediction of these cases is difficult. In a previous work, we have introduced evolving decision rules (EDR) to detect financial opportunities. The objective of EDR is to classify the minority class (positive cases) in imbalanced environments. EDR provides a range of classifications to find the best balance between not making mistakes and not missing opportunities. The goals of this paper are: 1) to show that EDR produces a range of solutions to suit the investor's preferences and 2) to analyze the factors that benefit the performance of EDR. A series of experiments was performed. EDR was tested using a data set from the London Financial Market. To analyze the EDR behaviour, another experiment was carried out using three artificial data sets, whose solutions have different levels of complexity. Finally, an illustrative example was provided to show how a bigger collection of rules is able to classify more positive cases in imbalanced data sets. Experimental results show that: 1) EDR offers a range of solutions to fit the risk guidelines of different types of investors, and 2) a bigger collection of rules is able to classify more positive cases in imbalanced environments.

  12. On the Predictivity of Neutrino Mass Sum Rules

    CERN Document Server

    Gehrlein, Julia; Spinrath, Martin

    2016-01-01

    Correlations between light neutrino observables are arguably the strongest predictions of lepton flavour models based on (discrete) symmetries, except for the very few cases which unambiguously predict the full set of leptonic mixing angles. A subclass of these correlations are neutrino mass sum rules, which connect the three (complex) light neutrino mass eigenvalues among each other. This connection constrains both the light neutrino mass scale and the Majorana phases, so that mass sum rules generically lead to a non-zero value of the lightest neutrino mass and to distinct predictions for the effective mass probed in neutrinoless double beta decay. However, in nearly all cases known, the neutrino mass sum rules are not exact and receive corrections from various sources. We introduce a formalism to handle these corrections perturbatively in a model-independent manner, which overcomes issues present in earlier approaches. Our ansatz allows us to quantify the modification of the predictions derived from neutrin...

  13. Knowledge Discovery for A Temporal Prediction Rules

    Institute of Scientific and Technical Information of China (English)

    TIAN Yuan; MENG Zhi-qing

    2007-01-01

    We are obtaining a large database of some objects' records of fluctuations of a stock market,medical treatments,changes of weather in certain area and so on,where each record consists of multi-attributes taking multi-values changing with time.Our worlk is motivated by prediction,which is difierent from the work in[4,5,8,11].We want to help learn from past data and make informed decisions for the future.This paper is very significant to perfect the theory and the development of the temporal data mining.

  14. Progression to microalbuminuria in type 1 diabetes: development and validation of a prediction rule

    NARCIS (Netherlands)

    Vergouwe, Y.; Soedamah-Muthu, S.S.; Zgibor, J.; Chaturvedi, N.; Forsblom, C.; Snell-Bergeon, J.K.; Maahs, D.M.; Groop, P.H.; Rewers, M.; Orchard, T.J.; Fuller, J.H.; Moons, K.G.M.

    2010-01-01

    AIMS/HYPOTHESIS: Microalbuminuria is common in type 1 diabetes and is associated with an increased risk of renal and cardiovascular disease. We aimed to develop and validate a clinical prediction rule that estimates the absolute risk of microalbuminuria. METHODS: Data from the European Diabetes Pros

  15. The derivation and validation of a prediction rule for differential diagnosis of thyroid nodules

    Institute of Scientific and Technical Information of China (English)

    李拓

    2013-01-01

    Objective To set up a prediction rule for the pro-operative differential diagnosis of thyroid nodules and evaluate its clinical value.Methods All patients of thyroid nodules undergoing thyroid operations in Changzheng hospital from June,1997 to July,2012 were included in this study.They were randomly divided into the derivation cohort (2/3) and the validation cohort (1/3) .A prediction rule was developed based on the logistic regression model and the scoring system was established in accordance with assigning of the value of each variableβ

  16. Associative Regressive Decision Rule Mining for Predicting Customer Satisfactory Patterns

    Directory of Open Access Journals (Sweden)

    P. Suresh

    2016-04-01

    Full Text Available Opinion mining also known as sentiment analysis, involves cust omer satisfactory patterns, sentiments and attitudes toward entities, products, service s and their attributes. With the rapid development in the field of Internet, potential customer’s provi des a satisfactory level of product/service reviews. The high volume of customer rev iews were developed for product/review through taxonomy-aware processing but, it was di fficult to identify the best reviews. In this paper, an Associative Regression Decisio n Rule Mining (ARDRM technique is developed to predict the pattern for service provider and to improve customer satisfaction based on the review comments. Associative Regression based Decisi on Rule Mining performs two- steps for improving the customer satisfactory level. Initial ly, the Machine Learning Bayes Sentiment Classifier (MLBSC is used to classify the cla ss labels for each service reviews. After that, Regressive factor of the opinion words and Class labels w ere checked for Association between the words by using various probabilistic rules. Based on t he probabilistic rules, the opinion and sentiments effect on customer reviews, are analyzed to arrive at specific set of service preferred by the customers with their review com ments. The Associative Regressive Decision Rule helps the service provider to take decision on imp roving the customer satisfactory level. The experimental results reveal that the Associ ative Regression Decision Rule Mining (ARDRM technique improved the performance in terms of true positive rate, Associative Regression factor, Regressive Decision Rule Generation time a nd Review Detection Accuracy of similar pattern.

  17. Prediction of users webpage access behaviour using association rule mining

    Indian Academy of Sciences (India)

    R Geetharamani; P Revathy; Shomona G Jacob

    2015-12-01

    Web Usage mining is a technique used to identify the user needs from the web log. Discovering hidden patterns from the logs is an upcoming research area. Association rules play an important role in many web mining applications to detect interesting patterns. However, it generates enormous rules that cause researchers to spend ample time and expertise to discover the really interesting ones. This paper works on the server logs from the MSNBC dataset for the month of September 1999. This research aims at predicting the probable subsequent page in the usage of web pages listed in this data based on their navigating behaviour by using Apriori prefix tree (PT) algorithm. The generated rules were ranked based on the support, confidence and lift evaluation measures. The final predictions revealed that the interestingness of pages mainly depended on the support and lift measure whereas confidence assumed a uniform value among all the pages. It proved that the system guaranteed 100% confidence with the support of 1.3E−05. It revealed that the pages such as Front page, On-air, News, Sports and BBS attracted more interested subsequent users compared to Travel, MSN-News and MSN-Sports which were of less interest.

  18. ASSOCIATION RULE DISCOVERY FOR STUDENT PERFORMANCE PREDICTION USING METAHEURISTIC ALGORITHMS

    Directory of Open Access Journals (Sweden)

    Roghayeh Saneifar

    2015-11-01

    Full Text Available According to the increase of using data mining techniques in improving educational systems operations, Educational Data Mining has been introduced as a new and fast growing research area. Educational Data Mining aims to analyze data in educational environments in order to solve educational research problems. In this paper a new associative classification technique has been proposed to predict students final performance. Despite of several machine learning approaches such as ANNs, SVMs, etc. associative classifiers maintain interpretability along with high accuracy. In this research work, we have employed Honeybee Colony Optimization and Particle Swarm Optimization to extract association rule for student performance prediction as a multi-objective classification problem. Results indicate that the proposed swarm based algorithm outperforms well-known classification techniques on student performance prediction classification problem.

  19. Prediction of Breast Cancer using Rule Based Classification

    Directory of Open Access Journals (Sweden)

    Nagendra Kumar SINGH

    2015-12-01

    Full Text Available The current work proposes a model for prediction of breast cancer using the classification approach in data mining. The proposed model is based on various parameters, including symptoms of breast cancer, gene mutation and other risk factors causing breast cancer. Mutations have been predicted in breast cancer causing genes with the help of alignment of normal and abnormal gene sequences; then predicting the class label of breast cancer (risky or safe on the basis of IF-THEN rules, using Genetic Algorithm (GA. In this work, GA has used variable gene encoding mechanisms for chromosomes encoding, uniform population generations and selects two chromosomes by Roulette-Wheel selection technique for two-point crossover, which gives better solutions. The performance of the model is evaluated using the F score measure, Matthews Correlation Coefficient (MCC and Receiver Operating Characteristic (ROC by plotting points (Sensitivity V/s 1- Specificity.

  20. Fast rule-based bioactivity prediction using associative classification mining

    Directory of Open Access Journals (Sweden)

    Yu Pulan

    2012-11-01

    Full Text Available Abstract Relating chemical features to bioactivities is critical in molecular design and is used extensively in the lead discovery and optimization process. A variety of techniques from statistics, data mining and machine learning have been applied to this process. In this study, we utilize a collection of methods, called associative classification mining (ACM, which are popular in the data mining community, but so far have not been applied widely in cheminformatics. More specifically, classification based on predictive association rules (CPAR, classification based on multiple association rules (CMAR and classification based on association rules (CBA are employed on three datasets using various descriptor sets. Experimental evaluations on anti-tuberculosis (antiTB, mutagenicity and hERG (the human Ether-a-go-go-Related Gene blocker datasets show that these three methods are computationally scalable and appropriate for high speed mining. Additionally, they provide comparable accuracy and efficiency to the commonly used Bayesian and support vector machines (SVM methods, and produce highly interpretable models.

  1. Rules for clinical diagnosis in babies with ambiguous genitalia.

    Science.gov (United States)

    Low, Y; Hutson, J M

    2003-08-01

    Intersex disorders are rare and complex; yet, in each case of genital ambiguity, accurate and expeditious management is required of the clinician. This article reviews the embryology of sexual differentiation, from which some 'rules' of diagnosis are derived. A simplified approach to the interpretation of clinical signs in ambiguous genitalia is presented and discussed.

  2. Using data-driven rules to predict mortality in severe community acquired pneumonia.

    Directory of Open Access Journals (Sweden)

    Chuang Wu

    Full Text Available Prediction of patient-centered outcomes in hospitals is useful for performance benchmarking, resource allocation, and guidance regarding active treatment and withdrawal of care. Yet, their use by clinicians is limited by the complexity of available tools and amount of data required. We propose to use Disjunctive Normal Forms as a novel approach to predict hospital and 90-day mortality from instance-based patient data, comprising demographic, genetic, and physiologic information in a large cohort of patients admitted with severe community acquired pneumonia. We develop two algorithms to efficiently learn Disjunctive Normal Forms, which yield easy-to-interpret rules that explicitly map data to the outcome of interest. Disjunctive Normal Forms achieve higher prediction performance quality compared to a set of state-of-the-art machine learning models, and unveils insights unavailable with standard methods. Disjunctive Normal Forms constitute an intuitive set of prediction rules that could be easily implemented to predict outcomes and guide criteria-based clinical decision making and clinical trial execution, and thus of greater practical usefulness than currently available prediction tools. The Java implementation of the tool JavaDNF will be publicly available.

  3. Rainfall events prediction using rule-based fuzzy inference system

    Science.gov (United States)

    Asklany, Somia A.; Elhelow, Khaled; Youssef, I. K.; Abd El-wahab, M.

    2011-07-01

    We are interested in rainfall events prediction by applying rule-based reasoning and fuzzy logic. Five parameters: relative humidity, total cloud cover, wind direction, temperature and surface pressure are the input variables for our model, each has three membership functions. The data used is twenty years METAR data for Cairo airport station (HECA) [1972-1992] 30° 3' 29″ N, 31° 13' 44″ E. and five years METAR data for Mersa Matruh station (HEMM) 31° 20' 0″ N, 27° 13' 0″ E. Different models for each station were constructed depending on the available data sets. Among the overall 243 possibilities we have based our models on one hundred eighteen fuzzy IF-THEN rules and fuzzy reasoning. The output variable which has four membership functions, takes values from zero to one hundred corresponding to the percentage for rainfall events given for every hourly data. We used two skill scores to verify our results, the Brier score and the Friction score. The results are in high agreements with the recorded data for the stations with increasing in output values towards the real time rain events. All implementation are done with MATLAB 7.9.

  4. A Comparison of the Pathogenesis of Marburg Virus Disease in Humans and Nonhuman Primates and Evaluation of the Suitability of These Animal Models for Predicting Clinical Efficacy under the 'Animal Rule'.

    Science.gov (United States)

    Glaze, Elizabeth R; Roy, Michael J; Dalrymple, Lonnie W; Lanning, Lynda L

    2015-06-01

    Marburg virus outbreaks are sporadic, infrequent, brief, and relatively small in terms of numbers of subjects affected. In addition, outbreaks most likely will occur in remote regions where clinical trials are not feasible; therefore, definitive, well-controlled human efficacy studies to test the effectiveness of a drug or biologic product are not feasible. Healthy human volunteers cannot ethically be deliberately exposed to a lethal agent such as Marburg virus in order to test the efficacy of a therapy or preventive prior to licensure. When human efficacy studies are neither ethical nor feasible, the US Food and Drug Administration may grant marketing approval of a drug or biologic product under the 'Animal Rule,' through which demonstration of the efficacy of a product can be 'based on adequate and well-controlled animal efficacy studies when the results of those studies establish that the drug is reasonably likely to produce clinical benefit in humans.' This process requires that the pathogenic determinants of the disease in the animal model are similar to those that have been identified in humans. After reviewing primarily English-language, peer-reviewed journal articles, we here summarize the clinical manifestations of Marburg virus disease and the results of studies in NHP showing the characteristics and progression of the disease. We also include a detailed comparison of the characteristics of the human disease relative to those for NHP. This review reveals that the disease characteristics of Marburg virus disease are generally similar for humans and 3 NHP species: cynomolgus macaques (Macaca fascicularis), rhesus macaques (Macaca mulatta), and African green monkeys (Chlorocebus aethiops).

  5. Madelung rule violation statistics and superheavy elements electron shell prediction

    CERN Document Server

    Loza, E

    2012-01-01

    The paper presents tetrahedron periodic table to conveniently include superheavy elements. Madelung rule violation statistics is discussed and a model for Madelung rule violation probability calculation is proposed. On its basis superheavy elements probable electron shell structure is determined.

  6. Rule based Part of speech Tagger for Homoeopathy Clinical realm

    CERN Document Server

    Dwivedi, Sanjay K

    2011-01-01

    A tagger is a mandatory segment of most text scrutiny systems, as it consigned a s yntax class (e.g., noun, verb, adjective, and adverb) to every word in a sentence. In this paper, we present a simple part of speech tagger for homoeopathy clinical language. This paper reports about the anticipated part of speech tagger for homoeopathy clinical language. It exploit standard pattern for evaluating sentences, untagged clinical corpus of 20085 words is used, from which we had selected 125 sentences (2322 tokens). The problem of tagging in natural language processing is to find a way to tag every word in a text as a meticulous part of speech. The basic idea is to apply a set of rules on clinical sentences and on each word, Accuracy is the leading factor in evaluating any POS tagger so the accuracy of proposed tagger is also conversed.

  7. Eleven rules for a more successful clinical psychology.

    Science.gov (United States)

    Hayes, Steven C

    2005-09-01

    The recommendations put forth in the target article, "Twenty-First Century Graduate Education in Clinical Psychology: A Four Level Matrix Model" (C.R. Snyder & T.R. Elliott, this issue, pp. 1033-1054), should be regarded in the context of the large need to develop a more progressive and effective discipline. No amount of "brute force" education and empiricism is certain to solve the problems of the scope of our field identified by the authors. Eleven rules are offered and defended that may lead to a more practically and empirically successful field.

  8. How to Establish Clinical Prediction Models

    Directory of Open Access Journals (Sweden)

    Yong-ho Lee

    2016-03-01

    Full Text Available A clinical prediction model can be applied to several challenging clinical scenarios: screening high-risk individuals for asymptomatic disease, predicting future events such as disease or death, and assisting medical decision-making and health education. Despite the impact of clinical prediction models on practice, prediction modeling is a complex process requiring careful statistical analyses and sound clinical judgement. Although there is no definite consensus on the best methodology for model development and validation, a few recommendations and checklists have been proposed. In this review, we summarize five steps for developing and validating a clinical prediction model: preparation for establishing clinical prediction models; dataset selection; handling variables; model generation; and model evaluation and validation. We also review several studies that detail methods for developing clinical prediction models with comparable examples from real practice. After model development and vigorous validation in relevant settings, possibly with evaluation of utility/usability and fine-tuning, good models can be ready for the use in practice. We anticipate that this framework will revitalize the use of predictive or prognostic research in endocrinology, leading to active applications in real clinical practice.

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

    Science.gov (United States)

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

    2015-01-01

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

  10. The Clinical Prediction of Dangerousness.

    Science.gov (United States)

    1985-05-01

    executive potential, psychopathy , suicidality and so forth. Unfor- tunately, this is not the case. There tend to be substantial dif- ferences among...Prediction from case material to personality data. New York Archives of Psychology, 29 (No. 207). Hare, R. D. (1970). Psychopathy : Theory and research. New...1967). Psychopathy , mental deficiency, aggressiveness, and the XYY syndrome. Nature, 214, (5087), 500-501. Wexler, D. (1979). Patients, therapists

  11. Enterococcal bloodstream infection. Design and validation of a mortality prediction rule

    OpenAIRE

    Perez-Garcia, Alejandra; Landecho, Manuel; Beunza Nuin, Juan Jose; Conde-Estévez, D; Horcajada, J.P.; Grau, S.; Gea Sánchez, Alfredo; E. Mauleón; Sorli, L.; Gómez, J.; Terradas, R.; Lucena, J.F. (Juan F.); Alegre Garrido, Félix; A. Huerta; Pozo, José Luis del

    2016-01-01

    To develop a prediction rule to describe the risk of death as a result of enterococcal bloodstream infection. A prediction rule was developed by analysing data collected from 122 patients diagnosed with enterococcal BSI admitted to the Clínica Universidad de Navarra (Pamplona, Spain); and validated by confirming its accuracy with the data of an external population (Hospital del Mar, Barcelona). According to this model, independent significant predictors for the risk of death were being diabet...

  12. Prediction on carbon dioxide emissions based on fuzzy rules

    Science.gov (United States)

    Pauzi, Herrini; Abdullah, Lazim

    2014-06-01

    There are several ways to predict air quality, varying from simple regression to models based on artificial intelligence. Most of the conventional methods are not sufficiently able to provide good forecasting performances due to the problems with non-linearity uncertainty and complexity of the data. Artificial intelligence techniques are successfully used in modeling air quality in order to cope with the problems. This paper describes fuzzy inference system (FIS) to predict CO2 emissions in Malaysia. Furthermore, adaptive neuro-fuzzy inference system (ANFIS) is used to compare the prediction performance. Data of five variables: energy use, gross domestic product per capita, population density, combustible renewable and waste and CO2 intensity are employed in this comparative study. The results from the two model proposed are compared and it is clearly shown that the ANFIS outperforms FIS in CO2 prediction.

  13. Predicting Clinical Outcomes Using Molecular Biomarkers.

    Science.gov (United States)

    Burke, Harry B

    2016-01-01

    Over the past 20 years, there has been an exponential increase in the number of biomarkers. At the last count, there were 768,259 papers indexed in PubMed.gov directly related to biomarkers. Although many of these papers claim to report clinically useful molecular biomarkers, embarrassingly few are currently in clinical use. It is suggested that a failure to properly understand, clinically assess, and utilize molecular biomarkers has prevented their widespread adoption in treatment, in comparative benefit analyses, and their integration into individualized patient outcome predictions for clinical decision-making and therapy. A straightforward, general approach to understanding how to predict clinical outcomes using risk, diagnostic, and prognostic molecular biomarkers is presented. In the future, molecular biomarkers will drive advances in risk, diagnosis, and prognosis, they will be the targets of powerful molecular therapies, and they will individualize and optimize therapy. Furthermore, clinical predictions based on molecular biomarkers will be displayed on the clinician's screen during the physician-patient interaction, they will be an integral part of physician-patient-shared decision-making, and they will improve clinical care and patient outcomes.

  14. Testing the performance of technical trading rules in the Chinese markets based on superior predictive test

    Science.gov (United States)

    Wang, Shan; Jiang, Zhi-Qiang; Li, Sai-Ping; Zhou, Wei-Xing

    2015-12-01

    Technical trading rules have a long history of being used by practitioners in financial markets. The profitable ability and efficiency of technical trading rules are yet controversial. In this paper, we test the performance of more than seven thousand traditional technical trading rules on the Shanghai Securities Composite Index (SSCI) from May 21, 1992 through June 30, 2013 and China Securities Index 300 (CSI 300) from April 8, 2005 through June 30, 2013 to check whether an effective trading strategy could be found by using the performance measurements based on the return and Sharpe ratio. To correct for the influence of the data-snooping effect, we adopt the Superior Predictive Ability test to evaluate if there exists a trading rule that can significantly outperform the benchmark. The result shows that for SSCI, technical trading rules offer significant profitability, while for CSI 300, this ability is lost. We further partition the SSCI into two sub-series and find that the efficiency of technical trading in sub-series, which have exactly the same spanning period as that of CSI 300, is severely weakened. By testing the trading rules on both indexes with a five-year moving window, we find that during the financial bubble from 2005 to 2007, the effectiveness of technical trading rules is greatly improved. This is consistent with the predictive ability of technical trading rules which appears when the market is less efficient.

  15. Radiogenomics: predicting clinical normal tissue radiosensitivity

    DEFF Research Database (Denmark)

    Alsner, Jan

    2006-01-01

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

  16. Performance of thirteen clinical rules to distinguish bacterial and presumed viral meningitis in Vietnamese children.

    Directory of Open Access Journals (Sweden)

    Nguyen Tien Huy

    Full Text Available BACKGROUND AND PURPOSE: Successful outcomes from bacterial meningitis require rapid antibiotic treatment; however, unnecessary treatment of viral meningitis may lead to increased toxicities and expense. Thus, improved diagnostics are required to maximize treatment and minimize side effects and cost. Thirteen clinical decision rules have been reported to identify bacterial from viral meningitis. However, few rules have been tested and compared in a single study, while several rules are yet to be tested by independent researchers or in pediatric populations. Thus, simultaneous test and comparison of these rules are required to enable clinicians to select an optimal diagnostic rule for bacterial meningitis in settings and populations similar to ours. METHODS: A retrospective cross-sectional study was conducted at the Infectious Department of Pediatric Hospital Number 1, Ho Chi Minh City, Vietnam. The performance of the clinical rules was evaluated by area under a receiver operating characteristic curve (ROC-AUC using the method of DeLong and McNemar test for specificity comparison. RESULTS: Our study included 129 patients, of whom 80 had bacterial meningitis and 49 had presumed viral meningitis. Spanos's rule had the highest AUC at 0.938 but was not significantly greater than other rules. No rule provided 100% sensitivity with a specificity higher than 50%. Based on our calculation of theoretical sensitivity and specificity, we suggest that a perfect rule requires at least four independent variables that posses both sensitivity and specificity higher than 85-90%. CONCLUSIONS: No clinical decision rules provided an acceptable specificity (>50% with 100% sensitivity when applying our data set in children. More studies in Vietnam and developing countries are required to develop and/or validate clinical rules and more very good biomarkers are required to develop such a perfect rule.

  17. A prediction rule for shoulder pain related sick leave: a prospective cohort study

    Directory of Open Access Journals (Sweden)

    van der Heijden Geert JMG

    2006-12-01

    Full Text Available Abstract Background Shoulder pain is common in primary care, and has an unfavourable outcome in many patients. Information about predictors of shoulder pain related sick leave in workers is scarce and inconsistent. The objective was to develop a clinical prediction rule for calculating the risk of shoulder pain related sick leave for individual workers, during the 6 months following first consultation in general practice. Methods A prospective cohort study with 6 months follow-up was conducted among 350 workers with a new episode of shoulder pain. Potential predictors included the results of a physical examination, sociodemographic variables, disease characteristics (duration of symptoms, sick leave in the 2 months prior to consultation, pain intensity, disability, comorbidity, physical activity, physical work load, psychological factors, and the psychosocial work environment. The main outcome measure was sick leave during 6 months following first consultation in general practice. Results Response rate to the follow-up questionnaire at 6 months was 85%. During the 6 months after first consultation 30% (89/298 of the workers reported sick leave. 16% (47 reported 10 days sick leave or more. Sick leave during this period was predicted in a multivariable model by a longer duration of sick leave prior to consultation, more shoulder pain, a perceived cause of strain or overuse during regular activities, and co-existing psychological complaints. The discriminative ability of the prediction model was satisfactory with an area under the curve of 0.70 (95% CI 0.64–0.76. Conclusion Although 30% of all workers with shoulder pain reported sick leave during follow-up, the duration of sick leave was limited to a few days in most workers. We developed a prediction rule and a score chart that can be used by general practitioners and occupational health care providers to calculate the absolute risk of sick leave in individual workers with shoulder pain, which

  18. Research on spatial state conversion rule mining and stochastic predicting based on CA

    Science.gov (United States)

    Li, Xinyun; Kong, Xiangqiang

    2007-06-01

    Spatial dynamic prediction in GIS is the process of spatial calculation that infers the thematic maps in future according to the historical thematic maps, and it is space-time calculation from map to map. There is great application value that spatial dynamic prediction applied to the land planning, urban land-use planning and town planning, but there is some imperfect in method and technique at present. The main technical difficulty is excavation and expression of spatial state conversion rule. In allusion to the deficiency in spatial dynamic prediction using CA, the method which excavated spatial state conversion rule based on spatial data mining was put forward. Stochastic simulation mechanism was put into the prediction calculating based on state conversion rule. The result of prediction was more rational and the relation between the prediction steps and the time course was clearer. The method was applied to prediction of spatial structure change of urban land-use in Jinan. The Urban land-use change maps were predicted in 2006 and 2010 by using the land-use maps in 1998 and 2002. The result of this test was rational by analyzing.

  19. Re-Evaluation of Acid-Base Prediction Rules in Patients with Chronic Respiratory Acidosis

    Directory of Open Access Journals (Sweden)

    Tereza Martinu

    2003-01-01

    Full Text Available RATIONALE: The prediction rules for the evaluation of the acid-base status in patients with chronic respiratory acidosis, derived primarily from an experimental canine model, suggest that complete compensation should not occur. This appears to contradict frequent observations of normal or near-normal pH levels in patients with chronic hypercapnia.

  20. A study of diverse clinical decision support rule authoring environments and requirements for integration

    Directory of Open Access Journals (Sweden)

    Zhou Li

    2012-11-01

    Full Text Available Abstract Background Efficient rule authoring tools are critical to allow clinical Knowledge Engineers (KEs, Software Engineers (SEs, and Subject Matter Experts (SMEs to convert medical knowledge into machine executable clinical decision support rules. The goal of this analysis was to identify the critical success factors and challenges of a fully functioning Rule Authoring Environment (RAE in order to define requirements for a scalable, comprehensive tool to manage enterprise level rules. Methods The authors evaluated RAEs in active use across Partners Healthcare, including enterprise wide, ambulatory only, and system specific tools, with a focus on rule editors for reminder and medication rules. We conducted meetings with users of these RAEs to discuss their general experience and perceived advantages and limitations of these tools. Results While the overall rule authoring process is similar across the 10 separate RAEs, the system capabilities and architecture vary widely. Most current RAEs limit the ability of the clinical decision support (CDS interventions to be standardized, sharable, interoperable, and extensible. No existing system meets all requirements defined by knowledge management users. Conclusions A successful, scalable, integrated rule authoring environment will need to support a number of key requirements and functions in the areas of knowledge representation, metadata, terminology, authoring collaboration, user interface, integration with electronic health record (EHR systems, testing, and reporting.

  1. A clinical decision rule for the use of plain radiography in children after acute wrist injury: development and external validation of the Amsterdam Pediatric Wrist Rules

    Energy Technology Data Exchange (ETDEWEB)

    Slaar, Annelie; Maas, Mario; Rijn, Rick R. van [University of Amsterdam, Department of Radiology, Academic Medical Centre, Meibergdreef 9, 1105, AZ, Amsterdam (Netherlands); Walenkamp, Monique M.J.; Bentohami, Abdelali; Goslings, J.C. [University of Amsterdam, Trauma Unit, Department of Surgery, Academic Medical Centre, Amsterdam (Netherlands); Steyerberg, Ewout W. [Erasmus MC - University Medical Centre, Department of Public Health, Rotterdam (Netherlands); Jager, L.C. [University of Amsterdam, Emergency Department, Academic Medical Centre, Amsterdam (Netherlands); Sosef, Nico L. [Spaarne Hospital, Department of Surgery, Hoofddorp (Netherlands); Velde, Romuald van [Tergooi Hospitals, Department of Surgery, Hilversum (Netherlands); Ultee, Jan M. [Sint Lucas Andreas Hospital, Department of Surgery, Amsterdam (Netherlands); Schep, Niels W.L. [University of Amsterdam, Trauma Unit, Department of Surgery, Academic Medical Centre, Amsterdam (Netherlands); Maasstadziekenhuis Rotterdam, Department of Surgery, Rotterdam (Netherlands)

    2016-01-15

    In most hospitals, children with acute wrist trauma are routinely referred for radiography. To develop and validate a clinical decision rule to decide whether radiography in children with wrist trauma is required. We prospectively developed and validated a clinical decision rule in two study populations. All children who presented in the emergency department of four hospitals with pain following wrist trauma were included and evaluated for 18 clinical variables. The outcome was a wrist fracture diagnosed by plain radiography. Included in the study were 787 children. The prediction model consisted of six variables: age, swelling of the distal radius, visible deformation, distal radius tender to palpation, anatomical snuffbox tender to palpation, and painful or abnormal supination. The model showed an area under the receiver operator characteristics curve of 0.79 (95% CI: 0.76-0.83). The sensitivity and specificity were 95.9% and 37.3%, respectively. The use of this model would have resulted in a 22% absolute reduction of radiographic examinations. In a validation study, 7/170 fractures (4.1%, 95% CI: 1.7-8.3%) would have been missed using the decision model. The decision model may be a valuable tool to decide whether radiography in children after wrist trauma is required. (orig.)

  2. Behavioral rules of bank’s point-of-sale for segments description and scoring prediction

    Directory of Open Access Journals (Sweden)

    Mehdi Bizhani

    2011-04-01

    Full Text Available One of the important factors for the success of a bank industry is to monitor their customers' behavior and their point-of-sale (POS. The bank needs to know its merchants' behavior to find interesting ones to attract more transactions which results in the growth of its income and assets. The recency, frequency and monetary (RFM analysis is a famous approach for extracting behavior of customers and is a basis for marketing and customer relationship management (CRM, but it is not aligned enough for banking context. Introducing RF*M* in this article results in a better understanding of groups of merchants. Another artifact of RF*M* is RF*M* scoring which is applied in two ways, preprocessing the POSs and assigning behavioral meaningful labels to the merchants’ segments. The class labels and the RF*M* parameters are entered into a rule-based classification algorithm to achieve descriptive rules of the clusters. These descriptive rules outlined the boundaries of RF*M* parameters for each cluster. Since the rules are generated by a classification algorithm, they can also be applied for predicting the behavioral label and scoring of the upcoming POSs. These rules are called behavioral rules.

  3. Clinical predictive factors of pathologic tumor response

    Energy Technology Data Exchange (ETDEWEB)

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

    2012-09-15

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

  4. Fuzzy C-means Rule Generation for Fuzzy Entry Temperature Prediction in a Hot Strip Mill

    Institute of Scientific and Technical Information of China (English)

    JosAngel BARRIOS; Csar VILLANUEVA; Alberto CAVAZOS; Rafael COLS

    2016-01-01

    Variable estimation for finishing mill set-up in hot rolling is greatly affected by measurement uncertainties, variations in the incoming bar conditions and product changes.The fuzzy C-means algorithm was evaluated for rule-base generation for fuzzy and fuzzy grey-box temperature estimation.Experimental data were collected from a real-life mill and three different sets were randomly drawn.The first set was used for rule-generation,the second set was used for training those systems with learning capabilities,while the third one was used for validation.The perform-ance of the developed systems was evaluated by five performance measures applied over the prediction error with the validation set and was compared with that of the empirical rule-base fuzzy systems and the physical model used in plant.The results show that the fuzzy C-means generated rule-bases improve temperature estimation;however,the best results are obtained when fuzzy C-means algorithm,grey-box modeling and learning functions are combined. Application of fuzzy C-means rule generation brings improvement on performance of up to 72%.

  5. Integrating reasoning and clinical archetypes using OWL ontologies and SWRL rules.

    Science.gov (United States)

    Lezcano, Leonardo; Sicilia, Miguel-Angel; Rodríguez-Solano, Carlos

    2011-04-01

    Semantic interoperability is essential to facilitate the computerized support for alerts, workflow management and evidence-based healthcare across heterogeneous electronic health record (EHR) systems. Clinical archetypes, which are formal definitions of specific clinical concepts defined as specializations of a generic reference (information) model, provide a mechanism to express data structures in a shared and interoperable way. However, currently available archetype languages do not provide direct support for mapping to formal ontologies and then exploiting reasoning on clinical knowledge, which are key ingredients of full semantic interoperability, as stated in the SemanticHEALTH report [1]. This paper reports on an approach to translate definitions expressed in the openEHR Archetype Definition Language (ADL) to a formal representation expressed using the Ontology Web Language (OWL). The formal representations are then integrated with rules expressed with Semantic Web Rule Language (SWRL) expressions, providing an approach to apply the SWRL rules to concrete instances of clinical data. Sharing the knowledge expressed in the form of rules is consistent with the philosophy of open sharing, encouraged by archetypes. Our approach also allows the reuse of formal knowledge, expressed through ontologies, and extends reuse to propositions of declarative knowledge, such as those encoded in clinical guidelines. This paper describes the ADL-to-OWL translation approach, describes the techniques to map archetypes to formal ontologies, and demonstrates how rules can be applied to the resulting representation. We provide examples taken from a patient safety alerting system to illustrate our approach.

  6. A Business Intelligence Model to Predict Bankruptcy using Financial Domain Ontology with Association Rule Mining Algorithm

    CERN Document Server

    Martin, A; Venkatesan, Dr V Prasanna

    2011-01-01

    Today in every organization financial analysis provides the basis for understanding and evaluating the results of business operations and delivering how well a business is doing. This means that the organizations can control the operational activities primarily related to corporate finance. One way that doing this is by analysis of bankruptcy prediction. This paper develops an ontological model from financial information of an organization by analyzing the Semantics of the financial statement of a business. One of the best bankruptcy prediction models is Altman Z-score model. Altman Z-score method uses financial rations to predict bankruptcy. From the financial ontological model the relation between financial data is discovered by using data mining algorithm. By combining financial domain ontological model with association rule mining algorithm and Zscore model a new business intelligence model is developed to predict the bankruptcy.

  7. Estimating the risk of gestational diabetes mellitus : a clinical prediction model based on patient characteristics and medical history

    NARCIS (Netherlands)

    van Leeuwen, M.; Opmeer, B. C.; Zweers, E. J. K.; van Ballegooie, E.; ter Brugge, H. G.; de Valk, H. W.; Visser, G. H. A.; Mol, B. W. J.

    2010-01-01

    Objective To develop a clinical prediction rule that can help the clinician to identify women at high and low risk for gestational diabetes mellitus (GDM) early in pregnancy in order to improve the efficiency of GDM screening. Design We used data from a prospective cohort study to develop the clinic

  8. A programmable rules engine to provide clinical decision support using HTML forms.

    Science.gov (United States)

    Heusinkveld, J; Geissbuhler, A; Sheshelidze, D; Miller, R

    1999-01-01

    The authors have developed a simple method for specifying rules to be applied to information on HTML forms. This approach allows clinical experts, who lack the programming expertise needed to write CGI scripts, to construct and maintain domain-specific knowledge and ordering capabilities within WizOrder, the order-entry and decision support system used at Vanderbilt Hospital. The clinical knowledge base maintainers use HTML editors to create forms and spreadsheet programs for rule entry. A test environment has been developed which uses Netscape to display forms; the production environment displays forms using an embedded browser.

  9. Predictions for the Dirac Phase in the Neutrino Mixing Matrix and Sum Rules

    Science.gov (United States)

    Girardi, I.; Petcov, S. T.; Titov, A. V.

    2015-07-01

    Using the fact that the neutrino mixing matrix U = U†eUν, where Ue and Uv result from the diagonalisation of the charged lepton and neutrino mass matrices, we analyse the sum rules which the Dirac phase δ present in U satisfies when Uv has a form dictated by, or associated with, discrete symmetries and Ue has a “minimal” form (in terms of angles and phases it contains) that can provide the requisite corrections to Uv, so that reactor, atmospheric and solar neutrino mixing angles θ13, θ23 and θ12 have values compatible with the current data. The following symmetry forms are considered: i) tri-bimaximal (TBM), ii) bimaximal (BM) (or corresponding to the conservation of the lepton charge L' = Le — Lμ — Lτ (LC)), iii) golden ratio type A (GRA), iv) golden ratio type B (GRB), and v) hexagonal (HG). We investigate the predictions for 5 in the cases of TBM, BM (LC), GRA, GRB and HG forms using the exact and the leading order sum rules for cos δ proposed in the literature, taking into account also the uncertainties in the measured values of sin2 θ12, sin2 θ23 and sin2 θ13. This allows us, in particular, to assess the accuracy of the predictions for cos δ based on the leading order sum rules and its dependence on the values of the indicated neutrino mixing parameters when the latter are varied in their respective 3σ experimentally allowed ranges.

  10. 20 CFR 30.402 - What are the special rules for the services of clinical psychologists?

    Science.gov (United States)

    2010-04-01

    ... 20 Employees' Benefits 1 2010-04-01 2010-04-01 false What are the special rules for the services of clinical psychologists? 30.402 Section 30.402 Employees' Benefits OFFICE OF WORKERS' COMPENSATION PROGRAMS, DEPARTMENT OF LABOR ENERGY EMPLOYEES OCCUPATIONAL ILLNESS COMPENSATION PROGRAM ACT OF 2000 CLAIMS FOR COMPENSATION UNDER THE...

  11. 20 CFR 10.312 - What are the special rules for the services of clinical psychologists?

    Science.gov (United States)

    2010-04-01

    ... 20 Employees' Benefits 1 2010-04-01 2010-04-01 false What are the special rules for the services of clinical psychologists? 10.312 Section 10.312 Employees' Benefits OFFICE OF WORKERS' COMPENSATION PROGRAMS, DEPARTMENT OF LABOR FEDERAL EMPLOYEES' COMPENSATION ACT CLAIMS FOR COMPENSATION UNDER THE FEDERAL EMPLOYEES' COMPENSATION ACT, AS...

  12. A patient with a large pulmonary saddle embolus eluding both clinical gestalt and validated decision rules.

    Science.gov (United States)

    Hennessey, Adam; Setyono, Devy A; Lau, Wayne Bond; Fields, Jason Matthew

    2012-06-01

    We report a patient with chest pain who was classified as having low risk for pulmonary embolism with clinical gestalt and accepted clinical decision rules. An inadvertently ordered D-dimer and abnormal result, however, led to the identification of a large saddle embolus. This case illustrates the fallibility of even well-validated decision aids and that an embolism missed by these tools is not necessarily low risk or indicative of a low clot burden.

  13. Use of Feedback in Clinical Prediction

    Science.gov (United States)

    Schroeder, Harold E.

    1972-01-01

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

  14. Prediction of high-grade vesicoureteral reflux after pediatric urinary tract infection: external validation study of procalcitonin-based decision rule.

    Directory of Open Access Journals (Sweden)

    Sandrine Leroy

    Full Text Available BACKGROUND: Predicting vesico-ureteral reflux (VUR ≥3 at the time of the first urinary tract infection (UTI would make it possible to restrict cystography to high-risk children. We previously derived the following clinical decision rule for that purpose: cystography should be performed in cases with ureteral dilation and a serum procalcitonin level ≥0.17 ng/mL, or without ureteral dilatation when the serum procalcitonin level ≥0.63 ng/mL. The rule yielded a 86% sensitivity with a 46% specificity. We aimed to test its reproducibility. STUDY DESIGN: A secondary analysis of prospective series of children with a first UTI. The rule was applied, and predictive ability was calculated. RESULTS: The study included 413 patients (157 boys, VUR ≥3 in 11% from eight centers in five countries. The rule offered a 46% specificity (95% CI, 41-52, not different from the one in the derivation study. However, the sensitivity significantly decreased to 64% (95%CI, 50-76, leading to a difference of 20% (95%CI, 17-36. In all, 16 (34% patients among the 47 with VUR ≥3 were misdiagnosed by the rule. This lack of reproducibility might result primarily from a difference between derivation and validation populations regarding inflammatory parameters (CRP, PCT; the validation set samples may have been collected earlier than for the derivation one. CONCLUSIONS: The rule built to predict VUR ≥3 had a stable specificity (ie. 46%, but a decreased sensitivity (ie. 64% because of the time variability of PCT measurement. Some refinement may be warranted.

  15. Challenges and Insights in Using HIPAA Privacy Rule for Clinical Text Annotation

    Science.gov (United States)

    Kayaalp, Mehmet; Browne, Allen C.; Sagan, Pamela; McGee, Tyne; McDonald, Clement J.

    2015-01-01

    The Privacy Rule of Health Insurance Portability and Accountability Act (HIPAA) requires that clinical documents be stripped of personally identifying information before they can be released to researchers and others. We have been manually annotating clinical text since 2008 in order to test and evaluate an algorithmic clinical text de-identification tool, NLM Scrubber, which we have been developing in parallel. Although HIPAA provides some guidance about what must be de-identified, translating those guidelines into practice is not as straightforward, especially when one deals with free text. As a result we have changed our manual annotation labels and methods six times. This paper explains why we have made those annotation choices, which have been evolved throughout seven years of practice on this field. The aim of this paper is to start a community discussion towards developing standards for clinical text annotation with the end goal of studying and comparing clinical text de-identification systems more accurately. PMID:26958206

  16. 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.

  17. Prediction of Metabolic Pathway Involvement in Prokaryotic UniProtKB Data by Association Rule Mining

    KAUST Repository

    Boudellioua, Imane

    2016-07-08

    The widening gap between known proteins and their functions has encouraged the development of methods to automatically infer annotations. Automatic functional annotation of proteins is expected to meet the conflicting requirements of maximizing annotation coverage, while minimizing erroneous functional assignments. This trade-off imposes a great challenge in designing intelligent systems to tackle the problem of automatic protein annotation. In this work, we present a system that utilizes rule mining techniques to predict metabolic pathways in prokaryotes. The resulting knowledge represents predictive models that assign pathway involvement to UniProtKB entries. We carried out an evaluation study of our system performance using cross-validation technique. We found that it achieved very promising results in pathway identification with an F1-measure of 0.982 and an AUC of 0.987. Our prediction models were then successfully applied to 6.2 million UniProtKB/TrEMBL reference proteome entries of prokaryotes. As a result, 663,724 entries were covered, where 436,510 of them lacked any previous pathway annotations.

  18. Parenting Practices and Adolescent Risk Behavior: Rules on Smoking and Drinking Also Predict Cannabis Use and Early Sexual Debut

    OpenAIRE

    de Looze, Margaretha; van den Eijnden, Regina; Verdurmen, Jacqueline; Vermeulen-Smit, Evelien; Schulten, Ingrid; Vollebergh, Wilma; ter Bogt, Tom

    2012-01-01

    Previous research has provided considerable support for idea that increased parental support and control are strong determinants of lower prevalence levels of adolescent risk behavior. Much less is known on the association between specific parenting practices, such as concrete rules with respect to smoking and drinking and adolescent risk behavior. The present paper examined whether such concrete parental rules (1) have an effect on the targeted behaviors and (2) predict other, frequently co-...

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

    OpenAIRE

    Iniesta, R.; Malki, K.; Maier, W; Rietschel, M.; Mors, O; Hauser, J; Henigsberg, N.; Dernovsek, M. Z.; Souery, D.; Stahl, D.; Dobson, R.; Aitchison, K. J.; Farmer, A; Lewis, C.M.; McGuffin, P.

    2016-01-01

    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 remissio...

  20. Evaluation of Machine Learning and Rules-Based Approaches for Predicting Antimicrobial Resistance Profiles in Gram-negative Bacilli from Whole Genome Sequence Data

    Directory of Open Access Journals (Sweden)

    Mitchell Pesesky

    2016-11-01

    Full Text Available The time-to-result for culture-based microorganism recovery and phenotypic antimicrobial susceptibility testing necessitate initial use of empiric (frequently broad-spectrum antimicrobial therapy. If the empiric therapy is not optimal, this can lead to adverse patient outcomes and contribute to increasing antibiotic resistance in pathogens. New, more rapid technologies are emerging to meet this need. Many of these are based on identifying resistance genes, rather than directly assaying resistance phenotypes, and thus require interpretation to translate the genotype into treatment recommendations. These interpretations, like other parts of clinical diagnostic workflows, are likely to be increasingly automated in the future. We set out to evaluate the two major approaches that could be amenable to automation pipelines: rules-based methods and machine learning methods. The rules-based algorithm makes predictions based upon current, curated knowledge of Enterobacteriaceae resistance genes. The machine-learning algorithm predicts resistance and susceptibility based on a model built from a training set of variably resistant isolates. As our test set, we used whole genome sequence data from 78 clinical Enterobacteriaceae isolates, previously identified to represent a variety of phenotypes, from fully-susceptible to pan-resistant strains for the antibiotics tested. We tested three antibiotic resistance determinant databases for their utility in identifying the complete resistome for each isolate. The predictions of the rules-based and machine learning algorithms for these isolates were compared to results of phenotype-based diagnostics. The rules based and machine-learning predictions achieved agreement with standard-of-care phenotypic diagnostics of 89.0% and 90.3%, respectively, across twelve antibiotic agents from six major antibiotic classes. Several sources of disagreement between the algorithms were identified. Novel variants of known resistance

  1. Evaluation of Machine Learning and Rules-Based Approaches for Predicting Antimicrobial Resistance Profiles in Gram-negative Bacilli from Whole Genome Sequence Data.

    Science.gov (United States)

    Pesesky, Mitchell W; Hussain, Tahir; Wallace, Meghan; Patel, Sanket; Andleeb, Saadia; Burnham, Carey-Ann D; Dantas, Gautam

    2016-01-01

    The time-to-result for culture-based microorganism recovery and phenotypic antimicrobial susceptibility testing necessitates initial use of empiric (frequently broad-spectrum) antimicrobial therapy. If the empiric therapy is not optimal, this can lead to adverse patient outcomes and contribute to increasing antibiotic resistance in pathogens. New, more rapid technologies are emerging to meet this need. Many of these are based on identifying resistance genes, rather than directly assaying resistance phenotypes, and thus require interpretation to translate the genotype into treatment recommendations. These interpretations, like other parts of clinical diagnostic workflows, are likely to be increasingly automated in the future. We set out to evaluate the two major approaches that could be amenable to automation pipelines: rules-based methods and machine learning methods. The rules-based algorithm makes predictions based upon current, curated knowledge of Enterobacteriaceae resistance genes. The machine-learning algorithm predicts resistance and susceptibility based on a model built from a training set of variably resistant isolates. As our test set, we used whole genome sequence data from 78 clinical Enterobacteriaceae isolates, previously identified to represent a variety of phenotypes, from fully-susceptible to pan-resistant strains for the antibiotics tested. We tested three antibiotic resistance determinant databases for their utility in identifying the complete resistome for each isolate. The predictions of the rules-based and machine learning algorithms for these isolates were compared to results of phenotype-based diagnostics. The rules based and machine-learning predictions achieved agreement with standard-of-care phenotypic diagnostics of 89.0 and 90.3%, respectively, across twelve antibiotic agents from six major antibiotic classes. Several sources of disagreement between the algorithms were identified. Novel variants of known resistance factors and

  2. Knowledge discovery and sequence-based prediction of pandemic influenza using an integrated classification and association rule mining (CBA) algorithm.

    Science.gov (United States)

    Kargarfard, Fatemeh; Sami, Ashkan; Ebrahimie, Esmaeil

    2015-10-01

    Pandemic influenza is a major concern worldwide. Availability of advanced technologies and the nucleotide sequences of a large number of pandemic and non-pandemic influenza viruses in 2009 provide a great opportunity to investigate the underlying rules of pandemic induction through data mining tools. Here, for the first time, an integrated classification and association rule mining algorithm (CBA) was used to discover the rules underpinning alteration of non-pandemic sequences to pandemic ones. We hypothesized that the extracted rules can lead to the development of an efficient expert system for prediction of influenza pandemics. To this end, we used a large dataset containing 5373 HA (hemagglutinin) segments of the 2009 H1N1 pandemic and non-pandemic influenza sequences. The analysis was carried out for both nucleotide and protein sequences. We found a number of new rules which potentially present the undiscovered antigenic sites at influenza structure. At the nucleotide level, alteration of thymine (T) at position 260 was the key discriminating feature in distinguishing non-pandemic from pandemic sequences. At the protein level, rules including I233K, M334L were the differentiating features. CBA efficiently classifies pandemic and non-pandemic sequences with high accuracy at both the nucleotide and protein level. Finding hotspots in influenza sequences is a significant finding as they represent the regions with low antibody reactivity. We argue that the virus breaks host immunity response by mutation at these spots. Based on the discovered rules, we developed the software, "Prediction of Pandemic Influenza" for discrimination of pandemic from non-pandemic sequences. This study opens a new vista in discovery of association rules between mutation points during evolution of pandemic influenza.

  3. Parenting practices and adolescent risk behavior: rules on smoking and drinking also predict cannabis use and early sexual debut.

    Science.gov (United States)

    de Looze, Margaretha; van den Eijnden, Regina; Verdurmen, Jacqueline; Vermeulen-Smit, Evelien; Schulten, Ingrid; Vollebergh, Wilma; ter Bogt, Tom

    2012-12-01

    Previous research has provided considerable support for idea that increased parental support and control are strong determinants of lower prevalence levels of adolescent risk behavior. Much less is known on the association between specific parenting practices, such as concrete rules with respect to smoking and drinking and adolescent risk behavior. The present paper examined whether such concrete parental rules (1) have an effect on the targeted behaviors and (2) predict other, frequently co-occurring, risk behaviors (i.e., cannabis use and early sexual intercourse). These hypotheses were tested in a nationally representative sample of 12- to 16-year-old adolescents in the Netherlands. We found that both types of rules were associated with a lower prevalence of the targeted behaviors (i.e., smoking and drinking). In addition, independent of adolescent smoking and drinking behaviors, parental rules on smoking predicted a lower prevalence of cannabis use and early sexual intercourse, and parental rules on alcohol use also predicted a lower prevalence of early sexual intercourse. This study showed that concrete parental rule setting is more strongly related to lower levels of risk behaviors in adolescents compared to the more general parenting practices (i.e., support and control). Additionally, the effects of such rules do not only apply to the targeted behavior but extend to related behaviors as well. These findings are relevant to the public health domain and suggest that a single intervention program that addresses a limited number of concrete parenting practices, in combination with traditional support and control practices, may be effective in reducing risk behaviors in adolescence.

  4. Prediction of Early Recurrence of Liver Cancer by a Novel Discrete Bayes Decision Rule for Personalized Medicine

    Science.gov (United States)

    Ogihara, Hiroyuki

    2016-01-01

    We discuss a novel diagnostic method for predicting the early recurrence of liver cancer with high accuracy for personalized medicine. The difficulty with cancer treatment is that even if the types of cancer are the same, the cancers vary depending on the patient. Thus, remarkable attention has been paid to personalized medicine. Unfortunately, although the Tokyo Score, the Modified JIS, and the TNM classification have been proposed as liver scoring systems, none of these scoring systems have met the needs of clinical practice. In this paper, we convert continuous and discrete data to categorical data and keep the natively categorical data as is. Then, we propose a discrete Bayes decision rule that can deal with the categorical data. This may lead to its use with various types of laboratory data. Experimental results show that the proposed method produced a sensitivity of 0.86 and a specificity of 0.49 for the test samples. This suggests that our method may be superior to the well-known Tokyo Score, the Modified JIS, and the TNM classification in terms of sensitivity. Additional comparative study shows that if the numbers of test samples in two classes are the same, this method works well in terms of the F1 measure compared to the existing scoring methods. PMID:27800494

  5. Beyond Atomic Sizes and Hume-Rothery Rules: Understanding and Predicting High-Entropy Alloys

    Science.gov (United States)

    Troparevsky, M. Claudia; Morris, James R.; Daene, Markus; Wang, Yang; Lupini, Andrew R.; Stocks, G. Malcolm

    2015-09-01

    High-entropy alloys constitute a new class of materials that provide an excellent combination of strength, ductility, thermal stability, and oxidation resistance. Although they have attracted extensive attention due to their potential applications, little is known about why these compounds are stable or how to predict which combination of elements will form a single phase. In this article, we present a review of the latest research done on these alloys focusing on the theoretical models devised during the last decade. We discuss semiempirical methods based on the Hume-Rothery rules and stability criteria based on enthalpies of mixing and size mismatch. To provide insights into the electronic and magnetic properties of high-entropy alloys, we show the results of first-principles calculations of the electronic structure of the disordered solid-solution phase based on both Korringa-Kohn-Rostoker coherent potential approximation and large supercell models of example face-centered cubic and body-centered cubic systems. We also discuss in detail a model based on enthalpy considerations that can predict which elemental combinations are most likely to form a single-phase high-entropy alloy. The enthalpies are evaluated via first-principles "high-throughput" density functional theory calculations of the energies of formation of binary compounds, and therefore it requires no experimental or empirically derived input. The model correctly accounts for the specific combinations of metallic elements that are known to form single-phase alloys while rejecting similar combinations that have been tried and shown not to be single phase.

  6. Leveraging Bibliographic RDF Data for Keyword Prediction with Association Rule Mining (ARM

    Directory of Open Access Journals (Sweden)

    Nidhi Kushwaha

    2014-11-01

    Full Text Available The Semantic Web (Web 3.0 has been proposed as an efficient way to access the increasingly large amounts of data on the internet. The Linked Open Data Cloud project at present is the major effort to implement the concepts of the Seamtic Web, addressing the problems of inhomogeneity and large data volumes. RKBExplorer is one of many repositories implementing Open Data and contains considerable bibliographic information. This paper discusses bibliographic data, an important part of cloud data. Effective searching of bibiographic datasets can be a challenge as many of the papers residing in these databases do not have sufficient or comprehensive keyword information. In these cases however, a search engine based on RKBExplorer is only able to use information to retrieve papers based on author names and title of papers without keywords. In this paper we attempt to address this problem by using the data mining algorithm Association Rule Mining (ARM to develop keywords based on features retrieved from Resource Description Framework (RDF data within a bibliographic citation. We have demonstrate the applicability of this method for predicting missing keywords for bibliographic entries in several typical databases. −−−−− Paper presented at 1st International Symposium on Big Data and Cloud Computing Challenges (ISBCC-2014 March 27-28, 2014. Organized by VIT University, Chennai, India. Sponsored by BRNS.

  7. SAE: an R package for early stopping rules in clinical trials.

    Science.gov (United States)

    Bascoul-Mollevi, C; Laplanche, A; Le Deley, M C; Kramar, A

    2011-11-01

    In the case of an unexpected high frequency of serious adverse events (SAE), statistical methods are needed to help in the decision making process as to continuation of accrual to the trial. This paper describes an R package, named SAE that implements a method recently developed by defining stopping rules after each observed SAE. The package function control for excessive toxicity either during the trial at the observation of each SAE (function SAE) or during the planning phase of a clinical trial (function DESIGN). This description and the package documentation are complementary to help the users to apply the method. The main difficulty in the implementation of the method is the choice of a priori parameters. Data from an ongoing clinical trial are presented as an example to improve the understanding and the use of the package.

  8. Evaluation of Clinical Decision Rules for Bone Mineral Density Testing among White Women

    Directory of Open Access Journals (Sweden)

    Michael E. Anders

    2013-01-01

    Full Text Available Background. Osteoporosis is a devastating, insidious disease that causes skeletal fragility. Half of women will suffer osteoporotic fractures during their lifetimes. Many fractures occur needlessly, because of inattentiveness to assessment, diagnosis, prevention, and treatment of osteoporosis. Study Purpose. Study Purpose. To evaluate the discriminatory performance of clinical decision rules to determine the need to undergo bone mineral density testing. Methods. A nationally representative sample from the Third National Health and Nutrition Examination Survey consisted of 14,060 subjects who completed surveys, physical examinations, laboratory tests, and bone mineral density exams. Multivariable linear regression tested the correlation of covariates that composed the clinical decision rules with bone mineral density. Results. Increased age and decreased weight were variables in the final regression models for each gender and race/ethnicity. Among the indices, the Osteoporosis Self-Assessment Tool, which is composed of age and weight, performed best for White women. Study Implications. These results have implications for the prevention, assessment, diagnosis, and treatment of osteoporosis. The Osteoporosis Self-Assessment Tool performed best and is inexpensive and the least time consuming to implement.

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

    Science.gov (United States)

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

    2016-01-01

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

  10. A diagnosis-based clinical decision rule for spinal pain part 2: review of the literature

    Directory of Open Access Journals (Sweden)

    Hurwitz Eric L

    2008-08-01

    Full Text Available Abstract Background Spinal pain is a common and often disabling problem. The research on various treatments for spinal pain has, for the most part, suggested that while several interventions have demonstrated mild to moderate short-term benefit, no single treatment has a major impact on either pain or disability. There is great need for more accurate diagnosis in patients with spinal pain. In a previous paper, the theoretical model of a diagnosis-based clinical decision rule was presented. The approach is designed to provide the clinician with a strategy for arriving at a specific working diagnosis from which treatment decisions can be made. It is based on three questions of diagnosis. In the current paper, the literature on the reliability and validity of the assessment procedures that are included in the diagnosis-based clinical decision rule is presented. Methods The databases of Medline, Cinahl, Embase and MANTIS were searched for studies that evaluated the reliability and validity of clinic-based diagnostic procedures for patients with spinal pain that have relevance for questions 2 (which investigates characteristics of the pain source and 3 (which investigates perpetuating factors of the pain experience. In addition, the reference list of identified papers and authors' libraries were searched. Results A total of 1769 articles were retrieved, of which 138 were deemed relevant. Fifty-one studies related to reliability and 76 related to validity. One study evaluated both reliability and validity. Conclusion Regarding some aspects of the DBCDR, there are a number of studies that allow the clinician to have a reasonable degree of confidence in his or her findings. This is particularly true for centralization signs, neurodynamic signs and psychological perpetuating factors. There are other aspects of the DBCDR in which a lesser degree of confidence is warranted, and in which further research is needed.

  11. A Modified Mixing Rule for PSRK Model and Application for the Prediction of Vapor-Liquid Equilibria of Polymer Solutions

    Institute of Scientific and Technical Information of China (English)

    李敏; 王利生; J.Gmehling

    2004-01-01

    To extend the PSRK (predictive Soave-Redlich-Kwong equation of state) model to vapor-liquid equilibria of polymer solutions, a new EOS-gE mixing rule is applied in which the term ∑xiln(b/bi) in the PSRK mixing rule for the parameter a, and the combinatorial part in the original universal functional activity coefficient (UNIFAC) model are cancelled. To take into account the free volume contribution to the excess Gibbs energy in polymer solution, a quadratic mixing rule for the cross co-volume bij with an exponent equals to 1/2 is applied [bij1/2=1/2(bi1/2+bj1/2)]. The literature reported Soave-Redlich-Kwong equation of state (SRK EOS) parameters of i3 - 2- pure polymer are employed. The PSRK model with the modified mixing rule is used to predict the vapor-liquid equilibrium (VLE) of 37 solvent-polymer systems over a large range of temperature and pressure with satisfactory results.

  12. Social cognition is not reducible to theory of mind: when children use deontic rules to predict the behaviour of others.

    Science.gov (United States)

    Clément, Fabrice; Bernard, Stéphane; Kaufmann, Laurence

    2011-11-01

    The objective of this paper is to discuss whether children have a capacity for deontic reasoning that is irreducible to mentalizing. The results of two experiments point to the existence of such non-mentalistic understanding and prediction of the behaviour of others. In Study 1, young children (3- and 4-year-olds) were told different versions of classic false-belief tasks, some of which were modified by the introduction of a rule or a regularity. When the task (a standard change of location task) included a rule, the performance of 3-year-olds, who fail traditional false-belief tasks, significantly improved. In Study 2, 3-year-olds proved to be able to infer a rule from a social situation and to use it in order to predict the behaviour of a character involved in a modified version of the false-belief task. These studies suggest that rules play a central role in the social cognition of young children and that deontic reasoning might not necessarily involve mind reading.

  13. Validity and clinical utility of the simplified Wells rule for assessing clinical probability for the exclusion of pulmonary embolism

    NARCIS (Netherlands)

    Douma, R.A.; Gibson, N.S.; Gerdes, V.E.A.; Buller, H.R.; Wells, P.S.; Perrier, A.; Le Gal, G.

    2009-01-01

    The recently introduced simplified Wells rule for the exclusion of pulmonary embolism (PE) assigns only one point to the seven variables of the original Wells rule. This study was performed to independently validate the simplified Wells rule for the exclusion of PE. We retrospectively calculated the

  14. Common clinical practice versus new PRIM score in predicting coronary heart disease risk

    DEFF Research Database (Denmark)

    Frikke-Schmidt, Ruth; Tybjærg-Hansen, Anne; Schnohr, Peter;

    2010-01-01

    To compare the new Patient Rule Induction Method (PRIM) Score and common clinical practice with the Framingham Point Score for classification of individuals with respect to coronary heart disease (CHD) risk.......To compare the new Patient Rule Induction Method (PRIM) Score and common clinical practice with the Framingham Point Score for classification of individuals with respect to coronary heart disease (CHD) risk....

  15. Modifications to the HIPAA Privacy, Security, Enforcement, and Breach Notification rules under the Health Information Technology for Economic and Clinical Health Act and the Genetic Information Nondiscrimination Act; other modifications to the HIPAA rules.

    Science.gov (United States)

    2013-01-25

    The Department of Health and Human Services (HHS or ``the Department'') is issuing this final rule to: Modify the Health Insurance Portability and Accountability Act (HIPAA) Privacy, Security, and Enforcement Rules to implement statutory amendments under the Health Information Technology for Economic and Clinical Health Act (``the HITECH Act'' or ``the Act'') to strengthen the privacy and security protection for individuals' health information; modify the rule for Breach Notification for Unsecured Protected Health Information (Breach Notification Rule) under the HITECH Act to address public comment received on the interim final rule; modify the HIPAA Privacy Rule to strengthen the privacy protections for genetic information by implementing section 105 of Title I of the Genetic Information Nondiscrimination Act of 2008 (GINA); and make certain other modifications to the HIPAA Privacy, Security, Breach Notification, and Enforcement Rules (the HIPAA Rules) to improve their workability and effectiveness and to increase flexibility for and decrease burden on the regulated entities.

  16. A Prediction Rule to Stratify Mortality Risk of Patients with Pulmonary Tuberculosis.

    Science.gov (United States)

    Bastos, Helder Novais; Osório, Nuno S; Castro, António Gil; Ramos, Angélica; Carvalho, Teresa; Meira, Leonor; Araújo, David; Almeida, Leonor; Boaventura, Rita; Fragata, Patrícia; Chaves, Catarina; Costa, Patrício; Portela, Miguel; Ferreira, Ivo; Magalhães, Sara Pinto; Rodrigues, Fernando; Sarmento-Castro, Rui; Duarte, Raquel; Guimarães, João Tiago; Saraiva, Margarida

    2016-01-01

    Tuberculosis imposes high human and economic tolls, including in Europe. This study was conducted to develop a severity assessment tool for stratifying mortality risk in pulmonary tuberculosis (PTB) patients. A derivation cohort of 681 PTB cases was retrospectively reviewed to generate a model based on multiple logistic regression analysis of prognostic variables with 6-month mortality as the outcome measure. A clinical scoring system was developed and tested against a validation cohort of 103 patients. Five risk features were selected for the prediction model: hypoxemic respiratory failure (OR 4.7, 95% CI 2.8-7.9), age ≥50 years (OR 2.9, 95% CI 1.7-4.8), bilateral lung involvement (OR 2.5, 95% CI 1.4-4.4), ≥1 significant comorbidity-HIV infection, diabetes mellitus, liver failure or cirrhosis, congestive heart failure and chronic respiratory disease-(OR 2.3, 95% CI 1.3-3.8), and hemoglobin <12 g/dL (OR 1.8, 95% CI 1.1-3.1). A tuberculosis risk assessment tool (TReAT) was developed, stratifying patients with low (score ≤2), moderate (score 3-5) and high (score ≥6) mortality risk. The mortality associated with each group was 2.9%, 22.9% and 53.9%, respectively. The model performed equally well in the validation cohort. We provide a new, easy-to-use clinical scoring system to identify PTB patients with high-mortality risk in settings with good healthcare access, helping clinicians to decide which patients are in need of closer medical care during treatment.

  17. A Prediction Rule to Stratify Mortality Risk of Patients with Pulmonary Tuberculosis

    Science.gov (United States)

    Osório, Nuno S.; Castro, António Gil; Ramos, Angélica; Carvalho, Teresa; Meira, Leonor; Araújo, David; Almeida, Leonor; Boaventura, Rita; Fragata, Patrícia; Chaves, Catarina; Costa, Patrício; Portela, Miguel; Ferreira, Ivo; Magalhães, Sara Pinto; Rodrigues, Fernando; Sarmento-Castro, Rui; Duarte, Raquel; Guimarães, João Tiago; Saraiva, Margarida

    2016-01-01

    Tuberculosis imposes high human and economic tolls, including in Europe. This study was conducted to develop a severity assessment tool for stratifying mortality risk in pulmonary tuberculosis (PTB) patients. A derivation cohort of 681 PTB cases was retrospectively reviewed to generate a model based on multiple logistic regression analysis of prognostic variables with 6-month mortality as the outcome measure. A clinical scoring system was developed and tested against a validation cohort of 103 patients. Five risk features were selected for the prediction model: hypoxemic respiratory failure (OR 4.7, 95% CI 2.8–7.9), age ≥50 years (OR 2.9, 95% CI 1.7–4.8), bilateral lung involvement (OR 2.5, 95% CI 1.4–4.4), ≥1 significant comorbidity—HIV infection, diabetes mellitus, liver failure or cirrhosis, congestive heart failure and chronic respiratory disease–(OR 2.3, 95% CI 1.3–3.8), and hemoglobin <12 g/dL (OR 1.8, 95% CI 1.1–3.1). A tuberculosis risk assessment tool (TReAT) was developed, stratifying patients with low (score ≤2), moderate (score 3–5) and high (score ≥6) mortality risk. The mortality associated with each group was 2.9%, 22.9% and 53.9%, respectively. The model performed equally well in the validation cohort. We provide a new, easy-to-use clinical scoring system to identify PTB patients with high-mortality risk in settings with good healthcare access, helping clinicians to decide which patients are in need of closer medical care during treatment. PMID:27636095

  18. A study to derive a clinical decision rule for triage of emergency department patients with chest pain: design and methodology

    Directory of Open Access Journals (Sweden)

    Jaffe Allan

    2008-02-01

    Full Text Available Abstract Background Chest pain is the second most common chief complaint in North American emergency departments. Data from the U.S. suggest that 2.1% of patients with acute myocardial infarction and 2.3% of patients with unstable angina are misdiagnosed, with slightly higher rates reported in a recent Canadian study (4.6% and 6.4%, respectively. Information obtained from the history, 12-lead ECG, and a single set of cardiac enzymes is unable to identify patients who are safe for early discharge with sufficient sensitivity. The 2007 ACC/AHA guidelines for UA/NSTEMI do not identify patients at low risk for adverse cardiac events who can be safely discharged without provocative testing. As a result large numbers of low risk patients are triaged to chest pain observation units and undergo provocative testing, at significant cost to the healthcare system. Clinical decision rules use clinical findings (history, physical exam, test results to suggest a diagnostic or therapeutic course of action. Currently no methodologically robust clinical decision rule identifies patients safe for early discharge. Methods/design The goal of this study is to derive a clinical decision rule which will allow emergency physicians to accurately identify patients with chest pain who are safe for early discharge. The study will utilize a prospective cohort design. Standardized clinical variables will be collected on all patients at least 25 years of age complaining of chest pain prior to provocative testing. Variables strongly associated with the composite outcome acute myocardial infarction, revascularization, or death will be further analyzed with multivariable analysis to derive the clinical rule. Specific aims are to: i apply standardized clinical assessments to patients with chest pain, incorporating results of early cardiac testing; ii determine the inter-observer reliability of the clinical information; iii determine the statistical association between the clinical

  19. An improved predictive association rule based classifier using gain ratio and T-test for health care data diagnosis

    Indian Academy of Sciences (India)

    M Nandhini; S N Sivanandam

    2015-09-01

    Health care data diagnosis is a significant task that needs to be executed precisely, which requires much experience and domain-knowledge. Traditional symptoms-based disease diagnosis may perhaps lead to false presumptions. In recent times, Associative Classification (AC), the combination of association rule mining and classification has received attention in health care applications which desires maximum accuracy. Though several AC techniques exist, they lack in generating quality rules for building efficient associative classifier. This paper aims to enhance the accuracy of the existing CPAR (Classification based on Predictive Association Rule) algorithm by generating quality rules using Gain Ratio. Mostly, health care applications deal with high dimensional datasets. Existence of high dimensions causes unfair estimates in disease diagnosis. Dimensionality reduction is commonly applied as a preprocessing step before classification task to improve classifier accuracy. It eliminates redundant and insignificant dimensions by keeping good ones without information loss. In this work, dimensionality reductions by T-test and reduct sets (or simply reducts) are performed as preprocessing step before CPAR and CPAR using Gain Ratio (CPAR-GR) algorithms. An investigation was also performed to determine the impact of T-test and reducts on CPAR and CPAR-GR. This paper synthesizes the existing work carried out in AC, and also discusses the factors that influence the performance of CPAR and CPAR-GR. Experiments were conducted using six health care datasets from UCI machine learning repository. Based on the experiments, CPAR-GR with T-test yields better classification accuracy than CPAR.

  20. How the brain predicts people's behavior in relation to rules and desires. Evidence of a medio-prefrontal dissociation.

    Science.gov (United States)

    Corradi-Dell'Acqua, Corrado; Turri, Francesco; Kaufmann, Laurence; Clément, Fabrice; Schwartz, Sophie

    2015-09-01

    Forming and updating impressions about others is critical in everyday life and engages portions of the dorsomedial prefrontal cortex (dMPFC), the posterior cingulate cortex (PCC) and the amygdala. Some of these activations are attributed to "mentalizing" functions necessary to represent people's mental states, such as beliefs or desires. Evolutionary psychology and developmental studies, however, suggest that interpersonal inferences can also be obtained through the aid of deontic heuristics, which dictate what must (or must not) be done in given circumstances. We used fMRI and asked 18 participants to predict whether unknown characters would follow their desires or obey external rules. Participants had no means, at the beginning, to make accurate predictions, but slowly learned (throughout the experiment) each character's behavioral profile. We isolated brain regions whose activity changed during the experiment, as a neural signature of impression updating: whereas dMPFC was progressively more involved in predicting characters' behavior in relation to their desires, the medial orbitofrontal cortex and the amygdala were progressively more recruited in predicting rule-based behavior. Our data provide evidence of a neural dissociation between deontic inference and theory-of-mind (ToM), and support a differentiation of orbital and dorsal prefrontal cortex in terms of low- and high-level social cognition.

  1. Fuzzy rule-based prediction of lovastatin productivity in continuous mode using pellets of Aspergillus terreus in an airlift reactor

    Directory of Open Access Journals (Sweden)

    Kamakshi Gupta

    2009-12-01

    Full Text Available Lovastatin production using pellets of Aspergillus terreus was investigated in an airlift reactor. A fuzzy system has been developed for predicting the lovastatin productivity. Analysis of the effect of dilution rate and biomass concentration on the productivity of lovastatin was carried out and hence these were taken as inputs for the fuzzy system. The rule base has been developed using the conceptions of developmental processes in lovastatin production. The fuzzy system has been constructed on the basis of experimental results and operator’s knowledge. The values predicted for lovastatin productivity by the fuzzy system has been compared with the experimental data. The R squared value and mean squared error has been calculated to evaluate the quality of the fuzzy system. The performance measures show that the rule-based results of the fuzzy system is in accordance with the experimental results. The utilization of fuzzy system aided in the increase of lovastatin productivity by about 1.3 times when compared to previous empirical experimental results. Keywords: Lovastatin, airlift reactor, fuzzy rule-based system, Aspergillus terreus, continuous fermentation, pellets. Received: 27 November 2009 / Received in revised form: 18 January 2010, Accepted: 11 February 2010, Published online: 23 March 2010

  2. Major League Baseball pace-of-play rules and their influence on predicted muscle fatigue during simulated baseball games.

    Science.gov (United States)

    Sonne, Michael W L; Keir, Peter J

    2016-11-01

    Major League Baseball (MLB) has proposed rule changes to speed up baseball games. Reducing the time between pitches may impair recovery from fatigue. Fatigue is a known precursor to injury and may jeopardise joint stability. This study examined how fatigue accumulated during baseball games and how different pace of play initiatives may influence fatigue. Pitcher data were retrieved from a public database. A predictive model of muscle fatigue estimated muscle fatigue in 8 arm muscles. A self-selected pace (22.7 s), 12 s pace (Rule 8.04 from the MLB) and a 20 s rest (a pitch clock examined in the 2014 Arizona Fall League (AFL)) were examined. Significantly more muscle fatigue existed in both the AFL and Rule 8.04 conditions, when compared to the self-selected pace condition (5.01 ± 1.73%, 3.95 ± 1.20% and 3.70 ± 1.10% MVC force lost, respectively). Elevated levels of muscle fatigue are predicted in the flexor-pronator mass, which is responsible for providing elbow stability. Reduced effectiveness of the flexor-pronator mass may reduce the active contributions to joint rotational stiffness, increasing strain on the ulnar collateral ligament (UCL) and possibly increasing injury risk.

  3. Prefrontal and parietal activity is modulated by the rule complexity of inductive reasoning and can be predicted by a cognitive model.

    Science.gov (United States)

    Jia, Xiuqin; Liang, Peipeng; Shi, Lin; Wang, Defeng; Li, Kuncheng

    2015-01-01

    In neuroimaging studies, increased task complexity can lead to increased activation in task-specific regions or to activation of additional regions. How the brain adapts to increased rule complexity during inductive reasoning remains unclear. In the current study, three types of problems were created: simple rule induction (i.e., SI, with rule complexity of 1), complex rule induction (i.e., CI, with rule complexity of 2), and perceptual control. Our findings revealed that increased activations accompany increased rule complexity in the right dorsal lateral prefrontal cortex (DLPFC) and medial posterior parietal cortex (precuneus). A cognitive model predicted both the behavioral and brain imaging results. The current findings suggest that neural activity in frontal and parietal regions is modulated by rule complexity, which may shed light on the neural mechanisms of inductive reasoning.

  4. Clinical prediction and the idea of a population.

    Science.gov (United States)

    Armstrong, David

    2017-01-01

    Using an analysis of the British Medical Journal over the past 170 years, this article describes how changes in the idea of a population have informed new technologies of medical prediction. These approaches have largely replaced older ideas of clinical prognosis based on understanding the natural histories of the underlying pathologies. The 19(th)-century idea of a population, which provided a denominator for medical events such as births and deaths, was constrained in its predictive power by its method of enumerating individual bodies. During the 20(th) century, populations were increasingly constructed through inferential techniques based on patient groups and samples seen to possess variable characteristics. The emergence of these new virtual populations created the conditions for the emergence of predictive algorithms that are used to foretell our medical futures.

  5. FDA publishes conflict of interest rules for clinical trials. Food and Drug Administration.

    Science.gov (United States)

    James, J S

    1998-03-01

    The Food and Drug Administration (FDA) published new rules defining conflict of interests between drug companies and medical researchers and clinicians. Certain financial arrangements will need to be disclosed, although the FDA estimates that only one to ten percent of pharmaceutical companies will need to submit disclosures for one or more of their investigators. The purpose of the new rule is to prevent bias in safety and efficacy studies of drugs and medical devices. The full rule is published in the Federal Register.

  6. A clinical prediction score for upper extremity deep venous thrombosis.

    Science.gov (United States)

    Constans, Joel; Salmi, Louis-Rachid; Sevestre-Pietri, Marie-Antoinette; Perusat, Sophie; Nguon, Monika; Degeilh, Maryse; Labarere, Jose; Gattolliat, Olivier; Boulon, Carine; Laroche, Jean-Pierre; Le Roux, Philippe; Pichot, Olivier; Quéré, Isabelle; Conri, Claude; Bosson, Jean-Luc

    2008-01-01

    It was the objective of this study to design a clinical prediction score for the diagnosis of upper extremity deep venous thrombosis (UEDVT). A score was built by multivariate logistic regression in a sample of patients hospitalized for suspicion of UEDVT (derivation sample). It was validated in a second sample in the same university hospital, then in a sample from the multicenter OPTIMEV study that included both outpatients and inpatients. In these three samples, UEDVT diagnosis was objectively confirmed by ultrasound. The derivation sample included 140 patients among whom 50 had confirmed UEDVT, the validation sample included 103 patients among whom 46 had UEDVT, and the OPTIMEV sample included 214 patients among whom 65 had UEDVT. The clinical score identified a combination of four items (venous material, localized pain, unilateral pitting edema and other diagnosis as plausible). One point was attributed to each item (positive for the first 3 and negative for the other diagnosis). A score of -1 or 0 characterized low probability patients, a score of 1 identified intermediate probability patients, and a score of 2 or 3 identified patients with high probability. Low probability score identified a prevalence of UEDVT of 12, 9 and 13%, respectively, in the derivation, validation and OPTIMEV samples. High probability score identified a prevalence of UEDVT of 70, 64 and 69% respectively. In conclusion we propose a simple score to calculate clinical probability of UEDVT. This score might be a useful test in clinical trials as well as in clinical practice.

  7. Towards computerizing intensive care sedation guidelines: design of a rule-based architecture for automated execution of clinical guidelines

    Directory of Open Access Journals (Sweden)

    Kerckhove Wannes

    2010-01-01

    Full Text Available Abstract Background Computerized ICUs rely on software services to convey the medical condition of their patients as well as assisting the staff in taking treatment decisions. Such services are useful for following clinical guidelines quickly and accurately. However, the development of services is often time-consuming and error-prone. Consequently, many care-related activities are still conducted based on manually constructed guidelines. These are often ambiguous, which leads to unnecessary variations in treatments and costs. The goal of this paper is to present a semi-automatic verification and translation framework capable of turning manually constructed diagrams into ready-to-use programs. This framework combines the strengths of the manual and service-oriented approaches while decreasing their disadvantages. The aim is to close the gap in communication between the IT and the medical domain. This leads to a less time-consuming and error-prone development phase and a shorter clinical evaluation phase. Methods A framework is proposed that semi-automatically translates a clinical guideline, expressed as an XML-based flow chart, into a Drools Rule Flow by employing semantic technologies such as ontologies and SWRL. An overview of the architecture is given and all the technology choices are thoroughly motivated. Finally, it is shown how this framework can be integrated into a service-oriented architecture (SOA. Results The applicability of the Drools Rule language to express clinical guidelines is evaluated by translating an example guideline, namely the sedation protocol used for the anaesthetization of patients, to a Drools Rule Flow and executing and deploying this Rule-based application as a part of a SOA. The results show that the performance of Drools is comparable to other technologies such as Web Services and increases with the number of decision nodes present in the Rule Flow. Most delays are introduced by loading the Rule Flows

  8. Integration of Rule Based Expert Systems and Case Based Reasoning in an Acute Bacterial Meningitis Clinical Decision Support System

    CERN Document Server

    Cabrera, Mariana Maceiras

    2010-01-01

    This article presents the results of the research carried out on the development of a medical diagnostic system applied to the Acute Bacterial Meningitis, using the Case Based Reasoning methodology. The research was focused on the implementation of the adaptation stage, from the integration of Case Based Reasoning and Rule Based Expert Systems. In this adaptation stage we use a higher level RBC that stores and allows reutilizing change experiences, combined with a classic rule-based inference engine. In order to take into account the most evident clinical situation, a pre-diagnosis stage is implemented using a rule engine that, given an evident situation, emits the corresponding diagnosis and avoids the complete process.

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

    Science.gov (United States)

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

    2016-06-01

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

  10. Sensitivity of palm print, modified mallampati score and 3-3-2 rule in prediction of difficult intubation

    Directory of Open Access Journals (Sweden)

    Ata Mahmoodpoor

    2013-01-01

    Full Text Available Background: This study evaluated the performance of modified Mallampati score, 3-3-2 rule and palm print in prediction of difficult intubation. Methods: In a prospective descriptive study, data from 500 patients scheduled for elective surgery under general anesthesia were collected. An anesthesiologist evaluated the airway using mentioned tests and another anesthesiologist evaluated difficult intubation. Laryngoscopic views were determined by Cormack and Lehane score. Grades 3 and 4 were defined as difficult intubation. Sensitivity, specificity, positive predictive value, negative predictive value and Youden index were determined for all tests. Results: Difficult intubation was reported in 8.9% of the patients. There was a significant correlation between body mass index and difficult intubation (P : 0.004; however, other demographic characteristics didn′t have a significant correlation with difficult intubation. Among three tests, palm print was of highest specificity (96.46% and modified Mallampati of highest sensitivity (98.40%. In a combination of the tests, the highest specificity, sensitivity and Youden index were observed when using all three tests together. Conclusions: Palm print has a high specificity for prediction of difficult intubation, but the best way for prediction of difficult intubation is using all three tests together.

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

    Institute of Scientific and Technical Information of China (English)

    Carvell T Nguyen; Michael W Kattan

    2012-01-01

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

  12. Mass Predictions of Open-Flavour Hybrid Mesons from QCD Sum Rules

    CERN Document Server

    Ho, Jason; Steele, Tom

    2016-01-01

    Within QCD, colourless states may be constructed corresponding to exotic matter outside of the traditional quark model. Experiments have recently observed tetraquark and pentaquark states, but no definitive hybrid meson signals have been observed. With the construction of the PANDA experiment at FAIR, and with full commissioning of the GlueX experiment at JLab expected to be completed this year, the opportunity for the observation of hybrid mesons has greatly increased. However, theoretical calculations are necessary to ascertain the identity of any experimental resonances that may be observed. We present selected QCD sum rule results from a full range of quantum numbers for open-flavour hybrid mesons with heavy valence quark content, including non-perturbative condensate contributions up to six-dimensions.

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

    Directory of Open Access Journals (Sweden)

    Nesrin Alharthy

    2015-01-01

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

  14. Do Institutional Logics Predict Interpretation of Contract Rules at the Dental Chair-side?

    DEFF Research Database (Denmark)

    Harris, Rebecca; Brown, Stephen; Holt, Robin

    2014-01-01

    In quasi-markets, contracts find purchasers influencing health care providers, although problems exist where providers use personal bias and heuristics to respond to written agreements, tending towards the moral hazard of opportunism. Previous research on quasi-market contracts typically...... earlier qualitative work where we identified four institutional logics in English general dental practice, and six dental contract areas where there was scope for opportunism; in 2013 we surveyed 924 dentists to investigate these logics and whether they had predictive purchase over dentists' chair......-side behaviour. Factor analysis involving 300 responses identified four logics entwined in (often technical) behaviour: entrepreneurial commercialism, duty to staff and patients, managerialism, public good....

  15. Do institutional logics predict interpretation of contract rules at the dental chair-side?

    Science.gov (United States)

    Harris, Rebecca; Brown, Stephen; Holt, Robin; Perkins, Elizabeth

    2014-01-01

    In quasi-markets, contracts find purchasers influencing health care providers, although problems exist where providers use personal bias and heuristics to respond to written agreements, tending towards the moral hazard of opportunism. Previous research on quasi-market contracts typically understands opportunism as fully rational, individual responses selecting maximally efficient outcomes from a set of possibilities. We take a more emotive and collective view of contracting, exploring the influence of institutional logics in relation to the opportunistic behaviour of dentists. Following earlier qualitative work where we identified four institutional logics in English general dental practice, and six dental contract areas where there was scope for opportunism; in 2013 we surveyed 924 dentists to investigate these logics and whether they had predictive purchase over dentists' chair-side behaviour. Factor analysis involving 300 responses identified four logics entwined in (often technical) behaviour: entrepreneurial commercialism, duty to staff and patients, managerialism, public good. PMID:25441320

  16. On the Rule of Mixtures for Predicting Stress-Softening and Residual Strain Effects in Biological Tissues and Biocompatible Materials

    Directory of Open Access Journals (Sweden)

    Alex Elías-Zúñiga

    2014-01-01

    Full Text Available In this work, we use the rule of mixtures to develop an equivalent material model in which the total strain energy density is split into the isotropic part related to the matrix component and the anisotropic energy contribution related to the fiber effects. For the isotropic energy part, we select the amended non-Gaussian strain energy density model, while the energy fiber effects are added by considering the equivalent anisotropic volumetric fraction contribution, as well as the isotropized representation form of the eight-chain energy model that accounts for the material anisotropic effects. Furthermore, our proposed material model uses a phenomenological non-monotonous softening function that predicts stress softening effects and has an energy term, derived from the pseudo-elasticity theory, that accounts for residual strain deformations. The model’s theoretical predictions are compared with experimental data collected from human vaginal tissues, mice skin, poly(glycolide-co-caprolactone (PGC25 3-0 and polypropylene suture materials and tracheal and brain human tissues. In all cases examined here, our equivalent material model closely follows stress-softening and residual strain effects exhibited by experimental data.

  17. Physiological functions and clinical implications of the N-end rule pathway.

    Science.gov (United States)

    Liu, Yujiao; Liu, Chao; Dong, Wen; Li, Wei

    2016-09-01

    The N-end rule pathway is a unique branch of the ubiquitin-proteasome system in which the determination of a protein's half-life is dependent on its N-terminal residue. The N-terminal residue serves as the degradation signal of a protein and thus called N-degron. N-degron can be recognized and modifed by several steps of post-translational modifications, such as oxidation, deamination, arginylation or acetylation, it then polyubiquitinated by the N-recognin for degradation. The molecular basis of the N-end rule pathway has been elucidated and its physiological functions have been revealed in the past 30 years. This pathway is involved in several biological aspects, including transcription, differentiation, chromosomal segregation, genome stability, apoptosis, mitochondrial quality control, cardiovascular development, neurogenesis, carcinogenesis, and spermatogenesis. Disturbance of this pathway often causes the failure of these processes, resulting in some human diseases. This review summarized the physiological functions of the N-end rule pathway, introduced the related biological processes and diseases, with an emphasis on the inner link between this pathway and certain symptoms.

  18. Implementation of virtual medical record object model for a standards-based clinical decision support rule engine.

    Science.gov (United States)

    Huang, Christine; Noirot, Laura A; Heard, Kevin M; Reichley, Richard M; Dunagan, Wm Claiborne; Bailey, Thomas C

    2006-01-01

    The Virtual Medical Record (vMR) is a structured data model for representing individual patient informations. Our implementation of vMR is based on HL7 Reference Information Model (RIM) v2.13 from which a minimum set of objects and attributes are selected to meet the requirement of a clinical decision support (CDS) rule engine. Our success of mapping local patient data to the vMR model and building a vMR adaptor middle layer demonstrate the feasibility and advantages of implementing a vMR in a portable CDS solution.

  19. Clinical prediction and diagnosis of neurosyphilis in HIV-infected patients with early Syphilis.

    Science.gov (United States)

    Dumaresq, Jeannot; Langevin, Stéphanie; Gagnon, Simon; Serhir, Bouchra; Deligne, Benoît; Tremblay, Cécile; Tsang, Raymond S W; Fortin, Claude; Coutlée, François; Roger, Michel

    2013-12-01

    The diagnosis of neurosyphilis (NS) is a challenge, especially in HIV-infected patients, and the criteria for deciding when to perform a lumbar puncture (LP) in HIV-infected patients with syphilis are controversial. We retrospectively reviewed demographic, clinical, and laboratory data from 122 cases of HIV-infected patients with documented early syphilis who underwent an LP to rule out NS, and we evaluated 3 laboratory-developed validated real-time PCR assays, the Treponema pallidum particle agglutination (TPPA) assay, the fluorescent treponemal antibody absorption (FTA-ABS) assay, and the line immunoassay INNO-LIA Syphilis, for the diagnosis of NS from cerebrospinal fluid (CSF) samples of these patients. NS was defined by a reactive CSF-VDRL test result and/or a CSF white blood cell (WBC) count of >20 cells/μl. Thirty of the 122 patients (24.6%) had early NS. Headache, visual symptoms, a CD4 cell count of HIV-1 RNA count of ≥50 copies/ml, were associated with NS in multivariate analysis (P = diagnosis of NS, the PCR, FTA-ABS, TPPA, and INNO-LIA assays had sensitivities of 58%, 100%, 68%, and 100%, specificities of 67%, 12%, 49%, and 13%, and negative predictive values of 85%, 100%, 84%, and 100%, respectively. Visual disturbances, headache, uncontrolled HIV-1 viremia, and a CD4 cell count of HIV-infected patients with early syphilis, while blood serum RPR titers were not; therefore, RPR titers should not be used as the sole criterion for deciding whether to perform an LP in early syphilis. When applied to CSF samples, the INNO-LIA Syphilis assay easily helped rule out NS.

  20. Clinical prediction rule for RSV bronchiolitis in healthy newborns: prognostic birth cohort study.

    NARCIS (Netherlands)

    Houben, M.L.; Bont, L.; Wilbrink, B.; Belderbos, M.E.; Kimpen, J.L.L.; Visser, G.H.; Rovers, M.M.

    2011-01-01

    OBJECTIVE: Our goal was to determine predictors of respiratory syncytial virus (RSV) lower respiratory tract infection (LRTI) among healthy newborns. METHODS: In this prospective birth cohort study, 298 healthy term newborns born in 2 large hospitals in the Netherlands were monitored throughout the

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

    Science.gov (United States)

    Carlson, Rae

    1969-01-01

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

  2. Software to compute and conduct sequential Bayesian phase I or II dose-ranging clinical trials with stopping rules.

    Science.gov (United States)

    Zohar, Sarah; Latouche, Aurelien; Taconnet, Mathieu; Chevret, Sylvie

    2003-10-01

    The aim of dose-ranging phase I (resp. phase II) clinical trials is to rapidly identify the maximum tolerated dose (MTD) (resp., minimal effective dose (MED)) of a new drug or combination. For the conduct and analysis of such trials, Bayesian approaches such as the Continual Reassessment Method (CRM) have been proposed, based on a sequential design and analysis up to a completed fixed sample size. To optimize sample sizes, Zohar and Chevret have proposed stopping rules (Stat. Med. 20 (2001) 2827), the computation of which is not provided by available softwares. We present in this paper a user-friendly software for the design and analysis of these Bayesian Phase I (resp. phase II) dose-ranging Clinical Trials (BPCT). It allows to carry out the CRM with stopping rules or not, from the planning of the trial, with choice of model parameterization based on its operating characteristics, up to the sequential conduct and analysis of the trial, with estimation at stopping of the MTD (resp. MED) of the new drug or combination.

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

    NARCIS (Netherlands)

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

    2015-01-01

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

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

    Science.gov (United States)

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

  5. 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.

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

    Institute of Scientific and Technical Information of China (English)

    Robert A.Beckman; Cong Chen

    2013-01-01

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

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

    DEFF Research Database (Denmark)

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

    2011-01-01

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

  8. Predicting Future Clinical Adjustment from Treatment Outcome and Process Variables.

    Science.gov (United States)

    Patterson, G. R.; Forgatch, Marion S.

    1995-01-01

    Issues related to the use of outcome and process data from the treatment of antisocial children to predict future childhood adjustment were examined through a study of 69 children. Data supported the hypothesis that measures of processes thought to produce changes in child behavior would serve to predict future adjustment. (SLD)

  9. Clinical rules in hospital pharmacy practice to prevent adverse drug events

    NARCIS (Netherlands)

    Rommers, Mirjam Kristien

    2014-01-01

    Adverse drug events (ADEs) refer to any injury from the use of a drug. ADEs occur frequently in hospitalized patients and a substantial proportion are considered preventable. A method to prevent ADEs is computerized physician order entry (CPOE) combined with a clinical decision support system (CDSS)

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

    Directory of Open Access Journals (Sweden)

    Jorge Milhem Haddad

    2016-02-01

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

  11. Sharing clinical research data in the United States under the Health Insurance Portability and Accountability Act and the Privacy Rule.

    Science.gov (United States)

    Miller, James D

    2010-11-19

    Sharing of final research data from clinical research is an essential part of the scientific method. The U.S. National Institutes of Health require some grant applications to include plans for sharing final research data, which it defines as the factual materials necessary to document, support, and validate research findings. In the U.S., however, the Privacy Rule adopted under the Health Insurance Portability and Accountability Act impedes the sharing of final research data. In most situations, final research data may be shared only where all information that could possibly be used to identify the subject has been deleted, or where the subject has given authorization for specific research, or an Institutional Review Board has granted a waiver.

  12. Sharing clinical research data in the United States under the health insurance portability and accountability act and the privacy rule

    Directory of Open Access Journals (Sweden)

    Miller James D

    2010-11-01

    Full Text Available Abstract Sharing of final research data from clinical research is an essential part of the scientific method. The U.S. National Institutes of Health require some grant applications to include plans for sharing final research data, which it defines as the factual materials necessary to document, support, and validate research findings. In the U.S., however, the Privacy Rule adopted under the Health Insurance Portability and Accountability Act impedes the sharing of final research data. In most situations, final research data may be shared only where all information that could possibly be used to identify the subject has been deleted, or where the subject has given authorization for specific research, or an Institutional Review Board has granted a waiver.

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

    Science.gov (United States)

    Chu, Stephen J

    2007-08-01

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

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

    Directory of Open Access Journals (Sweden)

    Douglas D Thompson

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

  15. Reporting and methods in clinical prediction research: a systematic review.

    Directory of Open Access Journals (Sweden)

    Walter Bouwmeester

    Full Text Available BACKGROUND: We investigated the reporting and methods of prediction studies, focusing on aims, designs, participant selection, outcomes, predictors, statistical power, statistical methods, and predictive performance measures. METHODS AND FINDINGS: We used a full hand search to identify all prediction studies published in 2008 in six high impact general medical journals. We developed a comprehensive item list to systematically score conduct and reporting of the studies, based on recent recommendations for prediction research. Two reviewers independently scored the studies. We retrieved 71 papers for full text review: 51 were predictor finding studies, 14 were prediction model development studies, three addressed an external validation of a previously developed model, and three reported on a model's impact on participant outcome. Study design was unclear in 15% of studies, and a prospective cohort was used in most studies (60%. Descriptions of the participants and definitions of predictor and outcome were generally good. Despite many recommendations against doing so, continuous predictors were often dichotomized (32% of studies. The number of events per predictor as a measure of statistical power could not be determined in 67% of the studies; of the remainder, 53% had fewer than the commonly recommended value of ten events per predictor. Methods for a priori selection of candidate predictors were described in most studies (68%. A substantial number of studies relied on a p-value cut-off of p<0.05 to select predictors in the multivariable analyses (29%. Predictive model performance measures, i.e., calibration and discrimination, were reported in 12% and 27% of studies, respectively. CONCLUSIONS: The majority of prediction studies in high impact journals do not follow current methodological recommendations, limiting their reliability and applicability.

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

    Science.gov (United States)

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

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

  17. Habit persistence, non-separability between consumption and leisure, or rule-of thumb consumers: which accounts for the predictability of consumption growth?

    OpenAIRE

    Michael T. Kiley

    2007-01-01

    Consumption growth is predictable, a basic violation of the permanent-income hypothesis. This paper examines three possible explanations: rule-of-thumb behavior, in which households allow consumption to track per-period income flows rather than permanent income; habit persistence; and non-separability in preferences over consumption and leisure. The data appear most consistent with non-separable preferences over consumption and leisure.

  18. Modifications to the Patient Rule-Induction Method that utilize non-additive combinations of genetic and environmental effects to define partitions that predict ischemic heart disease

    DEFF Research Database (Denmark)

    Dyson, Greg; Frikke-Schmidt, Ruth; Nordestgaard, Børge G;

    2009-01-01

    This article extends the Patient Rule-Induction Method (PRIM) for modeling cumulative incidence of disease developed by Dyson et al. (Genet Epidemiol 31:515-527) to include the simultaneous consideration of non-additive combinations of predictor variables, a significance test of each combination...... that assesses the utility of genetic variants in predicting the presence of ischemic heart disease beyond the established risk factors....

  19. Accurate Predictions of Mean Geomagnetic Dipole Excursion and Reversal Frequencies, Mean Paleomagnetic Field Intensity, and the Radius of Earth's Core Using McLeod's Rule

    Science.gov (United States)

    Voorhies, Coerte V.; Conrad, Joy

    1996-01-01

    The geomagnetic spatial power spectrum R(sub n)(r) is the mean square magnetic induction represented by degree n spherical harmonic coefficients of the internal scalar potential averaged over the geocentric sphere of radius r. McLeod's Rule for the magnetic field generated by Earth's core geodynamo says that the expected core surface power spectrum (R(sub nc)(c)) is inversely proportional to (2n + 1) for 1 less than n less than or equal to N(sub E). McLeod's Rule is verified by locating Earth's core with main field models of Magsat data; the estimated core radius of 3485 kn is close to the seismologic value for c of 3480 km. McLeod's Rule and similar forms are then calibrated with the model values of R(sub n) for 3 less than or = n less than or = 12. Extrapolation to the degree 1 dipole predicts the expectation value of Earth's dipole moment to be about 5.89 x 10(exp 22) Am(exp 2)rms (74.5% of the 1980 value) and the expected geomagnetic intensity to be about 35.6 (mu)T rms at Earth's surface. Archeo- and paleomagnetic field intensity data show these and related predictions to be reasonably accurate. The probability distribution chi(exp 2) with 2n+1 degrees of freedom is assigned to (2n + 1)R(sub nc)/(R(sub nc). Extending this to the dipole implies that an exceptionally weak absolute dipole moment (less than or = 20% of the 1980 value) will exist during 2.5% of geologic time. The mean duration for such major geomagnetic dipole power excursions, one quarter of which feature durable axial dipole reversal, is estimated from the modern dipole power time-scale and the statistical model of excursions. The resulting mean excursion duration of 2767 years forces us to predict an average of 9.04 excursions per million years, 2.26 axial dipole reversals per million years, and a mean reversal duration of 5533 years. Paleomagnetic data show these predictions to be quite accurate. McLeod's Rule led to accurate predictions of Earth's core radius, mean paleomagnetic field

  20. Somatic cell count distributions during lactation predict clinical mastitis

    NARCIS (Netherlands)

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

    2004-01-01

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

  1. Gene expression profiling predicts clinical outcome of breast cancer

    NARCIS (Netherlands)

    Veer, L.J. van 't; Dai, H.; Vijver, H. van de; He, Y.D.; Hart, A.A.M.; Mao, M.; Peterse, H.L.; Kooy, K. van der; Marton, M.J.; Witteveen, A.T.; Schreiber, G.J.; Kerkhoven, R.M.; Roberts, C.; Linsley, P.S.; Bernards, R.A.; Friend, S.H.

    2002-01-01

    Breast cancer patients with the same stage of disease can have markedly different treatment responses and overall outcome. The strongest predictors for metastases (for example, lymph node status and histological grade) fail to classify accurately breast tumours according to their clinical behaviour.

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

    Science.gov (United States)

    Chen, Xi; Wang, Lily; Ishwaran, Hemant

    2010-09-01

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

  3. Evaluation of the usefulness of 2 prediction models of clinical prediction models in physical therapy: a qualitative process evaluation.

    NARCIS (Netherlands)

    Oort, L. van; Verhagen, A.F.; Koes, B.; Vet, R. de; Anema, H.; Heymans, M.

    2014-01-01

    OBJECTIVE: The purposes of this study were to (1) evaluate the usefulness of 2 prediction models by assessing the actual use and advantages/disadvantages of application in daily clinical practice and (2) propose recommendations to enhance their implementation. METHODS: Physical therapists working in

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

    NARCIS (Netherlands)

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

    2002-01-01

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

  5. Establishing equivalence for microbial-growth-inhibitory effects ("iso-hurdle rules") by analyzing disparate listeria monocytogenes data with a gamma-type predictive model.

    Science.gov (United States)

    Pujol, Laure; Kan-King-Yu, Denis; Le Marc, Yvan; Johnston, Moira D; Rama-Heuzard, Florence; Guillou, Sandrine; McClure, Peter; Membré, Jeanne-Marie

    2012-02-01

    Preservative factors act as hurdles against microorganisms by inhibiting their growth; these are essential control measures for particular food-borne pathogens. Different combinations of hurdles can be quantified and compared to each other in terms of their inhibitory effect ("iso-hurdle"). We present here a methodology for establishing microbial iso-hurdle rules in three steps: (i) developing a predictive model based on existing but disparate data sets, (ii) building an experimental design focused on the iso-hurdles using the model output, and (iii) validating the model and the iso-hurdle rules with new data. The methodology is illustrated with Listeria monocytogenes. Existing data from industry, a public database, and the literature were collected and analyzed, after which a total of 650 growth rates were retained. A gamma-type model was developed for the factors temperature, pH, a(w), and acetic, lactic, and sorbic acids. Three iso-hurdle rules were assessed (40 logcount curves generated): salt replacement by addition of organic acids, sorbic acid replacement by addition of acetic and lactic acid, and sorbic acid replacement by addition of lactic/acetic acid and salt. For the three rules, the growth rates were equivalent in the whole experimental domain (γ from 0.1 to 0.5). The lag times were also equivalent in the case of mild inhibitory conditions (γ ≥ 0.2), while they were longer in the presence of salt than acids under stress conditions (γ microbial safety and stability.

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

    Science.gov (United States)

    Hey, Spencer Phillips

    2015-07-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    1994-10-01

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

  8. Interactions between parental alcohol-specific rules and risk personalities in the prediction of adolescent alcohol use

    NARCIS (Netherlands)

    Janssen, T.; Larsen, H.; Peeters, M.; Pronk, T.; Vollebergh, W.A.M.; Wiers, R.W.

    2014-01-01

    Aims: To examine the impact of an important context variable (alcohol-specific parental rules) and an important person variable (risky personality traits) and their interaction on prospective adolescent drinking. Methods: Participants were 252 adolescents, 67.9% female, between 13 and 16 years old.

  9. Interactions between Parental Alcohol-Specific Rules and Risk Personalities in the Prediction of Adolescent Alcohol Use

    NARCIS (Netherlands)

    Janssen, Tim; Larsen, Helle; Peeters, Margot; Pronk, Thomas; Vollebergh, Wilma A. M.; Wiers, Reinout W.

    2014-01-01

    Aims: To examine the impact of an important context variable (alcohol-specific parental rules) and an important person variable (risky personality traits) and their interaction on prospective adolescent drinking. Methods: Participants were 252 adolescents, 67.9% female, between 13 and 16 years old.

  10. Planning and predictability of clinical outcomes in esthetic rehabilitation.

    Science.gov (United States)

    Kurbad, A

    2015-01-01

    In esthetic rehabilitation, it is a challenge to meet the needs of patients with growing expectations. Creating predictable results is the key to success. This can be accomplished by performing a comprehensive esthetic diagnosis, elaborating treatment proposals that satisfy today's esthetic standards, and using modern computer-assisted methods. The diagnostic wax-up and mock-up are effective tools that allow patients to visualize treatment proposals without invasive procedures. Once the patient has approved the proposals, they provide the basis for the fabrication of the final restoration. The use of modern ceramic materials makes it possible to achieve a good esthetic outcome, even in restorations with extremely thin layer thicknesses. Esthetic cementation is the final step of restorative treatment.

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

    Science.gov (United States)

    Robinson, Lawrence R

    2015-09-01

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

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

    Science.gov (United States)

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

    2006-01-01

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

  13. Systematic review of clinical prediction tools and prognostic factors in aneurysmal subarachnoid hemorrhage

    Directory of Open Access Journals (Sweden)

    Benjamin W. Y. Lo

    2015-01-01

    Conclusions: Systematic reviews for clinical prognostic factors and clinical prediction tools in aneurysmal SAH face a number of methodological challenges. These include within and between study patient heterogeneity, regional variations in treatment protocols, patient referral biases, and differences in treatment, and prognosis viewpoints across different cultures.

  14. Clinical decision rules for the application of computed tomography in children with minor head injury%儿童轻型头部外伤 CT 检查临床决策规则及应用现状

    Institute of Scientific and Technical Information of China (English)

    张靖; 丁华新

    2015-01-01

    Pediatric head injury is the leading cause of death and disability,about 40% to 60% of kids of head injury get a CT,and the majority are those with minor head injury,about 10% of these CT scans are positive.Clinical decision rules for pediatric head injury exist to identify children at risk of traumatic brain injury.Those of the highest quality are children's head injury algorithm for the prediction of important clinical events(CHALICE),Pediatric Emergency Care Applied Research Network(PECARN)and the Canadian as-sessment of tomography for childhood head injury(CATCH)clinical decision rules.This review aimed to systematically introduce primary clinical decision rules for children with minor head injury and compare them for diagnostic accuracy in detecting intracranial injury and injury requiring neurosurgery.%脑外伤是儿童主要创伤性疾病和致死、致残原因,儿童头部外伤大约40%~60%进行了头部 CT 检查,其中不到10%发生外伤性脑损伤。为减少儿童不必要的头部 CT 检查,国外研究主要有预测儿童头部损伤重要临床事件、儿科急救治疗应用研究网络和加拿大儿童头部外伤 X 线检查评估等临床决策规则,指导临床医生决策儿童轻型头部外伤后 CT 的应用,现就目前临床应用的主要临床决策规则进行综述。

  15. Linguistic Valued Association Rules

    Institute of Scientific and Technical Information of China (English)

    LU Jian-jiang; QIAN Zuo-ping

    2002-01-01

    Association rules discovering and prediction with data mining method are two topics in the field of information processing. In this paper, the records in database are divided into many linguistic values expressed with normal fuzzy numbers by fuzzy c-means algorithm, and a series of linguistic valued association rules are generated. Then the records in database are mapped onto the linguistic values according to largest subject principle, and the support and confidence definitions of linguistic valued association rules are also provided. The discovering and prediction methods of the linguistic valued association rules are discussed through a weather example last.

  16. Ensuring patient privacy in image data sharing for clinical research : Design and implementation of rules and infrastructure

    NARCIS (Netherlands)

    Aryanto, Kadek Yota Ernanda

    2016-01-01

    The protection of personal data has become an important yet challenging process when patient data are distributed among health institutions. Regulations and rules have been issued to govern the protection of the privacy of personal information. To conform to these rules and regulations, data de-iden

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

    Science.gov (United States)

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

    2016-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Jennifer L. Whitwell

    2016-01-01

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

  19. A clinical tool to predict failed response to therapy in children with severe pneumonia.

    Science.gov (United States)

    Mamtani, Manju; Patel, Archana; Hibberd, Patricia L; Tuan, Tran Anh; Jeena, Prakash; Chisaka, Noel; Hassan, Mumtaz; Radovan, Irene Maulen; Thea, Donald M; Qazi, Shamim; Kulkarni, Hemant

    2009-04-01

    Severe pneumonia in children under 5 years of age continues to be an important clinical entity with treatment failure rates as high as 20%. Where severe pneumonias are common, predictive tools for treatment failure like chest radiography and pulse oximetry are not available or affordable. Thus, there is a need for development of simple, accurate and inexpensive clinical tools for prediction of treatment failure. Using clinical, chest radiographic and pulse oximetry data from 1702 children recruited in the Amoxicillin Penicillin Pneumonia International Study (APPIS) trial we developed and validated a simple clinical tool. For development, a randomly derived development sample (n = 889) was used. The tool which was based on the results of multivariate logistic regression models was validated on a separate sample of 813 children. The derived clinical tool in its final form contained three clinical predictors: age of child, excess age-specific respiratory rate at baseline and at 24 hr of hospitalization. This tool had a 70% and 66% predictive accuracy in the development and validation samples, respectively. The tool is presented as an easy-to-use nomogram. It is possible to predict the likelihood of treatment failure in children with severe pneumonia based on clinical features that are simple and inexpensive to measure.

  20. 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

  1. Predicting Out-of-Office Blood Pressure in the Clinic (PROOF-BP)

    Science.gov (United States)

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

    2016-01-01

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

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

    Science.gov (United States)

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

    2015-11-01

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

  3. Optimal search strategies for identifying sound clinical prediction studies in EMBASE

    Directory of Open Access Journals (Sweden)

    Haynes R Brian

    2005-04-01

    Full Text Available Abstract Background Clinical prediction guides assist clinicians by pointing to specific elements of the patient's clinical presentation that should be considered when forming a diagnosis, prognosis or judgment regarding treatment outcome. The numbers of validated clinical prediction guides are growing in the medical literature, but their retrieval from large biomedical databases remains problematic and this presents a barrier to their uptake in medical practice. We undertook the systematic development of search strategies ("hedges" for retrieval of empirically tested clinical prediction guides from EMBASE. Methods An analytic survey was conducted, testing the retrieval performance of search strategies run in EMBASE against the gold standard of hand searching, using a sample of all 27,769 articles identified in 55 journals for the 2000 publishing year. All articles were categorized as original studies, review articles, general papers, or case reports. The original and review articles were then tagged as 'pass' or 'fail' for methodologic rigor in the areas of clinical prediction guides and other clinical topics. Search terms that depicted clinical prediction guides were selected from a pool of index terms and text words gathered in house and through request to clinicians, librarians and professional searchers. A total of 36,232 search strategies composed of single and multiple term phrases were trialed for retrieval of clinical prediction studies. The sensitivity, specificity, precision, and accuracy of search strategies were calculated to identify which were the best. Results 163 clinical prediction studies were identified, of which 69 (42.3% passed criteria for scientific merit. A 3-term strategy optimized sensitivity at 91.3% and specificity at 90.2%. Higher sensitivity (97.1% was reached with a different 3-term strategy, but with a 16% drop in specificity. The best measure of specificity (98.8% was found in a 2-term strategy, but with a

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

    Institute of Scientific and Technical Information of China (English)

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

    2014-01-01

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

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

    Science.gov (United States)

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

    2014-01-01

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

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

    Science.gov (United States)

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

    2016-07-01

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

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

    Directory of Open Access Journals (Sweden)

    Hassan A Elechi

    2015-01-01

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

  8. Predictive biomarker discovery through the parallel integration of clinical trial and functional genomics datasets

    DEFF Research Database (Denmark)

    Swanton, C.; Larkin, J.M.; Gerlinger, M.

    2010-01-01

    RNA screens to identify and validate functionally important genomic or transcriptomic predictive biomarkers of individual drug response in patients. PREDICT's approach to predictive biomarker discovery differs from conventional associative learning approaches, which can be susceptible to the detection...... inhibitor. Through the analysis of tumour tissue derived from pre-operative renal cell carcinoma (RCC) clinical trials, the PREDICT consortium will use established and novel methods to integrate comprehensive tumour-derived genomic data with personalised tumour-derived shRNA and high throughput si......, reducing ineffective therapy in drug resistant disease, leading to improved quality of life and higher cost efficiency, which in turn should broaden patient access to beneficial therapeutics, thereby enhancing clinical outcome and cancer survival. The consortium will also establish and consolidate...

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

    Science.gov (United States)

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

    2010-01-01

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

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

    DEFF Research Database (Denmark)

    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...

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

    Directory of Open Access Journals (Sweden)

    Fine Howard A

    2010-07-01

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

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

    Institute of Scientific and Technical Information of China (English)

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

    2008-01-01

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

  13. Endometrial histology and predictable clinical factors for endometrial disease in women with polycystic ovary syndrome

    OpenAIRE

    Park, Joon Cheol; Lim, Su Yeon; Jang, Tae Kyu; Bae, Jin Gon; Kim, Jong In; Rhee, Jeong Ho

    2011-01-01

    Objective This study was aimed to investigate endometrial histology and to find predictable clinical factors for endometrial disease (hyperplasia or cancer) in women with polycystic ovary syndrome (PCOS). Methods We investigated the endometrial histology and analyzed the relationship between endometrial histology and clinical parameters, such as LH, FSH, estradiol, testosterone, fasting and 2 hours postprandial glucose and insulin, insulin resistance, body mass index, endometrial thickness, m...

  14. 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.

  15. Mechanisms of rule acquisition and rule following in inductive reasoning.

    Science.gov (United States)

    Crescentini, Cristiano; Seyed-Allaei, Shima; De Pisapia, Nicola; Jovicich, Jorge; Amati, Daniele; Shallice, Tim

    2011-05-25

    Despite the recent interest in the neuroanatomy of inductive reasoning processes, the regional specificity within prefrontal cortex (PFC) for the different mechanisms involved in induction tasks remains to be determined. In this study, we used fMRI to investigate the contribution of PFC regions to rule acquisition (rule search and rule discovery) and rule following. Twenty-six healthy young adult participants were presented with a series of images of cards, each consisting of a set of circles numbered in sequence with one colored blue. Participants had to predict the position of the blue circle on the next card. The rules that had to be acquired pertained to the relationship among succeeding stimuli. Responses given by subjects were categorized in a series of phases either tapping rule acquisition (responses given up to and including rule discovery) or rule following (correct responses after rule acquisition). Mid-dorsolateral PFC (mid-DLPFC) was active during rule search and remained active until successful rule acquisition. By contrast, rule following was associated with activation in temporal, motor, and medial/anterior prefrontal cortex. Moreover, frontopolar cortex (FPC) was active throughout the rule acquisition and rule following phases before a rule became familiar. We attributed activation in mid-DLPFC to hypothesis generation and in FPC to integration of multiple separate inferences. The present study provides evidence that brain activation during inductive reasoning involves a complex network of frontal processes and that different subregions respond during rule acquisition and rule following phases.

  16. Predictor characteristics necessary for building a clinically useful risk prediction model: a simulation study

    Directory of Open Access Journals (Sweden)

    Laura Schummers

    2016-09-01

    Full Text Available Abstract Background Compelled by the intuitive appeal of predicting each individual patient’s risk of an outcome, there is a growing interest in risk prediction models. While the statistical methods used to build prediction models are increasingly well understood, the literature offers little insight to researchers seeking to gauge a priori whether a prediction model is likely to perform well for their particular research question. The objective of this study was to inform the development of new risk prediction models by evaluating model performance under a wide range of predictor characteristics. Methods Data from all births to overweight or obese women in British Columbia, Canada from 2004 to 2012 (n = 75,225 were used to build a risk prediction model for preeclampsia. The data were then augmented with simulated predictors of the outcome with pre-set prevalence values and univariable odds ratios. We built 120 risk prediction models that included known demographic and clinical predictors, and one, three, or five of the simulated variables. Finally, we evaluated standard model performance criteria (discrimination, risk stratification capacity, calibration, and Nagelkerke’s r2 for each model. Results Findings from our models built with simulated predictors demonstrated the predictor characteristics required for a risk prediction model to adequately discriminate cases from non-cases and to adequately classify patients into clinically distinct risk groups. Several predictor characteristics can yield well performing risk prediction models; however, these characteristics are not typical of predictor-outcome relationships in many population-based or clinical data sets. Novel predictors must be both strongly associated with the outcome and prevalent in the population to be useful for clinical prediction modeling (e.g., one predictor with prevalence ≥20 % and odds ratio ≥8, or 3 predictors with prevalence ≥10 % and odds ratios ≥4. Area

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

    Science.gov (United States)

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

    2011-01-01

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

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

    DEFF Research Database (Denmark)

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

    1993-01-01

    This study investigated the number of blood culture-positive cattle among 215 animals clinically suspected of having bacterial endocarditis. For animals that were necropsied, the sensitivity, specificity and predictive value of the diagnosis of endocarditis were calculated on the basis...

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

    DEFF Research Database (Denmark)

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

    2015-01-01

    AIMS: The aim of this study was to investigate the clinical picture and outcome of cardiogenic shock and to develop a risk prediction score for short-term mortality. METHODS AND RESULTS: The CardShock study was a multicentre, prospective, observational study conducted between 2010 and 2012. Patie...

  20. Clinical prediction of fall risk and white matter abnormalities: a diffusion tensor imaging study

    Science.gov (United States)

    The Tinetti scale is a simple clinical tool designed to predict risk of falling by focusing on gait and stance impairment in elderly persons. Gait impairment is also associated with white matter (WM) abnormalities. Objective: To test the hypothesis that elderly subjects at risk for falling, as deter...

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

    Directory of Open Access Journals (Sweden)

    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.

  2. Longitudinal clinical score prediction in Alzheimer's disease with soft-split sparse regression based random forest.

    Science.gov (United States)

    Huang, Lei; Jin, Yan; Gao, Yaozong; Thung, Kim-Han; Shen, Dinggang

    2016-10-01

    Alzheimer's disease (AD) is an irreversible neurodegenerative disease and affects a large population in the world. Cognitive scores at multiple time points can be reliably used to evaluate the progression of the disease clinically. In recent studies, machine learning techniques have shown promising results on the prediction of AD clinical scores. However, there are multiple limitations in the current models such as linearity assumption and missing data exclusion. Here, we present a nonlinear supervised sparse regression-based random forest (RF) framework to predict a variety of longitudinal AD clinical scores. Furthermore, we propose a soft-split technique to assign probabilistic paths to a test sample in RF for more accurate predictions. In order to benefit from the longitudinal scores in the study, unlike the previous studies that often removed the subjects with missing scores, we first estimate those missing scores with our proposed soft-split sparse regression-based RF and then utilize those estimated longitudinal scores at all the previous time points to predict the scores at the next time point. The experiment results demonstrate that our proposed method is superior to the traditional RF and outperforms other state-of-art regression models. Our method can also be extended to be a general regression framework to predict other disease scores.

  3. Spatial rule-based assessment of habitat potential to predict impact of land use changes on biodiversity at municipal scale.

    Science.gov (United States)

    Scolozzi, Rocco; Geneletti, Davide

    2011-03-01

    In human dominated landscapes, ecosystems are under increasing pressures caused by urbanization and infrastructure development. In Alpine valleys remnant natural areas are increasingly affected by habitat fragmentation and loss. In these contexts, there is a growing risk of local extinction for wildlife populations; hence assessing the consequences on biodiversity of proposed land use changes is extremely important. The article presents a methodology to assess the impacts of land use changes on target species at a local scale. The approach relies on the application of ecological profiles of target species for habitat potential (HP) assessment, using high resolution GIS-data within a multiple level framework. The HP, in this framework, is based on a species-specific assessment of the suitability of a site, as well of surrounding areas. This assessment is performed through spatial rules, structured as sets of queries on landscape objects. We show that by considering spatial dependencies in habitat assessment it is possible to perform better quantification of impacts of local-level land use changes on habitats.

  4. Practical Guidance for Implementing Predictive Biomarkers into Early Phase Clinical Studies

    Directory of Open Access Journals (Sweden)

    Matthew J. Marton

    2013-01-01

    Full Text Available The recent U.S. Food and Drug Administration (FDA coapprovals of several therapeutic compounds and their companion diagnostic devices (FDA News Release, 2011, 2013 to identify patients who would benefit from treatment have led to considerable interest in incorporating predictive biomarkers in clinical studies. Yet, the translation of predictive biomarkers poses unique technical, logistic, and regulatory challenges that need to be addressed by a multidisciplinary team including discovery scientists, clinicians, biomarker experts, regulatory personnel, and assay developers. These issues can be placed into four broad categories: sample collection, assay validation, sample analysis, and regulatory requirements. In this paper, we provide a primer for drug development teams who are eager to implement a predictive patient segmentation marker into an early clinical trial in a way that facilitates subsequent development of a companion diagnostic. Using examples of nucleic acid-based assays, we briefly review common issues encountered when translating a biomarker to the clinic but focus primarily on key practical issues that should be considered by clinical teams when planning to use a biomarker to balance arms of a study or to determine eligibility for a clinical study.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    Hunt, Michael A; Bennell, Kim L

    2011-08-01

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

  7. 关联规则评分预测的协同过滤推荐算法%Collaborative Filtering Recommendation Algorithm Based on Association Rule Score Prediction

    Institute of Scientific and Technical Information of China (English)

    王竹婷

    2016-01-01

    协同过滤算法是目前应用于电子商务个性化推荐系统中的一种最成功的推荐算法。为缓解因数据稀疏性问题导致的算法推荐质量下降,将关联规则分析引入协同过滤算法中,预测部分未评分项目的评分值,再运用传统的基于用户的协同过滤算法实施推荐。实验结果表明:与传统的协同过滤算法相比,采用关联规则预测评分可以一定程度提高算法推荐质量。%Collaborative filtering algorithm is one of the most successful recommendation algorithms ap-plied to the personalized recommendation system of E-commerce.In order to alleviate the problem of the algorithm recommendation quality decline that caused by the data sparse,the association rule anal-ysis is introduced into the collaborative filtering algorithm,which predicts the item ratings of the non rating items,and then uses the traditional user_based collaborative filtering algorithm to implement the recommendation.The experimental results show that compared with the traditional collaborative filte-ring algorithm,the algorithm uses association rules to predict the item ratings can improve the recom-mended quality.

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

    Science.gov (United States)

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

    2016-10-01

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

  9. Predicting counseling psychologists attitudes and clinical judgments with respect to older adults.

    Science.gov (United States)

    Tomko, Jody K; Munley, Patrick H

    2013-01-01

    The purpose of this study was to examine age, gender, training and experience in aging issues, fear of death, and multicultural competence in predicting counseling psychologists' global attitudes toward older adults and specific clinical judgments concerning a case vignette of an older client. A national sample of 364 practicing counseling psychologists participated in the study. Participants completed a demographic measure, Polizzi's refined version of the Aging Semantic Differential (Polizzi, 2003 ), a survey of professional bias based on a clinical vignette of a 70-year-old woman (James & Haley, 1995), the Collett-Lester Fear of Death Scale 3.0 (Lester, & Abdel-Khalek, 2003), the Multicultural Counseling Knowledge and Awareness Scale (MCKAS; Ponterotto, Gretchen, Utsey, Rieger, & Austin, 2002), and a Training and Experience Questionnaire. Hierarchical multiple regression analyses were used to investigate the extent to which the selected variables predicted more favorable attitudes toward older adults and less professional bias toward an older client beyond prediction by age and gender. Results revealed that older age and higher total scores on the MCKAS predicted less professional bias in clinical judgments. Gender was a significant predictor of global attitudes toward older adults. Findings suggest that multicultural knowledge, awareness, and skills are important in working with older adults.

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

    Science.gov (United States)

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

    2016-01-01

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

  11. An 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 BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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.

  12. Ability of clinicopathologic variables and clinical examination findings to predict race elimination in endurance horses.

    Science.gov (United States)

    Fielding, C Langdon; Meier, Chloe A; Fellers, Greg K; Magdesian, K Gary

    2017-01-01

    OBJECTIVE To compare results of point-of-care laboratory testing with standard veterinary clinical examination findings at a single time point during endurance competition to identify horses at risk for elimination. ANIMALS 101 endurance horses participating in the 2013 Western States 160-km (100-mile) endurance ride. PROCEDURES At the 58-km checkpoint, blood samples were collected from all horses. Samples were analyzed for pH, Pco2, base excess, anion gap, PCV, and whole blood concentrations of sodium, potassium, chloride, total carbon dioxide, BUN, glucose, and bicarbonate. Corrected electrolyte and PCV values were calculated on the basis of plasma total protein concentration. Immediately following the blood sample collection, each horse underwent a clinical examination. In addition to standard examination variables, an adjusted heart rate was calculated on the basis of the variable interval between entry into the checkpoint and heart rate recording. A combination of stepwise logistic regression, classification and regression tree analysis, and generalized additive models was used to identify variables that were associated with overall elimination or each of 3 other elimination categories (metabolic elimination, lameness elimination, and elimination for other reasons). RESULTS Corrected whole blood potassium concentration and adjusted heart rate were predictive for overall elimination. Breed, plasma total protein concentration, and attitude were predictive for elimination due to metabolic causes. Whole blood chloride concentration and corrected PCV were predictive for elimination due to lameness. Corrected PCV was predictive for elimination due to other causes. CONCLUSIONS AND CLINICAL RELEVANCE Results indicated that for horses in endurance competition, a combination of breed and clinical examination and laboratory variables provided the best prediction of overall elimination.

  13. Integration of preclinical and clinical knowledge to predict intravenous PK in human: bilastine case study.

    Science.gov (United States)

    Vozmediano, Valvanera; Ortega, Ignacio; Lukas, John C; Gonzalo, Ana; Rodriguez, Monica; Lucero, Maria Luisa

    2014-03-01

    Modern pharmacometrics can integrate and leverage all prior proprietary and public knowledge. Such methods can be used to scale across species or comparators, perform clinical trial simulation across alternative designs, confirm hypothesis and potentially reduce development burden, time and costs. Crucial yet typically lacking in integration is the pre-clinical stage. Prediction of PK in man, using in vitro and in vivo studies in different animal species, is increasingly well theorized but could still find wider application in drug development. The aim of the present work was to explore methods for bridging pharmacokinetic knowledge from animal species (i.v. and p.o.) and man (p.o.) into i.v. in man using the antihistamine drug bilastine as example. A model, predictive of i.v. PK in man, was developed on data from two pre-clinical species (rat and dog) and p.o. in man bilastine trials performed earlier. In the knowledge application stage, two different approaches were used to predict human plasma concentration after i.v. of bilastine: allometry (several scaling methods) and a semi-physiological method. Both approaches led to successful predictions of key i.v. PK parameters of bilastine in man. The predictive i.v. PK model was validated using later data from a clinical study of i.v. bilastine. Introduction of such knowledge in development permits proper leveraging of all emergent knowledge as well as quantification-based exploration of PK scenario, e.g. in special populations (pediatrics, renal insufficiency, comedication). In addition, the methods permit reduction or elimination and certainly optimization of learning trials, particularly those concerning alternative off-label administration routes.

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

    Directory of Open Access Journals (Sweden)

    Klearchos K Papas

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

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

    CERN Document Server

    Bennett, Casey; Selove, Rebecca

    2012-01-01

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

  16. Location of brain lesions predicts conversion of clinically isolated syndromes to multiple sclerosis

    DEFF Research Database (Denmark)

    Giorgio, Antonio; Battaglini, Marco; Rocca, Maria Assunta

    2013-01-01

    : In CIS patients with hemispheric, multifocal, and brainstem/cerebellar onset, lesion probability map clusters were seen in clinically eloquent brain regions. Significant lesion clusters were not found in CIS patients with optic nerve and spinal cord onset. At 1 year, clinically definite MS developed......OBJECTIVES: To assess in a large population of patients with clinically isolated syndrome (CIS) the relevance of brain lesion location and frequency in predicting 1-year conversion to multiple sclerosis (MS). METHODS: In this multicenter, retrospective study, clinical and MRI data at onset...... in 26% of patients. The converting group, despite a greater baseline lesion load compared with the nonconverting group (7 ± 8.1 cm(3) vs 4.6 ± 6.7 cm(3), p brain voxels occupied by lesions). High lesion frequency was found...

  17. Predictive monitoring of mobile patients by combining clinical observations with data from wearable sensors.

    Science.gov (United States)

    Clifton, Lei; Clifton, David A; Pimentel, Marco A F; Watkinson, Peter J; Tarassenko, Lionel

    2014-05-01

    The majority of patients in the hospital are ambulatory and would benefit significantly from predictive and personalized monitoring systems. Such patients are well suited to having their physiological condition monitored using low-power, minimally intrusive wearable sensors. Despite data-collection systems now being manufactured commercially, allowing physiological data to be acquired from mobile patients, little work has been undertaken on the use of the resultant data in a principled manner for robust patient care, including predictive monitoring. Most current devices generate so many false-positive alerts that devices cannot be used for routine clinical practice. This paper explores principled machine learning approaches to interpreting large quantities of continuously acquired, multivariate physiological data, using wearable patient monitors, where the goal is to provide early warning of serious physiological determination, such that a degree of predictive care may be provided. We adopt a one-class support vector machine formulation, proposing a formulation for determining the free parameters of the model using partial area under the ROC curve, a method arising from the unique requirements of performing online analysis with data from patient-worn sensors. There are few clinical evaluations of machine learning techniques in the literature, so we present results from a study at the Oxford University Hospitals NHS Trust devised to investigate the large-scale clinical use of patient-worn sensors for predictive monitoring in a ward with a high incidence of patient mortality. We show that our system can combine routine manual observations made by clinical staff with the continuous data acquired from wearable sensors. Practical considerations and recommendations based on our experiences of this clinical study are discussed, in the context of a framework for personalized monitoring.

  18. Some uses of predictive probability of success in clinical drug development

    Directory of Open Access Journals (Sweden)

    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.

  19. Phonological reduplication in sign language: rules rule

    Directory of Open Access Journals (Sweden)

    Iris eBerent

    2014-06-01

    Full Text Available Productivity—the hallmark of linguistic competence—is typically attributed to algebraic rules that support broad generalizations. Past research on spoken language has documented such generalizations in both adults and infants. But whether algebraic rules form part of the linguistic competence of signers remains unknown. To address this question, here we gauge the generalization afforded by American Sign Language (ASL. As a case study, we examine reduplication (X→XX—a rule that, inter alia, generates ASL nouns from verbs. If signers encode this rule, then they should freely extend it to novel syllables, including ones with features that are unattested in ASL. And since reduplicated disyllables are preferred in ASL, such rule should favor novel reduplicated signs. Novel reduplicated signs should thus be preferred to nonreduplicative controls (in rating, and consequently, such stimuli should also be harder to classify as nonsigns (in the lexical decision task. The results of four experiments support this prediction. These findings suggest that the phonological knowledge of signers includes powerful algebraic rules. The convergence between these conclusions and previous evidence for phonological rules in spoken language suggests that the architecture of the phonological mind is partly amodal.

  20. A few remarks on the rules about personal data protection when conducting clinical trials in Italy, also from abroad.

    Science.gov (United States)

    Petrini, Carlo

    2009-01-01

    The Italian Authority for the Protection of Personal Data has definitively adopted the Guidelines for data processing within the framework of clinical drug trials. The Guidelines are addressed to sponsors and other subjects who intervene, also from abroad, in clinical trials. The document provides practical instructions for the processing of personal data of human subject participating in clinical trials.

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

    DEFF Research Database (Denmark)

    Clausen, Frederik Banch

    2014-01-01

    of the fetus and newborn to fetuses of immunized women. Prediction of the fetal RhD type has been very successful and is now integrated into clinical practice to assist in the management of the pregnancies of RhD immunized women. In addition, noninvasive prediction of the fetal RhD type can be applied to guide......Incompatibility of red blood cell blood group antigens between a pregnant woman and her fetus can cause maternal immunization and, consequently, hemolytic disease of the fetus and newborn. Noninvasive prenatal testing of cell-free fetal DNA can be used to assess the risk of hemolytic disease...

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

    Science.gov (United States)

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

    2015-04-01

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

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

    Directory of Open Access Journals (Sweden)

    W. B. Mattes

    2013-01-01

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

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

    Science.gov (United States)

    Hickey, Graeme L; Blackstone, Eugene H

    2016-08-01

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

  5. Pre and per operative prediction of difficult laparoscopic cholecystectomy using clinical and ultrasonographic parameters

    Directory of Open Access Journals (Sweden)

    Gaurav Gupta

    2015-11-01

    Methods: In 50 consecutive patients who underwent LC during 2013 to 2014 patient's characteristics, clinical history, laboratory data, ultrasonography results and intraoperative details were prospectively analyzed to determine predictors of difficult LC. Results: Of 50 patients 3 (06% required conversion to open cholecystectomy. Significant predictors of conversion were obscured anatomy of Calot's due to adhesions, sessile gall bladder, male gender and gall bladder wall thickness >3 mm. Conclusions: With preoperative clinical and ultrasonographic parameters, proper patient selection can be made to help predict difficult LC and a likelihood of conversion to open cholecystectomy. [Int J Res Med Sci 2015; 3(11.000: 3342-3346

  6. The Diagnostic Accuracy of Clinical and External Pelvimetry in Prediction of Dystocia in Nulliparous Women

    Directory of Open Access Journals (Sweden)

    R Alijahan

    2011-08-01

    Full Text Available Introduction: Clinical pelvimetry is very uncomfortable for the patient and is associated with subjective error, while external pelvimetry is a simple and acceptable method for patients. The objective of this study was to compare the diagnostic accuracy of clinical and external pelvimetry in prediction of dystocia in nulliparous women. Methods: In this study between December 2008 and January 2009, 447 nulliparous women with a single pregnancy in vertex presentation and gestational age 38-42 weeks referring to the Ommolbanin hospital of Mashhad were included. External pelvic dimensions were assessed at the time of admission and clinical pelvimetry was performed by another examiner. These measurements were not available to the clinician in charge of the delivery. Dystocia was defined as caesarean section and vacuum or forceps delivery for abnormal progress of labor ( active uterine contractions, arrest of cervical dilatation or cervical dilatation less than 1 cm /h in the active phase for 2 hours, prolongation of second stage beyond 2 hours or fetal head descent less than 1cm/h. Statistical tests included Fisher exact test and Chi- square test. Results: The highest sensitivity obtained from clinical pelvimetry was 33.3% and related to diagonal conjugate less than 11.5 cm. The sensitivity of external pelvic dimensions was higher than clinical pelvimetry that was highest for the Michaelis transverse diameter(60.72%. Conclusion: External pelvimetry in comparison to clinical pelvimetry is a better method for identifying dystocia in nulliparous women and can replace clinical pelvimetry in antenatal care programs.

  7. Time series analysis as input for clinical predictive modeling: Modeling cardiac arrest in a pediatric ICU

    Directory of Open Access Journals (Sweden)

    Kennedy Curtis E

    2011-10-01

    Full Text Available Abstract Background Thousands of children experience cardiac arrest events every year in pediatric intensive care units. Most of these children die. Cardiac arrest prediction tools are used as part of medical emergency team evaluations to identify patients in standard hospital beds that are at high risk for cardiac arrest. There are no models to predict cardiac arrest in pediatric intensive care units though, where the risk of an arrest is 10 times higher than for standard hospital beds. Current tools are based on a multivariable approach that does not characterize deterioration, which often precedes cardiac arrests. Characterizing deterioration requires a time series approach. The purpose of this study is to propose a method that will allow for time series data to be used in clinical prediction models. Successful implementation of these methods has the potential to bring arrest prediction to the pediatric intensive care environment, possibly allowing for interventions that can save lives and prevent disabilities. Methods We reviewed prediction models from nonclinical domains that employ time series data, and identified the steps that are necessary for building predictive models using time series clinical data. We illustrate the method by applying it to the specific case of building a predictive model for cardiac arrest in a pediatric intensive care unit. Results Time course analysis studies from genomic analysis provided a modeling template that was compatible with the steps required to develop a model from clinical time series data. The steps include: 1 selecting candidate variables; 2 specifying measurement parameters; 3 defining data format; 4 defining time window duration and resolution; 5 calculating latent variables for candidate variables not directly measured; 6 calculating time series features as latent variables; 7 creating data subsets to measure model performance effects attributable to various classes of candidate variables; 8

  8. Cannabidiol is a partial agonist at dopamine D2High receptors, predicting its antipsychotic clinical dose

    Science.gov (United States)

    Seeman, P

    2016-01-01

    Although all current antipsychotics act by interfering with the action of dopamine at dopamine D2 receptors, two recent reports showed that 800 to 1000 mg of cannabidiol per day alleviated the signs and symptoms of schizophrenia, although cannabidiol is not known to act on dopamine receptors. Because these recent clinical findings may indicate an important exception to the general rule that all antipsychotics interfere with dopamine at dopamine D2 receptors, the present study examined whether cannabidiol acted directly on D2 receptors, using tritiated domperidone to label rat brain striatal D2 receptors. It was found that cannabidiol inhibited the binding of radio-domperidone with dissociation constants of 11 nm at dopamine D2High receptors and 2800 nm at dopamine D2Low receptors, in the same biphasic manner as a dopamine partial agonist antipsychotic drug such as aripiprazole. The clinical doses of cannabidiol are sufficient to occupy the functional D2High sites. it is concluded that the dopamine partial agonist action of cannabidiol may account for its clinical antipsychotic effects. PMID:27754480

  9. Validation of a Prediction Rule for the Diagnosis of Rheumatoid Arthritis in Patients with Recent Onset Undifferentiated Arthritis

    Directory of Open Access Journals (Sweden)

    Zaida Bedran

    2013-01-01

    Full Text Available Objectives. To validate van der Helm-van Mil score (vHvM and new ACR/EULAR criteria for the diagnosis of rheumatoid arthritis (RA in patients with undifferentiated arthritis (UA. Patients and Methods. Adult patients with UA (swelling ≥2 joints of less than 6 months duration, without diagnosis, and never treated with disease modifying drugs. Results. Ninety-one patients were included. Mean age: 55.6 years (SD: 17.4, 74% females. Median symptoms duration was 2 months (IR: 1–4 months. Mean van der Helm-van Mil score was 6.9 (SD: 2. After a mean followup of 6.2 months (SD: 6, 40.7% patients fulfilled ACR 1987 RA classification criteria, 28.6% fulfilled other diagnostic criteria, and 31% remained as UA. Receiver operator characteristic curve's (ROC's area under the curve (AUC for the vHvM score for diagnosis of RA was 0.83. A cutoff value of 6.94 showed sensitivity of 81% and 79.7% specificity. For the new ACR/EULAR criteria, the ROC AUC was 0.93, and a value equal to or greater than 6 showed 86.5% sensitivity and 87% specificity. Conclusion. van der Helm-van Mil prediction score and the new ACR/EULAR criteria proved to be valuable for the diagnosis of RA in patients with early UA.

  10. HPA axis in major depression: cortisol, clinical symptomatology and genetic variation predict cognition.

    Science.gov (United States)

    Keller, J; Gomez, R; Williams, G; Lembke, A; Lazzeroni, L; Murphy, G M; Schatzberg, A F

    2016-08-16

    The hypothalamic-pituitary-adrenal (HPA) axis has been implicated in the pathophysiology of a variety of mood and cognitive disorders. Neuroendocrine studies have demonstrated HPA axis overactivity in major depression, a relationship of HPA axis activity to cognitive performance and a potential role of HPA axis genetic variation in cognition. The present study investigated the simultaneous roles HPA axis activity, clinical symptomatology and HPA genetic variation play in cognitive performance. Patients with major depression with psychotic major depression (PMD) and with nonpsychotic major depression (NPMD) and healthy controls (HC) were studied. All participants underwent a diagnostic interview and psychiatric ratings, a comprehensive neuropsychological battery, overnight hourly blood sampling for cortisol and genetic assessment. Cognitive performance differed as a function of depression subtype. Across all subjects, cognitive performance was negatively correlated with higher cortisol, and PMD patients had higher cortisol than did NPMDs and HCs. Cortisol, clinical symptoms and variation in genes, NR3C1 (glucocorticoid receptor; GR) and NR3C2 (mineralocorticoid receptor; MR) that encode for GRs and MRs, predicted cognitive performance. Beyond the effects of cortisol, demographics and clinical symptoms, NR3C1 variation predicted attention and working memory, whereas NR3C2 polymorphisms predicted memory performance. These findings parallel the distribution of GR and MR in primate brain and their putative roles in specific cognitive tasks. HPA axis genetic variation and activity were important predictors of cognition across the entire sample of depressed subjects and HR. GR and MR genetic variation predicted unique cognitive functions, beyond the influence of cortisol and clinical symptoms. GR genetic variation was implicated in attention and working memory, whereas MR was implicated in verbal memory.Molecular Psychiatry advance online publication, 16 August 2016; doi

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

    Directory of Open Access Journals (Sweden)

    Erfantalab-Avini Peyman

    2011-06-01

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

  12. Evaluating clinical abdominal scoring system in predicting the necessity of laparotomy in blunt abdominal trauma

    Institute of Scientific and Technical Information of China (English)

    Peyman Erfantalab-Avini; Nima Hafezi-Nejad; Mojtaba Chardoli; Vafa Rahimi-Movaghar

    2011-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Ali Kazemisaeid

    2011-02-01

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

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

    OpenAIRE

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

    2015-01-01

    A Clinical Scoring System to Predict the Development of Bronchopulmonary Dysplasia Tugba Gursoy, MD1 Mutlu Hayran, MD2 Hatice Derin, MD3 Fahri Ovali, MD3 1Department of Neonatology, School of Medicine, KOC University, Istanbul, Turkey 2Department of Preventive Oncology, Faculty of Medicine, Hacettepe University, Ankara, Turkey 3Department of Pediatrics, Zeynep Kamil Maternity and Children’s Research and Training Hospital, Istanbul, Turkey 4Department of Neonatology,...

  15. Clinical Features That Predict the Need for Operative Intervention in Gluteus Medius Tears

    OpenAIRE

    Chandrasekaran, Sivashankar; Vemula, S. Pavan; Gui, Chengcheng; Suarez-Ahedo, Carlos; Lodhia, Parth; Domb, Benjamin G.

    2015-01-01

    Background: Gluteus medius tears are a common cause of lateral hip pain. Operative intervention is usually prescribed for patients with pain despite physical therapy and/or peritrochanteric injections. Purpose: To identify clinical features that predict operative intervention in gluteus medius tears. Study Design: Case control study; Level of evidence, 3. Methods: A matched-pair controlled study was conducted on patients who underwent endoscopic gluteus medius repairs from June 2008 to August...

  16. HPA Axis in Major Depression: Cortisol, Clinical Symptomatology, and Genetic Variation Predict Cognition

    Science.gov (United States)

    Keller, Jennifer; Gomez, Rowena; Williams, Gordon; Lembke, Anna; Lazzeroni, Laura; Murphy, Greer M.; Schatzberg, Alan F.

    2016-01-01

    The Hypothalamic Pituitary Adrenal (HPA) axis has been implicated in the pathophysiology of a variety of mood and cognitive disorders. Neuroendocrine studies have demonstrated HPA axis overactivity in major depression, a relationship of HPA axis activity to cognitive performance, and a potential role of HPA axis genetic variation in cognition. The present study investigated the simultaneous roles HPA axis activity, clinical symptomatology, and HPA genetic variation play in cognitive performance. Patients with major depression with psychosis (PMD) and without psychosis (NPMD) and healthy controls (HC) were studied. All participants underwent a diagnostic interview and psychiatric ratings, a comprehensive neuropsychological battery, overnight hourly blood sampling for cortisol, and genetic assessment. Cognitive performance differed as a function of depression subtype. Across all subjects, cognitive performance was negatively correlated with higher cortisol, and PMD patients had higher cortisol than did NPMDs and HCs. Cortisol, clinical symptoms, and variation in genes, NR3C1 (glucocorticoid receptor - GR) and NR3C2 (minercorticoid receptor – MR) that encode for glucocorticoid and mineralcorticoid receptors, predicted cognitive performance. Beyond the effects of cortisol, demographics, and clinical symptoms, NR3C1 variation predicted attention and working memory, whereas NR3C2 polymorphisms predicted memory performance. These findings parallel the distribution of GR and MR in primate brain and their putative roles in specific cognitive tasks. HPA axis genetic variation and activity were important predictors of cognition across the entire sample of depressed subjects and healthy controls. GR and MR genetic variation predicted unique cognitive functions, beyond the influence of cortisol and clinical symptoms. GR genetic variation was implicated in attention and working memory, whereas MR was implicated in verbal memory. PMID:27528460

  17. Some uses of predictive probability of success in clinical drug development

    OpenAIRE

    Mauro Gasparini; Lilla Di Scala; Frank Bretz; Amy Racine-Poon

    2013-01-01

    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 impose...

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2013-02-15

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

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

    Directory of Open Access Journals (Sweden)

    I. V. Shirinsky

    2009-01-01

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

  20. 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.

  1. Predictive factors of rapidly progressive-interstitial lung disease in patients with clinically amyopathic dermatomyositis.

    Science.gov (United States)

    Xu, Y; Yang, C S; Li, Y J; Liu, X D; Wang, J N; Zhao, Q; Xiao, W G; Yang, P T

    2016-01-01

    Clinically amyopathic dermatomyositis (CADM) is a unique subset of dermatomyositis, showing a high incidence of lung involvements. The aim of this study is to identify risk factors, other than melanoma differentiation-associated protein (MDA)-5, for developing rapidly progressive-interstitial lung disease (RP-ILD) in patients with CADM. Forty CADM patients, in whom 11 patients developed RP-ILD, were enrolled. Clinical features and laboratory findings were compared between the patients with and without RP-ILD. We found that skin ulceration, CRP, serum ferritin, anti-MDA5 Ab, and lymphocytopenia were significantly associated with ILD. Multivariate logistic regression analysis indicated that anti-MDA5 Ab(+), elevated CRP, and decreased counts of lymphocyte were independent risk factors for RP-ILD, which can provide a precise predict for RP-ILD in CADM patients. When anti-MDA5 Ab(+) was removed from the multivariate regression model, using skin ulcerations, elevated serum ferritin and decreased counts of lymphocyte can also precisely predict RP-ILD. Except for MDA-5, more commonly available clinical characteristics, such as skin ulcerations, serum ferritin, and count of lymphocyte may also help to predict prognosis in CADM.

  2. Development of the A-DIVA Scale: A Clinical Predictive Scale to Identify Difficult Intravenous Access in Adult Patients Based on Clinical Observations.

    Science.gov (United States)

    van Loon, Fredericus H J; Puijn, Lisette A P M; Houterman, Saskia; Bouwman, Arthur R A

    2016-04-01

    Placement of a peripheral intravenous catheter is a routine procedure in clinical practice, but failure of intravenous cannulation regularly occurs. An accurate and reliable predictive scale for difficult venous access creates the possibility to use other techniques in an earlier time frame. We aimed to develop a predictive scale to identify adult patients with a difficult intravenous access prospectively: the A-DIVA scale. This prospective, observational, cross-sectional cohort study was conducted between January 2014 and January 2015, and performed at the department of anesthesiology of the Catharina Hospital (Eindhoven, The Netherlands). Patients 18 years or older were eligible if scheduled for any surgical procedure, regardless ASA classification, demographics, and medical history. Experienced and certified anesthesiologists and nurse anesthetists routinely obtained peripheral intravenous access. Cannulation was performed regarding standards for care. A failed peripheral intravenous cannulation on the first attempt was the outcome of interest. A population-based sample of 1063 patients was included. Failure of intravenous cannulation was observed in 182/1063 patients (17%). Five variables were associated with a failed first attempt of peripheral intravenous cannulation: palpability of the target vein (OR = 4.94, 95% CI [2.85-8.56]; P < 0.001), visibility of the target vein (OR = 3.63, 95% CI [2.09-6.32]; P < 0.001), a history of difficult peripheral intravenous cannulation (OR = 3.86, 95% CI [2.39-6.25]; P < 0.001), an unplanned indication for surgery (OR = 4.86, 95% CI [2.92-8.07]; P < 0.001), and the vein diameter of at most 2 millimeters (OR = 3.37, 95% CI [2.12-5.36]; P < 0.001). The scoring system was applied in 3 risk groups: 36/788 patients (5%) suffered from a failed first attempt in the low-risk group (A-DIVA score 0 or 1), whereas the medium (A-DIVA score 2 or 3) and high-risk group (A-DIVA score 4 plus

  3. Pharmacogenomics of Methotrexate Membrane Transport Pathway: Can Clinical Response to Methotrexate in Rheumatoid Arthritis Be Predicted?

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    Aurea Lima

    2015-06-01

    Full Text Available Background: Methotrexate (MTX is widely used for rheumatoid arthritis (RA treatment. Single nucleotide polymorphisms (SNPs could be used as predictors of patients’ therapeutic outcome variability. Therefore, this study aims to evaluate the influence of SNPs in genes encoding for MTX membrane transport proteins in order to predict clinical response to MTX. Methods: Clinicopathological data from 233 RA patients treated with MTX were collected, clinical response defined, and patients genotyped for 23 SNPs. Genotype and haplotype analyses were performed using multivariate methods and a genetic risk index (GRI for non-response was created. Results: Increased risk for non-response was associated to SLC22A11 rs11231809 T carriers; ABCC1 rs246240 G carriers; ABCC1 rs3784864 G carriers; CGG haplotype for ABCC1 rs35592, rs2074087 and rs3784864; and CGG haplotype for ABCC1 rs35592, rs246240 and rs3784864. GRI demonstrated that patients with Index 3 were 16-fold more likely to be non-responders than those with Index 1. Conclusions: This study revealed that SLC22A11 and ABCC1 may be important to identify those patients who will not benefit from MTX treatment, highlighting the relevance in translating these results to clinical practice. However, further validation by independent studies is needed to develop the field of personalized medicine to predict clinical response to MTX treatment.

  4. Prediction of peak pressure from clinical and radiological measurements in patients with diabetes

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    Nieman Fred HM

    2008-12-01

    Full Text Available Abstract Background Various structural and functional factors of foot function have been associated with high local plantar pressures. The therapist focuses on these features which are thought to be responsible for plantar ulceration in patients with diabetes. Risk assessment of the diabetic foot would be made easier if locally elevated plantar pressure could be indicated with a minimum set of clinical measures. Methods Ninety three patients were evaluated through vascular, orthopaedic, neurological and radiological assessment. A pressure platform was used to quantify the barefoot peak pressure for six forefoot regions: big toe (BT and metatarsals one (MT-1 to five (MT-5. Stepwise regression modelling was performed to determine which set of the clinical and radiological measures explained most variability in local barefoot plantar peak pressure in each of the six forefoot regions. Comprehensive models were computed with independent variables from the clinical and radiological measurements. The difference between the actual plantar pressure and the predicted value was examined through Bland-Altman analysis. Results Forefoot pressures were significant higher in patients with neuropathy, compared to patients without neuropathy for the whole forefoot, the MT-1 region and the MT-5 region (respectively 138 kPa, 173 kPa and 88 kPa higher: mean difference. The clinical models explained up to 39 percent of the variance in local peak pressures. Callus formation and toe deformity were identified as relevant clinical predictors for all forefoot regions. Regression models with radiological variables explained about 26 percent of the variance in local peak pressures. For most regions the combination of clinical and radiological variables resulted in a higher explained variance. The Bland and Altman analysis showed a major discrepancy between the predicted and the actual peak pressure values. Conclusion At best, clinical and radiological measurements could

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

    Science.gov (United States)

    Benson, M

    2016-03-01

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

  6. Magnetic resonance imaging and morphometric histologic analysis of prostate tissue composition in predicting the clinical outcome of terazosin therapy in benign prostatic hyperplasia

    Energy Technology Data Exchange (ETDEWEB)

    Isen, K. [Karaelmas Univ., Zonguldak (Turkey). School of Medicine; Sinik, Z.; Alkibay, T.; Sezer, C.; Soezen, S.; Atilla, S.; Ataoglu, O.; Isik, S.

    2001-02-01

    The purpose of this study was to determine whether magnetic resonance imaging (MRI) or quantitative color-imaged morphometric analysis (MA) of the prostate gland are related to the clinical response to terazosin. Thirty-six male patients with symptomatic benign prostatic hyperplasia (BPH) with a serum prostate-specific antigen level of 4-10 ng/mL underwent MRI with body coil, transrectal prostate unltrasonography and biopsy prior to terazosin therapy. For MRI-determined stromal and non-stromal BPH, the ratio of the signal intensity of the inner gland to the obturator internus muscle was evaluated. Histologic sections were stained with hematoxylin and eosin. The MA of the specimens was performed by Samba 2000. Results of the two techniques were interpreted according to the terazosin therapy results. The mean stromal percentage was 60.5{+-}18.0%. No statistically significant relationship was found between the clinical outcome of terazosin and the MRI findings. The MA results showed a significant relationship between the percentage of stroma and the percent change of the peak urinary flow rate, but not with the percent change of the international prostate symptom score after terazosin therapy (P<0.05). Magnetic resonance imaging alone is not sufficient in predicting the response to terazosin therapy. Morphometric analysis of BPH tissue composition can be used in predicting the clinical outcome of terazosin therapy but it is suitable only in patients for whom prostatic biopsy is necessary in order to rule out prostate cancer. (author)

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

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    Pereira J.C.R.

    2004-01-01

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

  8. Predicting cognitive function from clinical measures of physical function and health status in older adults.

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    Niousha Bolandzadeh

    Full Text Available Current research suggests that the neuropathology of dementia-including brain changes leading to memory impairment and cognitive decline-is evident years before the onset of this disease. Older adults with cognitive decline have reduced functional independence and quality of life, and are at greater risk for developing dementia. Therefore, identifying biomarkers that can be easily assessed within the clinical setting and predict cognitive decline is important. Early recognition of cognitive decline could promote timely implementation of preventive strategies.We included 89 community-dwelling adults aged 70 years and older in our study, and collected 32 measures of physical function, health status and cognitive function at baseline. We utilized an L1-L2 regularized regression model (elastic net to identify which of the 32 baseline measures were strongly predictive of cognitive function after one year. We built three linear regression models: 1 based on baseline cognitive function, 2 based on variables consistently selected in every cross-validation loop, and 3 a full model based on all the 32 variables. Each of these models was carefully tested with nested cross-validation.Our model with the six variables consistently selected in every cross-validation loop had a mean squared prediction error of 7.47. This number was smaller than that of the full model (115.33 and the model with baseline cognitive function (7.98. Our model explained 47% of the variance in cognitive function after one year.We built a parsimonious model based on a selected set of six physical function and health status measures strongly predictive of cognitive function after one year. In addition to reducing the complexity of the model without changing the model significantly, our model with the top variables improved the mean prediction error and R-squared. These six physical function and health status measures can be easily implemented in a clinical setting.

  9. Predictive Factors of Clinical Response of Infliximab Therapy in Active Nonradiographic Axial Spondyloarthritis Patients

    Science.gov (United States)

    Lin, Zhiming; Liao, Zetao; Huang, Jianlin; Ai, Maixing; Pan, Yunfeng; Wu, Henglian; Lu, Jun; Cao, Shuangyan; Li, Li; Wei, Qiujing; Tang, Deshen; Wei, Yanlin; Li, Tianwang; Wu, Yuqiong; Xu, Manlong; Li, Qiuxia; Jin, Ou; Yu, Buyun; Gu, Jieruo

    2015-01-01

    Objectives. To evaluate the efficiency and the predictive factors of clinical response of infliximab in active nonradiographic axial spondyloarthritis patients. Methods. Active nonradiographic patients fulfilling ESSG criteria for SpA but not fulfilling modified New York criteria were included. All patients received infliximab treatment for 24 weeks. The primary endpoint was ASAS20 response at weeks 12 and 24. The abilities of baseline parameters and response at week 2 to predict ASAS20 response at weeks 12 and 24 were assessed using ROC curve and logistic regression analysis, respectively. Results. Of 70 axial SpA patients included, the proportions of patients achieving an ASAS20 response at weeks 2, 6, 12, and 24 were 85.7%, 88.6%, 87.1%, and 84.3%, respectively. Baseline MRI sacroiliitis score (AUC = 0.791; P = 0.005), CRP (AUC = 0.75; P = 0.017), and ASDAS (AUC = 0.778, P = 0.007) significantly predicted ASAS20 response at week 12. However, only ASDAS (AUC = 0.696, P = 0.040) significantly predicted ASAS20 response at week 24. Achievement of ASAS20 response after the first infliximab infusion was a significant predictor of subsequent ASAS20 response at weeks 12 and 24 (wald χ2 = 6.87, P = 0.009, and wald χ2 = 5.171, P = 0.023). Conclusions. Infliximab shows efficiency in active nonradiographic axial spondyloarthritis patients. ASDAS score and first-dose response could help predicting clinical efficacy of infliximab therapy in these patients. PMID:26273654

  10. Precision and negative predictive value of links between ClinicalTrials.gov and PubMed.

    Science.gov (United States)

    Huser, Vojtech; Cimino, James J

    2012-01-01

    One of the goals of translational science is to shorten the time from discovery to clinical use. Clinical trial registries were established to increase transparency in completed and ongoing clinical trials, and they support linking trials with resulting publications. We set out to investigate precision and negative predictive value (NPV) of links between ClinicalTrials.gov (CT.gov) and PubMed. CT.gov has been established to increase transparency in clinical trials and the link to PubMed is crucial for supporting a number of important functions, including ascertaining publication bias. We drew a random sample of trials downloaded from CT.gov and performed manual review of retrieved publications. We characterize two types of links between trials and publications (NCT-link originating from MEDLINE and PMID-link originating from CT.gov).The link precision is different based on type (NCT-link: 100%; PMID-link: 63% to 96%). In trials with no linked publication, we were able to find publications 44% of the time (NPV=56%) by searching PubMed. This low NPV shows that there are potentially numerous publications that should have been formally linked with the trials. Our results indicate that existing trial registry and publisher policies may not be fully enforced. We suggest some automated methods for improving link quality.

  11. Trabecular bone structure analysis of the spine using clinical MDCT: can it predict vertebral bone strength?

    Science.gov (United States)

    Baum, Thomas; Gräbeldinger, Martin; Räth, Christoph; Garcia, Eduardo Grande; Burgkart, Rainer; Patsch, Janina M; Rummeny, Ernst J; Link, Thomas M; Bauer, Jan S

    2014-01-01

    Recent technical improvements have made it possible to determine trabecular bone structure parameters of the spine using clinical multi-detector computed tomography (MDCT). Therefore, the purpose of this study was to analyze trabecular bone structure parameters obtained from clinical MDCT in relation to high resolution peripheral quantitative computed tomography (HR-pQCT) as a standard of reference and to investigate whether clinical MDCT can predict vertebral bone strength. Fourteen functional spinal segment units between T7 and L3 were harvested from 14 formalin-fixed human cadavers (11 women and 3 men; age 84 ± 10 years). All functional spinal segment units were examined using HR-pQCT (isotropic voxel size of 41 μm(3)) and a clinical whole-body MDCT (interpolated voxel size of 146 × 146 × 300 μm(3)). Trabecular bone structure analyses (histomorphometric and texture measures) were performed in the HR-pQCT as well as MDCT images. Vertebral failure load (FL) of the functional spinal segment units was determined in an uniaxial biomechanical test. The HR-pQCT and MDCT derived trabecular bone structure parameters showed correlations ranging from r = 0.60 to r = 0.90 (p parameters and FL amounted up to r = 0.86 (p parameters obtained with HR-pQCT and MDCT were not significantly different (p > 0.05). In this cadaver model, the spatial resolution of clinically available whole-body MDCT scanners was suitable for trabecular bone structure analysis of the spine and to predict vertebral bone strength.

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

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    Nagueh Sherif F

    2009-03-01

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

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

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    Boscarino JA

    2013-04-01

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

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

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    Dina Oktavia

    2013-01-01

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

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

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    Ramyar Molania

    2014-01-01

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

  16. Metabolite signal identification in accurate mass metabolomics data with MZedDB, an interactive m/z annotation tool utilising predicted ionisation behaviour 'rules'

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    Snowdon Stuart

    2009-07-01

    Full Text Available Abstract Background Metabolomics experiments using Mass Spectrometry (MS technology measure the mass to charge ratio (m/z and intensity of ionised molecules in crude extracts of complex biological samples to generate high dimensional metabolite 'fingerprint' or metabolite 'profile' data. High resolution MS instruments perform routinely with a mass accuracy of Results Metabolite 'structures' harvested from publicly accessible databases were converted into a common format to generate a comprehensive archive in MZedDB. 'Rules' were derived from chemical information that allowed MZedDB to generate a list of adducts and neutral loss fragments putatively able to form for each structure and calculate, on the fly, the exact molecular weight of every potential ionisation product to provide targets for annotation searches based on accurate mass. We demonstrate that data matrices representing populations of ionisation products generated from different biological matrices contain a large proportion (sometimes > 50% of molecular isotopes, salt adducts and neutral loss fragments. Correlation analysis of ESI-MS data features confirmed the predicted relationships of m/z signals. An integrated isotope enumerator in MZedDB allowed verification of exact isotopic pattern distributions to corroborate experimental data. Conclusion We conclude that although ultra-high accurate mass instruments provide major insight into the chemical diversity of biological extracts, the facile annotation of a large proportion of signals is not possible by simple, automated query of current databases using computed molecular formulae. Parameterising MZedDB to take into account predicted ionisation behaviour and the biological source of any sample improves greatly both the frequency and accuracy of potential annotation 'hits' in ESI-MS data.

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

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    Pekka Kuittinen

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

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

    Science.gov (United States)

    Zang, Yong; Liu, Suyu; Yuan, Ying

    2016-07-01

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

  19. 几种野值剔除准则在目标预测中的应用研究%Research on Rules for Eliminating Outliers and Its Application to Target Prediction

    Institute of Scientific and Technical Information of China (English)

    卢元磊; 何佳洲; 安瑾; 苗高洁

    2011-01-01

    The outliers in the measured data will have a bad effect on the precision of target prediction. So how to eliminate outliers is an all-important problem. In this paper we first introduce several rules for eliminating outliers, and apply them to data preprocess in target prediction. By simulation on these rules, we demonstrate not only their capability of eliminating outliers but also how they impact the precision of target prediction. The results indicate that these rules can greatly improve the precision of target prediction, and the better the rule behaves, the more precise the prediction will be. This paper provides a good reference on how to choose appropriate rules for eliminating outliers while there is rare literature in this field up to now.%观测数据中的野值会影响目标预测的精度.分析比较了几种常用的野值剔除准则,包括最常用的3δ准则、奈尔准则、格拉布斯准则和狄克逊准则,将其应用到目标预测的数据预处理中,并比较了各种方法的野值剔除能力和对目标预测精度的影响.仿真结果表明:野值剔除准则的引入可有效减少数据中野值的数量,提高目标预测的精度.其中,格拉布斯准则的实用效果尤为明显,且误剔除率也得到了较好的控制.

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

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    Cherie Quingking

    2013-03-01

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

  1. Acute axonal damage predicts clinical outcome in patients with multiple sclerosis

    DEFF Research Database (Denmark)

    Lim, E.T; Sellebjerg, F; Jensen, C.V

    2005-01-01

    The objectives of this study were (1) to determine how cerebrospinal fluid (CSF) neurofilament heavy chain (NfH(SM134) and NfH(SM135)) levels relate to clinical outcome in optic neuritis (ON) and multiple sclerosis (MS) relapse patients treated with high dose oral methylprednisolone; and (2...... in the MS attack trial were treated with oral methylprednisolone. In the MS attack trial group, CSF NfH(SM134) and NfH(SM135) measured at week 3 and deltaCSF NfH(SMI34) levels from baseline to week 3 were predictive of clinical outcome at week 8 and 52. In the ON group, no such association was seen. When...... both groups were combined, baseline CSF NfH(SHM134) and NfH(SM135) correlated positively with baseline enhancing lesion volume (ELV) (r(s) =0.50, P

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

    Science.gov (United States)

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

    2015-04-01

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

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

    Directory of Open Access Journals (Sweden)

    Theodore G Liou

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

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

    Institute of Scientific and Technical Information of China (English)

    Edouard; Louis; Jacques; Belaiche; Catherine; Reenaers

    2010-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2011-02-15

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

  6. Cosmic Sum Rules

    DEFF Research Database (Denmark)

    T. Frandsen, Mads; Masina, Isabella; Sannino, Francesco

    2011-01-01

    We introduce new sum rules allowing to determine universal properties of the unknown component of the cosmic rays and show how it can be used to predict the positron fraction at energies not yet explored by current experiments and to constrain specific models.......We introduce new sum rules allowing to determine universal properties of the unknown component of the cosmic rays and show how it can be used to predict the positron fraction at energies not yet explored by current experiments and to constrain specific models....

  7. Exploiting missing clinical data in Bayesian network modeling for predicting medical problems.

    Science.gov (United States)

    Lin, Jau-Huei; Haug, Peter J

    2008-02-01

    When machine learning algorithms are applied to data collected during the course of clinical care, it is generally accepted that the data has not been consistently collected. The absence of expected data elements is common and the mechanism through which a data element is missing often involves the clinical relevance of that data element in a specific patient. Therefore, the absence of data may have information value of its own. In the process of designing an application intended to support a medical problem list, we have studied whether the "missingness" of clinical data can provide useful information in building prediction models. In this study, we experimented with four methods of treating missing values in a clinical data set-two of them explicitly model the absence or "missingness" of data. Each of these data sets were used to build four different kinds of Bayesian classifiers-a naive Bayes structure, a human-composed network structure, and two networks based on structural learning algorithms. We compared the performance between groups with and without explicit models of missingness using the area under the ROC curve. The results showed that in most cases the classifiers trained using the explicit missing value treatments performed better. The result suggests that information may exist in "missingness" itself. Thus, when designing a decision support system, we suggest one consider explicitly representing the presence/absence of data in the underlying logic.

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

    LENUS (Irish Health Repository)

    Anyansi, Tochukwu E

    2013-06-01

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

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

    NARCIS (Netherlands)

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

    2013-01-01

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

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

    Science.gov (United States)

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

    2015-03-01

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

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

    OpenAIRE

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

    2015-01-01

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

  12. Early clinical signs in neonates with hypoxic ischemic encephalopathy predict an abnormal amplitude-integrated electroencephalogram at age 6 hours

    OpenAIRE

    Horn, Alan R; Swingler, George H; Myer, Landon; Linley, Lucy L; Raban, Moegammad S; Joolay, Yaseen; Harrison, Michael C; Chandrasekaran, Manigandan; Rhoda, Natasha R; Robertson, Nicola J.

    2013-01-01

    Background An early clinical score predicting an abnormal amplitude-integrated electroencephalogram (aEEG) or moderate-severe hypoxic ischemic encephalopathy (HIE) may allow rapid triage of infants for therapeutic hypothermia. We aimed to determine if early clinical examination could predict either an abnormal aEEG at age 6 hours or moderate-severe HIE presenting within 72 hours of birth. Methods Sixty infants ≥ 36 weeks gestational age were prospectively enrolled following suspected intrapar...

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

    Science.gov (United States)

    Cole, B L; Maddocks, J D

    1998-11-01

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

  14. Valuing structured professional judgment: predictive validity, decision-making, and the clinical-actuarial conflict.

    Science.gov (United States)

    Falzer, Paul R

    2013-01-01

    Structured professional judgment (SPJ) has received considerable attention as an alternative to unstructured clinical judgment and actuarial assessment, and as a means of resolving their ongoing conflict. However, predictive validity studies have typically relied on receiver operating characteristic (ROC) analysis, the same technique commonly used to validate actuarial assessment tools. This paper presents SPJ as distinct from both unstructured clinical judgment and actuarial assessment. A key distinguishing feature of SPJ is the contribution of modifiable factors, either dynamic or protective, to summary risk ratings. With modifiable factors, the summary rating scheme serves as a prognostic model rather than a classification procedure. However, prognostic models require more extensive and thorough predictive validity testing than can be provided by ROC analysis. It is proposed that validation should include calibration and reclassification techniques, as well as additional measures of discrimination. Several techniques and measures are described and illustrated. The paper concludes by tracing the limitations of ROC analysis to its philosophical foundation and its origin as a statistical theory of decision-making. This foundation inhibits the performance of crucial tasks, such as determining the sufficiency of a risk assessment and examining the evidentiary value of statistical findings. The paper closes by noting a current effort to establish a viable and complementary relationship between SPJ and decision-making theory.

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

    Directory of Open Access Journals (Sweden)

    Chris Poulin

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

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

    Science.gov (United States)

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

    2014-06-01

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

  17. 全血细胞分析复检规则临床调查报告%Clinical Investigation Report of Complete Blood Analysis Review Rules

    Institute of Scientific and Technical Information of China (English)

    陈国添

    2012-01-01

    目的 宣传、解释和讨论全血细胞分析复检规则(下称规则),为掌握复检重点提供依据.方法 将规则设计成调查问卷,通过院内网E-mail信访、访谈的形式向临床医生作调查.结果 发送E-mail信访医院32个临床科室152名医生,收回答卷36份,回收率23.7%.信访后访谈各级医生24名,访谈与信访获得的信息基本一致.经调查,在不同的疾病和同一疾病不同的临床阶段中,医生对全血细胞分析检验结果关注的重点不同:对于一般疾病,医生关注病人的WBC计数、WBC分类百分率、Hb含量和Plt计数;对于血液病,医生同时关注病人的WBC分类绝对值和MCV,MCH,MCHC和Ret等;对于手术病人,医生同时关注Hct.而某些RBC,Plt和Ret新参数在临床上则未能得到充分应用.结论 通过临床调查,检验人员进一步明确了全血细胞分析复检重点,同时血细胞新参数的临床应用有待加强.%Objective To propaganda,explain and discuss the complete blood cell analysis review rules (hereinafter referred to as the rules) and grasp the key to provide basis for review. Methods The rules designed questionnaire,through the hospital network E-mail letters and the form of interview to clinical doctor for investigation. Results Send E-mail letters hospital 32 clinical 152 doctors,far back of 36,recovery was 23. 7%. After interview complaint at all levels of the doctor 24,interviews, and the complaint information obtained were basically the same. After investigation,in different diseases and the same disease different clinical stage,the doctor to complete blood analysis test results focus of concern different:for general disease, doctors focus on the patient's leukocyte count, leukocyte classification percentage, hemoglobin concentration and platelets count. For blood disease,the doctor at the same time paied attention to the patient's leukocyte classification absolute value and MCV,MCH,MCHC and Ret. For surgery patients,doctors at

  18. A comparative study: classification vs. user-based collaborative filtering for clinical prediction

    Directory of Open Access Journals (Sweden)

    Fang Hao

    2016-12-01

    Full Text Available Abstract Background Recommender systems have shown tremendous value for the prediction of personalized item recommendations for individuals in a variety of settings (e.g., marketing, e-commerce, etc.. User-based collaborative filtering is a popular recommender system, which leverages an individuals’ prior satisfaction with items, as well as the satisfaction of individuals that are “similar”. Recently, there have been applications of collaborative filtering based recommender systems for clinical risk prediction. In these applications, individuals represent patients, and items represent clinical data, which includes an outcome. Methods Application of recommender systems to a problem of this type requires the recasting a supervised learning problem as unsupervised. The rationale is that patients with similar clinical features carry a similar disease risk. As the “Big Data” era progresses, it is likely that approaches of this type will be reached for as biomedical data continues to grow in both size and complexity (e.g., electronic health records. In the present study, we set out to understand and assess the performance of recommender systems in a controlled yet realistic setting. User-based collaborative filtering recommender systems are compared to logistic regression and random forests with different types of imputation and varying amounts of missingness on four different publicly available medical data sets: National Health and Nutrition Examination Survey (NHANES, 2011-2012 on Obesity, Study to Understand Prognoses Preferences Outcomes and Risks of Treatment (SUPPORT, chronic kidney disease, and dermatology data. We also examined performance using simulated data with observations that are Missing At Random (MAR or Missing Completely At Random (MCAR under various degrees of missingness and levels of class imbalance in the response variable. Results Our results demonstrate that user-based collaborative filtering is consistently inferior

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-06-15

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

  20. Clinical utility of C-reactive protein to predict treatment response during cystic fibrosis pulmonary exacerbations

    Science.gov (United States)

    Sharma, Ashutosh; Kirkpatrick, Gordon; Chen, Virginia; Skolnik, Kate; Hollander, Zsuzsanna; Wilcox, Pearce; Quon, Bradley S.

    2017-01-01

    Rationale C-reactive protein (CRP) is a systemic marker of inflammation that correlates with disease status in cystic fibrosis (CF). The clinical utility of CRP measurement to guide pulmonary exacerbation (PEx) treatment decisions remains uncertain. Objectives To determine whether monitoring CRP during PEx treatment can be used to predict treatment response. We hypothesized that early changes in CRP can be used to predict treatment response. Methods We reviewed all PEx events requiring hospitalization for intravenous (IV) antibiotics over 2 years at our institution. 83 PEx events met our eligibility criteria. CRP levels from admission to day 5 were evaluated to predict treatment non-response, using a modified version of a prior published composite definition. CRP was also evaluated to predict time until next exacerbation (TUNE). Measurements and main results 53% of 83 PEx events were classified as treatment non-response. Paradoxically, 24% of PEx events were characterized by a ≥ 50% increase in CRP levels within the first five days of treatment. Absolute change in CRP from admission to day 5 was not associated with treatment non-response (p = 0.58). Adjusted for FEV1% predicted, admission log10 CRP was associated with treatment non-response (OR: 2.39; 95% CI: 1.14 to 5.91; p = 0.03) and shorter TUNE (HR: 1.60; 95% CI: 1.13 to 2.27; p = 0.008). The area under the receiver operating characteristics (ROC) curve of admission CRP to predict treatment non-response was 0.72 (95% CI 0.61–0.83; p 75 mg/L with a specificity of 90% for treatment non-response. Conclusions Admission CRP predicts treatment non-response and time until next exacerbation. A very elevated admission CRP (>75mg/L) is highly specific for treatment non-response and might be used to target high-risk patients for future interventional studies aimed at improving exacerbation outcomes. PMID:28178305

  1. Can a Clinical Test of Reaction Time Predict a Functional Head-Protective Response?

    Science.gov (United States)

    ECKNER, JAMES T.; LIPPS, DAVID B.; KIM, HOGENE; RICHARDSON, JAMES K.; ASHTON-MILLER, JAMES A.

    2015-01-01

    Purpose Reaction time is commonly prolonged after a sport-related concussion. Besides being a marker for injury, a rapid reaction time is necessary for protective maneuvers that can reduce the frequency and severity of additional head impacts. The purpose of this study was to determine whether a clinical test of simple visuomotor reaction time predicted the time taken to raise the hands to protect the head from a rapidly approaching ball. Methods Twenty-six healthy adult participants recruited from campus and community recreation and exercise facilities completed two experimental protocols during a single session: a manual visuomotor simple reaction time test (RTclin) and a sport-related head-protective response (RTsprt). RTclin measured the time required to catch a thin vertically oriented device on its release by the tester and was calculated from the distance the device fell before being arrested. RTsprt measured the time required to raise the hands from waist level to block a foam tennis ball fired toward the subject’s face from an air cannon and was determined using an optoelectronic camera system. A correlation coefficient was calculated between RTclin and RTsprt, with linear regression used to assess for effect modification by other covariates. Results A strong positive correlation was found between RTclin and RTsprt (r = 0.725, P < 0.001) independent of age, gender, height, or weight. Conclusions RTclin is predictive of a functional sport-related head-protective response. To our knowledge, this is the first demonstration of a clinical test predicting the ability to protect the head in a simulated sport environment. This correlation with a functional head-protective response is a relevant consideration for the potential use of RTclin as part of a multifaceted concussion assessment program. PMID:20689458

  2. Advanced Online Survival Analysis Tool for Predictive Modelling in Clinical Data Science.

    Science.gov (United States)

    Montes-Torres, Julio; Subirats, José Luis; Ribelles, Nuria; Urda, Daniel; Franco, Leonardo; Alba, Emilio; Jerez, José Manuel

    2016-01-01

    One of the prevailing applications of machine learning is the use of predictive modelling in clinical survival analysis. In this work, we present our view of the current situation of computer tools for survival analysis, stressing the need of transferring the latest results in the field of machine learning to biomedical researchers. We propose a web based software for survival analysis called OSA (Online Survival Analysis), which has been developed as an open access and user friendly option to obtain discrete time, predictive survival models at individual level using machine learning techniques, and to perform standard survival analysis. OSA employs an Artificial Neural Network (ANN) based method to produce the predictive survival models. Additionally, the software can easily generate survival and hazard curves with multiple options to personalise the plots, obtain contingency tables from the uploaded data to perform different tests, and fit a Cox regression model from a number of predictor variables. In the Materials and Methods section, we depict the general architecture of the application and introduce the mathematical background of each of the implemented methods. The study concludes with examples of use showing the results obtained with public datasets.

  3. Strategies to design clinical studies to identify predictive biomarkers in cancer research.

    Science.gov (United States)

    Perez-Gracia, Jose Luis; Sanmamed, Miguel F; Bosch, Ana; Patiño-Garcia, Ana; Schalper, Kurt A; Segura, Victor; Bellmunt, Joaquim; Tabernero, Josep; Sweeney, Christopher J; Choueiri, Toni K; Martín, Miguel; Fusco, Juan Pablo; Rodriguez-Ruiz, Maria Esperanza; Calvo, Alfonso; Prior, Celia; Paz-Ares, Luis; Pio, Ruben; Gonzalez-Billalabeitia, Enrique; Gonzalez Hernandez, Alvaro; Páez, David; Piulats, Jose María; Gurpide, Alfonso; Andueza, Mapi; de Velasco, Guillermo; Pazo, Roberto; Grande, Enrique; Nicolas, Pilar; Abad-Santos, Francisco; Garcia-Donas, Jesus; Castellano, Daniel; Pajares, María J; Suarez, Cristina; Colomer, Ramon; Montuenga, Luis M; Melero, Ignacio

    2017-02-01

    The discovery of reliable biomarkers to predict efficacy and toxicity of anticancer drugs remains one of the key challenges in cancer research. Despite its relevance, no efficient study designs to identify promising candidate biomarkers have been established. This has led to the proliferation of a myriad of exploratory studies using dissimilar strategies, most of which fail to identify any promising targets and are seldom validated. The lack of a proper methodology also determines that many anti-cancer drugs are developed below their potential, due to failure to identify predictive biomarkers. While some drugs will be systematically administered to many patients who will not benefit from them, leading to unnecessary toxicities and costs, others will never reach registration due to our inability to identify the specific patient population in which they are active. Despite these drawbacks, a limited number of outstanding predictive biomarkers have been successfully identified and validated, and have changed the standard practice of oncology. In this manuscript, a multidisciplinary panel reviews how those key biomarkers were identified and, based on those experiences, proposes a methodological framework-the DESIGN guidelines-to standardize the clinical design of biomarker identification studies and to develop future research in this pivotal field.

  4. Thyroid Hormones, Autoantibodies, Ultrasonography, and Clinical Parameters for Predicting Thyroid Cancer

    Science.gov (United States)

    He, Lin-zheng; Zeng, Tian-shu; Pu, Lin; Pan, Shi-xiu; Xia, Wen-fang; Chen, Lu-lu

    2016-01-01

    Our objective was to evaluate thyroid nodule malignancy prediction using thyroid function tests, autoantibodies, ultrasonographic imaging, and clinical data. We conducted a retrospective cohort study in 1400 patients with nodular thyroid disease (NTD). The thyroid stimulating hormone (TSH) concentration was significantly higher in patients with differentiated thyroid cancer (DTC) versus benign thyroid nodular disease (BTND) (p = 0.004). The receiver operating characteristic curve of TSH showed an AUC of 0.58 (95% CI 0.53–0.62, p = 0.001), sensitivity of 74%, and specificity of 57% at a cut-off of 1.59 mIU/L. There was an incremental increase in TSH concentration along with the increasing tumor size (p < 0.001). Thyroglobulin antibody (TgAb) concentration was associated with an increased risk of malignancy (p = 0.029), but this association was lost when the effect of TSH was taken into account (p = 0.11). Thyroid ultrasonographic characteristics, including fewer than three nodules, hypoechoic appearance, solid component, poorly defined margin, intranodular or peripheral-intranodular flow, and punctate calcification, can be used to predict the risk of thyroid cancer. In conclusion, our study suggests that preoperative serum TSH concentration, age, and ultrasonographic features can be used to predict the risk of malignancy in patients with NTD. PMID:27313612

  5. Cross-sectional imaging for diagnosis and clinical outcome prediction of acute basilar artery thrombosis

    Energy Technology Data Exchange (ETDEWEB)

    Mortimer, A.M., E-mail: alex_mortimer@hotmail.co [Severn School of Radiology, Bristol (United Kingdom); Department of Radiology, Great Western Hospital, Swindon (United Kingdom); Saunders, T.; Cook, J.-L. [Department of Radiology, Great Western Hospital, Swindon (United Kingdom)

    2011-06-15

    Basilar artery occlusion is a potentially fatal condition and imaging findings can be subtle. Prompt diagnosis is vital, as recognition may lead to therapeutic recanalization that may improve functional outcome and survival. Furthermore, cross-sectional imaging signs may help predict eventual outcome and, therefore, guide which patients should be subjected to aggressive treatment. Computed tomography (CT) signs include a hyperdense basilar artery that has a high specificity, accuracy, positive and negative predictive value. Evidence regarding the prognostic significance of the hyperdense basilar artery sign is conflicting. Early magnetic resonance imaging (MRI) features include loss of flow void, seen as increased signal intensity within the basilar artery on T2-weigted images and identification of acute thrombus, seen as intermediate signal on T1-weighted images. MRI sequences are more sensitive for early detection of acute ischaemia or infarction, ideally with diffusion-weighted imaging (DWI). Both CT and MR angiography are sensitive for detection of acute thrombus, seen as a filling defect or occlusion. These are the non-invasive imaging techniques of choice to confirm diagnosis, with perhaps the speed and accessibility of CT angiography resulting in this technique being valuable in the acute setting. Several new scoring systems based on arterial segmentation rather than global volume assessment using CT angiography source images and DWI have shown early promise in the prediction of eventual clinical outcome in order to isolate those patients who may benefit from therapeutic recanalization.

  6. Side-effects of subthalamic stimulation in Parkinson's disease: clinical evolution and predictive factors.

    Science.gov (United States)

    Guehl, D; Cuny, E; Benazzouz, A; Rougier, A; Tison, F; Machado, S; Grabot, D; Gross, C; Bioulac, B; Burbaud, P

    2006-09-01

    Chronic bilateral high-frequency stimulation of the subthalamic nucleus (STN) is an alternative treatment for disabling forms of Parkinson's disease when on-off fluctuations and levodopa-induced dyskinesias compromise patients' quality of life. The aim of this study was to assess the evolution of side-effects during the first year of follow-up and search for clinical predictive factors accounting for their occurrence. We compared the frequency of side-effects at 3 and 12 months after surgery in a cohort of 44 patients. The off-medication scores of Unified Parkinson's Disease Rating Scale (UPDRS) II, III, axial symptoms, disease duration and age at surgery were retained for correlation analysis. Dysarthria/hypophonia, weight gain and postural instability were the most frequent chronic side-effects. Whereas dysarthria/hypophonia remained stable over time, weight gain and postural instability increased during the first year post-op. High axial and UPDRS II scores at surgery were predictive of dysarthria/hypophonia. Age and axial score at surgery were positively correlated with postural instability. Despite the occurrence of side-effects, the benefit/side-effects ratio of STN stimulation was largely positive during the first year of follow-up. Age, intensity of axial symptoms and UDPRS II off-medication score before surgery are predictive factors of dysarthria/hypophonia and postural instability after surgery.

  7. A Clinical Indications Prediction Scale Based on TWIST1 for Human Mesenchymal Stem Cells

    Directory of Open Access Journals (Sweden)

    Siddaraju V. Boregowda

    2016-02-01

    Full Text Available In addition to their stem/progenitor properties, mesenchymal stem cells (MSCs also exhibit potent effector (angiogenic, antiinflammatory, immuno-modulatory functions that are largely paracrine in nature. It is widely believed that effector functions underlie most of the therapeutic potential of MSCs and are independent of their stem/progenitor properties. Here we demonstrate that stem/progenitor and effector functions are coordinately regulated at the cellular level by the transcription factor Twist1 and specified within populations according to a hierarchical model. We further show that manipulation of Twist1 levels by genetic approaches or by exposure to widely used culture supplements including fibroblast growth factor 2 (Ffg2 and interferon gamma (IFN-gamma alters MSC efficacy in cell-based and in vivo assays in a predictable manner. Thus, by mechanistically linking stem/progenitor and effector functions our studies provide a unifying framework in the form of an MSC hierarchy that models the functional complexity of populations. Using this framework, we developed a CLinical Indications Prediction (CLIP scale that predicts how donor-to-donor heterogeneity and culture conditions impact the therapeutic efficacy of MSC populations for different disease indications.

  8. Predictive Value of IL-8 for Sepsis and Severe Infections After Burn Injury: A Clinical Study.

    Science.gov (United States)

    Kraft, Robert; Herndon, David N; Finnerty, Celeste C; Cox, Robert A; Song, Juquan; Jeschke, Marc G

    2015-03-01

    The inflammatory response induced by burn injury contributes to increased incidence of infections, sepsis, organ failure, and mortality. Thus, monitoring postburn inflammation is of paramount importance but, so far, there are no reliable biomarkers available to monitor and/or predict infectious complications after burn. As interleukin 8 (IL-8) is a major mediator for inflammatory responses, the aim of our study was to determine whether IL-8 expression can be used to predict postburn sepsis, infections, and mortality. Plasma cytokines, acute-phase proteins, constitutive proteins, and hormones were analyzed during the first 60 days after injury from 468 pediatric burn patients. Demographics and clinical outcome variables (length of stay, infection, sepsis, multiorgan failure [MOF], and mortality) were recorded. A cutoff level for IL-8 was determined using receiver operating characteristic analysis. Statistical significance is set at P Patients were grouped according to their average IL-8 levels relative to this cutoff and stratified into high (H) (n = 133) and low (L) (n = 335) groups. In the L group, regression analysis revealed a significant predictive value of IL-8 to percent of total body surface area burned and incidence of MOF (P inflammatory and acute-phase responses compared with the L group (P burn patients.

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

    Science.gov (United States)

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

    2015-02-01

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

  10. Outcomes of Health System Structures, Highly Pertinent Clinical Information, Idea Stimulators, Clinical Reviews, and Prediction Tools: JABFM Exemplified.

    Science.gov (United States)

    Bowman, Marjorie A; Neale, Anne Victoria; Seehusen, Dean A

    2016-01-01

    This issue exemplifies the types of articles that JABFM publishes to advance family medicine. We have articles on the implications of health system organizational structures. Three of these are international articles at the level of the national health system (1 from China) and systematic local health interventions (1 from Canada and 1 from Netherlands). Inside the United States, where there are more family physicians, there is less obesity, and designation as a Patient Centered Medical Home is related to increased rates of colorectal cancer screening. Review articles on common clinical topics discuss treatments that are changing (acne in pregnancy) or lack consensus (distal radial fractures). We have articles on making life easier in the office, such as for predicting Vitamin D levels, osteoporosis, and pre-diabetes in normal weight adults. There are articles to raise awareness of the "newest" testing or treatments, that is, auditory brainstem implants. "Reminder" articles highlight known entities that need to be reinforced to prevent over-/underdiagnosis or treatment, for example, "cotton fever." Another article discusses the increased risk for postoperative complications with sleep apnea. We also provide "thought" pieces, in this case about the terminology we are using to extend our concept of patient-centered medical homes.

  11. Prediction of clinical factors associated with pandemic influenza A (H1N1 2009 in Pakistan.

    Directory of Open Access Journals (Sweden)

    Nadia Nisar

    Full Text Available BACKGROUND: Influenza is a viral infection that can lead to serious complications and death(s in vulnerable groups if not diagnosed and managed in a timely manner. This study was conducted to improve the accuracy of predicting influenza through various clinical and statistical models. METHODOLOGY: A retrospective cross sectional analysis was done on demographic and epidemiological data collected from March 2009 to March 2010. Patients were classified as ILI or SARI using WHO case definitions. Respiratory specimens were tested by RT-PCR. Clinical symptoms and co-morbid conditions were analyzed using binary logistic regression models. RESULTS: In the first approach, analysis compared children (≤12 and adults (>12. Of 1,243 cases, 262 (21% tested positive for A(H1N1pdm09 and the proportion of children (≤12 and adults (>12 were 27% and 73% respectively. Four symptoms predicted influenza in children: fever (OR 2.849, 95% CI 1.931-8.722, cough (OR 1.99, 95% CI 1.512-3.643, diarrhea (OR 2.100, 95% CI 2.040-3.25 and respiratory disease (OR 3.269, 95% CI 2.128-12.624. In adults, the strongest clinical predictor was fever (OR 2.80, 95% CI 1.025-3.135 followed by cough (OR 1.431, 95% CI 1.032-2.815. In the second instance, patients were separated into two groups: SARI 326 (26% and ILI 917 (74% cases. Male to female ratio was 1.41∶1.12 for SARI and 2∶1.5 for ILI cases. Chi-square test showed that fever, cough and sore throat were significant factors for A(H1N1pdm09 infections (p = 0.008. CONCLUSION: Studies in a primary care setting should be encouraged focused on patients with influenza-like illness to develop sensitive clinical case definition that will help to improve accuracy of detecting influenza infections. Formulation of a standard "one size fits all" case definition that best correlates with influenza infections can help guide decisions for additional diagnostic testing and also discourage unjustified antibiotic prescription and usage

  12. Incorporation of expert variability into breast cancer treatment recommendation in designing clinical protocol guided fuzzy rule system models.

    Science.gov (United States)

    Garibaldi, Jonathan M; Zhou, Shang-Ming; Wang, Xiao-Ying; John, Robert I; Ellis, Ian O

    2012-06-01

    It has been often demonstrated that clinicians exhibit both inter-expert and intra-expert variability when making difficult decisions. In contrast, the vast majority of computerized models that aim to provide automated support for such decisions do not explicitly recognize or replicate this variability. Furthermore, the perfect consistency of computerized models is often presented as a de facto benefit. In this paper, we describe a novel approach to incorporate variability within a fuzzy inference system using non-stationary fuzzy sets in order to replicate human variability. We apply our approach to a decision problem concerning the recommendation of post-operative breast cancer treatment; specifically, whether or not to administer chemotherapy based on assessment of five clinical variables: NPI (the Nottingham Prognostic Index), estrogen receptor status, vascular invasion, age and lymph node status. In doing so, we explore whether such explicit modeling of variability provides any performance advantage over a more conventional fuzzy approach, when tested on a set of 1310 unselected cases collected over a fourteen year period at the Nottingham University Hospitals NHS Trust, UK. The experimental results show that the standard fuzzy inference system (that does not model variability) achieves overall agreement to clinical practice around 84.6% (95% CI: 84.1-84.9%), while the non-stationary fuzzy model can significantly increase performance to around 88.1% (95% CI: 88.0-88.2%), p<0.001. We conclude that non-stationary fuzzy models provide a valuable new approach that may be applied to clinical decision support systems in any application domain.

  13. Clinical findings just after return to play predict hamstring re-injury, but baseline MRI findings do not

    NARCIS (Netherlands)

    R.J. de Vos (Robert-Jan); G. Reurink (Gustaaf); G.J. Goudswaard (Gert Jan); M.H. Moen (Maaike); A. Weir (Adam); J.L. Tol (Johannes)

    2014-01-01

    markdownabstract__Abstract__ Background Acute hamstring re-injuries are common and hard to predict. The aim of this study was to investigate the association between clinical and imaging findings and the occurrence of hamstring re-injuries. Methods We obtained baseline data (clinical and MRI finding

  14. Prediction of clinical response based on pharmacokinetic/pharmacodynamic models of 5-hydroxytryptamine reuptake inhibitors in mice

    DEFF Research Database (Denmark)

    Kreilgaard, Mads; Smith, D. G.; Brennum, L. T.;

    2008-01-01

    Bridging the gap between preclinical research and clinical trials is vital for drug development. Predicting clinically relevant steady-state drug concentrations (Css) in serum from preclinical animal models may facilitate this transition. Here we used a pharmacokinetic/pharmacodynamic (PK/PD) mod...

  15. Outcome prediction in mild traumatic brain injury : age and clinical variables are stronger predictors than CT abnormalities

    NARCIS (Netherlands)

    Jacobs, Bram; Beems, Tjemme; Stulemeijer, Maja; van Vugt, Arie B; van der Vliet, Ton M; Borm, George F; Vos, Pieter E

    2010-01-01

    Mild traumatic brain injury (mTBI) is a common heterogeneous neurological disorder with a wide range of possible clinical outcomes. Accurate prediction of outcome is desirable for optimal treatment. This study aimed both to identify the demographic, clinical, and computed tomographic (CT) characteri

  16. Indoor Quality Control Rules for Routine Clinical Biochemical Tests%临床常规生化项目室内质控方法的设计

    Institute of Scientific and Technical Information of China (English)

    郑强

    2015-01-01

    Objective To study the indoor quality control rules for routine clinical biochemical tests. Methods Quality control indexes of Alkaline phosphatase (ALKP), potassium (K) and calcium (Ca) from July to December 2012 were collected. The accumulative coefficient of variation (CA) of indoor quality control was used as imprecision degree;bias was calculated using external quality assessment of Clinical Laboratory Center of Chinese Ministry of Public Health;total error al-lowance was evaluated using proficiency testing in American Clinical Laboratory Improvement Amendments 88 (CLIA'88). The feasible indoor quality control methods were made based on operational process of specification chart so as to improve the prob-ability for error detection (Ped) and reduce the probability for false rejection (Pfr). Results The measured value of each batch control number was 2, and ALKP and K were chosen for 1-3 s as quality control rule in order to achieve Ped above 90%and Pfr below 5%;however, the measured value of each batch control number was 4, and Ca was chosen for 1-3 s/2-2 s/R-4 s/4-1 s/12-X as quality control rule in order to achieve Ped above 90% and Pfr below 5%. Conclusion Different biochem-ical analysis projects should select different control rules based on the different performance characteristics of analytical methods.%目的:探讨保证临床质量要求的常规生化项目室内质控规则的设计。方法收集2012年7—12月碱性磷酸酶(ALKP)、钾、钙的质控数据,以室内质控的累积变异系数(CV)作为项目的不精密度,应用卫生部临床检验中心室间质评结果计算偏倚,选择美国临床实验室改进修正法规88能力比对检验评价限为总允许误差,借助操作过程规范图设计符合本实验室切实可行的室内质控方法,从而提高误差检出概率( Ped),降低假失控概率( Pfr)。结果ALKP、钾每天测定质控品个数为2,选择1-3 s单质控规则即可满足Ped>90%,Pfr90%,Pfr<5%。结论

  17. Remarks on kernel Bayes' rule

    OpenAIRE

    Johno, Hisashi; Nakamoto, Kazunori; Saigo, Tatsuhiko

    2015-01-01

    Kernel Bayes' rule has been proposed as a nonparametric kernel-based method to realize Bayesian inference in reproducing kernel Hilbert spaces. However, we demonstrate both theoretically and experimentally that the prediction result by kernel Bayes' rule is in some cases unnatural. We consider that this phenomenon is in part due to the fact that the assumptions in kernel Bayes' rule do not hold in general.

  18. Predicting long-term independency in activities of daily living after middle cerebral artery stroke: does information from MRI have added predictive value compared with clinical information?

    NARCIS (Netherlands)

    Schiemanck, S.K.; Kwakkel, G.; Post, M.W.; Kappelle, L.J.; Prevo, A.J.

    2006-01-01

    BACKGROUND AND PURPOSE: To investigate whether neuroimaging information has added predictive value compared with clinical information for independency in activities of daily living (ADL) 1 year after stroke. METHODS: Seventy-five first-ever middle cerebral artery stroke survivors were evaluated in l

  19. Predictability of the individual clinical outcome of extracorporeal shock wave therapy for cellulite

    Directory of Open Access Journals (Sweden)

    Schlaudraff KU

    2014-05-01

    Full Text Available Kai-Uwe Schlaudraff,1 Maren C Kiessling,2 Nikolaus BM Császár,2 Christoph Schmitz21Concept Clinic, Geneva, Switzerland; 2Department of Anatomy II, Ludwig-Maximilians-University of Munich, Munich, GermanyBackground: Extracorporeal shock wave therapy has been successfully introduced for the treatment of cellulite in recent years. However, it is still unknown whether the individual clinical outcome of cellulite treatment with extracorporeal shock wave therapy can be predicted by the patient's individual cellulite grade at baseline, individual patient age, body mass index (BMI, weight, and/or height.Methods: Fourteen Caucasian females with cellulite were enrolled in a prospective, single-center, randomized, open-label Phase II study. The mean (± standard error of the mean cellulite grade at baseline was 2.5±0.09 and mean BMI was 22.8±1.17. All patients were treated with radial extracorporeal shock waves using the Swiss DolorClast® device (Electro Medical Systems, S.A., Nyon, Switzerland. Patients were treated unilaterally with 2 weekly treatments for 4 weeks on a randomly selected side (left or right, totaling eight treatments on the selected side. Treatment was performed at 3.5–4.0 bar, with 15,000 impulses per session applied at 15 Hz. Impulses were homogeneously distributed over the posterior thigh and buttock area (resulting in 7,500 impulses per area. Treatment success was evaluated after the last treatment and 4 weeks later by clinical examination, photographic documentation, contact thermography, and patient satisfaction questionnaires.Results: The mean cellulite grade improved from 2.5±0.09 at baseline to 1.57±0.18 after the last treatment (ie, mean δ-1 was 0.93 cellulite grades and 1.68±0.16 at follow-up (ie, mean δ-2 was 0.82 cellulite grades. Compared with baseline, no patient's condition worsened, the treatment was well tolerated, and no unwanted side effects were observed. No statistically significant (ie, P<0

  20. Predictable risk factors and clinical courses for prolonged transient tachypnea of the newborn

    Directory of Open Access Journals (Sweden)

    Ji Young Chang

    2010-03-01

    Full Text Available Purpose : Transient tachypnea of the newborn (TTN is usually benign and improves within 72 hours. However, it can also progress to prolonged tachypnea over 72 hours, profound hypoxemia, respiratory failure, and even death. The aim of this study is to find predictable risk factors and describe the clinical courses and outcomes of prolonged TTN (PTTN. Methods : The medical records of 107 newborns, &gt;35+0 weeks of gestational age with TTN, who were admitted to the NICU at Seoul Asan Medical Center from January 2001 to September 2007 were reviewed. They were divided into 2 groups based on duration of tachypnea. PTTN was defined as tachypnea ?#247;2 hours of age, and simple TTN (STTN as tachypnea &lt;72 hours of age. We randomly selected 126 healthy-term newborns as controls. We evaluated neonatal and maternal demographic findings, and various clinical factors. Results : Fifty-five infants (51% with total TTN were PTTN. PTTN infants had grunting, tachypnea &gt;90/min, FiO2 &gt;0.4, and required ventilator care more frequently than STTN infants. PTTN had lower level of serum total protein and albumin than STTN. The independent predictable risk factors for PTTN were grunting, maximal respiration rate &gt;90/min, and FiO2 &gt;0.4 within 6 hours of life. Conclusion : When a newborn has grunting, respiration rate &gt;90/min, and oxygen requirement &gt;0.4 of FiO2 within 6 hours of life, the infant is at high risk of having persistent tachypnea ?#247;2 hours. We need further study to find the way to reduce PTTN.

  1. DNA Methylation-Guided Prediction of Clinical Failure in High-Risk Prostate Cancer.

    Directory of Open Access Journals (Sweden)

    Kirill Litovkin

    Full Text Available Prostate cancer (PCa is a very heterogeneous disease with respect to clinical outcome. This study explored differential DNA methylation in a priori selected genes to diagnose PCa and predict clinical failure (CF in high-risk patients.A quantitative multiplex, methylation-specific PCR assay was developed to assess promoter methylation of the APC, CCND2, GSTP1, PTGS2 and RARB genes in formalin-fixed, paraffin-embedded tissue samples from 42 patients with benign prostatic hyperplasia and radical prostatectomy specimens of patients with high-risk PCa, encompassing training and validation cohorts of 147 and 71 patients, respectively. Log-rank tests, univariate and multivariate Cox models were used to investigate the prognostic value of the DNA methylation.Hypermethylation of APC, CCND2, GSTP1, PTGS2 and RARB was highly cancer-specific. However, only GSTP1 methylation was significantly associated with CF in both independent high-risk PCa cohorts. Importantly, trichotomization into low, moderate and high GSTP1 methylation level subgroups was highly predictive for CF. Patients with either a low or high GSTP1 methylation level, as compared to the moderate methylation groups, were at a higher risk for CF in both the training (Hazard ratio [HR], 3.65; 95% CI, 1.65 to 8.07 and validation sets (HR, 4.27; 95% CI, 1.03 to 17.72 as well as in the combined cohort (HR, 2.74; 95% CI, 1.42 to 5.27 in multivariate analysis.Classification of primary high-risk tumors into three subtypes based on DNA methylation can be combined with clinico-pathological parameters for a more informative risk-stratification of these PCa patients.

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

    Directory of Open Access Journals (Sweden)

    Bahloul Mabrouk

    2010-01-01

    Full Text Available Objective : To determine predictive factors, clinical and demographics characteristics of patients with pulmonary embolism (PE in ICU, and to identify factors associated with poor outcome in the hospital and in the ICU. Methods : During a four-year prospective study, a medical committee of six ICU physicians prospectively examined all available data for each patient in order to classify patients according to the level of clinical suspicion of pulmonary thromboembolism. During the study periods, all patients admitted to our ICU were classified into four groups. The first group includes all patients with confirmed PE; the second group includes some patients without clinical manifestations of PE; the third group includes patients with suspected and not confirmed PE and the fourth group includes all patients with only deep vein thromboses (DVTs without suspicion of PE. The diagnosis of PE was confirmed either by a high-probability ventilation/perfusion (V/Q scan or by a spiral computed tomography (CT scan showing one or more filling defects in the pulmonary artery or in its branches. The diagnosis was also confirmed by echocardiography when a thrombus in the pulmonary artery was observed. Results : During the study periods, 4408 patients were admitted in our ICU. The diagnosis of PE was confirmed in 87 patients (1.9%. The mean delay of development of PE was 7.8 ± 9.5 days. On the day of PE diagnosis, clinical examination showed that 50 patients (57.5% were hypotensive, 63 (72.4% have SIRS, 15 (17.2% have clinical manifestations of DVT and 71 (81.6% have respiratory distress requiring mechanical ventilation. In our study, intravenous unfractionated heparin was used in 81 cases (93.1% and low molecular weight heparins were used in 4 cases (4.6%. The mean ICU stay was 20.2 ± 25.3 days and the mean hospital stay was 25.5 ± 25 days. The mortality rate in ICU was 47.1% and the in-hospital mortality rate was 52.9%. Multivariate analysis showed that

  3. Traditional clinical risk factors predict clopidogrel hypo-responsiveness in unselected patients undergoing non-emergent percutaneous coronary intervention

    DEFF Research Database (Denmark)

    Ratcovich, Hanna; Holmvang, Lene; Johansson, Pär Inge

    2016-01-01

    High and low platelet reactivity, HPR and LPR respectively, to clopidogrel and aspirin have previously been associated with adverse events following percutaneous coronary intervention (PCI). The aim is to test the ability of a previously developed clinical risk-score, the PREDICT score, to identify...... of PREDICT score variables and the incidence of HPR for clopidogrel (HPR (ADP)) (p ... = 0.003); 7-9 points OR 9.84 (95% CI 3.49-27.7, p clopidogrel LPR (LPR (ADP)). On the other hand, there was no clear association between PREDICT score and AA response. The PREDICT...

  4. Clinical usefulness of the clock drawing test applying rasch analysis in predicting of cognitive impairment.

    Science.gov (United States)

    Yoo, Doo Han; Lee, Jae Shin

    2016-07-01

    [Purpose] This study examined the clinical usefulness of the clock drawing test applying Rasch analysis for predicting the level of cognitive impairment. [Subjects and Methods] A total of 187 stroke patients with cognitive impairment were enrolled in this study. The 187 patients were evaluated by the clock drawing test developed through Rasch analysis along with the mini-mental state examination of cognitive evaluation tool. An analysis of the variance was performed to examine the significance of the mini-mental state examination and the clock drawing test according to the general characteristics of the subjects. Receiver operating characteristic analysis was performed to determine the cutoff point for cognitive impairment and to calculate the sensitivity and specificity values. [Results] The results of comparison of the clock drawing test with the mini-mental state showed significant differences in according to gender, age, education, and affected side. A total CDT of 10.5, which was selected as the cutoff point to identify cognitive impairement, showed a sensitivity, specificity, Youden index, positive predictive, and negative predicive values of 86.4%, 91.5%, 0.8, 95%, and 88.2%. [Conclusion] The clock drawing test is believed to be useful in assessments and interventions based on its excellent ability to identify cognitive disorders.

  5. Multidetector-CT angiography in pulmonary embolism - can image parameters predict clinical outcome?

    Energy Technology Data Exchange (ETDEWEB)

    Heyer, Christoph M.; Lemburg, Stefan P.; Nicolas, Volkmar; Roggenland, Daniela [Berufsgenossenschaftliches Universitaetsklinikum Bergmannsheil GmbH, Ruhr-University of Bochum, Institute of Diagnostic Radiology, Interventional Radiology and Nuclear Medicine, Bochum (Germany); Knoop, Heiko [Berufsgenossenschaftliches Universitaetsklinikum Bergmannsheil GmbH, Medical Clinic III - Pneumology, Allergology, and Sleep Medicine, Bochum (Germany); Holland-Letz, Tim [Ruhr-University of Bochum, Department of Medical Informatics, Biometry and Epidemiology, Bochum (Germany)

    2011-09-15

    To assess if pulmonary CT angiography (CTA) can predict outcome in patients with pulmonary embolism (PE). Retrospective analysis of CTA studies of patients with PE and documentation of pulmonary artery (PA)/aorta ratio, right ventricular (RV)/left ventricular (LV) ratio, superior vena cava (SVC) diameter, pulmonary obstruction index (POI), ventricular septal bowing (VSB), venous contrast reflux (VCR), pulmonary infarction and pleural effusion. Furthermore, duration of total hospital stay, necessity for/duration of ICU therapy, necessity for mechanical ventilation and mortality were recorded. Comparison was performed by logistic/linear regression analysis with significance at 5%. 152 patients were investigated. Mean duration of hospital stay was 21 {+-} 24 days. 66 patients were admitted to the ICU; 20 received mechanical ventilation. Mean duration of ICU therapy was 3 {+-} 8 days. Mortality rate was 8%. Significant positive associations of POI, VCR and pulmonary infarction with necessity for ICU therapy were shown. VCR was significantly associated with necessity for mechanical ventilation and duration of ICU treatment. Pleural effusions were significantly associated with duration of total hospital stay whereas the RV/LV ratio correlated with mortality. Selected CTA findings showed significant associations with the clinical course of PE and may thus be used as predictive parameters. (orig.)

  6. [Using CTS and PK-PD models to predict the effect of uncertainty about population parameters on clinical trial power].

    Science.gov (United States)

    Zhu, Ling; Shi, Xinling; Liu, Yajie

    2009-02-01

    The traditional clinical trail designs always depend on expert opinions and lack statistical evaluations. In this article, we present a method and illustrate how population parameter uncertainty may be incorporated in the overall simulation model. Using the techniques of clinical trail simulation (CTS) and setting up predictions on the basis of pharmacokinetics-pharmacodynamics (PK-PD) models, we advance the modeling methods for simulation, for treatment effects, and for the clinical trail power under the given PK-PD conditions. Then we discuss the model of uncertainty, suggest an ANOVA-based method, add eta2 statistics for sensitivity analysis, and canvass the effect of uncertainty about population parameters on clinical trail power. The results from simulations and the indices derived from this type of sensitivity analysis may be used for grading the influence on the prediction quality of uncertainty about different population parameters. The experiment results are satisfactory and the approach presented has practical value in clinical trails.

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

    Directory of Open Access Journals (Sweden)

    Walters EH

    2012-07-01

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

  8. Clinical effectiveness of modified sequential organ failure assessment scoring system for predicting ICU indexing scores

    Directory of Open Access Journals (Sweden)

    Hassan Babamohamadi

    2016-10-01

    Full Text Available Background: The ability to recognize the severity of the disease in those who their survival depend entirely on admission to the intensive care unit, is very valuable clinically. This study aimed to evaluate the clinical effectiveness of modified sequential organ failure assessment (MSOFA scale to predict mortality and length of stay in intensive care unit patients respectively. Methods: This was a retrospective cross-sectional study conducted on hospital records of patients admitted to the intensive care unit. All patients’ records who admitted to the intensive care unit of Kowsar Hospital, Semnan city (the capital of the province, Iran, in 2015 considered as the sample. Collecting data were done during 4 weeks in April and May 2016. The data collection tool was a demographic questionnaire and modified sequential organ failure assessment scale. Exclusion criteria included discharge in the first 24 hours after admission, the patient died a few hours after admission and incomplete information to complete the modified sequential organ failure assessment form. Results: The study of 105 patients' records of the intensive care unit showed that 45.7% of patients were died, 15.2% and 39% were discharged and moved to other wards respectively. The results of logistic regression analysis and receiver operating characteristic (ROC curve showed that this criterion had moderate sensitivity and specificity for prediction of mortality and length of stay in ICU patients (Area=0.635, CI= 0.527-0.743 and each unit increase in modified sequential organ failure assessment score is accompanied by increasing 32 percent chance of death (OR=1.325; 95% CI:1.129,1.555; P= 0.001(. Also each unit increase in modified sequential organ failure assessment (MSOFA score accompanied by increasing 19% length of stay in ICU (OR=1.191; 95% CI: 1.034, 1.371; P= 0.015(. Conclusion: The results of this study showed that the modified sequential organ failure assessment scale is not

  9. PREDICTING OUTCOME AND SEVERITY IN ACUTE ORGANOPHOSPHOROUS POISONING WITH CLINICAL SCORING AND SERUM CHOLINESTERASE LEVELS

    Directory of Open Access Journals (Sweden)

    Basavaraj R

    2014-11-01

    Full Text Available BACKGROUND AND OBJECTIVES: Organophosphorus compound poisoning is the most common medico toxic emergency in India the increase in pesticide use in agriculture has paralleled the increase in the use of these products for deliberate self-warm. Respiratory failure is the most common complication of OP poisoning leading to death. Early recognition and prompt ventilator support may improve survival. Owing to limited availability of resources, all OP poisoning patients are not managed in ICUs in Indian setup. It is therefore important that clinical features and criteria to predict the need for ventilator support be identified at initial examination. Hence this study was undertaken to assess the severity of organophosphorus compound poisoning both clinically by using Peradeniya scoring and by estimating serum choline esterase levels. METHODS: Cross sectional study was done at basaveswar teaching and general hospital attached to MR Medical College. Cases with history of exposure to organophosphorus compound within previous 24 hours were chosen after applying inclusion and exclusion criteria. Patients were evaluated for Peradeniya OP poisoning scale and serum cholinesterase levels for assessment of severity of poisoning. Serum cholinesterase levels and Peradeniya OP poisoning scale were studied to predict the need for ventilator support. The results were analyzed using Chi-square test. STATISTICAL ANALYSIS: It was done using pearson’s chi square test. RESULTS: In this study requirement of ventilator support was seen in 36% of patients. Mortality in our study was 18%. Only 15.6% of patients with mild grade of poisoning according to Peradeniya OP poisoning scale required ventilator support, whereas 84.4% did not require ventilator support. Most of patients with moderate (70.6% and severe poisoning (100% according to Peradeniya OP poisoning scale required ventilator support. 93.7% of patients with serum cholinesterase levels more than 50% did not require

  10. Predictive factors of clinical response in steroid-refractory ulcerative colitis treated with granulocyte-monocyte apheresis

    Institute of Scientific and Technical Information of China (English)

    Valeria D'Ovidio; Donatella Meo; Angelo Viscido; Giampaolo Bresci; Piero Vernia; Renzo Caprilli

    2011-01-01

    AIM: To identify factors predicting the clinical response of ulcerative colitis patients to granulocyte-monocyte apheresis (GMA).METHODS: Sixty-nine ulcerative colitis patients (39 F, 30 M) dependent upon/refractory to steroids were treated with GMA.Steroid dependency, clinical activity index (CAI), C reactive protein (CRP) level, erythrocyte sedimentation rate (ESR), values at baseline, use of immunosuppressant, duration of disease, and age and extent of disease were considered for statistical analysis as predictive factors of clinical response.Univariate and multivariate logistic regression models were used.RESULTS: In the univariate analysis, CAI (P = 0.039) and ESR (P = 0.017) levels at baseline were singled out as predictive of clinical remission.In the multivariate analysis steroid dependency [Odds ratio (OR) = 0.390, 95% Confidence interval (CI): 0.176-0.865, Wald 5.361, P = 0.0160] and low CAI levels at baseline (4 < CAI < 7) (OR = 0.770, 95% CI: 0.425-1.394, Wald 3.747, P = 0.028) proved to be effective as factors predicting clinical response.CONCLUSION: GMA may be a valid therapeutic option for steroid-dependent ulcerative colitis patients with mild-moderate disease and its clinical efficacy seems to persist for 12 mo.

  11. Evaluation of clinical and immunological markers for predicting virological failure in a HIV/AIDS treatment cohort in Busia, Kenya.

    Directory of Open Access Journals (Sweden)

    Cecilia Ferreyra

    Full Text Available BACKGROUND: In resource-limited settings where viral load (VL monitoring is scarce or unavailable, clinicians must use immunological and clinical criteria to define HIV virological treatment failure. This study examined the performance of World Health Organization (WHO clinical and immunological failure criteria in predicting virological failure in HIV patients receiving antiretroviral therapy (ART. METHODS: In a HIV/AIDS program in Busia District Hospital, Kenya, a retrospective, cross-sectional cohort analysis was performed in April 2008 for all adult patients (>18 years old on ART for ≥12 months, treatment-naive at ART start, attending the clinic at least once in last 6 months, and who had given informed consent. Treatment failure was assessed per WHO clinical (disease stage 3 or 4 and immunological (CD4 cell count criteria, and compared with virological failure (VL >5,000 copies/mL. RESULTS: Of 926 patients, 123 (13.3% had clinically defined treatment failure, 53 (5.7% immunologically defined failure, and 55 (6.0% virological failure. Sensitivity, specificity, positive predictive value, and negative predictive value of both clinical and immunological criteria (combined in predicting virological failure were 36.4%, 83.5%, 12.3%, and 95.4%, respectively. CONCLUSIONS: In this analysis, clinical and immunological criteria were found to perform relatively poorly in predicting virological failure of ART. VL monitoring and new algorithms for assessing clinical or immunological treatment failure, as well as improved adherence strategies, are required in ART programs in resource-limited settings.

  12. External validation of a clinical scoring system for the risk of gestational diabetes mellitus

    NARCIS (Netherlands)

    van Leeuwen, M.; Opmeer, B. C.; Zweers, E. J. K.; van Ballegooie, E.; ter Brugge, H. G.; de Valk, H. W.; Visser, G. H. A.; Mol, B. W. J.

    2009-01-01

    Aim: A prediction rule for gestational diabetes mellitus (GDM) could be helpful in early detection and increased efficiency of screening. A prediction rule by means of a clinical scoring system is available, but has never been validated externally. The aim of this study was to validate the scoring s

  13. Following the Rules Set by Accreditation Agencies and Governing Bodies to Maintain In-Compliance Status: Applying Critical Thinking Skills When Evaluating the Need for Change in the Clinical Laboratory.

    Science.gov (United States)

    Byrne, Karen M; Levy, Kimberly Y; Reese, Erika M

    2016-05-01

    Maintaining an in-compliance clinical laboratory takes continuous awareness and review of standards, regulations, and best practices. A strong quality assurance program and well informed leaders who maintain professional networks can aid in this necessary task. This article will discuss a process that laboratories can follow to interpret, understand, and comply with the rules and standards set by laboratory accreditation bodies.

  14. Autoreactive T Cells in Human Smokers Is Predictive of Clinical Outcome

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    Chuang eXu

    2012-08-01

    Full Text Available Cross-sectional studies have suggested a role for activation of adaptive immunity in smokers with emphysema, but the clinical application of these findings has not been explored. Here we examined the utility of detecting autoreactive T cells as a screening tool for emphysema in an at-risk population of smokers. We followed 156 former and current (ever-smokers for two years to assess whether peripheral blood CD4 T cell cytokine responses to lung elastin fragments (EFs could discriminate between those with and without emphysema, and to evaluate the relevance of autoreactive T cells to predict changes during follow-up in lung physiological parameters. Volunteers underwent baseline complete phenotypic assessment with pulmonary function tests, quantitative chest CT, yearly six minutes walk distance (6MWD testing, and annual measurement of CD4 T cell cytokine responses to EFs. The areas under the receiver operating characteristic curve to predict emphysema for interferon gamma (IFN-γ, and interleukin 6 (IL-6 responses to EFs were 0.81 (95% CI of 0.74 to 0.88 and 0.79 (95% CI of 0.72 to 0.86 respectively. We developed a dual cytokine enzyme-linked immunocell spot assay, the γ-6 Spot, using CD4 T cell IFN-γ and IL-6 responses and found that it discriminated emphysema with 90% sensitivity. After adjusting for potential confounders, the presence of autoreactive T cells was predictive of a decrease in 6MWD over two years (decline in 6MWD, -19 meters (m per fold change in IFN-γ; P=0.026, and -26 m per fold change in IL-6; P=0.003. These findings collectively suggest that the EF specific autoreactive CD4 T cell assay, γ-6 Spot, could provide a non-invasive diagnostic tool with potential application to large-scale screening to discriminate emphysema in ever-smokers, and predict early relevant physiological outcomes in those at risk.

  15. 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

  16. Predictive validity of measurements of clinical competence using the team objective structured bedside assessment (TOSBA): assessing the clinical competence of final year medical students.

    LENUS (Irish Health Repository)

    Meagher, Frances M

    2009-11-01

    The importance of valid and reliable assessment of student competence and performance is gaining increased recognition. Provision of valid patient-based formative assessment is an increasing challenge for clinical teachers in a busy hospital setting. A formative assessment tool that reliably predicts performance in the summative setting would be of value to both students and teachers.

  17. Predicting asthma in preschool children at high risk presenting in primary care: Development of a clinical asthma prediction score

    NARCIS (Netherlands)

    L.B. Van Der Mark (Lonneke); K.E. Wonderen (Karina); J. Mohrs (Jacob); W.M.C. van Aalderen (Willem); G. ter Riet; P.J.E. Bindels (Patrick)

    2014-01-01

    textabstractBackground: A setting-specific asthma prediction score for preschool children with wheezing and/or dyspnoea presenting in primary healthcare is needed since existing indices are mainly based on general populations. Aims: To find an optimally informative yet practical set of predictors fo

  18. Pre-clinical grades predict clinical performance in the MBBS stage II examination at the University of the West Indies, Mona Campus.

    Science.gov (United States)

    Pepple, Dagogo J; Young, Lauriann E; Gordon-Strachan, Georgiana M; Carroll, Robert G

    2013-12-20

    In the preclinical sciences, statistically significant predictive values have been reported between the performances in one discipline and the others, supporting the hypothesis that students who perform well in one discipline were likely to perform well in the other disciplines. We therefore decided to conduct a retrospective study to investigate the predictive effects of preclinical subjects on clinical subjects from 87 students of The University of the West Indies (UWI), Mona Campus who took the MBBS Stage II examination at various times between May 2000 and May 2002. The grade in Pathology was significantly predicted by scores in Anatomy and Pharmacology; Medicine by Physiology and Pharmacology scores; Surgery by Anatomy and Social and Preventive Medicine scores; while, the Obstetrics and Gynecology grade was predicted by the Anatomy score. The results support the hypothesis that the scores in some preclinical subjects can predict the performance in specific clinical subjects, which could be interpreted to suggest that poor performance in specific preclinical disciplines could be a warning sign of future poor performance in the related clinical disciplines.

  19. Relative power of clinical, exercise test, and angiographic variables in predicting clinical outcome after myocardial infarction: the Newham and Tower Hamlets study.

    Science.gov (United States)

    de Belder, M A; Pumphrey, C W; Skehan, J D; Rimington, H; al Wakeel, B; Evans, S J; Rothman, M; Mills, P G

    1988-11-01

    The interrelations of clinical, exercise test, and angiographic variables and their relative values in predicting specific clinical outcomes after myocardial infarction have not been fully established. Of 302 consecutive stable survivors of infarction, 262 performed a predischarge submaximal exercise test. In the first year after infarction patients with a "positive" exercise test were 13 times more likely to die, 2.8 times more likely to have an ischaemic event, and 2.3 times more likely to develop left ventricular failure than patients with negative tests. Patients with positive exercise tests underwent cardiac catheterization. Features of the history, 12 lead electrocardiogram, in-hospital clinical course, exercise test, and left ventricular and coronary angiograms that predicted these clinical end points were identified by univariate analysis. Then multivariable analysis was used to assess the relative powers of all variables in predicting end points. Certain features of the exercise test remained independent predictors of future ischaemic events and the development of overt left ventricular failure, but clinical and angiographic variables were more powerful predictors of mortality. Because the exercise test is also used to select patients for angiography, however, the results of this study strongly support the use of early submaximal exercise testing after infarction.

  20. Predictive value of clinical risk indicators in child development: final results of a study based on psychoanalytic theory

    OpenAIRE

    Maria Cristina Machado Kupfer; Alfredo Nestor Jerusalinsky; Leda Mariza Fischer Bernardino; Daniele Wanderley; Paulina Schmidtbauer Barbosa Rocha; Silvia Eugenia Molina; Léa Martins Sales; Regina Stellin; M. Eugênia Pesaro; Rogerio Lerner

    2010-01-01

    We present the final results of a study using the IRDI (Clinical Risk Indicators in Child Development). Based on a psychoanalytic approach, 31 risk signs for child development were constructed and applied to 726 children between the ages of 0 and 18 months. One sub-sample was evaluated at the age of three. The results showed a predictive capacity of IRDIs to indicate developmental problems; 15 indicators for the IRDI were also highlighted that predict psychic risk for the constitution of the ...

  1. Prediction of myotonic dystrophy clinical severity based on the number of intragenic [CTG]{sub n} trinucleotide repeats

    Energy Technology Data Exchange (ETDEWEB)

    Gennarelli, M.; Dallapiccola, B. [Universita Tor Vergata, Rome (Italy); Novelli, G. [Universita Cattolica del Sacro Cuore, Rome (Italy)] [and others

    1996-11-11

    We carried out a genotype-phenotype correlation study, based on clinical findings in 465 patients with myotonic dystrophy (DM), in order to assess [CTG] repeat number as a predictive test of disease severity. Our analysis showed that the DM subtypes defined by strict clinical criteria fall into three different classes with a log-normal distribution. This distribution is useful in predicting the probability of specific DM phenotypes based on triplet [CTG] number. This study demonstrates that measurement of triplet expansions in patients` lymphocyte DNA is highly valuable and accurate for prognostic assessment. 45 refs., 1 fig., 2 tabs.

  2. Usefulness of fecal lactoferrin in predicting and monitoring the clinical severity of infectious diarrhea

    Institute of Scientific and Technical Information of China (English)

    Chien-Chang Chen; Chee-Jen Chang; Tzou-Yien Lin; Ming-Wei Lai; Hsun-Chin Chao; Man-Shan Kong

    2011-01-01

    AIM: To explore the value of fecal lactoferrin in predicting and monitoring the clinical severity of infectious diarrhea.``METHODS: Patients with acute infectious diarrhea ranging from 3 mo to 10 years in age were enrolled, and one to three stool samples from each subject were collected. Certain parameters, including white blood cells/differential count, C-reactive protein, fecal mucus, fecal pus cells, duration of fever, vomiting, diarrhea and severity (indicated by Clark and Vesikari scores), were recorded and analyzed. Fecal lactoferrin was determined by enzyme-linked immunosorbent assay and compared in different pathogen and disease activity. Generalized estimating equations (GEE) were also used for analysis.``RESULTS: Data included 226 evaluations for 117 individuals across three differenttime points. Fecal lactoferrin was higher in patients with Salmonella (11.17 )j,g/g ± 2.73 μg/g) or Campyhbacter (10.32 μg/g ± 2.94 μig/g) infections and lower in patients with rotavirus (2.82 μg/g ± 1.27 μg/g) or norovirus (3.16 μg/g ± 1.18 |ag/g) infections. Concentrations of fecal lactoferrin were significantly elevated in patients with severe (11.32 μg/g ± 3.29 μag/g) or moderate (3.77 μg/g ± 2.08 μg/g) disease activity compared with subjects with mild (1.51 yig/g ± 1.36 μg/g) disease activity (P < 0.05). GEE analysis suggests that this marker could be used to monitor the severity and course of gastrointestinal infections and may provide information for disease management.``CONCLUSION: Fecal lactoferrin increased during bacterial infection and with greater disease severity and may be a good marker for predicting and monitoring intestinal inflammation in children with infectious diarrhea.

  3. READMIT: a clinical risk index to predict 30-day readmission after discharge from acute psychiatric units.

    Science.gov (United States)

    Vigod, Simone N; Kurdyak, Paul A; Seitz, Dallas; Herrmann, Nathan; Fung, Kinwah; Lin, Elizabeth; Perlman, Christopher; Taylor, Valerie H; Rochon, Paula A; Gruneir, Andrea

    2015-02-01

    Our aim was to create a clinically useful risk index, administered prior to discharge, for determining the probability of psychiatric readmission within 30 days of hospital discharge for general psychiatric inpatients. We used population-level sociodemographic and health administrative data to develop a predictive model for 30-day readmission among adults discharged from an acute psychiatric unit in Ontario, Canada (2008-2011), and converted the final model into a risk index system. We derived the predictive model in one-half of the sample (n = 32,749) and validated it in the other half of the sample (n = 32,750). Variables independently associated with 30-day readmission (forming the mnemonic READMIT) were: (R) Repeat admissions; (E) Emergent admissions (i.e. harm to self/others); (D) Diagnoses (psychosis, bipolar and/or personality disorder), and unplanned Discharge; (M) Medical comorbidity; (I) prior service use Intensity; and (T) Time in hospital. Each 1-point increase in READMIT score (range 0-41) increased the odds of 30-day readmission by 11% (odds ratio 1.11, 95% CI 1.10-1.12). The index had moderate discriminative capacity in both derivation (C-statistic = 0.631) and validation (C-statistic = 0.630) datasets. Determining risk of psychiatric readmission for individual patients is a critical step in efforts to address the potentially avoidable high rate of this negative outcome. The READMIT index provides a framework for identifying patients at high risk of 30-day readmission prior to discharge, and for the development, evaluation and delivery of interventions that can assist with optimizing the transition to community care for patients following psychiatric discharge.

  4. Predicting Ebola Severity: A Clinical Prioritization Score for Ebola Virus Disease

    Science.gov (United States)

    Okoni-Williams, Harry Henry; Suma, Mohamed; Mancuso, Brooke; Al-Dikhari, Ahmed; Faouzi, Mohamed

    2017-01-01

    Background Despite the notoriety of Ebola virus disease (EVD) as one of the world’s most deadly infections, EVD has a wide range of outcomes, where asymptomatic infection may be almost as common as fatality. With increasingly sensitive EVD diagnosis, there is a need for more accurate prognostic tools that objectively stratify clinical severity to better allocate limited resources and identify those most in need of intensive treatment. Methods/Principal Findings This retrospective cohort study analyses the clinical characteristics of 158 EVD(+) patients at the GOAL-Mathaska Ebola Treatment Centre, Sierra Leone. The prognostic potential of each characteristic was assessed and incorporated into a statistically weighted disease score. The mortality rate among EVD(+) patients was 60.8% and highest in those aged 25 years (pEbola viral load (p = 0.1), potentially indicating a pathologic synergy between the infections. Similarly, referral-time interacted with viral load, and adjustment revealed referral-time as a significant determinant of mortality, thus quantifying the benefits of early reporting as a 12% mortality risk reduction per day (p = 0.012). Disorientation was the strongest unadjusted predictor of death (OR = 13.1, p = 0.014) followed by hiccups, diarrhoea, conjunctivitis, dyspnoea and myalgia. Including these characteristics in multivariate prognostic scores, we obtained a 91% and 97% ability to discriminate death at or after triage respectively (area under ROC curve). Conclusions/Significance This study proposes highly predictive and easy-to-use prognostic tools, which stratify the risk of EVD mortality at or after EVD triage. PMID:28151955

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

    Directory of Open Access Journals (Sweden)

    Shinsuke eKoike

    2013-11-01

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

  6. Preoperative neutrophil response as a predictive marker of clinical outcome following open heart surgery and the impact of leukocyte filtration.

    LENUS (Irish Health Repository)

    Soo, Alan W

    2010-11-01

    Open heart surgery is associated with a massive systemic inflammatory response. Neutrophils, are the main mediator of this response. We hypothesised that the degree of neutrophil activation and inflammatory response to open heart surgery varies individually and correlates with clinical outcome. The aim of this study was to determine if individual clinical outcome can be predicted preoperatively through assessment of in-vitro stimulated neutrophil responses. Following that, the effects of neutrophil depletion through leukocyte filters are examined.

  7. Innovative drugs to treat depression: did animal models fail to be predictive or did clinical trials fail to detect effects?

    Science.gov (United States)

    Belzung, Catherine

    2014-04-01

    Over recent decades, encouraging preclinical evidence using rodent models pointed to innovative pharmacological targets to treat major depressive disorder. However, subsequent clinical trials have failed to show convincing results. Two explanations for these rather disappointing results can be put forward, either animal models of psychiatric disorders have failed to predict the clinical effectiveness of treatments or clinical trials have failed to detect the effects of these new drugs. A careful analysis of the literature reveals that both statements are true. Indeed, in some cases, clinical efficacy has been predicted on the basis of inappropriate animal models, although the contrary is also true, as some clinical trials have not targeted the appropriate dose or clinical population. On the one hand, refinement of animal models requires using species that have better homological validity, designing models that rely on experimental manipulations inducing pathological features, and trying to model subtypes of depression. On the other hand, clinical research should consider carefully the results from preclinical studies, in order to study these compounds at the correct dose, in the appropriate psychiatric nosological entity or symptomatology, in relevant subpopulations of patients characterized by specific biomarkers. To achieve these goals, translational research has to strengthen the dialogue between basic and clinical science.

  8. Prospective assessment of a gene signature potentially predictive of clinical benefit in metastatic melanoma patients following MAGE-A3 immunotherapeutic (PREDICT)

    Science.gov (United States)

    Saiag, P.; Gutzmer, R.; Ascierto, P. A.; Maio, M.; Grob, J.-J.; Murawa, P.; Dreno, B.; Ross, M.; Weber, J.; Hauschild, A.; Rutkowski, P.; Testori, A.; Levchenko, E.; Enk, A.; Misery, L.; Vanden Abeele, C.; Vojtek, I.; Peeters, O.; Brichard, V. G.; Therasse, P.

    2016-01-01

    Background Genomic profiling of tumor tissue may aid in identifying predictive or prognostic gene signatures (GS) in some cancers. Retrospective gene expression profiling of melanoma and non-small-cell lung cancer led to the characterization of a GS associated with clinical benefit, including improved overall survival (OS), following immunization with the MAGE-A3 immunotherapeutic. The goal of the present study was to prospectively evaluate the predictive value of the previously characterized GS. Patients and methods An open-label prospective phase II trial (‘PREDICT’) in patients with MAGE-A3-positive unresectable stage IIIB-C/IV-M1a melanoma. Results Of 123 subjects who received the MAGE-A3 immunotherapeutic, 71 (58.7%) displayed the predictive GS (GS+). The 1-year OS rate was 83.1%/83.3% in the GS+/GS− populations. The rate of progression-free survival at 12 months was 5.8%/4.1% in GS+/GS− patients. The median time-to-treatment failure was 2.7/2.4 months (GS+/GS−). There was one complete response (GS−) and two partial responses (GS+). The MAGE-A3 immunotherapeutic was similarly immunogenic in both populations and had a clinically acceptable safety profile. Conclusion Treatment of patients with MAGE-A3-positive unresectable stage IIIB-C/IV-M1a melanoma with the MAGE-A3 immunotherapeutic demonstrated an overall 1-year OS rate of 83.5%. GS− and GS+ patients had similar 1-year OS rates, indicating that in this study, GS was not predictive of outcome. Unexpectedly, the objective response rate was lower in this study than in other studies carried out in the same setting with the MAGE-A3 immunotherapeutic. Investigation of a GS to predict clinical benefit to adjuvant MAGE-A3 immunotherapeutic treatment is ongoing in another melanoma study. This study is registered at www.clinicatrials.gov NCT00942162. PMID:27502712

  9. Development of a Simple Clinical Risk Score for Early Prediction of Severe Dengue in Adult Patients.

    Directory of Open Access Journals (Sweden)

    Ing-Kit Lee

    , irrespective of the day of illness onset, suggesting that our simple risk score can be easily implemented in resource-limited countries for early prediction of dengue patients at risk of SD provided that they have rapid dengue confirmed tests. For patients with other acute febrile illnesses or bacterial infections usually have SD risk score of >1. Thus, these scoring algorithms cannot totally replace good clinical judgement of the physician, and most importantly, early differentiating dengue from other febrile illnesses is critical for appropriate monitoring and management.

  10. Angiographically Negative Acute Arterial Upper and Lower Gastrointestinal Bleeding: Incidence, Predictive Factors, and Clinical Outcomes

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Jin Hyoung; Shin, Ji Hoon; Yoon, Hyun Ki; Chae, Eun Young; Myung, Seung Jae; Ko, Gi Young; Gwon, Dong Il; Sung, Kyu Bo [Asan Medical Center, Seoul (Korea, Republic of)

    2009-08-15

    To evaluate the incidence, predictive factors, and clinical outcomes of angiographically negative acute arterial upper and lower gastrointestinal (GI) bleeding. From 2001 to 2008, 143 consecutive patients who underwent an angiography for acute arterial upper or lower GI bleeding were examined. The angiographies revealed a negative bleeding focus in 75 of 143 (52%) patients. The incidence of an angiographically negative outcome was significantly higher in patients with a stable hemodynamic status (p < 0.001), or in patients with lower GI bleeding (p = 0.032). A follow-up of the 75 patients (range: 0-72 months, mean: 8 {+-} 14 months) revealed that 60 of the 75 (80%) patients with a negative bleeding focus underwent conservative management only, and acute bleeding was controlled without rebleeding. Three of the 75 (4%) patients underwent exploratory surgery due to prolonged bleeding; however, no bleeding focus was detected. Rebleeding occurred in 12 of 75 (16%) patients. Of these, six patients experienced massive rebleeding and died of disseminated intravascular coagulation within four to nine hours after the rebleeding episode. Four of the 16 patients underwent a repeat angiography and the two remaining patients underwent a surgical intervention to control the bleeding. Angiographically negative results are relatively common in patients with acute GI bleeding, especially in patients with a stable hemodynamic status or lower GI bleeding. Most patients with a negative bleeding focus have experienced spontaneous resolution of their condition.

  11. Primary gastric mucosa associated lymphoid tissue lymphoma: Clinical data predicted treatment outcome

    Institute of Scientific and Technical Information of China (English)

    Milena Todorovic; Miodrag Krstic; Bela Balint; Miodrag Jevtic; Nada Suvajdzic; Amela Ceric; Dragana Stamatovic; Olivera Markovic; Maja Perunicic; Slobodan Marjanovic

    2008-01-01

    AIM: To determine clinical characteristics and treatmentoutcome of gastric lymphoma after chemotherapy and immuno-chemotherapy.METHODS: Thirty four patients with primary gastric mucosa associated lymphoid tissue (MALT) lymphoma (Ann Arbor stages I to IV) were enrolled. All had upper gastric endoscopy, abdominal ultrasonography, CT and H py/or/status assessment (histology and serology).After anti-/-/py/or/treatment and initial chemotherapy,patients were re-examined every 4 mo.RESULTS: Histological regression of the lymphoma wascomplete in 22/34 (64.7%) and partial in 9 (26.5%)patients. Median follow up time for these 31 responders was 60 mo (range 48-120). No regression was noted in 3 patients. Among the 25 (73.5%) H py/or/positive patients, the eradication rate was 100%.CONCLUSION: Using univariate analysis, predictive factors for overall survival were international prognostic index (IPI) score, hemoglobin level, erythrocyte sedimentation rate (ESR), and platelet numbers (P < 0.005). In addition to this, Cox proportion hazard model differentiate IPI score, ESR, and platelets as predictors of survival.

  12. Modeling using clinical examination indicators predicts interstitial lung disease among patients with rheumatoid arthritis

    Science.gov (United States)

    Wang, Yao; Song, Wuqi; Wu, Jing; Li, Zhangming; Mu, Fengyun; Li, Yang; Huang, He; Zhu, Wenliang

    2017-01-01

    Interstitial lung disease (ILD) is a severe extra-articular manifestation of rheumatoid arthritis (RA) that is well-defined as a chronic systemic autoimmune disease. A proportion of patients with RA-associated ILD (RA-ILD) develop pulmonary fibrosis (PF), resulting in poor prognosis and increased lifetime risk. We investigated whether routine clinical examination indicators (CEIs) could be used to identify RA patients with high PF risk. A total of 533 patients with established RA were recruited in this study for model building and 32 CEIs were measured for each of them. To identify PF risk, a new artificial neural network (ANN) was built, in which inputs were generated by calculating Euclidean distance of CEIs between patients. Receiver operating characteristic curve analysis indicated that the ANN performed well in predicting the PF risk (Youden index = 0.436) by only incorporating four CEIs including age, eosinophil count, platelet count, and white blood cell count. A set of 218 RA patients with healthy lungs or suffering from ILD and a set of 87 RA patients suffering from PF were used for independent validation. Results showed that the model successfully identified ILD and PF with a true positive rate of 84.9% and 82.8%, respectively. The present study suggests that model integration of multiple routine CEIs contributes to identification of potential PF risk among patients with RA.

  13. Prediction of the potential clinical outcomes for post-resuscitated patients after cardiac arrest

    Science.gov (United States)

    Hong, Sungmin; Kwon, Bojun; Yun, Il Dong; Lee, Sang Uk; Kim, Kyuseok; Kim, Joonghee

    2013-02-01

    Cerebral injuries after cardiac arrest are serious causes for morbidity. Many previous researches in the medical society have been proposed to prognosticate the functional recoveries of post-resuscitated patients after cardiac arrest, but the validity of suggested features and the automation of prognostication have not been made yet. This paper presents the automatic classification method which predicts the potential clinical outcomes of post-resuscitated patients who suffered from cardiac arrest. The global features and the local features are adapted from the researches from the medical society. The global features, which are consisted of the percentage of the partial volume under the uniformly increasing thresholds, represent the global tendency of apparent diffusion coefficient value in a DWI. The local features are localized and measured on the refined local apparent diffusion coefficient minimal points. The local features represent the ischemic change of small areas in a brain. The features are trained and classified by the random forest method, which have been widely used in the machine learning society for classification. The validity of features is automatically evaluated during the classification process. The proposed method achieved the 0.129 false-positive rate while maintaining the perfect true-positive rate. The area-under-curve of the proposed method was 0.9516, which showed the feasibility and the robustness of the proposed method.

  14. 多时间序列关联规则分析的论坛舆情趋势预测%Forum Sentiment Trend Prediction Based on Multi Time Series Association Rule Analysis

    Institute of Scientific and Technical Information of China (English)

    钱爱玲; 瞿彬彬; 卢炎生; 陈攀攀; 陈国栋

    2012-01-01

    为了预测论坛舆情及其动态演变趋势,基于多时间序列的关联分析,集中分析了论坛中3个量的时间序列之间的关联规则:活跃者之间的关系强度的时间序列、坚定支持者人数的时间序列以及坚定支持者成员的变化频度的时间序列.然后给出了一种新的基于多时间序列关联分析的论坛舆情预测算法(Forum sentiment trend prediction based on multi time series association rule analysis,TPMTSA),并在真实数据集和拟合数据集上进行了大量的实验.结果表明:TPMTSA算法具有有效性和较高的运行效率.研究结果可用于论坛舆情预警监控.%In order to predict the evolving trend of forum sentiment, based on the association analysis of multi time series, the association rules of three-quantity time series over forum sentiment are anlyzed, namely, the strength of relationship between actors, the number of pillars, and the changing frequency of pillars. Then a novel prediction algorithm, forum sentiment trend prediction based on multi time series association rule analysis (TPMTSA), is proposed. Extensive experiments over real and synthetic datasets are conducted. Results show the effectiveness and the efficiency of TPMTSA. The research results can be used to monitor the forum opinion.

  15. Predicting Calcium Values for Gastrointestinal Bleeding Patients in Intensive Care Unit Using Clinical Variables and Fuzzy Modeling

    Directory of Open Access Journals (Sweden)

    G Khalili-Zadeh-Mahani

    2016-07-01

    Full Text Available Introduction: Reducing unnecessary laboratory tests is an essential issue in the Intensive Care Unit. One solution for this issue is to predict the value of a laboratory test to specify the necessity of ordering the tests. The aim of this paper was to propose a clinical decision support system for predicting laboratory tests values. Calcium laboratory tests of three categories of patients, including upper and lower gastrointestinal bleeding, and unspecified hemorrhage of gastrointestinal tract, have been selected as the case studies for this research. Method: In this research, the data have been collected from MIMIC-II database. For predicting calcium laboratory values, a Fuzzy Takagi-Sugeno model is used and the input variables of the model are heart rate and previous value of calcium laboratory test. Results: The results showed that the values of calcium laboratory test for the understudy patients were predictable with an acceptable accuracy. In average, the mean absolute errors of the system for the three categories of the patients are 0.27, 0.29, and 0.28, respectively. Conclusion: In this research, using fuzzy modeling and two variables of heart rate and previous calcium laboratory values, a clinical decision support system was proposed for predicting laboratory values of three categories of patients with gastrointestinal bleeding. Using these two clinical values as input variables, the obtained results were acceptable and showed the capability of the proposed system in predicting calcium laboratory values. For achieving better results, the impact of more input variables should be studied. Since, the proposed system predicts the laboratory values instead of just predicting the necessity of the laboratory tests; it was more generalized than previous studies. So, the proposed method let the specialists make the decision depending on the condition of each patient.

  16. Prediction of Deep Neck Abscesses by Contrast-Enhanced Computerized Tomography in 76 Clinically Suspect Consecutive Patients

    NARCIS (Netherlands)

    Freling, Nicole; Roele, Elise; Schaefer-Prokop, Cornelia; Fokkens, Wytske

    2009-01-01

    Objectives/Hypothesis: Contrast-enhanced computerized tomography (CECT) has become the imaging method of choice in patients with clinical suspicion of a deep neck abscess. The purpose of this retrospective study was to assess the predictive value of the diagnosis of deep neck abscess using CECT. Stu

  17. Prediction of the Clinical Course of COPD using the new GOLD Classification A Study of the General Population

    DEFF Research Database (Denmark)

    Lange, Peter; Marott, Jacob Louis; Vestbo, Jørgen;

    2012-01-01

    RATIONALE: The new Global initiative for obstructive lung disease (GOLD) stratification of COPD into categories A, B, C and D is based on symptoms, level of lung function, and history of exacerbations. OBJECTIVE: To investigate the abilities of this stratification to predict clinical course of COPD...

  18. Immunohistochemical profiling of caspase signaling pathways predicts clinical response to chemotherapy in primary nodal diffuse large B-cell lymphomas.

    NARCIS (Netherlands)

    Muris, J.J.; Cillessen, S.A.; Vos, W.; Houdt, I.S. van; Kummer, J.A.; Krieken, J.H.J.M. van; Jiwa, N.M.; Jansen, P.A.M.; Kluin-Nelemans, H.C.; Ossenkoppele, G.J.; Gundy, C.; Meijer, C.J.M.; Oudejans, J.J.

    2005-01-01

    We used biopsy specimens of primary nodal diffuse large B-cell lymphoma (DLBCL) to investigate whether the inhibition of caspase 8 and/or 9 apoptosis signaling pathways predicts clinical outcome. Expression levels of cellular FLICE inhibitory protein (c-Flip) and numbers of active caspase 3-positive

  19. Immunohistochemical profiling of caspase signaling pathways predicts clinical response to chemotherapy in primary nodal diffuse large B-cell lymphomas

    NARCIS (Netherlands)

    Muris, JJF; Cillessen, SAGM; Vos, W; van Houdt, IS; Kummer, JA; van Krieken, JHJM; Jiwa, NM; Jansen, PM; Kluin-Nelemans, HC; Ossenkoppele, GJ; Gundy, C; Meijer, CJLM; Oudejans, JJ

    2005-01-01

    We used biopsy specimens of primary nodal diffuse large B-cell lymphoma (DLBCL) to investigate whether the inhibition of caspase 8 and/or 9 apoplosis signaling pathways predicts clinical outcome. Expression levels of cellular FLICE inhibitory protein (c-Flip) and numbers of active caspase 3-positive

  20. Prediction

    CERN Document Server

    Sornette, Didier

    2010-01-01

    This chapter first presents a rather personal view of some different aspects of predictability, going in crescendo from simple linear systems to high-dimensional nonlinear systems with stochastic forcing, which exhibit emergent properties such as phase transitions and regime shifts. Then, a detailed correspondence between the phenomenology of earthquakes, financial crashes and epileptic seizures is offered. The presented statistical evidence provides the substance of a general phase diagram for understanding the many facets of the spatio-temporal organization of these systems. A key insight is to organize the evidence and mechanisms in terms of two summarizing measures: (i) amplitude of disorder or heterogeneity in the system and (ii) level of coupling or interaction strength among the system's components. On the basis of the recently identified remarkable correspondence between earthquakes and seizures, we present detailed information on a class of stochastic point processes that has been found to be particu...

  1. Task Analysis of the UH-60 Mission and Decision Rules for Developing a UH-60 Workload Prediction Model. Volume 1. Summary Report

    Science.gov (United States)

    1989-02-01

    as a baseline for all proposed model changes or other proposed multistage improvement program ( MSIP ). A computer model of this analysis was used to...support in the coordination of activities with F Company. The authors wish to thank Ms . Cassandra Hocutt, Anacapa Sciences, Inc., for her assistance in...develop smooth-flowing function and segment decision rules. Her assistance is greatly appreciated. The authors also wish to thank Ms . Nadine McCollim

  2. Coronary bifurcation angle from 3-D predicts clinical outcomes after stenting bifurcation lesions

    Institute of Scientific and Technical Information of China (English)

    CHEN Shao-liang; DING Shi-qing; Tak W Kwan; Teguh Santoso; ZHANG Jun-jie; YE Fei; XU Ya-wei; FU Qiang; KAN Jing; Chitprapai Paiboon; ZHOU Yong

    2012-01-01

    Background The predictive value of bifurcation angle (BA) for worse events after stenting bifurcation lesions remains to be unknown.The present study was to investigate the dynamic change of BA and clinical relevance for patients with coronary bifurcation lesions treated by drug-eluting stent (DES).Methods BA was calculated by 3-D quantitative coronary analysis from 347 patients in DKCRUSH-Ⅱ study.Primary endpoint was the occurrence of composite major adverse cardiac events (MACE) at 12-month,including cardiac death,myocardial infarction (MI) and target vessel revascularization (TVR).Secondary end points were the rate of binary restenosis and stent thrombosis at 12-month.Results Stenting was associated with the reduction of distal BA.The cut-off value of distal BAfor predicting MACE was 60° Distal BA in <60° group had less reduction after stenting ((-1.96±13.58)° vs.(-12.12±23.58)°,P <0.001 ); two-stent technique was associated with significant reduction of distal BA (△(-4.05±14.20)°),compared to single stent group (△+1.55±11.73,P=0.003); the target lesion revascularization (TLR),TVR and MACE rate was higher in one-stent group (16.5%,19.0% and 21.5%),compared to two-stent group (3.8%,P=0.002; 7.5%,P=0.016; and 9.8%,P=0.024),respectively.Among patients in ≥60° group,there were no significant differences in distal BA,stent thrombosis (ST),MI,MACE,death,TLR,TVR between one- and two-stent groups; after stenting procedure,there was only slight change of distal BA in left anterior descending (LAD)-Ieft circumflex (LCX) subgroup (from (88.54±21.33)° at baseline to (82.44±31.72)° post-stenting),compared to either LAD-diagonal branch (Di),or LCX-obtuse marginal branch (OM),or RCA distal (RCAd) (all P <0.001 ).Conclusion Two-stent technique was associated with significant reduction of distal BA.DK crush stenting had reduced rate of MACE in patients in <60° group,compared to one-stent technique.

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

    Energy Technology Data Exchange (ETDEWEB)

    Zhou, Dan, E-mail: DZhou@syntapharma.com [Synta Pharmaceuticals Corp., 45 Hartwell Avenue, Lexington, MA 02421 (United States); Liu, Yuan; Ye, Josephine; Ying, Weiwen; Ogawa, Luisa Shin; Inoue, Takayo; Tatsuta, Noriaki; Wada, Yumiko; Koya, Keizo [Synta Pharmaceuticals Corp., 45 Hartwell Avenue, Lexington, MA 02421 (United States); Huang, Qin [Department of Pathology and Laboratory Medicine, Veterans Affairs Boston Healthcare System, 1400 VFW Parkway, West Roxbury, MA 02132 (United States); Bates, Richard C.; Sonderfan, Andrew J. [Synta Pharmaceuticals Corp., 45 Hartwell Avenue, Lexington, MA 02421 (United States)

    2013-12-01

    In human trials certain heat shock protein 90 (Hsp90) inhibitors, including 17-DMAG and NVP-AUY922, have caused visual disorders indicative of retinal dysfunction; others such as 17-AAG and ganetespib have not. To understand these safety profile differences we evaluated histopathological changes and exposure profiles of four Hsp90 inhibitors, with or without clinical reports of adverse ocular effects, using a rat retinal model. Retinal morphology, Hsp70 expression (a surrogate marker of Hsp90 inhibition), apoptotic induction and pharmacokinetic drug exposure analysis were examined in rats treated with the ansamycins 17-DMAG and 17-AAG, or with the second-generation compounds NVP-AUY922 and ganetespib. Both 17-DMAG and NVP-AUY922 induced strong yet restricted retinal Hsp70 up-regulation and promoted marked photoreceptor cell death 24 h after the final dose. In contrast, neither 17-AAG nor ganetespib elicited photoreceptor injury. When the relationship between drug distribution and photoreceptor degeneration was examined, 17-DMAG and NVP-AUY922 showed substantial retinal accumulation, with high retina/plasma (R/P) ratios and slow elimination rates, such that 51% of 17-DMAG and 65% of NVP-AUY922 present at 30 min post-injection were retained in the retina 6 h post-dose. For 17-AAG and ganetespib, retinal elimination was rapid (90% and 70% of drugs eliminated from the retina at 6 h, respectively) which correlated with lower R/P ratios. These findings indicate that prolonged inhibition of Hsp90 activity in the eye results in photoreceptor cell death. Moreover, the results suggest that the retina/plasma exposure ratio and retinal elimination rate profiles of Hsp90 inhibitors, irrespective of their chemical class, may predict for ocular toxicity potential. - Highlights: • In human trials some Hsp90 inhibitors cause visual disorders, others do not. • Prolonged inhibition of Hsp90 in the rat eye results in photoreceptor cell death. • Retina/plasma ratio and retinal

  4. Prediction of transition from ultra-high risk to first-episode psychosis using a probabilistic model combining history, clinical assessment and fatty-acid biomarkers

    Science.gov (United States)

    Clark, S R; Baune, B T; Schubert, K O; Lavoie, S; Smesny, S; Rice, S M; Schäfer, M R; Benninger, F; Feucht, M; Klier, C M; McGorry, P D; Amminger, G P

    2016-01-01

    Current criteria identifying patients with ultra-high risk of psychosis (UHR) have low specificity, and less than one-third of UHR cases experience transition to psychosis within 3 years of initial assessment. We explored whether a Bayesian probabilistic multimodal model, combining baseline historical and clinical risk factors with biomarkers (oxidative stress, cell membrane fatty acids, resting quantitative electroencephalography (qEEG)), could improve this specificity. We analyzed data of a UHR cohort (n=40) with a 1-year transition rate of 28%. Positive and negative likelihood ratios were calculated for predictor variables with statistically significant receiver operating characteristic curves (ROCs), which excluded oxidative stress markers and qEEG parameters as significant predictors of transition. We clustered significant variables into historical (history of drug use), clinical (Positive and Negative Symptoms Scale positive, negative and general scores and Global Assessment of Function) and biomarker (total omega-3, nervonic acid) groups, and calculated the post-test probability of transition for each group and for group combinations using the odds ratio form of Bayes' rule. Combination of the three variable groups vastly improved the specificity of prediction (area under ROC=0.919, sensitivity=72.73%, specificity=96.43%). In this sample, our model identified over 70% of UHR patients who transitioned within 1 year, compared with 28% identified by standard UHR criteria. The model classified 77% of cases as very high or low risk (P>0.9, <0.1) based on history and clinical assessment, suggesting that a staged approach could be most efficient, reserving fatty-acid markers for 23% of cases remaining at intermediate probability following bedside interview. PMID:27648919

  5. Positive Predictive Value of the WHO Clinical and Immunologic Criteria to Predict Viral Load Failure among Adults on First, or Second-Line Antiretroviral Therapy in Kenya.

    Directory of Open Access Journals (Sweden)

    Anthony Waruru

    Full Text Available Routine HIV viral load (VL monitoring is the standard of care for persons receiving antiretroviral therapy (ART in developed countries. Although the World Health Organization recommends annual VL monitoring of patients on ART, recognizing difficulties in conducting routine VL testing, the WHO continues to recommend targeted VL testing to confirm treatment failure for persons who meet selected immunologic and clinical criteria. Studies have measured positive predictive value (PPV, negative predictive value, sensitivity and specificity of these criteria among patients receiving first-line ART but not specifically among those on second-line or subsequent regimens. Between 2008 and 2011, adult ART patients in Nyanza, Kenya who met national clinical or immunologic criteria for treatment failure received targeted VL testing. We calculated PPV and 95% confidence intervals (CI of these criteria to detect virologic treatment failure among patients receiving a first-line ART, b second/subsequent ART, and c any regimen. Of 12,134 patient specimens tested, 2,874 (23.7% were virologically confirmed as treatment failures. The PPV for 2,834 first-line ART patients who met either the clinical or immunologic criteria for treatment failure was 34.4% (95% CI 33.2-35.7, 33.1% (95% CI 24.7-42.3 for the 40 patients on second-line/subsequent regimens, and 33.4% (95% CI 33.1-35.6 for any ART. PPV, regardless of criteria, for first-line ART patients was lowest among patients over 44 years old and highest for patients aged 15 to 34 years. PPV of immunological and clinical criteria for correctly identifying treatment failure was similarly low for adult patients receiving either first-line or second-line/subsequent ART regimens. Our data confirm the inadequacy of clinical and immunologic criteria to correctly identify treatment failure and support the implementation of routine VL testing.

  6. Positive Predictive Value of the WHO Clinical and Immunologic Criteria to Predict Viral Load Failure among Adults on First, or Second-Line Antiretroviral Therapy in Kenya.

    Science.gov (United States)

    Waruru, Anthony; Muttai, Hellen; Ng'ang'a, Lucy; Ackers, Marta; Kim, Andrea; Miruka, Fredrick; Erick, Opiyo; Okonji, Julie; Ayuaya, Tolbert; Schwarcz, Sandra

    2016-01-01

    Routine HIV viral load (VL) monitoring is the standard of care for persons receiving antiretroviral therapy (ART) in developed countries. Although the World Health Organization recommends annual VL monitoring of patients on ART, recognizing difficulties in conducting routine VL testing, the WHO continues to recommend targeted VL testing to confirm treatment failure for persons who meet selected immunologic and clinical criteria. Studies have measured positive predictive value (PPV), negative predictive value, sensitivity and specificity of these criteria among patients receiving first-line ART but not specifically among those on second-line or subsequent regimens. Between 2008 and 2011, adult ART patients in Nyanza, Kenya who met national clinical or immunologic criteria for treatment failure received targeted VL testing. We calculated PPV and 95% confidence intervals (CI) of these criteria to detect virologic treatment failure among patients receiving a) first-line ART, b) second/subsequent ART, and c) any regimen. Of 12,134 patient specimens tested, 2,874 (23.7%) were virologically confirmed as treatment failures. The PPV for 2,834 first-line ART patients who met either the clinical or immunologic criteria for treatment failure was 34.4% (95% CI 33.2-35.7), 33.1% (95% CI 24.7-42.3) for the 40 patients on second-line/subsequent regimens, and 33.4% (95% CI 33.1-35.6) for any ART. PPV, regardless of criteria, for first-line ART patients was lowest among patients over 44 years old and highest for patients aged 15 to 34 years. PPV of immunological and clinical criteria for correctly identifying treatment failure was similarly low for adult patients receiving either first-line or second-line/subsequent ART regimens. Our data confirm the inadequacy of clinical and immunologic criteria to correctly identify treatment failure and support the implementation of routine VL testing.

  7. The Implications of Endoscopic Ulcer in Early Gastric Cancer: Can We Predict Clinical Behaviors from Endoscopy?

    Science.gov (United States)

    Lee, Yoo Jin; Kim, Jie-Hyun; Park, Jae Jun; Youn, Young Hoon; Park, Hyojin; Kim, Jong Won; Choi, Seung Ho; Noh, Sung Hoon

    2016-01-01

    Background The presence of ulcer in early gastric cancer (EGC) is important for the feasibility of endoscopic resection, only a few studies have examined the clinicopathological implications of endoscopic ulcer in EGC. Objectives To determine the role of endoscopic ulcer as a predictor of clinical behaviors in EGC. Methods Data of 3,270 patients with EGC who underwent surgery between January 2005 and December 2012 were reviewed. Clinicopathological characteristics were analyzed in relation to the presence and stage of ulcer in EGC. Based on endoscopic findings, the stage of ulcer was categorized as active, healing, or scar. Logistic regression analysis was performed to analyze factors associated with lymph node metastasis (LNM). Results 2,343 (71.7%) patients had endoscopic findings of ulceration in EGC. Submucosal (SM) invasion, LNM, lymphovascular invasion (LVI), perineural invasion, and undifferentiated-type histology were significantly higher in ulcerative than non-ulcerative EGC. Comparison across different stages of ulcer revealed that SM invasion, LNM, and LVI were significantly associated with the active stage, and that these features exhibited significant stage-based differences, being most common at the active stage, and least common at the scar stage. The presence of endoscopic ulcer and active status of the ulcer were identified as independent risk factors for LNM. Conclusions Ulcerative EGC detected by endoscopy exhibited more aggressive behaviors than non-ulcerative EGC. Additionally, the endoscopic stage of ulcer may predict the clinicopathological behaviors of EGC. Therefore, the appearance of ulcers should be carefully evaluated to determine an adequate treatment strategy for EGC. PMID:27741275

  8. Validation of World Health Organisation HIV/AIDS clinical staging in predicting initiation of antiretroviral therapy and clinical predictors of low CD4 cell count in Uganda.

    Directory of Open Access Journals (Sweden)

    Steven Baveewo

    Full Text Available INTRODUCTION: The WHO clinical guidelines for HIV/AIDS are widely used in resource limited settings to represent the gold standard of CD4 counts for antiviral therapy initiation. The utility of the WHO-defined stage 1 and 2 clinical factors used in WHO HIV/AIDS clinical staging in predicting low CD4 cell count has not been established in Uganda. Although the WHO staging has shown low sensitivity for predicting CD4<200 cells/mm(3, it has not been evaluated at for CD4 cut-offs of <250 cells/mm(3 or <350 cells/mm(3. OBJECTIVE: To validate the World Health Organisation HIV/AIDS clinical staging in predicting initiation of antiretroviral therapy in a low-resource setting and to determine the clinical predictors of low CD4 cell count in Uganda. RESULTS: Data was collected on 395 participants from the Joint Clinical Research Centre, of whom 242 (61.3% were classified as in stages 1 and 2 and 262 (68% were females. Participants had a mean age of 36.8 years (SD 8.5. We found a significant inverse correlation between the CD4 lymphocyte count and WHO clinical stages. The sensitivity the WHO clinical staging at CD4 cell count of 250 cells/mm(3 and 350 cells/mm(3 was 53.5% and 49.1% respectively. Angular cheilitis, papular pruritic eruptions and recurrent upper respiratory tract infections were found to be significant predictors of low CD4 cell count among participants in WHO stage 1 and 2. CONCLUSION: The WHO HIV/AIDS clinical staging guidelines have a low sensitivity and about half of the participants in stages 1 and 2 would be eligible for ART initiation if they had been tested for CD4 count. Angular cheilitis and papular pruritic eruptions and recurrent upper respiratory tract infections may be used, in addition to the WHO staging, to improve sensitivity in the interim, as access to CD4 machines increases in Uganda.

  9. Rule, Britannia

    DEFF Research Database (Denmark)

    Christensen, Jørgen Riber

    2011-01-01

    Thomas Arne’s The Masque of Alfred (1740) with a libretto by James Thomson and David Mallet was written and performed in the historical context of George II’s reign where a kind of constitutional monarchy based on the Bill of Rights from 1689 was granting civil rights to the early bourgeoisie...... of the Proms, and this article considers it as a global real-time media event. “Rule, Britannia!” is placed in the contexts of political history, cultural history and experience economy....

  10. Study of the prediction system for clinical response to M-VAC neoadjuvant chemotherapy for bladder cancer.

    Science.gov (United States)

    Takata, R; Obara, W; Fujioka, T

    2010-01-01

    Neoadjuvant chemotherapy for invasive bladder cancer, involving a regimen of M-VAC, can manage micrometastasis and improve the prognosis. However, some patients suffer from severe adverse drug reactions without any effect, and no method yet exists for predicting the response of an individual patient to chemotherapy. Our purpose in this study is to establish a method for predicting the response to the M-VAC therapy. We analyzed gene-expression profiles of biopsy materials from 40 invasive bladder cancers using a cDNA microarray consisting of 27 648 genes, after populations of cancer cells had been purified by laser-microbeam microdissection. We identified 14 predictive genes that were expressed differently between nine responder and nine non-responder tumors and devised a prediction-scoring system that clearly separated the responder group from the non-responder group. This system accurately predicted the clinical response for 19 of the 22 additional test cases. The group of patients with positive predictive scores had significantly longer survival times than that with negative scores. As real-time RT-PCR data were highly concordant with the cDNA microarray data for those 14 genes, we developed a quantitative RT-PCR-based prediction system that could be feasible for routine clinical use. Taken together, our results suggest that the sensitivity of an invasive bladder cancer to the M-VAC neoadjuvant chemotherapy can be predicted by expression patterns in this set of genes, a step toward achievement of "personalized therapy" for treatment of this disease.

  11. Two new prediction rules for spontaneous pregnancy leading to live birth among subfertile couples, based on the synthesis of three previous models.

    NARCIS (Netherlands)

    C.C. Hunault; J.D.F. Habbema (Dik); M.J.C. Eijkemans (René); J.A. Collins (John); J.L.H. Evers (Johannes); E.R. te Velde (Egbert)

    2004-01-01

    textabstractBACKGROUND: Several models have been published for the prediction of spontaneous pregnancy among subfertile patients. The aim of this study was to broaden the empirical basis for these predictions by making a synthesis of three previously published models. METHODS: We u

  12. Clinical Exposure Boost Predictions by Integrating Cytochrome P450 3A4-Humanized Mouse Studies With PBPK Modeling.

    Science.gov (United States)

    Zhang, Jin; Heimbach, Tycho; Scheer, Nico; Barve, Avantika; Li, Wenkui; Lin, Wen; He, Handan

    2016-04-01

    NVS123 is a poorly water-soluble protease 56 inhibitor in clinical development. Data from in vitro hepatocyte studies suggested that NVS123 is mainly metabolized by CYP3A4. As a consequence of limited solubility, NVS123 therapeutic plasma exposures could not be achieved even with high doses and optimized formulations. One approach to overcome NVS123 developability issues was to increase plasma exposure by coadministrating it with an inhibitor of CYP3A4 such as ritonavir. A clinical boost effect was predicted by using physiologically based pharmacokinetic (PBPK) modeling. However, initial boost predictions lacked sufficient confidence because a key parameter, fraction of drug metabolized by CYP3A4 (fmCYP3A4), could not be estimated with accuracy on account of disconnects between in vitro and in vivo preclinical data. To accurately estimate fmCYP3A4 in human, an in vivo boost effect study was conducted using CYP3A4-humanized mouse model which showed a 33- to 56-fold exposure boost effect. Using a top-down approach, human fmCYP3A4 for NVS123 was estimated to be very high and included in the human PBPK modeling to support subsequent clinical study design. The combined use of the in vivo boost study in CYP3A4-humanized mouse model mice along with PBPK modeling accurately predicted the clinical outcome and identified a significant NVS123 exposure boost (∼42-fold increase) with ritonavir.

  13. 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.

  14. A Novel Rule Induction Algorithm

    Institute of Scientific and Technical Information of China (English)

    ZHENG Jianguo; LIU Fang; WANG Lei; JIAO Licheng

    2001-01-01

    Knowledge discovery in databases is concerned with extracting useful information from databases, and the immune algorithm is a biological theory-based and globally searching algorithm. A specific immune algorithm is designed for discovering a few interesting, high-level prediction rules from databases, rather than discovering classification knowledge as usual in the literatures. Simulations show that this novel algorithm is able to improve the stability of the population, increase the holistic performance and make the rules extracted have higher precision.

  15. Behavioral Indicators on a Mobile Sensing Platform Predict Clinically Validated Psychiatric Symptoms of Mood and Anxiety Disorders

    Science.gov (United States)

    Place, Skyler; Rubin, Channah; Gorrostieta, Cristina; Mead, Caroline; Kane, John; Marx, Brian P; Feast, Joshua; Deckersbach, Thilo; Pentland, Alex “Sandy”; Nierenberg, Andrew; Azarbayejani, Ali

    2017-01-01

    Background There is a critical need for real-time tracking of behavioral indicators of mental disorders. Mobile sensing platforms that objectively and noninvasively collect, store, and analyze behavioral indicators have not yet been clinically validated or scalable. Objective The aim of our study was to report on models of clinical symptoms for post-traumatic stress disorder (PTSD) and depression derived from a scalable mobile sensing platform. Methods A total of 73 participants (67% [49/73] male, 48% [35/73] non-Hispanic white, 33% [24/73] veteran status) who reported at least one symptom of PTSD or depression completed a 12-week field trial. Behavioral indicators were collected through the noninvasive mobile sensing platform on participants’ mobile phones. Clinical symptoms were measured through validated clinical interviews with a licensed clinical social worker. A combination hypothesis and data-driven approach was used to derive key features for modeling symptoms, including the sum of outgoing calls, count of unique numbers texted, absolute distance traveled, dynamic variation of the voice, speaking rate, and voice quality. Participants also reported ease of use and data sharing concerns. Results Behavioral indicators predicted clinically assessed symptoms of depression and PTSD (cross-validated area under the curve [AUC] for depressed mood=.74, fatigue=.56, interest in activities=.75, and social connectedness=.83). Participants reported comfort sharing individual data with physicians (Mean 3.08, SD 1.22), mental health providers (Mean 3.25, SD 1.39), and medical researchers (Mean 3.03, SD 1.36). Conclusions Behavioral indicators passively collected through a mobile sensing platform predicted symptoms of depression and PTSD. The use of mobile sensing platforms can provide clinically validated behavioral indicators in real time; however, further validation of these models and this platform in large clinical samples is needed. PMID:28302595

  16. Nonzero Solubility Rule

    Institute of Scientific and Technical Information of China (English)

    尉志武; 周蕊; 刘芸

    2002-01-01

    A solubility-related rule, nonzero solubility rule, is introduced in this paper. It is complementary to the existing rules such as the "like dissolves like" rule and can be understood on the basis of classical chemical thermodynamics.

  17. The usefulness of holotranscobalamin in predicting vitamin B12 status in different clinical settings.

    Science.gov (United States)

    Herrmann, Wolfgang; Obeid, Rima; Schorr, Heike; Geisel, Jürgen

    2005-02-01

    Serum concentrations of homocysteine (Hcy) and methylmalonic acid (MMA) become increased in B12-deficient subjects and are therefore, considered specific markers of B12 deficiency. Serum level of holotranscobalamin (holoTC) becomes decreased before the development of the metabolic dysfunction. We investigated the usefulness of holoTC in diagnosing B12 deficiency in some clinical settings. We measured serum concentrations of holoTC, MMA, Hcy and total B12 in omnivores, vegetarians, elderly people and haemodialysis patients. Our results indicated that the incidence of holoTC vegans (76%). Low holoTC and elevated MMA were detected in 64% of the vegans and 43% of the lacto- and lacto-ovovegetarians. An elevated MMA and a low holoTC were found in subjects with total serum B12 as high as 300 pmol/L. The distribution of holoTC in elderly people was similar to that in younger adults (median holoTC 55 pmol/L in both groups). A low holoTC and an elevated MMA were found in 16% of the elderly group. An elevated MMA and a normal holoTC were found in 20% of the elderly group who had a relatively high median serum concentration of creatinine (106.1 micromol/L). Serum concentrations of holoTC in dialysis patients were considerably higher than all other groups (median 100 pmol/L). This was also associated with severely increased serum levels of MMA (median 987 nmol/L). From these results it can be concluded that serum concentration of holoTC is a much better predictor of B12 status than total B12. This was particularly evident in case of dietary B12 deficiency. Serum concentrations of holoTC as well as MMA can be affected by renal dysfunction. Elevated MMA and normal holoTC in patients with renal insufficiency may not exclude vitamin B12 deficiency. HoloTC seems not to be a promising marker in predicting B12 status in renal patients.

  18. The REFER (REFer for EchocaRdiogram protocol: a prospective validation of a clinical decision rule, NT-proBNP, or their combination, in the diagnosis of heart failure in primary care. Rationale and design

    Directory of Open Access Journals (Sweden)

    Tait Lynda

    2012-10-01

    Full Text Available Abstract Background Heart failure is a major cause of mortality and morbidity. As mortality rates are high, it is important that patients seen by general practitioners with symptoms suggestive of heart failure are identified quickly and treated appropriately. Identifying patients with heart failure or deciding which patients need further tests is a challenge. All patients with suspected heart failure should be diagnosed using objective tests such as echocardiography, but it is expensive, often delayed, and limited by the significant skill shortage of trained echocardiographers. Alternative approaches for diagnosing heart failure are currently limited. Clinical decision tools that combine clinical signs, symptoms or patient characteristics are designed to be used to support clinical decision-making and validated according to strict methodological procedures. The REFER Study aims to determine the accuracy and cost-effectiveness of our previously derived novel, simple clinical decision rule, a natriuretic peptide assay, or their combination, in the triage for referral for echocardiography of symptomatic adult patients who present in general practice with symptoms suggestive of heart failure. Methods/design This is a prospective, Phase II observational, diagnostic validation study of a clinical decision rule, natriuretic peptides or their combination, for diagnosing heart failure in primary care. Consecutive adult primary care patients 55 years of age or over presenting to their general practitioner with a chief complaint of recent new onset shortness of breath, lethargy or peripheral ankle oedema of over 48 hours duration, with no obvious recurrent, acute or self-limiting cause will be enrolled. Our reference standard is based upon a three step expert specialist consensus using echocardiography and clinical variables and tests. Discussion Our clinical decision rule offers a potential solution to the diagnostic challenge of providing a timely and

  19. Comparison and clinical suitability of eight prediction models for cardiac surgery-related acute kidney injury

    NARCIS (Netherlands)

    Kiers, H.D.; Boogaard, M.H.W.A. van den; Schoenmakers, M.C.J.; Hoeven, J.G. van der; Swieten, H.A. van; Heemskerk, S.; Pickkers, P.

    2013-01-01

    BACKGROUND: Cardiac surgery-related acute kidney injury (CS-AKI) results in increased morbidity and mortality. Different models have been developed to identify patients at risk of CS-AKI. While models that predict dialysis and CS-AKI defined by the RIFLE criteria are available, their predictive powe

  20. Social Anxiety Predicts Aggression in Children with ASD: Clinical Comparisons with Socially Anxious and Oppositional Youth

    Science.gov (United States)

    Pugliese, Cara E.; White, Bradley A.; White, Susan W.; Ollendick, Thomas H.

    2013-01-01

    The present study examined the degree to which social anxiety predicts aggression in children with high functioning autism spectrum disorders (HFASD, n = 20) compared to children with Social Anxiety Disorder (SAD, n = 20) or with Oppositional Defiant Disorder or Conduct Disorder (ODD/CD, n = 20). As predicted, children with HFASD reported levels…

  1. Clinical versus Actuarial Predictions of Violence in Patients with Mental Illness.

    Science.gov (United States)

    Gardner, William; And Others

    1996-01-01

    Compared accuracy of an actuarial procedure for the prediction of community violence by patients with mental illnesses to accuracy of clinicians' concern ratings of patient violence. Data came from a study of 357 pairs of patients seen in a psychiatric emergency room. Actuarial predictions based only on patients' histories of violence were more…

  2. Selecting new health technologies for evaluation:Can clinical experts predict which new anticancer drugswill impact Danish health care?

    DEFF Research Database (Denmark)

    Douw, Karla; Vondeling, Hindrik

    2007-01-01

    source of information on new health technologies, but research on the relevance of their input is scarce. In 2000, we asked six Danish expert oncologists to predict whether a sample of 19 new anticancer drugs would impact Danish health care over the next 5 years. In 2005, we assessed the accuracy...... that clinical experts have the ability to predict which new anticancer drugs are unlikely to have an impact. This information can be used to increase the efficiency of selecting new technologies for evaluation. As the experts missed 37% of drugs that are in need of guidance, they should not be relied upon......Several countries have systems in place to support the managed entry of new health technologies. The big challenge for these so-called horizon-scanning systems is to select those technologies that require decision support by means of an early evaluation. Clinical experts are considered a valuable...

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

    Science.gov (United States)

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

    2016-06-01

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

  4. Development of a classification rule for four clinical therapeutic psychotropic drug classes with EEG power-spectrum variables of human volunteers.

    Science.gov (United States)

    Herrmann, W M; Fichte, K; Itil, T M; Kubicki, S

    1979-01-01

    An objective rule for the classification of psychotropic substances has been developed. Classification is based on data from five basic studies simultaneously designed and performed and involving 75 healthy volunteers who ingested 20 different psychotropic drugs and 5 placebos in single oral dosages. Each volunteer took one psychostimulant, one antidepressant, one neuroleptic, one minor tranquilizer and one placebo in a double-blind Latin square cross-over design. The variables were 6 frequency bands, based on power spectrum estimates and determined by factor analysis, plus total power in the 1.5-30.0 Hz range. An objective classification rule was established by multi-group (5 groups) linear discriminant analysis. Reclassification of the substances by the new rule yielded correct results for 17 out of 20 psychotropic drugs and 4 out of 5 placebos. Of placebos from various studies not used for the establishment of the classification rule, 7/9 were classified correctly. The validity of the rule for other classes of substances will have to be verified in independent studies.

  5. Predictive value of clinical evaluation in the follow-up of children with a brain tumor.

    NARCIS (Netherlands)

    Graaf, N. de; Hew, J.M.; Fock, J.M.; Kamps, W.A.; Graaf, S.S.N. de

    2002-01-01

    BACKGROUND: During follow-up of children with a brain tumor, traditionally surveillance-imaging studies are done in addition to clinical evaluations. The purpose of this study was to determine the role of clinical evaluations by a multidisciplinary team for the detection of recurrent tumor. PROCEDUR

  6. Predictive value of clinical evaluation in the follow-up of children with a brain tumor

    NARCIS (Netherlands)

    Hew, JM; Fock, JM; Kamps, WA

    2002-01-01

    Background. During follow-up of children with a brain tumor, traditionally surveillance-imaging studies are done in addition to clinical evaluations, The purpose of this study was to determine the role of clinical evaluations by a multidisciplinary team for the detection of recurrent tumor. Procedur

  7. Is magnetic resonance imaging reliable in predicting clinical outcome after articular cartilage repair of the knee?

    NARCIS (Netherlands)

    Windt, de T.S.; Welsch, G.H.; Brittberg, M.; Vonk, L.A.; Marlovits, S.; Trattnig, S.; Saris, D.B.F.

    2013-01-01

    Background: While MRI can provide a detailed morphological evaluation after articular cartilage repair, its additional value in determining clinical outcome has yet to be determined. Purpose: To evaluate the correlation between MRI and clinical outcome after cartilage repair and to identify parame

  8. Empirically and Clinically Useful Decision Making in Psychotherapy: Differential Predictions with Treatment Response Models

    Science.gov (United States)

    Lutz, Wolfgang; Saunders, Stephen M.; Leon, Scott C.; Martinovich, Zoran; Kosfelder, Joachim; Schulte, Dietmar; Grawe, Klaus; Tholen, Sven

    2006-01-01

    In the delivery of clinical services, outcomes monitoring (i.e., repeated assessments of a patient's response to treatment) can be used to support clinical decision making (i.e., recurrent revisions of outcome expectations on the basis of that response). Outcomes monitoring can be particularly useful in the context of established practice research…

  9. Evaluation of the Cerebral State Index in Cats under Isoflurane Anaesthesia: Dose-Effect Relationship and Prediction of Clinical Signs

    Directory of Open Access Journals (Sweden)

    Joana R. Sousa

    2014-01-01

    Full Text Available The performance of the cerebral state index (CSI in reflecting different levels of isoflurane anaesthesia was evaluated in ten cats subjected to four end-tidal isoflurane concentrations (EtIso, each maintained for 15 minutes (0.8%, 1.2%, 1.6%, or 2.0% EtIso. The CSI, hemodynamic data, ocular reflexes, and eye position were recorded for each EtIso concentration. Pharmacodynamic analysis of CSI with EtIso was performed, as well as prediction probability analysis with a clinical scale based on the eye reflexes. The CSI values showed great variability. Between all parameters, burst suppression ratio showed the better fitting with the sigmoidal concentration-effect model (R2=0.93 followed by CSI (R2=0.82 and electromyographic activity (R2=0.79. EtIso was the variable with better prediction of the clinical scale of anaesthesia (prediction probability value of 0.94. Although the CSI values decrease with increasing isoflurane concentrations, the huge variability in CSI values may be a strong limitation for its use in cats and it seems to be no better than EtIso as a predictor of clinical signs.

  10. DEVELOPMENT OF THE NOMOGRAM THAT PREDICTS PATHOLOGICAL LYMPH NODE INVOLVEMENT IN BLADDER CANCER PATIENTS BASED ON CLINICAL VARIABLES

    Directory of Open Access Journals (Sweden)

    L. V. Mirylenko

    2012-01-01

    Full Text Available Objective: to develop nomogram based on clinical variables, that predicts pathological lymph node involvement (рN+ in bladder cancer patients.Material and methods: We used data of 511 patients with bladder cancer, that have undergone radical cystectomy between 1999 and 2008 at N.N. Alexandrov National Cancer Centre. Mono- and multivariate logistic regression analyses were used for pN+ prediction on preoperative data. Coefficients from logistic regression equation were used to construct the nomogram. Nomogram accuracy was evaluated with concordance index and construction of the calibration plot. Internal validation by bootstrap method with 200 variants of dataset was performed.Results: We developed nomogram, that includes: clinical stage сТ, tumor grade, tumor macroscopic appearance, and creatinine level. Bootstrap-corrected prognostic accuracy of nomogram was 71,6%, that was 9,4% better than clinical stage accuracy.Conclusion: utilization of developed nomogram can significantly improve pathologic tumor stage prediction accuracy that may be used to select patients for neoadjuvant chemotherapy.

  11. DEVELOPMENT OF THE NOMOGRAM THAT PREDICTS PATHOLOGICAL LYMPH NODE INVOLVEMENT IN BLADDER CANCER PATIENTS BASED ON CLINICAL VARIABLES

    Directory of Open Access Journals (Sweden)

    L. V. Mirylenko

    2014-07-01

    Full Text Available Objective: to develop nomogram based on clinical variables, that predicts pathological lymph node involvement (рN+ in bladder cancer patients.Material and methods: We used data of 511 patients with bladder cancer, that have undergone radical cystectomy between 1999 and 2008 at N.N. Alexandrov National Cancer Centre. Mono- and multivariate logistic regression analyses were used for pN+ prediction on preoperative data. Coefficients from logistic regression equation were used to construct the nomogram. Nomogram accuracy was evaluated with concordance index and construction of the calibration plot. Internal validation by bootstrap method with 200 variants of dataset was performed.Results: We developed nomogram, that includes: clinical stage сТ, tumor grade, tumor macroscopic appearance, and creatinine level. Bootstrap-corrected prognostic accuracy of nomogram was 71,6%, that was 9,4% better than clinical stage accuracy.Conclusion: utilization of developed nomogram can significantly improve pathologic tumor stage prediction accuracy that may be used to select patients for neoadjuvant chemotherapy.

  12. CREATION OF THE NOMOGRAM THAT PREDICTS PATHOLOGICAL LOCAL EXTENT OF THE BLADDER CANCER BASED ON CLINICAL VARIABLES

    Directory of Open Access Journals (Sweden)

    L. V. Mirylenka

    2014-08-01

    Full Text Available Objective: to develop nomogram based on clinical variables, that predicts pathological local extent of the bladder cancer рТ3-рТ4 (рТ3+.Material and methods: We used data of 511 patients with bladder cancer, that have undergone radical cystectomy between 1999 and 2008 at N.N. Alexandrov National Cancer Centre. For prediction of pT3+ on preoperative data were used mono- and multivariate logistic regression analysis. Coefficients from logistic regression equalization were used to construct nomogram. Nomogram accuracy was evaluated with concordance index (с-index and by building the calibration plot. Internal validation by bootstrap method with 200 variants of dataset was performed.Results: We developed nomogram, that include: clinical stage сТ, tumor grade, tumor macroscopic appearance, presence of upper tract dilatation, prostatic urethra and/or prostatic lobe(s involvement, 3 or more bladder walls involvement, ESR and creatinine level. Bootstrapcorrected prognostic accuracy of nomogram was 81,4%, that 12,6% better than clinical stage accuracy.Conclusion: developed nomogram can significantly improve pathologic tumor stage prediction accuracy that may be used to select patients for neoadjuvant chemotherapy.

  13. CREATION OF THE NOMOGRAM THAT PREDICTS PATHOLOGICAL LOCAL EXTENT OF THE BLADDER CANCER BASED ON CLINICAL VARIABLES

    Directory of Open Access Journals (Sweden)

    L. V. Mirylenka

    2012-01-01

    Full Text Available Objective: to develop nomogram based on clinical variables, that predicts pathological local extent of the bladder cancer рТ3-рТ4 (рТ3+.Material and methods: We used data of 511 patients with bladder cancer, that have undergone radical cystectomy between 1999 and 2008 at N.N. Alexandrov National Cancer Centre. For prediction of pT3+ on preoperative data were used mono- and multivariate logistic regression analysis. Coefficients from logistic regression equalization were used to construct nomogram. Nomogram accuracy was evaluated with concordance index (с-index and by building the calibration plot. Internal validation by bootstrap method with 200 variants of dataset was performed.Results: We developed nomogram, that include: clinical stage сТ, tumor grade, tumor macroscopic appearance, presence of upper tract dilatation, prostatic urethra and/or prostatic lobe(s involvement, 3 or more bladder walls involvement, ESR and creatinine level. Bootstrapcorrected prognostic accuracy of nomogram was 81,4%, that 12,6% better than clinical stage accuracy.Conclusion: developed nomogram can significantly improve pathologic tumor stage prediction accuracy that may be used to select patients for neoadjuvant chemotherapy.

  14. A prospective, clinical study on asymptomatic sensitisation and development of allergic rhinitis: high negative predictive value of allergological testing

    DEFF Research Database (Denmark)

    Bodtger, Uffe; Assing, Kristian; Poulsen, Lars K

    2011-01-01

    populations, conferring bias towards higher incidence rates. Objective: The aim was to determine the incidence of onset of symptoms among clinically well-characterised asymptomatic, sensitised subjects compared with controls, and to evaluate the predictive values of common allergological tests. Methods: We...... an annual incidence rate of 5% for the onset of symptoms in the AS group (healthy control group 0%). At baseline, the AS group displayed intermediate experimental allergen susceptibility. Subjects developing symptoms had higher levels of specific IgE and larger late-phase reaction than those persistently...... asymptomatic. However, the positive predictive values were low (14-27%) in contrast to the negative predictive values (95-100%). Conclusion: In a well-characterised young population, asymptomatic aeroallergen sensitisation conferred a low risk for onset of symptoms during the 2-year follow-up. Persistent...

  15. Facets of psychopathy among mentally disordered offenders: clinical comorbidity patterns and prediction of violent and criminal behavior.

    Science.gov (United States)

    Wallinius, Märta; Nilsson, Thomas; Hofvander, Björn; Anckarsäter, Henrik; Stålenheim, Gunilla

    2012-07-30

    The complexity and consequences of psychopathy are still debated, and its relation to other mental disorders, pathological personality traits, and criminality needs to be further investigated by clinical, longitudinal studies using structured diagnostic instruments. The present study used two groups of mentally disordered offenders (N=153) investigated with in-depth clinical assessments and prospective long-term follow-up to identify the convergence between 1) the four facets of psychopathy defined by the Psychopathy Checklist-Revised (PCL-R; Interpersonal, Affective, Lifestyle, and Antisocial), 2) mental disorders according to SCID I and II interviews, 3) personality traits as measured by the Karolinska Scales of Personality, and 4) criminal recidivism. The Interpersonal facet differed substantially from the other three facets by not being significantly associated with substance use disorders, antisocial personality disorder (the other facets at P≤0.001 level), or personality traits involving impulsive and aggressive antisocial behaviors (the other facets at Pfacet could not predict violent recidivism better than random. The Antisocial facet outperformed not only the other facets but also the total PCL-R score in the prediction of violent recidivism, P<0.001.The findings confirm psychopathy as a heterogeneous phenomenon and have clinical implications for assessments of psychopathy and violence risk assessments in clinical and forensic contexts.

  16. Women's age and embryo developmental speed accurately predict clinical pregnancy after single vitrified-warmed blastocyst transfer.

    Science.gov (United States)

    Kato, Keiichi; Ueno, Satoshi; Yabuuchi, Akiko; Uchiyama, Kazuo; Okuno, Takashi; Kobayashi, Tamotsu; Segawa, Tomoya; Teramoto, Shokichi

    2014-10-01

    The aim of this study was to establish a simple, objective blastocyst grading system using women's age and embryo developmental speed to predict clinical pregnancy after single vitrified-warmed blastocyst transfer. A 6-year retrospective cohort study was conducted in a private infertility centre. A total of 7341 single vitrified-armed blastocyst transfer cycles were included, divided into those carried out between 2006 and 2011 (6046 cycles) and 2012 (1295 cycles). Clinical pregnancy rate, ongoing pregnancy rate and delivery rates were stratified by women's age (149 h) as embryo developmental speed. In all the age groups, clinical pregnancy rate, ongoing pregnancy rate and delivery rates decreased as the embryo developmental speed decreased (P pregnancy rates observed in the 2006-2011 cohort. Subsequently, the novel grading score was validated in the 2012 cohort (1295 cycles), finding an excellent association. In conclusion, we established a novel blastocyst grading system using women's age and embryo developmental speed as objective parameters.

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

    Directory of Open Access Journals (Sweden)

    Ruby Yadav

    2016-08-01

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

  18. MRI characteristics are predictive for CDMS in monofocal, but not in multifocal patients with a clinically isolated syndrome

    Directory of Open Access Journals (Sweden)

    Nielsen Jessica M

    2009-05-01

    Full Text Available Abstract Background To diagnose multiple sclerosis (MS, evidence for dissemination in space and time is required. There is no clear definition on how symptoms and signs of a patient indicate clinical dissemination in space. To provide a uniform approach on this subject, a clinical classification system was described recently differentiating patients with mono- and multifocal clinical presentation. Here we assess the predictive value of clinically defined dissemination in space at first presentation for time to clinically definite MS (CDMS. Methods Four hundred and sixty-eight patients with a first episode suggestive of MS were classified as clinically mono- or multifocal by two neurologists blinded to magnetic resonance imaging (MRI results. These patients were part of the BENEFIT study in which 292 patients were randomized to interferon beta-1b (IFNB-1b and 176 to placebo. By using Kaplan-Meier statistics the risk for CDMS was studied in mono- and multifocal patients of the placebo group, both with and without taking into account MRI measures of potential prognostic relevance. Results Time to CDMS was similar in monofocal and multifocal patients. In monofocal patients, the risk for CDMS over 2 years was significantly higher when ≥ 9 T2 lesions or at least one Gd-enhancing lesion were present at the first event or 3 or 6 months after the first event. In patients with multifocal presentation, these MRI measures had no significant added value in predicting time to CDMS. Conclusion These data indicate that a carefully performed neurological assessment of symptoms and signs, combined with lesions on MRI, is important for defining the risk of conversion to CDMS. Trial Registration The Benefit trial has been registered under NCT00185211 http://www.clinicaltrials.gov

  19. Burnout and Work Demands Predict Reduced Job Satisfaction in Health Professionals Working In a Surgery Clinic

    Directory of Open Access Journals (Sweden)

    Dragan Mijakoski

    2015-03-01

    CONCLUSIONS: Adequate management of work demands, particularly excessive workload, time pressure, and lack of staff can lead to prevention of burnout and reduced job satisfaction in surgery clinic HPs, and contribute to better quality of patient care.

  20. Can Psychological, Social and Demographical Factors Predict Clinical Characteristics Symptomatology of Bipolar Affective Disorder and Schizophrenia?

    Science.gov (United States)

    Maciukiewicz, Malgorzata; Pawlak, Joanna; Kapelski, Pawel; Łabędzka, Magdalena; Skibinska, Maria; Zaremba, Dorota; Leszczynska-Rodziewicz, Anna; Dmitrzak-Weglarz, Monika; Hauser, Joanna

    2016-09-01

    Schizophrenia (SCH) is a complex, psychiatric disorder affecting 1 % of population. Its clinical phenotype is heterogeneous with delusions, hallucinations, depression, disorganized behaviour and negative symptoms. Bipolar affective disorder (BD) refers to periodic changes in mood and activity from depression to mania. It affects 0.5-1.5 % of population. Two types of disorder (type I and type II) are distinguished by severity of mania episodes. In our analysis, we aimed to check if clinical and demographical characteristics of the sample are predictors of symptom dimensions occurrence in BD and SCH cases. We included total sample of 443 bipolar and 439 schizophrenia patients. Diagnosis was based on DSM-IV criteria using Structured Clinical Interview for DSM-IV. We applied regression models to analyse associations between clinical and demographical traits from OPCRIT and symptom dimensions. We used previously computed dimensions of schizophrenia and bipolar affective disorder as quantitative traits for regression models. Male gender seemed protective factor for depression dimension in schizophrenia and bipolar disorder sample. Presence of definite psychosocial stressor prior disease seemed risk factor for depressive and suicidal domain in BD and SCH. OPCRIT items describing premorbid functioning seemed related with depression, positive and disorganised dimensions in schizophrenia and psychotic in BD. We proved clinical and demographical characteristics of the sample are predictors of symptom dimensions of schizophrenia and bipolar disorder. We also saw relation between clinical dimensions and course of disorder and impairment during disorder.

  1. Protein-Based Classifier to Predict Conversion from Clinically Isolated Syndrome to Multiple Sclerosis.

    Science.gov (United States)

    Borràs, Eva; Cantó, Ester; Choi, Meena; Maria Villar, Luisa; Álvarez-Cermeño, José Carlos; Chiva, Cristina; Montalban, Xavier; Vitek, Olga; Comabella, Manuel; Sabidó, Eduard

    2016-01-01

    Multiple sclerosis is an inflammatory, demyelinating, and neurodegenerative disease of the central nervous system. In most patients, the disease initiates with an episode of neurological disturbance referred to as clinically isolated syndrome, but not all patients with this syndrome develop multiple sclerosis over time, and currently, there is no clinical test that can conclusively establish whether a patient with a clinically isolated syndrome will eventually develop clinically defined multiple sclerosis. Here, we took advantage of the capabilities of targeted mass spectrometry to establish a diagnostic molecular classifier with high sensitivity and specificity able to differentiate between clinically isolated syndrome patients with a high and a low risk of developing multiple sclerosis. Based on the combination of abundances of proteins chitinase 3-like 1 and ala-β-his-dipeptidase in cerebrospinal fluid, we built a statistical model able to assign to each patient a precise probability of conversion to clinically defined multiple sclerosis. Our results are of special relevance for patients affected by multiple sclerosis as early treatment can prevent brain damage and slow down the disease progression.

  2. Predicting Anxiety Among Patients In LPU Clinical Dispensary During Dental Treatment: Towards Student’s Clinical Performance Enhancement

    Directory of Open Access Journals (Sweden)

    Maribel D. Mayuga-Barrion

    2013-12-01

    Full Text Available The study aimed to determine the respondents’ profile in terms of age, gender, frequency of dental visit, and type of patient whether dental phobic or not; to determine the dental anxiety of patients in LPU dental dispensary; to identify the causes and severity of anxiety of the patients in LPU dental dispensary; to determine if there is a significant difference between the respondents’ demographic profile and their level of anxiety; and lastly, to propose a program that will help the patients cope with dental anxiety and a program that will enhance the students’ clinical performance. The study used the descriptive research design with the combination of content analysis of documents and related materials. Results showed that majority of the respondents belonged to age range of 14-18 years old range whereas for gender or sex, majority who avail of the clinic’s services are males. This is because women are more afraid than men in terms of dental problems. Further, younger people are more afraid than older ones. The weighted mean distribution of the level of anxiety showed that the level of anxiety of patients varies on moderately to not anxious. Feeling or experiencing pain during dental treatment ranked first followed by the fear or worry of not working the proposed treatment and thirdly, the dentist is in a hurry while treating also made the patients moderately anxious. Overall, the level of anxiety of patients is moderately anxious. Probing to asses gum disease, dislike the numb feeling and injection were the top three causes of dental anxiety. Only type of patient shows significant difference, thus the null hypothesis of no significant difference on the level of anxiety when grouped according to profile variables is rejected. This means that the level of anxiety of both phobic and not phobic differs.

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

    Science.gov (United States)

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

    2015-01-01

    Abstract It is important to identify the severity of acute pancreatitis (AP) in the early course of the disease. Clinical scoring systems may be helpful to predict the prognosis of patients with early AP; however, few analysts have forecast the accuracy of scoring systems for the prognosis in hyperlipidemic acute pancreatitis (HLAP). The purpose of this study was to summarize the clinical characteristics of HLAP and compare the accuracy of conventional scoring systems in predicting the prognosis of HLAP. This study retrospectively analyzed all consecutively diagnosed AP patients between September 2008 and March 2014. We compared the clinical characteristics between HLAP and nonhyperlipidemic acute pancreatitis. The bedside index for severity of acute pancreatitis (BISAP), Ranson, computed tomography severity index (CTSI), and systemic inflammatory response syndrome (SIRS) scores were applied within 48 hours following admission. Of 909 AP patients, 129 (14.2%) had HLAP, 20 were classified as severe acute pancreatitis (SAP), 8 had pseudocysts, 9 had pancreatic necrosis, 30 had pleural effusions, 33 had SIRS, 14 had persistent organ failure, and there was 1 death. Among the HLAP patients, the area under curves for BISAP, Ranson, SIRS, and CTSI in predicting SAP were 0.905, 0.938, 0.812, and 0.834, 0.874, 0.726, 0.668, and 0.848 for local complications, and 0.904, 0.917, 0.758, and 0.849 for organ failure, respectively. HLAP patients were characterized by younger age at onset, higher recurrence rate, and being more prone to pancreatic necrosis, organ failure, and SAP. BISAP, Ranson, SIRS, and CTSI all have accuracy in predicting the prognosis of HLAP patients, but each has different strengths and weaknesses. PMID:26061329

  4. A Prediction Algorithm for Drug Response in Patients with Mesial Temporal Lobe Epilepsy Based on Clinical and Genetic Information

    Science.gov (United States)

    Carvalho, Benilton S.; Bilevicius, Elizabeth; Alvim, Marina K. M.; Lopes-Cendes, Iscia

    2017-01-01

    Mesial temporal lobe epilepsy is the most common form of adult epilepsy in surgical series. Currently, the only characteristic used to predict poor response to clinical treatment in this syndrome is the presence of hippocampal sclerosis. Single nucleotide polymorphisms (SNPs) located in genes encoding drug transporter and metabolism proteins could influence response to therapy. Therefore, we aimed to evaluate whether combining information from clinical variables as well as SNPs in candidate genes could improve the accuracy of predicting response to drug therapy in patients with mesial temporal lobe epilepsy. For this, we divided 237 patients into two groups: 75 responsive and 162 refractory to antiepileptic drug therapy. We genotyped 119 SNPs in ABCB1, ABCC2, CYP1A1, CYP1A2, CYP1B1, CYP2C9, CYP2C19, CYP2D6, CYP2E1, CYP3A4, and CYP3A5 genes. We used 98 additional SNPs to evaluate population stratification. We assessed a first scenario using only clinical variables and a second one including SNP information. The random forests algorithm combined with leave-one-out cross-validation was used to identify the best predictive model in each scenario and compared their accuracies using the area under the curve statistic. Additionally, we built a variable importance plot to present the set of most relevant predictors on the best model. The selected best model included the presence of hippocampal sclerosis and 56 SNPs. Furthermore, including SNPs in the model improved accuracy from 0.4568 to 0.8177. Our findings suggest that adding genetic information provided by SNPs, located on drug transport and metabolism genes, can improve the accuracy for predicting which patients with mesial temporal lobe epilepsy are likely to be refractory to drug treatment, making it possible to identify patients who may benefit from epilepsy surgery sooner. PMID:28052106

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

    Institute of Scientific and Technical Information of China (English)

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

    2009-01-01

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

  6. Predicting radiotherapy-related clinical toxicities in cancer: a literature review.

    Science.gov (United States)

    O'Gorman, Claire; Sasiadek, Wojciech; Denieffe, Suzanne; Gooney, Martina

    2014-06-01

    Assessment of patients receiving radiotherapy for cancer is essential, with the ability to identify those who may be more likely to experience radiotherapy-related side effects noted as an important issue for nurses. Body mass, age, and radiation dose may be predictive factors for the development of such side effects. This review considers these factors and how nurses can use this evidence to inform their care, with results indicating that the dose of radiation, the site treated, and body mass index are predictive of toxicities that may develop. Increased awareness of these predictive factors will aid nurses in identifying patients at greater risk of developing radiation-related side effects. This will assist in guiding nursing interventions, as well as enabling the individualization of patient education, by placing greater emphasis on preventive measures for patients who are more vulnerable to the development of radiation-related toxicities.

  7. Predictive factors for a severe clinical course in ulcerative colitis: Results from population-based studies

    Institute of Scientific and Technical Information of China (English)

    Magnus Hofrenning Wander?s; Bj?rn A Moum; Marte Lie H?ivik; ?istein Hovde

    2016-01-01

    Ulcerative colitis(UC)is characterized by chronic inflammation of the large bowel in genetically suscep-tible individuals exposed to environmental risk factors.The disease course can be difficult to predict,with symptoms ranging from mild to severe.There is no generally accepted definition of severe UC,and no single outcome is sufficient to classify a disease course as severe.There are several outcomes indicating a severe disease course,including progression of the disease’s extension,a high relapse rate,the development of acute severe colitis,colectomy,the occurrence of colorectal cancer and UC-related mortality.When evaluating a patient’s prognosis,it is helpful to do so in relation to these outcomes.Using these outcomes also makes it easier to isolate factors predictive of severe disease.The aims of this article are to evaluate different disease outcomes and to present predictive factors for these outcomes.

  8. A dynamic model of once-daily 5-aminosalicylic acid predicts clinical efficacy

    Institute of Scientific and Technical Information of China (English)

    Deepak; Parakkal; Eli; D; Ehrenpreis; Matthew; P; Thorpe; Karson; S; Putt; Bruce; Hannon

    2010-01-01

    New once daily mesalamine formulations may improve adherence to medication usage.Response to Asacol and other forms of 5-aminosalicyclic acid(5-ASA)is better correlated with tissue concentrations and best predicted by concentrations of the drug within the lumen of the colon.Our group used computer simulation to predict colonic 5-ASA levels after Asacol administration.In our study,the model simulated Asacol distribution in the healthy colon,and during quiescent and active ulcerative colitis.An Asacol dosage ...

  9. Added value of CT perfusion compared to CT angiography in predicting clinical outcomes of stroke patients treated with mechanical thrombectomy

    Energy Technology Data Exchange (ETDEWEB)

    Tsogkas, Ioannis; Knauth, Michael; Schregel, Katharina; Behme, Daniel; Psychogios, Marios Nikos [University Medicine Goettingen, Department of Neuroradiology, Goettingen (Germany); Wasser, Katrin; Maier, Ilko; Liman, Jan [University Medicine Goettingen, Department of Neurology, Goettingen (Germany)

    2016-11-15

    CTP images analyzed with the Alberta stroke program early CT scale (ASPECTS) have been shown to be optimal predictors of clinical outcome. In this study we compared two biomarkers, the cerebral blood volume (CBV)-ASPECTS and the CTA-ASPECTS as predictors of clinical outcome after thrombectomy. Stroke patients with thrombosis of the M1 segment of the middle cerebral artery were included in our study. All patients underwent initial multimodal CT with CTP and CTA on a modern CT scanner. Treatment consisted of full dose intravenous tissue plasminogen activator, when applicable, and mechanical thrombectomy. Three neuroradiologists separately scored CTP and CTA images with the ASPECTS score. Sixty-five patients were included. Median baseline CBV-ASPECTS and CTA-ASPECTS for patients with favourable clinical outcome at follow-up were 8 [interquartile range (IQR) 8-9 and 7-9 respectively]. Patients with poor clinical outcome showed a median baseline CBV-ASPECTS of 6 (IQR 5-8, P < 0.0001) and a median baseline CTA-ASPECTS of 7 (IQR 7-8, P = 0.18). Using CBV-ASPECTS and CTA-ASPECTS raters predicted futile reperfusions in 96 % and 56 % of the cases, respectively. CBV-ASPECTS is a significant predictor of clinical outcome in patients with acute ischemic stroke treated with mechanical thrombectomy. (orig.)

  10. SU-E-T-629: Prediction of the ViewRay Radiotherapy Treatment Time for Clinical Logistics

    Energy Technology Data Exchange (ETDEWEB)

    Liu, S; Wooten, H; Wu, Y; Yang, D [Washington University in St Louis, St Louis, MO (United States)

    2015-06-15

    Purpose: An algorithm is developed in our clinic, given a new treatment plan, to predict treatment delivery time for radiation therapy (RT) treatments of patients on ViewRay magnetic resonance-image guided radiation therapy (MR-IGRT) delivery system. This algorithm is necessary for managing patient treatment appointments, and is useful as an indicator to assess the treatment plan complexity. Methods: A patient’s total treatment delivery time, not including time required for localization, may be described as the sum of four components: (1) the treatment initialization time; (2) the total beam-on time; (3) the gantry rotation time; and (4) the multileaf collimator (MLC) motion time. Each of the four components is predicted separately. The total beam-on time can be calculated using both the planned beam-on time and the decay-corrected delivery dose rate. To predict the remaining components, we quantitatively analyze the patient treatment delivery record files. The initialization time is demonstrated to be random since it depends on the final gantry angle and MLC leaf positions of the previous treatment. Based on modeling the relationships between the gantry rotation angles and the corresponding rotation time, and between the furthest MLC leaf moving distance and the corresponding MLC motion time, the total delivery time is predicted using linear regression. Results: The proposed algorithm has demonstrated the feasibility of predicting the ViewRay treatment delivery time for any treatment plan of any patient. The average prediction error is 0.89 minutes or 5.34%, and the maximal prediction error is 2.09 minutes or 13.87%. Conclusion: We have developed a treatment delivery time prediction algorithm based on the analysis of previous patients’ treatment delivery records. The accuracy of our prediction is sufficient for guiding and arranging patient treatment appointments on a daily basis. The predicted delivery time could also be used as an indicator to assess the

  11. A clinical diagnostic model for predicting influenza among young adult military personnel with febrile respiratory illness in Singapore.

    Directory of Open Access Journals (Sweden)

    Vernon J Lee

    Full Text Available INTRODUCTION: Influenza infections present with wide-ranging clinical features. We aim to compare the differences in presentation between influenza and non-influenza cases among those with febrile respiratory illness (FRI to determine predictors of influenza infection. METHODS: Personnel with FRI (defined as fever ≥ 37.5 °C, with cough or sore throat were recruited from the sentinel surveillance system in the Singapore military. Nasal washes were collected, and tested using the Resplex II and additional PCR assays for etiological determination. Interviewer-administered questionnaires collected information on patient demographics and clinical features. Univariate comparison of the various parameters was conducted, with statistically significant parameters entered into a multivariate logistic regression model. The final multivariate model for influenza versus non-influenza cases was used to build a predictive probability clinical diagnostic model. RESULTS: 821 out of 2858 subjects recruited from 11 May 2009 to 25 Jun 2010 had influenza, of which 434 (52.9% had 2009 influenza A (H1N1, 58 (7.1% seasonal influenza A (H3N2 and 269 (32.8% influenza B. Influenza-positive cases were significantly more likely to present with running nose, chills and rigors, ocular symptoms and higher temperature, and less likely with sore throat, photophobia, injected pharynx, and nausea/vomiting. Our clinical diagnostic model had a sensitivity of 65% (95% CI: 58%, 72%, specificity of 69% (95% CI: 62%, 75%, and overall accuracy of 68% (95% CI: 64%, 71%, performing significantly better than conventional influenza-like illness (ILI criteria. CONCLUSIONS: Use of a clinical diagnostic model may help predict influenza better than the conventional ILI definition among young adults with FRI.

  12. Admission to intensive care can be reliably predicted using only clinical judgment

    DEFF Research Database (Denmark)

    Brabrand, M.

    2015-01-01

    staffwere able to identify patients in need of critical care using only clinical judgment and to compare this with the National Early Warning Score (NEWS). Methods This was a prospective cohort study of all adult patients with a first-time admission to a medical admission unit at a 450-bed regional teaching......Introduction Not all patients in need of critical care arrive in clinical distress and some deteriorate after arrival. Identifying these patients early in their clinical course could potentially improve outcome. The present study was performed with the aim of assessing whether nursing and physician...... hospital over a 3-month period in 2010. All subspecialties of internal medicine are present as well as a level 2 ICU. Upon first contact with the patient after arrival, nursing staffand physicians were asked to report their estimation of the probability of ICU admission (0 to 100%). Survival status...

  13. Assessment of dual tasking has no clinical value for fall prediction in Parkinson's disease

    NARCIS (Netherlands)

    Smulders, K.; Esselink, R.A.J.; Weiss, A.; Kessels, R.P.C.; Geurts, A.C.H.; Bloem, B.R.

    2012-01-01

    The objective of this study is to investigate the value of dual-task performance for the prediction of falls inpatients with Parkinson's disease (PD). Two hundred sixty three patients with PD (H&Y 1-3, 65.2 +/- 7.9 years)walked two times along a 10-m trajectory, both under single-task and dual-task

  14. Predictive Validity of the MMPI-2 Clinical, PSY-5, and RC Scales for Therapy Disruptive Behavior

    NARCIS (Netherlands)

    Scholte, W.; Tiemens, B.G.; Verheul, R.; Meerman, A.; Egger, J.; Hutschemaekers, G.

    2012-01-01

    Background. Impulsive acts, parasuicidal behavior, and other therapy disruptive incidents occur frequently in the treatment of patients with personality disorders and increase the risk that patients will drop out of treatment. Objective. This study examined the predictive validity of the Minnesota M

  15. CONFIRMATION OF CLINICAL-DIAGNOSIS IN REQUESTS FOR PRENATAL PREDICTION OF SMA TYPE-I

    NARCIS (Netherlands)

    COBBEN, JM; DEVISSER, M; SCHEFFER, H; OSINGA, J; VANDERSTEEGE, G; BUYS, CHCM; VANOMMEN, GJ; TENKATE, LP

    1993-01-01

    The recent discovery of a major SMA-locus in the chromosomal region 5q makes it possible to carry out prenatal DNA studies in families in which a child with SMA type I has been born. Since direct mutation analysis is not yet possible, the reliability of prenatal prediction of SMA type I usually depe

  16. Quantifying risk of early relapse in patients with first demyelinating events: Prediction in clinical practice

    DEFF Research Database (Denmark)

    Spelman, Tim; Meyniel, Claire; Rojas, Juan Ignacio

    2016-01-01

    BACKGROUND: Characteristics at clinically isolated syndrome (CIS) examination assist in identification of patient at highest risk of early second attack and could benefit the most from early disease-modifying drugs (DMDs). OBJECTIVE: To examine determinants of second attack and validate a prognos......BACKGROUND: Characteristics at clinically isolated syndrome (CIS) examination assist in identification of patient at highest risk of early second attack and could benefit the most from early disease-modifying drugs (DMDs). OBJECTIVE: To examine determinants of second attack and validate...

  17. Clinical and biomarker changes in premanifest Huntington disease show trial feasibility: a decade of the PREDICT-HD study

    Directory of Open Access Journals (Sweden)

    Jane S Paulsen

    2014-04-01

    Full Text Available There is growing consensus that intervention and treatment of Huntington disease (HD should occur at the earliest stage possible. Various early-intervention methods for this fatal neurodegenerative disease have been identified, but preventive clinical trials for HD are limited by a lack of knowledge of the natural history of the disease and a dearth of appropriate outcome measures. Objectives of the current study are to document the natural history of premanifest HD progression in the largest cohort ever studied and to develop a battery of imaging and clinical markers of premanifest HD progression that can be used as outcome measures in preventive clinical trials. PREDICT-HD is a 32-site, international, observational study of premanifest HD, with annual examination of 1013 participants with premanifest HD and 301 gene-expansion negative controls between 2001 and 2012. Findings document 39 variables representing imaging, motor, cognitive, functional, and psychiatric domains, showing different rates of decline between premanifest Huntington disease and controls. Required sample size and models of premanifest HD are presented to inform future design of clinical and preclinical research. Preventive clinical trials in premanifest HD with participants who have a medium or high probability of motor onset are calculated to be as resource-effective as those conducted in diagnosed HD and could interrupt disease seven to twelve years earlier. Methods and measures for preventive clinical trials in premanifest HD more than a dozen years from motor onset are also feasible. These findings represent the most thorough documentation of a clinical battery for experimental therapeutics in stages of premanifest HD, the time period for which effective intervention may provide the most positive possible outcome for patients and their families affected by this devastating disease.

  18. Identification and individualized prediction of clinical phenotypes in bipolar disorders using neurocognitive data, neuroimaging scans and machine learning.

    Science.gov (United States)

    Wu, Mon-Ju; Mwangi, Benson; Bauer, Isabelle E; Passos, Ives C; Sanches, Marsal; Zunta-Soares, Giovana B; Meyer, Thomas D; Hasan, Khader M; Soares, Jair C

    2017-01-15

    Diagnosis, clinical management and research of psychiatric disorders remain subjective - largely guided by historically developed categories which may not effectively capture underlying pathophysiological mechanisms of dysfunction. Here, we report a novel approach of identifying and validating distinct and biologically meaningful clinical phenotypes of bipolar disorders using both unsupervised and supervised machine learning techniques. First, neurocognitive data were analyzed using an unsupervised machine learning approach and two distinct clinical phenotypes identified namely; phenotype I and phenotype II. Second, diffusion weighted imaging scans were pre-processed using the tract-based spatial statistics (TBSS) method and 'skeletonized' white matter fractional anisotropy (FA) and mean diffusivity (MD) maps extracted. The 'skeletonized' white matter FA and MD maps were entered into the Elastic Net machine learning algorithm to distinguish individual subjects' phenotypic labels (e.g. phenotype I vs. phenotype II). This calculation was performed to ascertain whether the identified clinical phenotypes were biologically distinct. Original neurocognitive measurements distinguished individual subjects' phenotypic labels with 94% accuracy (sensitivity=92%, specificity=97%). TBSS derived FA and MD measurements predicted individual subjects' phenotypic labels with 76% and 65% accuracy respectively. In addition, individual subjects belonging to phenotypes I and II were distinguished from healthy controls with 57% and 92% accuracy respectively. Neurocognitive task variables identified as most relevant in distinguishing phenotypic labels included; Affective Go/No-Go (AGN), Cambridge Gambling Task (CGT) coupled with inferior fronto-occipital fasciculus and callosal white matter pathways. These results suggest that there may exist two biologically distinct clinical phenotypes in bipolar disorders which can be identified from healthy controls with high accuracy and at an

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

    Science.gov (United States)

    Stacey, D Graham; Whittaker, John M

    2005-02-01

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

  20. Do medical students’ scores using different assessment instruments predict their scores in clinical reasoning using a computer-based simulation?

    Directory of Open Access Journals (Sweden)

    Fida M

    2015-02-01

    Full Text Available Mariam Fida,1 Salah Eldin Kassab2 1Department of Molecular Medicine, College of Medicine and Medical Sciences, Arabian Gulf University, Manama, Bahrain; 2Department of Medical Education, Faculty of Medicine, Suez Canal University, Ismailia, Egypt Purpose: The development of clinical problem-solving skills evolves over time and requires structured training and background knowledge. Computer-based case simulations (CCS have been used for teaching and assessment of clinical reasoning skills. However, previous studies examining the psychometric properties of CCS as an assessment tool have been controversial. Furthermore, studies reporting the integration of CCS into problem-based medical curricula have been limited. Methods: This study examined the psychometric properties of using CCS software (DxR Clinician for assessment of medical students (n=130 studying in a problem-based, integrated multisystem module (Unit IX during the academic year 2011–2012. Internal consistency reliability of CCS scores was calculated using Cronbach's alpha statistics. The relationships between students' scores in CCS components (clinical reasoning, diagnostic performance, and patient management and their scores in other examination tools at the end of the unit including multiple-choice questions, short-answer questions, objective structured clinical examination (OSCE, and real patient encounters were analyzed using stepwise hierarchical linear regression. Results: Internal consistency reliability of CCS scores was high (α=0.862. Inter-item correlations between students' scores in different CCS components and their scores in CCS and other test items were statistically significant. Regression analysis indicated that OSCE scores predicted 32.7% and 35.1% of the variance in clinical reasoning and patient management scores, respectively (P<0.01. Multiple-choice question scores, however, predicted only 15.4% of the variance in diagnostic performance scores (P<0.01, while

  1. Development of predictive models for estimating warfarin maintenance dose based on genetic and clinical factors.

    Science.gov (United States)

    Yang, Lu; Linder, Mark W

    2013-01-01

    In this chapter, we use calculation of estimated warfarin maintenance dosage as an example to illustrate how to develop a multiple linear regression model to quantify the relationship between several independent variables (e.g., patients' genotype information) and a dependent variable (e.g., measureable clinical outcome).

  2. Undergraduate Nurse Variables that Predict Academic Achievement and Clinical Competence in Nursing

    Science.gov (United States)

    Blackman, Ian; Hall, Margaret; Darmawan, I Gusti Ngurah.

    2007-01-01

    A hypothetical model was formulated to explore factors that influenced academic and clinical achievement for undergraduate nursing students. Sixteen latent variables were considered including the students' background, gender, type of first language, age, their previous successes with their undergraduate nursing studies and status given for…

  3. Factors Predicting Oncology Care Providers' Behavioral Intention to Adopt Clinical Decision Support Systems

    Science.gov (United States)

    Wolfenden, Andrew

    2012-01-01

    The purpose of this quantitative correlation study was to examine the predictors of user behavioral intention on the decision of oncology care providers to adopt or reject the clinical decision support system. The Unified Theory of Acceptance and Use of Technology (UTAUT) formed the foundation of the research model and survey instrument. The…

  4. Cultural Responsivity in Clinical Psychology Graduate Students: A Developmental Approach to the Prediction of Learning

    Science.gov (United States)

    Berrin, Sebastian Everett

    2010-01-01

    This study used a mixed-method approach to examine students' experiences in multicultural training and their opinions about various aspects of their course(s). A developmental model of learning was employed to analyze results. More specifically, this study explored the relationship between clinical psychology doctoral students' self-reported…

  5. Early prediction of a benign course of multiple sclerosis on clinical grounds : a systematic review

    NARCIS (Netherlands)

    Ramsaransing, G; Maurits, N; Zwanikken, C; De Keyser, J

    2001-01-01

    Background. There is growing consensus that neurologists should consider disease-modifying therapies early in multiple sclerosis (MS). However there is a subgroup with a natural benign course, in which treatment could be postponed. We sought to determine the frequency of benign MS and early clinical

  6. An Endotoxin Tolerance Signature Predicts Sepsis and Organ Dysfunction at Initial Clinical Presentation

    Directory of Open Access Journals (Sweden)

    Olga M. Pena

    2014-11-01

    Interpretation: Our data support an updated model of sepsis pathogenesis in which endotoxin tolerance-mediated immune dysfunction (cellular reprogramming is present throughout the clinical course of disease and related to disease severity. Thus endotoxin tolerance might offer new insights guiding the development of new therapies and diagnostics for early sepsis.

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

    Science.gov (United States)

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

    2016-07-01

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

  8. Relationship-Specific Condom Attitudes Predict Condom Use among STD Clinic Patients with both Primary and Non-Primary Partners

    Science.gov (United States)

    Senn, Theresa E.; Scott-Sheldon, Lori A. J.; Carey, Michael P.

    2014-01-01

    Although condom use differs by partner type (i.e., primary vs. non-primary partner), attitudes towards condom use are typically measured without consideration of partner type. This study investigated the predictive utility of condom attitudes measured separately by partner type. Participants were 270 patients (37% women, 72% Black) recruited from a publicly-funded STD clinic who reported having both primary and non-primary partners. They completed a computerized survey assessing relationship-specific condom attitudes by partner type, condom attitudes related to pleasure and respect, and condom use with primary and non-primary partners. Participants reported more positive relationship-specific condom attitudes with a non-primary vs. primary partner. When considering pleasure-related, respect-related, and relationship-specific condom attitudes simultaneously, only relationship-specific condom attitudes predicted unprotected sex, with both primary and non-primary partners. In general, pleasure and respect-related condom attitudes did not predict unprotected sex; however, pleasure-related attitudes predicted unprotected sex with a non-primary partner for men. Future research should assess relationship-specific condom attitudes. Sexual risk reduction interventions that address interpersonal consequences of condom use in both primary and non-primary relationships should be a priority. PMID:24567031

  9. Clinical Application of AIMS65 Scores to Predict Outcomes in Patients with Upper Gastrointestinal Hemorrhage

    Science.gov (United States)

    Sharma, Manik; John, Anil K; Al-Ejji, Khalid Mohsin; Wani, Hamidulla; Sultan, Khaleel; Al-Mohannadi, Muneera; Yakoob, Rafie; Derbala, Moutaz; Al-Dweik, Nazeeh; Butt, Muhammed Tariq; Al-Kaabi, Saad Rashid

    2015-01-01

    Background/Aims To evaluate the ability of the recently proposed albumin, international normalized ratio (INR), mental status, systolic blood pressure, age >65 years (AIMS65) score to predict mortality in patients with acute upper gastrointestinal bleeding (UGIB). Methods AIMS65 scores were calculated in 251 consecutive patients presenting with acute UGIB by allotting 1 point each for albumin level 1.5, alteration in mental status, systolic blood pressure ≤90 mm Hg, and age ≥65 years. Risk stratification was done during the initial 12 hours of hospital admission. Results Intensive care unit (ICU) admission, endoscopic therapy, or surgery were required in 51 patients (20.3%), 64 (25.5%), and 12 (4.8%), respectively. The predictive accuracy of AIMS65 scores ≥2 was high for blood transfusion (area under the receiver operator characteristic curve [AUROC], 0.59), ICU admission (AUROC, 0.61), and mortality (AUROC, 0.74). The overall mortality was 10.3% (n=26), and was 3%, 7.8%, 20%, 36%, and 40% for AIMS65 scores of 0, 1, 2, 3, and 4, respectively; these values were significantly higher in those with scores ≥2 (30.9%) than in those with scores <2 (4.5%, p<0.001). Conclusions AIMS65 is a simple, accurate, non-endoscopic risk score that can be applied early (within 12 hours of hospital admission) in patients with acute UGIB. AIMS65 scores ≥2 predict high in-hospital mortality. PMID:26473120

  10. Prediction of new drug indications based on clinical data and network modularity.

    Science.gov (United States)

    Yu, Liang; Ma, Xiaoke; Zhang, Long; Zhang, Jing; Gao, Lin

    2016-09-28

    Drug repositioning is commonly done within the drug discovery process in order to adjust or expand the application line of an active molecule. Previous computational methods in this domain mainly focused on shared genes or correlations between genes to construct new drug-disease associations. We propose a method that can not only handle drugs or diseases with or without related genes but consider the network modularity. Our method firstly constructs a drug network and a disease network based on side effects and symptoms respectively. Because similar drugs imply similar diseases, we then cluster the two networks to identify drug and disease modules, and connect all possible drug-disease module pairs. Further, based on known drug-disease associations in CTD and using local connectivity of modules, we predict potential drug-disease associations. Our predictions are validated by testing their overlaps with drug indications reported in published literatures and CTD, and KEGG enrichment analysis are also made on their related genes. The experimental results demonstrate that our approach can complement the current computational approaches and its predictions can provide new clues for the candidate discovery of drug repositioning.

  11. Prediction of new drug indications based on clinical data and network modularity

    Science.gov (United States)

    Yu, Liang; Ma, Xiaoke; Zhang, Long; Zhang, Jing; Gao, Lin

    2016-01-01

    Drug repositioning is commonly done within the drug discovery process in order to adjust or expand the application line of an active molecule. Previous computational methods in this domain mainly focused on shared genes or correlations between genes to construct new drug-disease associations. We propose a method that can not only handle drugs or diseases with or without related genes but consider the network modularity. Our method firstly constructs a drug network and a disease network based on side effects and symptoms respectively. Because similar drugs imply similar diseases, we then cluster the two networks to identify drug and disease modules, and connect all possible drug-disease module pairs. Further, based on known drug-disease associations in CTD and using local connectivity of modules, we predict potential drug-disease associations. Our predictions are validated by testing their overlaps with drug indications reported in published literatures and CTD, and KEGG enrichment analysis are also made on their related genes. The experimental results demonstrate that our approach can complement the current computational approaches and its predictions can provide new clues for the candidate discovery of drug repositioning. PMID:27678071

  12. Applying psychological theories to evidence-based clinical practice: Identifying factors predictive of managing upper respiratory tract infections without antibiotics

    Directory of Open Access Journals (Sweden)

    Glidewell Elizabeth

    2007-08-01

    Full Text Available Abstract Background Psychological models can be used to understand and predict behaviour in a wide range of settings. However, they have not been consistently applied to health professional behaviours, and the contribution of differing theories is not clear. The aim of this study was to explore the usefulness of a range of psychological theories to predict health professional behaviour relating to management of upper respiratory tract infections (URTIs without antibiotics. Methods Psychological measures were collected by postal questionnaire survey from a random sample of general practitioners (GPs in Scotland. The outcome measures were clinical behaviour (using antibiotic prescription rates as a proxy indicator, behavioural simulation (scenario-based decisions to managing URTI with or without antibiotics and behavioural intention (general intention to managing URTI without antibiotics. Explanatory variables were the constructs within the following theories: Theory of Planned Behaviour (TPB, Social Cognitive Theory (SCT, Common Sense Self-Regulation Model (CS-SRM, Operant Learning Theory (OLT, Implementation Intention (II, Stage Model (SM, and knowledge (a non-theoretical construct. For each outcome measure, multiple regression analysis was used to examine the predictive value of each theoretical model individually. Following this 'theory level' analysis, a 'cross theory' analysis was conducted to investigate the combined predictive value of all significant individual constructs across theories. Results All theories were tested, but only significant results are presented. When predicting behaviour, at the theory level, OLT explained 6% of the variance and, in a cross theory analysis, OLT 'evidence of habitual behaviour' also explained 6%. When predicting behavioural simulation, at the theory level, the proportion of variance explained was: TPB, 31%; SCT, 26%; II, 6%; OLT, 24%. GPs who reported having already decided to change their management to

  13. Three-tiered risk stratification model to predict progression in Barrett's esophagus using epigenetic and clinical features.

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    Fumiaki Sato

    Full Text Available Barrett's esophagus predisposes to esophageal adenocarcinoma. However, the value of endoscopic surveillance in Barrett's esophagus has been debated because of the low incidence of esophageal adenocarcinoma in Barrett's esophagus. Moreover, high inter-observer and sampling-dependent variation in the histologic staging of dysplasia make clinical risk assessment problematic. In this study, we developed a 3-tiered risk stratification strategy, based on systematically selected epigenetic and clinical parameters, to improve Barrett's esophagus surveillance efficiency.We defined high-grade dysplasia as endpoint of progression, and Barrett's esophagus progressor patients as Barrett's esophagus patients with either no dysplasia or low-grade dysplasia who later developed high-grade dysplasia or esophageal adenocarcinoma. We analyzed 4 epigenetic and 3 clinical parameters in 118 Barrett's esophagus tissues obtained from 35 progressor and 27 non-progressor Barrett's esophagus patients from Baltimore Veterans Affairs Maryland Health Care Systems and Mayo Clinic. Based on 2-year and 4-year prediction models using linear discriminant analysis (area under the receiver-operator characteristic (ROC curve: 0.8386 and 0.7910, respectively, Barrett's esophagus specimens were stratified into high-risk (HR, intermediate-risk (IR, or low-risk (LR groups. This 3-tiered stratification method retained both the high specificity of the 2-year model and the high sensitivity of the 4-year model. Progression-free survivals differed significantly among the 3 risk groups, with p = 0.0022 (HR vs. IR and p<0.0001 (HR or IR vs. LR. Incremental value analyses demonstrated that the number of methylated genes contributed most influentially to prediction accuracy.This 3-tiered risk stratification strategy has the potential to exert a profound impact on Barrett's esophagus surveillance accuracy and efficiency.

  14. A novel model to combine clinical and pathway-based transcriptomic information for the prognosis prediction of breast cancer.

    Directory of Open Access Journals (Sweden)

    Sijia Huang

    2014-09-01

    Full Text Available Breast cancer is the most common malignancy in women worldwide. With the increasing awareness of heterogeneity in breast cancers, better prediction of breast cancer prognosis is much needed for more personalized treatment and disease management. Towards this goal, we have developed a novel computational model for breast cancer prognosis by combining the Pathway Deregulation Score (PDS based pathifier algorithm, Cox regression and L1-LASSO penalization method. We trained the model on a set of 236 patients with gene expression data and clinical information, and validated the performance on three diversified testing data sets of 606 patients. To evaluate the performance of the model, we conducted survival analysis of the dichotomized groups, and compared the areas under the curve based on the binary classification. The resulting prognosis genomic model is composed of fifteen pathways (e.g., P53 pathway that had previously reported cancer relevance, and it successfully differentiated relapse in the training set (log rank p-value = 6.25e-12 and three testing data sets (log rank p-value < 0.0005. Moreover, the pathway-based genomic models consistently performed better than gene-based models on all four data sets. We also find strong evidence that combining genomic information with clinical information improved the p-values of prognosis prediction by at least three orders of magnitude in comparison to using either genomic or clinical information alone. In summary, we propose a novel prognosis model that harnesses the pathway-based dysregulation as well as valuable clinical information. The selected pathways in our prognosis model are promising targets for therapeutic intervention.

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

    Directory of Open Access Journals (Sweden)

    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.

  16. Translating biology into clinic: new insights on prognostic and predictive biomarkers for urothelial bladder carcinoma

    OpenAIRE

    2013-01-01

    Tese de doutoramento em Ciências da Saúde Urothelial bladder carcinoma (UBC) represents a significant health problem, as a consequence of its heterogeneous natural history and clinical behavior. Most morbidity and mortality associated with UBC is caused by the muscle-invasive (MI) form of the disease, which represents about 20-30% of all newly diagnosed cases. Moreover, an important proportion of high risk non-muscle invasive (NMI) tumours relapse after transurethral resection and progress...

  17. Predictive value of combined clinically diagnosed bruxism and occlusal features for TMJ pain.

    Science.gov (United States)

    Manfredini, Daniele; Peretta, Redento; Guarda-Nardini, Luca; Ferronato, Giuseppe

    2010-04-01

    Several works showed a decreased role for occlusion in the etiology of temporomandibular disorders (TMD). Nonetheless, it may be hypothesized that occlusion acts as a modulator through which bruxism activities may cause damage to the stomatognathic structures. To test this hypothesis, a logistic regression model was created with the inclusion of clinically diagnosed bruxism and eight occlusal features as potential predictors for temporomandibular joint (TMJ) pain in a sample of 276 consecutive TMD patients. The final logit showed that the percentage of the total log likelihood for TMJ pain explained by the significant factors was small and amounted to 13.2%, with unacceptable levels of sensitivity (16.4%). The parameters overbite > or = 4 mm combined with clinically diagnosed bruxism [OR (odds ratio) 4.62], overjet > or = 5 mm (OR 2.83), and asymmetrical molar relationship combined with clinically diagnosed bruxism (OR 2.77) were those with the highest odds for disease, even though none of those values was significant with respect to confidence intervals. Thus, the hypothesis under evaluation has to be rejected. It is possible that future studies with a higher discriminatory power for the different bruxism activities might be indicated to get deeper into the analysis of the potential mechanisms through which occlusion may play a role, even if small, in the etiology of the different TMD.

  18. Endomysial antibodies predict celiac disease irrespective of the titers or clinical presentation

    Institute of Scientific and Technical Information of China (English)

    Kalle Kurppa; Markku M(a)ki; Katri Kaukinen; Tiia R(a)s(a)nen; Pekka Collin; Sari Iltanen; Heini Huhtala; Merja Ashorn; P(a)ivi Saavalainen; Katri Haimila; Jukka Partanen

    2012-01-01

    AIM:To investigate the association between serum antibody levels and a subsequent celiac disease diagnosis in a large series of children and adults.METHODS:Besides subjects with classical gastrointestinal presentation of celiac disease,the study cohort included a substantial number of individuals with extraintestinal symptoms and those found by screening in at-risk groups.Altogether 405 patients underwent clinical,serological and histological evaluations.After collection of data,the antibody values were further graded as low [endomysial (EmA) 1:5-200,transglutaminase 2 antibodies (TG2-ab) 5.0-30.0 U/L] and high (EmA 1:≥ 500,TG2-ab ≥ 30.0 U/L),and the serological results were compared with the small intestinal mucosal histology and clinical presentation.RESULTS:In total,79% of the subjects with low and 94% of those with high serum EmA titers showed small-bowel mucosal villous atrophy.Furthermore,96% of the 47 EmA positive subjects who had normal mucosal villi and remained on follow-up either subsequently developed mucosal atrophy while on a glutencontaining diet,or responded positively to a glutenfree diet.CONCLUSION:Irrespective of the initial serum titers or clinical presentation,EmA positivity as such is a very strong predictor of a subsequent celiac disease diagnosis.

  19. Are clinical features able to predict Helicobacter pylori gastritis patterns? Evidence from tertiary centers.

    Science.gov (United States)

    Carabotti, Marilia; Lahner, Edith; Porowska, Barbara; Colacci, Enzo; Trentino, Paolo; Annibale, Bruno; Severi, Carola

    2014-12-01

    Outcome of Helicobacter pylori infection is different according to gastritis extension (i.e. antrum-restricted gastritis or pangastritis). The aim of this study is to evaluate whether different gastritis patterns are associated with specific gastrointestinal symptoms or clinical signs that could be suggestive of the topography of gastritis. 236 consecutive symptomatic outpatients were recruited in two tertiary centers. They filled in a validated and self-administered Rome III modular symptomatic questionnaire, and underwent gastroscopy with histological sampling. 154 patients with Helicobacter pylori infection were included. Clinical presentation did not differ between antrum-restricted gastritis and pangastritis, gastro-esophageal reflux disease being present in 48.2 and 54.1 % of patients and dyspepsia in 51.8 and 45.9 %, respectively. However, pangastritis statistically differed from antrum-restricted gastritis in that the presence of clinical signs (p gastritis pattern whereas their association with signs, accurately detected, is indicative for the presence of pangastritis.

  20. Applying psychological theories to evidence-based clinical practice: identifying factors predictive of placing preventive fissure sealants

    Directory of Open Access Journals (Sweden)

    Maclennan Graeme

    2010-04-01

    Full Text Available Abstract Background Psychological models are used to understand and predict behaviour in a wide range of settings, but have not been consistently applied to health professional behaviours, and the contribution of differing theories is not clear. This study explored the usefulness of a range of models to predict an evidence-based behaviour -- the placing of fissure sealants. Methods Measures were collected by postal questionnaire from a random sample of general dental practitioners (GDPs in Scotland. Outcomes were behavioural simulation (scenario decision-making, and behavioural intention. Predictor variables were from the Theory of Planned Behaviour (TPB, Social Cognitive Theory (SCT, Common Sense Self-regulation Model (CS-SRM, Operant Learning Theory (OLT, Implementation Intention (II, Stage Model, and knowledge (a non-theoretical construct. Multiple regression analysis was used to examine the predictive value of each theoretical model individually. Significant constructs from all theories were then entered into a 'cross theory' stepwise regression analysis to investigate their combined predictive value Results Behavioural simulation - theory level variance explained was: TPB 31%; SCT 29%; II 7%; OLT 30%. Neither CS-SRM nor stage explained significant variance. In the cross theory analysis, habit (OLT, timeline acute (CS-SRM, and outcome expectancy (SCT entered the equation, together explaining 38% of the variance. Behavioural intention - theory level variance explained was: TPB 30%; SCT 24%; OLT 58%, CS-SRM 27%. GDPs in the action stage had significantly higher intention to place fissure sealants. In the cross theory analysis, habit (OLT and attitude (TPB entered the equation, together explaining 68% of the variance in intention. Summary The study provides evidence that psychological models can be useful in understanding and predicting clinical behaviour. Taking a theory-based approach enables the creation of a replicable methodology for

  1. A systematic review of models to predict recruitment to multicentre clinical trials

    Directory of Open Access Journals (Sweden)

    Cook Andrew

    2010-07-01

    Full Text Available Abstract Background Less than one third of publicly funded trials managed to recruit according to their original plan often resulting in request for additional funding and/or time extensions. The aim was to identify models which might be useful to a major public funder of randomised controlled trials when estimating likely time requirements for recruiting trial participants. The requirements of a useful model were identified as usability, based on experience, able to reflect time trends, accounting for centre recruitment and contribution to a commissioning decision. Methods A systematic review of English language articles using MEDLINE and EMBASE. Search terms included: randomised controlled trial, patient, accrual, predict, enrol, models, statistical; Bayes Theorem; Decision Theory; Monte Carlo Method and Poisson. Only studies discussing prediction of recruitment to trials using a modelling approach were included. Information was extracted from articles by one author, and checked by a second, using a pre-defined form. Results Out of 326 identified abstracts, only 8 met all the inclusion criteria. Of these 8 studies examined, there are five major classes of model discussed: the unconditional model, the conditional model, the Poisson model, Bayesian models and Monte Carlo simulation of Markov models. None of these meet all the pre-identified needs of the funder. Conclusions To meet the needs of a number of research programmes, a new model is required as a matter of importance. Any model chosen should be validated against both retrospective and prospective data, to ensure the predictions it gives are superior to those currently used.

  2. Protein phosphatase methylesterase-1 (PME-1) expression predicts a favorable clinical outcome in colorectal cancer.

    Science.gov (United States)

    Kaur, Amanpreet; Elzagheid, Adam; Birkman, Eva-Maria; Avoranta, Tuulia; Kytölä, Ville; Korkeila, Eija; Syrjänen, Kari; Westermarck, Jukka; Sundström, Jari

    2015-12-01

    Colorectal cancer (CRC) accounts for high mortality. So far, there is lack of markers capable of predicting which patients are at risk of aggressive course of the disease. Protein phosphatase-2A (PP2A) inhibitor proteins have recently gained interest as markers of more aggressive disease in certain cancers. Here, we report the role of PP2A inhibitor PME-1 in CRC. PME-1 expression was assessed from a rectal cancer patient cohort by immunohistochemistry, and correlations were performed for various clinicopathological variables and patient survival. Rectal cancer patients with higher cytoplasmic PME-1 protein expression (above median) had less recurrences (P = 0.003, n = 195) and better disease-free survival (DFS) than the patients with low cytoplasmic PME-1 protein expression (below median). Analysis of PPME-1 mRNA expression from TCGA dataset of colon and rectal adenocarcinoma (COADREAD) patient cohort confirmed high PPME1 expression as an independent protective factor predicting favorable overall survival (OS) (P = 0.005, n = 396) compared to patients with low PPME1 expression. CRC cell lines were used to study the effect of PME-1 knockdown by siRNA on cell survival. Contrary to other cancer types, PME-1 inhibition in CRC cell lines did not reduce the viability of cells or the expression of active phosphorylated AKT and ERK proteins. In conclusion, PME-1 expression predicts for a favorable outcome of CRC patients. The unexpected role of PME-1 in CRC in contrast with the oncogenic role of PP2A inhibitor proteins in other malignancies warrants further studies of cancer-specific function for each of these proteins.

  3. Predictive factors for familiality in a Danish clinical cohort of children with Tourette syndrome

    DEFF Research Database (Denmark)

    Debes, Nanette M M M; Hjalgrim, Helle; Skov, Liselotte

    2010-01-01

    Tourette syndrome (TS) is a chronic, neurobiological disease, characterized by the presence of motor and vocal tics and it is often accompanied by associated symptoms. The two best-known co-morbidities are Obsessive-Compulsive Disorder (OCD) and Attention Deficit Hyperactivity Disorder (ADHD......). The fact that TS aggregates strongly in families suggests that family members share either genetic and/or environmental risk factors contributing to TS. Numerous studies have been performed to examine the familiality in TS, but clear-cut factors to predict hereditability in TS have not been found yet. We...

  4. The impact of p53 in predicting clinical outcome of breast cancer patients with visceral metastasis

    OpenAIRE

    Yang, P.; Du, C.W.; Kwan, M; Liang, S. X.; Zhang, G.J.

    2013-01-01

    In the study, we analyzed role of p53 in predicting outcome in visceral metastasis breast cancer (VMBC) patients. 97 consecutive VMBC patients were studied. P53 positivity rate was 29.9%. In the p53-negative group, median disease free survival (DFS), and time from primary breast cancer diagnosis to death (OS1), time from metastases to death (OS2) were 25, 42.5, and 13.5 months, respectively. In the p53-positive group, they were 10, 22, and 8 months, respectively. Statistically significant dif...

  5. RGANN: An Efficient Algorithm to Extract Rules from ANNs

    CERN Document Server

    Kamruzzaman, S M

    2010-01-01

    This paper describes an efficient rule generation algorithm, called rule generation from artificial neural networks (RGANN) to generate symbolic rules from ANNs. Classification rules are sought in many areas from automatic knowledge acquisition to data mining and ANN rule extraction. This is because classification rules possess some attractive features. They are explicit, understandable and verifiable by domain experts, and can be modified, extended and passed on as modular knowledge. A standard three-layer feedforward ANN is the basis of the algorithm. A four-phase training algorithm is proposed for backpropagation learning. Comparing them to the symbolic rules generated by other methods supports explicitness of the generated rules. Generated rules are comparable with other methods in terms of number of rules, average number of conditions for a rule, and predictive accuracy. Extensive experimental studies on several benchmarks classification problems, including breast cancer, wine, season, golf-playing, and ...

  6. Clinical characteristics of hand, foot and mouth disease in Harbin and the prediction of severe cases

    Institute of Scientific and Technical Information of China (English)

    ZHOU Hong; GUO Shu-zhen; ZHOU Hao; ZHU Yue-feng; ZHANG Li-juan; ZHANG Wei

    2012-01-01

    Background Hand,foot and mouth disease (HFMD) is an emerging public health problem in China,not only threatening the health of children,but also causing tremendous loss and burden to both families and society.The aim of this study was to characterize the epidemiology and clinical features of HFMD,and to understand the key factors affecting HFMD in the Harbin region to provide scientific evidence for effective prevention and control strategies.@@Methods Epidemiological and clinical information from 2379 randomly chosen cases of HFMD treated at the Harbin Center for Disease Control and Prevention from May 2008 to November 2011 were analyzed.All cases were separated into common and severe HFMD,with key factors for severe HFMD analyzed using multivariable Logistic regression.@@Results Among the 2379 patients,1798 were common cases and 581 severe cases,14 of which resulted in death.Most cases were in children younger than 5 years.Morbidity peaked in July and was higher in the surrounding country and cities than in Harbin proper.Medical expenses were significantly higher for severe than for common cases (P <0.001).The primary clinical symptoms were fever and erythema; laboratory examination showed leucocytosis together with pneumonia,carditis,and abnormal electrocardiogram and electroencephalogram in severe cases.Multivariable Logistic regression analysis showed that the key factors for severe HFMD were age,morbidity location,morbidity area,fever duration,mouth mucosal symptoms,and abnormal serum levels of neutrophils (NEUT),hemoglobin and glucose (P <0.05).@@Conclusions To improve prognosis,reduce medical expense and prevent the development of severe cases,we should improve the epidemiological detection of HFMD to treat patients quickly.We should also closely monitor children with the EV71 virus,who present with continuous fever as well as abnormal laboratory results,from areas highly susceptible to HFMD attacks.

  7. Prediction of dengue disease severity among pediatric Thai patients using early clinical laboratory indicators.

    Directory of Open Access Journals (Sweden)

    James A Potts

    Full Text Available Dengue virus is endemic in tropical and sub-tropical resource-poor countries. Dengue illness can range from a nonspecific febrile illness to a severe disease, Dengue Shock Syndrome (DSS, in which patients develop circulatory failure. Earlier diagnosis of severe dengue illnesses would have a substantial impact on the allocation of health resources in endemic countries.We compared clinical laboratory findings collected within 72 hours of fever onset from a prospective cohort children presenting to one of two hospitals (one urban and one rural in Thailand. Classification and regression tree analysis was used to develop diagnostic algorithms using different categories of dengue disease severity to distinguish between patients at elevated risk of developing a severe dengue illness and those at low risk. A diagnostic algorithm using WBC count, percent monocytes, platelet count, and hematocrit achieved 97% sensitivity to identify patients who went on to develop DSS while correctly excluding 48% of non-severe cases. Addition of an indicator of severe plasma leakage to the WHO definition led to 99% sensitivity using WBC count, percent neutrophils, AST, platelet count, and age.This study identified two easily applicable diagnostic algorithms using early clinical indicators obtained within the first 72 hours of illness onset. The algorithms have high sensitivity to distinguish patients at elevated risk of developing severe dengue illness from patients at low risk, which included patients with mild dengue and other non-dengue febrile illnesses. Although these algorithms need to be validated in other populations, this study highlights the potential usefulness of specific clinical indicators early in illness.

  8. Can Preterm Labour Be Predicted in Low Risk Pregnancies? Role of Clinical, Sonographic, and Biochemical Markers

    Directory of Open Access Journals (Sweden)

    Reva Tripathi

    2014-01-01

    Full Text Available Background and Objectives. This is a prospective nested cohort study conducted over a period of 3 years. 2644 women were recruited, out of which final analysis was done for 1884 women. Methods. Cervicovaginal and blood samples were collected for all recruited women. Out of these, 137 women who delivered before 35 weeks were treated as cases and equal number of matched controls were chosen. Analysis of samples for serum G-CSF, AFP, ferritin, and cervicovaginal interleukin-6 and IGFBP-1 was done. Results. Poor orodental hygiene, which can be a social marker, was significantly more common in women who delivered preterm (P=0.008. Serum alkaline phosphatase and serum ferritin were found to be significantly associated with preterm deliveries. The 90th percentile value of these parameters was considered as cut-off as there is no specific cut-off. Conclusions. Our study did not prove usefulness of any predictive marker. Serum ferritin and alkaline phosphatase were found to have correlation but their values are affected in many conditions and need to be elucidated with caution. Larger studies are needed for predicting preterm labour in asymptomatic women.

  9. Clinical and psychosocial factors predicting health-related quality of life in hemodialysis patients.

    Science.gov (United States)

    Kang, Gun Woo; Lee, In Hee; Ahn, Ki Sung; Lee, Jonghun; Ji, Yunmi; Woo, Jungmin

    2015-07-01

    Many patients with end-stage renal disease have significant impairment in health-related quality of life (HRQoL). Most previous studies have focused on clinical factors; however, quality of life can also be affected by psychosocial factors. The aim of this study was to identify the possible predictors of HRQoL among clinical and psychosocial factors in hemodialysis (HD) patients. The study included 101 patients who were undergoing HD. Psychosocial factors were evaluated using the Hospital Anxiety and Depression Scale, Multidimensional Scale of Perceived Social Support, Montreal Cognitive Assessment, and Pittsburgh Sleep Quality Index. We also assessed laboratory and clinical factors, including albumin, Kt/V as a marker of dialysis adequacy, normalized protein catabolic rate, and duration of HD. The Euro Quality of Life Questionnaire 5-Dimensional Classification (EQ-5D) was used to evaluate HRQoL. The mean EQ-5D index score was 0.704 ± 0.199. The following variables showed a significant association with the EQ-5D index: age (P < 0.001), depression (P < 0.001), anxiety (P < 0.001), support from friends (P < 0.001), cognitive function (P < 0.001), duration of HD (P = 0.034), triglyceride (P = 0.031), total iron-binding capacity (P = 0.036), and phosphorus (P = 0.037). Multiple regression analysis showed that age (95% confidence interval [CI] -0.008 to -0.002), anxiety (95% CI -0.025 to -0.009), and support from friends (95% CI 0.004 to 0.018) were independent predictors of impaired HRQoL. This study explored determinants of impaired HRQoL in HD patients. We found that impaired HRQoL was independently associated with age, anxiety, and support from friends. We should consider psychosocial as well as clinical factors when evaluating ways to improve HRQoL in HD patients.

  10. Predicted levels of human radiation tolerance extrapolated from clinical studies of radiation effects

    Science.gov (United States)

    Lushbaugh, C. C.

    1972-01-01

    Results of clinical studies of radiation effects on man are used to evaluate space radiation hazards encountered during manned space travel. Considered are effects of photons as well as of mixed fission neutrons and gamma irradiations in establishing body radiosensitivity and tolerance levels. Upper and lower dose-response-time relations for acute radiation syndromes in patients indicate that man is more than sufficiently radioresistant to make the risks of an early radiation effect during one short space mission intangibly small in relation to the other nonradiation risks involved.

  11. A multi-centre phase IIa clinical study of predictive testing for preeclampsia

    DEFF Research Database (Denmark)

    Navaratnam, Kate; Alfirevic, Zarko; Baker, Philip N;

    2013-01-01

    5% of first time pregnancies are complicated by pre-eclampsia, the leading cause of maternal death in Europe. No clinically useful screening test exists; consequentially clinicians are unable to offer targeted surveillance or preventative strategies. IMPROvED Consortium members have pioneered...... a personalised medicine approach to identifying blood-borne biomarkers through recent technological advancements, involving mapping of the blood metabolome and proteome. The key objective is to develop a sensitive, specific, high-throughput and economically viable early pregnancy screening test for pre-eclampsia....

  12. Serum BAP as the clinically useful marker for predicting BMD reduction in diabetic hemodialysis patients with low PTH.

    Science.gov (United States)

    Ueda, Misako; Inaba, Masaaki; Okuno, Senji; Maeno, Yoshifumi; Ishimura, Eiji; Yamakawa, Tomoyuki; Nishizawa, Yoshiki

    2005-07-22

    With decrease of serum PTH in hemodialysis (HD) patients, other factors besides parathyroid hormone (PTH) become important in regulating bone metabolism. We investigated which serum bone metabolic marker is the best to predict the bone mineral density (BMD) reduction in HD patients with serum PTHBAP), intact osteocalcin (OC), and N-terminal propeptide of type I collagen (PINP), and the bone resorption markers, deoxypyridinoline (DPD), pyridinoline (PYD), and beta-crossLaps (beta-CTx) were measured in serum from 137 HD patients. BMD of all patients was measured twice, approximately 1.5 years before and 1.5 years after measurement of their markers of bone metabolism. In all 137 HD patients, serum BAP was the only marker significantly higher in those with BMD reduction than in those without. In 42 diabetes mellitus (DM) HD patients with serum PTHBAP was again the only marker to discriminate those with BMD reduction from those without. At serum PTHBAP retained tendency toward higher value. These findings suggest that serum BAP might be the most sensitive to identify small changes of bone metabolism in low bone turnover state. Retrospective study confirmed the usefulness of serum BAP in clinical practice by significantly higher values in those with bone loss at PTHBAP is a clinically useful bone formation marker to predict the BMD reduction in DM HD patients with low level of PTH.

  13. Visualisation of metastatic oesophageal and gastric cancer and prediction of clinical response to palliative chemotherapy using {sup 18}FDG PET

    Energy Technology Data Exchange (ETDEWEB)

    Lorenzen, S.; Peschel, C.; Lordick, F. [Dept. of Internal Medicine, Haematology/Medical Oncology, Technical Univ. Munich (Germany); Herrmann, K.; Wieder, H.; Schwaiger, M. [Dept. of Nuclear Medicine, Technical Univ. Munich (Germany); Weber, W.A.; Hennig, M. [Inst. for Medical Statistics and Epidemiology, Technical Univ. Munich (Germany); Ott, K. [Dept. of Surgery, Technical Univ. of Munich (Germany); Bredenkamp, R. [Munich Centre for Clinical Studies, Munich (Germany)

    2007-07-01

    Aim: This study assessed the value of {sup 18}F-deoxyglucose positron emission tomography (FDG-PET) for visualisation and early metabolic response assessment in metastatic gastro-oesophageal cancer. Patients, methods: Twenty-six patients who were treated for metastatic disease (20 adenocarcinomas, 6 squamous cell cancers) underwent FDG-PET before and two weeks after the onset of palliative chemotherapy with either oxaliplatin + 5-FU/LV or with docetaxel + capecitabine. PET results were validated according to clinical response based on RECIST criteria. Results: Twenty-four tumours (92%) could be visualised by FDG-PET and were also assessable by a second PET scan at 2 weeks. The 2 tumours that were not detectable by PET were both gastric cancers belonging to the non-intestinal subtype according to Lauren. Median time to progression and overall survival were not significantly different for metabolic responders and non-responders (6.3 vs 5.3 months and 14.1 vs 12.5 months, respectively). Conclusion: In this heterogeneous study population, FDG-PET had a limited accuracy in predicting clinical response. However, the metabolic response prediction was particularly good in the subgroup of patients with oesophageal squamous cell cancer. Therefore, FDG-PET and assessment of cancer therapy clearly merits further investigation in circumscribed patient populations with metastatic disease. (orig.)

  14. Predictive Modeling of Physician-Patient Dynamics That Influence Sleep Medication Prescriptions and Clinical Decision-Making

    Science.gov (United States)

    Beam, Andrew L.; Kartoun, Uri; Pai, Jennifer K.; Chatterjee, Arnaub K.; Fitzgerald, Timothy P.; Shaw, Stanley Y.; Kohane, Isaac S.

    2017-02-01

    Insomnia remains under-diagnosed and poorly treated despite its high economic and social costs. Though previous work has examined how patient characteristics affect sleep medication prescriptions, the role of physician characteristics that influence this clinical decision remains unclear. We sought to understand patient and physician factors that influence sleep medication prescribing patterns by analyzing Electronic Medical Records (EMRs) including the narrative clinical notes as well as codified data. Zolpidem and trazodone were the most widely prescribed initial sleep medication in a cohort of 1,105 patients. Some providers showed a historical preference for one medication, which was highly predictive of their future prescribing behavior. Using a predictive model (AUC = 0.77), physician preference largely determined which medication a patient received (OR = 3.13 p = 3 × 10‑37). In addition to the dominant effect of empirically determined physician preference, discussion of depression in a patient’s note was found to have a statistically significant association with receiving a prescription for trazodone (OR = 1.38, p = 0.04). EMR data can yield insights into physician prescribing behavior based on real-world physician-patient interactions.

  15. Positron emission tomography scan for predicting clinical outcome of patients with recurrent cervical carcinoma following radiation therapy

    Directory of Open Access Journals (Sweden)

    Daya Nand Sharma

    2012-01-01

    Materials and Methods: Twenty two patients of post irradiated recurrent cervical carcinoma (PIRCC were enrolled in this prospective study. 18-fluorodeoxyglucose (FDG PET imaging was performed in each patient before the salvage therapy. The maximum standardized uptake value (SUVmax and metabolic tumor volume (MTV were measured and correlated with cumulative progression free survival (PFS. Results: Median age of patients was 42 years. Majority of patients had stage III disease at the initial presentation and all 22 patients had received prior definitive RT. The median recurrence free period was 11 months. Salvage therapy consisted of surgical resection or re-irradiation depending upon the various clinical and radiological factors. Median SUVmax was 5.8 (range 1.8-50.6 and median MTV was 43 cm 3 (range 5.8-243. The cumulative PFS for all patients was 20% at 30 months. The one-year PFS was 28% for patients with SUVmax value of >5.8 versus 42% for those with SUVmax value of 43 cm 3 versus 45% for those with MTV value of <43 cm 3 (P value 0.8. Conclusion: Our preliminary experience has suggested that FDG uptake on PET scan can predict the clinical outcome of PIRCC patients. Further randomized studies may be conducted with large sample size and longer follow up to establish its definite predictive value.

  16. Predictive Modeling of Physician-Patient Dynamics That Influence Sleep Medication Prescriptions and Clinical Decision-Making

    Science.gov (United States)

    Beam, Andrew L.; Kartoun, Uri; Pai, Jennifer K.; Chatterjee, Arnaub K.; Fitzgerald, Timothy P.; Shaw, Stanley Y.; Kohane, Isaac S.

    2017-01-01

    Insomnia remains under-diagnosed and poorly treated despite its high economic and social costs. Though previous work has examined how patient characteristics affect sleep medication prescriptions, the role of physician characteristics that influence this clinical decision remains unclear. We sought to understand patient and physician factors that influence sleep medication prescribing patterns by analyzing Electronic Medical Records (EMRs) including the narrative clinical notes as well as codified data. Zolpidem and trazodone were the most widely prescribed initial sleep medication in a cohort of 1,105 patients. Some providers showed a historical preference for one medication, which was highly predictive of their future prescribing behavior. Using a predictive model (AUC = 0.77), physician preference largely determined which medication a patient received (OR = 3.13; p = 3 × 10−37). In addition to the dominant effect of empirically determined physician preference, discussion of depression in a patient’s note was found to have a statistically significant association with receiving a prescription for trazodone (OR = 1.38, p = 0.04). EMR data can yield insights into physician prescribing behavior based on real-world physician-patient interactions. PMID:28181568

  17. Predicting the Pathogenic Potential of BRCA1 and BRCA2 Gene Variants Identified in Clinical Genetic Testing

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    Clare Brookes

    2015-05-01

    Full Text Available Objectives: Missense variants are very commonly detected when screening for mutations in the BRCA1 and BRCA2 genes. Pathogenic mutations in the BRCA1 and BRCA2 genes lead to an increased risk of developing breast, ovarian, prostate and/or pancreatic cancer. This study aimed to assess the predictive capability of in silico programmes and mutation databases in assisting diagnostic laboratories to determine the pathogenicity of sequence-detectable mutations. Methods: Between July 2011 and April 2013, an analysis was undertaken of 13 missense BRCA gene variants that had been detected in patients referred to the Genetic Health Services New Zealand (Northern Hub for BRCA gene analysis. The analysis involved the use of 13 in silico protein prediction programmes, two in silico transcript analysis programmes and the examination of three BRCA gene databases. Results: In most of the variants, the analysis showed different in silico interpretations. This illustrates the interpretation challenges faced by diagnostic laboratories. Conclusion: Unfortunately, when using online mutation databases and carrying out in silico analyses, there is significant discordance in the classification of some missense variants in the BRCA genes. This discordance leads to complexities in interpreting and reporting these variants in a clinical context. The authors have developed a simple procedure for analysing variants; however, those of unknown significance largely remain unknown. As a consequence, the clinical value of some reports may be negligible.

  18. International Study to Predict Optimized Treatment for Depression (iSPOT-D, a randomized clinical trial: rationale and protocol

    Directory of Open Access Journals (Sweden)

    Cooper Nicholas J

    2011-01-01

    Full Text Available Abstract Background Clinically useful treatment moderators of Major Depressive Disorder (MDD have not yet been identified, though some baseline predictors of treatment outcome have been proposed. The aim of iSPOT-D is to identify pretreatment measures that predict or moderate MDD treatment response or remission to escitalopram, sertraline or venlafaxine; and develop a model that incorporates multiple predictors and moderators. Methods/Design The International Study to Predict Optimized Treatment - in Depression (iSPOT-D is a multi-centre, international, randomized, prospective, open-label trial. It is enrolling 2016 MDD outpatients (ages 18-65 from primary or specialty care practices (672 per treatment arm; 672 age-, sex- and education-matched healthy controls. Study-eligible patients are antidepressant medication (ADM naïve or willing to undergo a one-week wash-out of any non-protocol ADM, and cannot have had an inadequate response to protocol ADM. Baseline assessments include symptoms; distress; daily function; cognitive performance; electroencephalogram and event-related potentials; heart rate and genetic measures. A subset of these baseline assessments are repeated after eight weeks of treatment. Outcomes include the 17-item Hamilton Rating Scale for Depression (primary and self-reported depressive symptoms, social functioning, quality of life, emotional regulation, and side-effect burden (secondary. Participants may then enter a naturalistic telephone follow-up at weeks 12, 16, 24 and 52. The first half of the sample will be used to identify potential predictors and moderators, and the second half to replicate and confirm. Discussion First enrolment was in December 2008, and is ongoing. iSPOT-D evaluates clinical and biological predictors of treatment response in the largest known sample of MDD collected worldwide. Trial registration International Study to Predict Optimised Treatment - in Depression (iSPOT-D ClinicalTrials.gov Identifier

  19. Gasdermin B expression predicts poor clinical outcome in HER2-positive breast cancer

    Science.gov (United States)

    Hergueta-Redondo, Marta; Sarrio, David; Molina-Crespo, Ángela; Vicario, Rocío; Bernadó-Morales, Cristina; Martínez, Lidia; Rojo-Sebastián, Alejandro; Serra-Musach, Jordi; Mota, Alba; Martínez-Ramírez, Ángel; Castilla, Maria Ángeles; González-Martin, Antonio; Pernas, Sonia; Cano, Amparo; Cortes, Javier; Nuciforo, Paolo G.; Peg, Vicente; Palacios, José; Pujana, Miguel Ángel; Arribas, Joaquín; Moreno-Bueno, Gema

    2016-01-01

    Around, 30–40% of HER2-positive breast cancers do not show substantial clinical benefit from the targeted therapy and, thus, the mechanisms underlying resistance remain partially unknown. Interestingly, ERBB2 is frequently co-amplified and co-expressed with neighbour genes that may play a relevant role in this cancer subtype. Here, using an in silico analysis of data from 2,096 breast tumours, we reveal a significant correlation between Gasdermin B (GSDMB) gene (located 175 kilo bases distal from ERBB2) expression and the pathological and clinical parameters of poor prognosis in HER2-positive breast cancer. Next, the analysis of three independent cohorts (totalizing 286 tumours) showed that approximately 65% of the HER2-positive cases have GSDMB gene amplification and protein over-expression. Moreover, GSDMB expression was also linked to poor therapeutic responses in terms of lower relapse free survival and pathologic complete response as well as positive lymph node status and the development of distant metastasis under neoadjuvant and adjuvant treatment settings, respectively. Importantly, GSDMB expression promotes survival to trastuzumab in different HER2-positive breast carcinoma cells, and is associated with trastuzumab resistance phenotype in vivo in Patient Derived Xenografts. In summary, our data identifies the ERBB2 co-amplified and co-expressed gene GSDMB as a critical determinant of poor prognosis and therapeutic response in HER2-positive breast cancer. PMID:27462779

  20. Highly accurate chemical formula prediction tool utilizing high-resolution mass spectra, MS/MS fragmentation, heuristic rules, and isotope pattern matching.

    Science.gov (United States)

    Pluskal, Tomáš; Uehara, Taisuke; Yanagida, Mitsuhiro

    2012-05-15

    Mass spectrometry is commonly applied to qualitatively and quantitatively profile small molecules, such as peptides, metabolites, or lipids. Modern mass spectrometers provide accurate measurements of mass-to-charge ratios of ions, with errors as low as 1 ppm. Even such high mass accuracy, however, is not sufficient to determine the unique chemical formula of each ion, and additional algorithms are necessary. Here we present a universal software tool for predicting chemical formulas from high-resolution mass spectrometry data, developed within the MZmine 2 framework. The tool is based on the use of a combination of heuristic techniques, including MS/MS fragmentation analysis and isotope pattern matching. The performance of the tool was evaluated using a real metabolomic data set obtained with the Orbitrap MS detector. The true formula was correctly determined as the highest-ranking candidate for 79% of the tested compounds. The novel isotope pattern-scoring algorithm outperformed a previously published method in 64% of the tested Orbitrap spectra. The software described in this manuscript is freely available and its source code can be accessed within the MZmine 2 source code repository.

  1. Outcome prediction in pneumonia induced ALI/ARDS by clinical features and peptide patterns of BALF determined by mass spectrometry.

    Directory of Open Access Journals (Sweden)

    Jochen Frenzel

    Full Text Available BACKGROUND: Peptide patterns of bronchoalveolar lavage fluid (BALF were assumed to reflect the complex pathology of acute lung injury (ALI/acute respiratory distress syndrome (ARDS better than clinical and inflammatory parameters and may be superior for outcome prediction. METHODOLOGY/PRINCIPAL FINDINGS: A training group of patients suffering from ALI/ARDS was compiled from equal numbers of survivors and nonsurvivors. Clinical history, ventilation parameters, Murray's lung injury severity score (Murray's LISS and interleukins in BALF were gathered. In addition, samples of bronchoalveolar lavage fluid were analyzed by means of hydrophobic chromatography and MALDI-ToF mass spectrometry (MALDI-ToF MS. Receiver operating characteristic (ROC analysis for each clinical and cytokine parameter revealed interleukin-6>interleukin-8>diabetes mellitus>Murray's LISS as the best outcome predictors. Outcome predicted on the basis of BALF levels of interleukin-6 resulted in 79.4% accuracy, 82.7% sensitivity and 76.1% specificity (area under the ROC curve, AUC, 0.853. Both clinical parameters and cytokines as well as peptide patterns determined by MALDI-ToF MS were analyzed by classification and regression tree (CART analysis and support vector machine (SVM algorithms. CART analysis including Murray's LISS, interleukin-6 and interleukin-8 in combination was correct in 78.0%. MALDI-ToF MS of BALF peptides did not reveal a single identifiable biomarker for ARDS. However, classification of patients was successfully achieved based on the entire peptide pattern analyzed using SVM. This method resulted in 90% accuracy, 93.3% sensitivity and 86.7% specificity following a 10-fold cross validation (AUC = 0.953. Subsequent validation of the optimized SVM algorithm with a test group of patients with unknown prognosis yielded 87.5% accuracy, 83.3% sensitivity and 90.0% specificity. CONCLUSIONS/SIGNIFICANCE: MALDI-ToF MS peptide patterns of BALF, evaluated by appropriate

  2. Literature based drug interaction prediction with clinical assessment using electronic medical records: novel myopathy associated drug interactions.

    Directory of Open Access Journals (Sweden)

    Jon D Duke

    Full Text Available Drug-drug interactions (DDIs are a common cause of adverse drug events. In this paper, we combined a literature discovery approach with analysis of a large electronic medical record database method to predict and evaluate novel DDIs. We predicted an initial set of 13197 potential DDIs based on substrates and inhibitors of cytochrome P450 (CYP metabolism enzymes identified from published in vitro pharmacology experiments. Using a clinical repository of over 800,000 patients, we narrowed this theoretical set of DDIs to 3670 drug pairs actually taken by patients. Finally, we sought to identify novel combinations that synergistically increased the risk of myopathy. Five pairs were identified with their p-values less than 1E-06: loratadine and simvastatin (relative risk or RR = 1.69; loratadine and alprazolam (RR = 1.86; loratadine and duloxetine (RR = 1.94; loratadine and ropinirole (RR = 3.21; and promethazine and tegaserod (RR = 3.00. When taken together, each drug pair showed a significantly increased risk of myopathy when compared to the expected additive myopathy risk from taking either of the drugs alone. Based on additional literature data on in vitro drug metabolism and inhibition potency, loratadine and simvastatin and tegaserod and promethazine were predicted to have a strong DDI through the CYP3A4 and CYP2D6 enzymes, respectively. This new translational biomedical informatics approach supports not only detection of new clinically significant DDI signals, but also evaluation of their potential molecular mechanisms.

  3. A novel metric for quantification of homogeneous and heterogeneous tumors in PET for enhanced clinical outcome prediction

    Science.gov (United States)

    Rahmim, Arman; Schmidtlein, C. Ross; Jackson, Andrew; Sheikhbahaei, Sara; Marcus, Charles; Ashrafinia, Saeed; Soltani, Madjid; Subramaniam, Rathan M.

    2016-01-01

    Oncologic PET images provide valuable information that can enable enhanced prognosis of disease. Nonetheless, such information is simplified significantly in routine clinical assessment to meet workflow constraints. Examples of typical FDG PET metrics include: (i) SUVmax, (2) total lesion glycolysis (TLG), and (3) metabolic tumor volume (MTV). We have derived and implemented a novel metric for tumor quantification, inspired in essence by a model of generalized equivalent uniform dose as used in radiation therapy. The proposed metric, denoted generalized effective total uptake (gETU), is attractive as it encompasses the abovementioned commonly invoked metrics, and generalizes them, for both homogeneous and heterogeneous tumors, using a single parameter a. We evaluated this new metric for improved overall survival (OS) prediction on two different baseline FDG PET/CT datasets: (a) 113 patients with squamous cell cancer of the oropharynx, and (b) 72 patients with locally advanced pancreatic adenocarcinoma. Kaplan-Meier survival analysis was performed, where the subjects were subdivided into two groups using the median threshold, from which the hazard ratios (HR) were computed in Cox proportional hazards regression. For the oropharyngeal cancer dataset, MTV, TLG, SUVmax, SUVmean and SUVpeak produced HR values of 1.86, 3.02, 1.34, 1.36 and 1.62, while the proposed gETU metric for a  = 0.25 (greater emphasis on volume information) enabled significantly enhanced OS prediction with HR  =  3.94. For the pancreatic cancer dataset, MTV, TLG, SUVmax, SUVmean and SUVpeak resulted in HR values of 1.05, 1.25, 1.42, 1.45 and 1.52, while gETU at a  = 3.2 (greater emphasis on SUV information) arrived at an improved HR value of 1.61. Overall, the proposed methodology allows placement of differing degrees of emphasis on tumor volume versus uptake for different types of tumors to enable enhanced clinical outcome prediction.

  4. Non-invasive clinical parameters for the prediction of urodynamic bladder outlet obstruction: analysis using causal Bayesian networks.

    Directory of Open Access Journals (Sweden)

    Myong Kim

    Full Text Available To identify non-invasive clinical parameters to predict urodynamic bladder outlet obstruction (BOO in patients with benign prostatic hyperplasia (BPH using causal Bayesian networks (CBN.From October 2004 to August 2013, 1,381 eligible BPH patients with complete data were selected for analysis. The following clinical variables were considered: age, total prostate volume (TPV, transition zone volume (TZV, prostate specific antigen (PSA, maximum flow rate (Qmax, and post-void residual volume (PVR on uroflowmetry, and International Prostate Symptom Score (IPSS. Among these variables, the independent predictors of BOO were selected using the CBN model. The predictive performance of the CBN model using the selected variables was verified through a logistic regression (LR model with the same dataset.Mean age, TPV, and IPSS were 6.2 (±7.3, SD years, 48.5 (±25.9 ml, and 17.9 (±7.9, respectively. The mean BOO index was 35.1 (±25.2 and 477 patients (34.5% had urodynamic BOO (BOO index ≥40. By using the CBN model, we identified TPV, Qmax, and PVR as independent predictors of BOO. With these three variables, the BOO prediction accuracy was 73.5%. The LR model showed a similar accuracy (77.0%. However, the area under the receiver operating characteristic curve of the CBN model was statistically smaller than that of the LR model (0.772 vs. 0.798, p = 0.020.Our study demonstrated that TPV, Qmax, and PVR are independent predictors of urodynamic BOO.

  5. Automated development of artificial neural networks for clinical purposes: Application for predicting the outcome of choledocholithiasis surgery.

    Science.gov (United States)

    Vukicevic, Arso M; Stojadinovic, Miroslav; Radovic, Milos; Djordjevic, Milena; Cirkovic, Bojana Andjelkovic; Pejovic, Tomislav; Jovicic, Gordana; Filipovic, Nenad

    2016-08-01

    Among various expert systems (ES), Artificial Neural Network (ANN) has shown to be suitable for the diagnosis of concurrent common bile duct stones (CBDS) in patients undergoing elective cholecystectomy. However, their application in practice remains limited since the development of ANNs represents a slow process that requires additional expertize from potential users. The aim of this study was to propose an ES for automated development of ANNs and validate its performances on the problem of prediction of CBDS. Automated development of the ANN was achieved by applying the evolutionary assembling approach, which assumes optimal configuring of the ANN parameters by using Genetic algorithm. Automated selection of optimal features for the ANN training was performed using a Backward sequential feature selection algorithm. The assessment of the developed ANN included the evaluation of predictive ability and clinical utility. For these purposes, we collected data from 303 patients who underwent surgery in the period from 2008 to 2014. The results showed that the total bilirubin, alanine aminotransferase, common bile duct diameter, number of stones, size of the smallest calculus, biliary colic, acute cholecystitis and pancreatitis had the best prognostic value of CBDS. Compared to the alternative approaches, the ANN obtained by the proposed ES had better sensitivity and clinical utility, which are considered to be the most important for the particular problem. Besides the fact that it enabled the development of ANNs with better performances, the proposed ES significantly reduced the complexity of ANNs' development compared to previous studies that required manual selection of optimal features and/or ANN configuration. Therefore, it is concluded that the proposed ES represents a robust and user-friendly framework that, apart from the prediction of CBDS, could advance and simplify the application of ANNs for solving a wider range of problems.

  6. Assessment of uncertainties in radiation-induced cancer risk predictions at clinically relevant doses

    Energy Technology Data Exchange (ETDEWEB)

    Nguyen, J. [Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts 02114 and Department of Physics, Ruprecht-Karls-Universität Heidelberg, Heidelberg 69117 (Germany); Moteabbed, M.; Paganetti, H., E-mail: hpaganetti@mgh.harvard.edu [Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts 02114 and Harvard Medical School, Boston, Massachusetts 02114 (United States)

    2015-01-15

    Purpose: Theoretical dose–response models offer the possibility to assess second cancer induction risks after external beam therapy. The parameters used in these models are determined with limited data from epidemiological studies. Risk estimations are thus associated with considerable uncertainties. This study aims at illustrating uncertainties when predicting the risk for organ-specific second cancers in the primary radiation field illustrated by choosing selected treatment plans for brain cancer patients. Methods: A widely used risk model was considered in this study. The uncertainties of the model parameters were estimated with reported data of second cancer incidences for various organs. Standard error propagation was then subsequently applied to assess the uncertainty in the risk model. Next, second cancer risks of five pediatric patients treated for cancer in the head and neck regions were calculated. For each case, treatment plans for proton and photon therapy were designed to estimate the uncertainties (a) in the lifetime attributable risk (LAR) for a given treatment modality and (b) when comparing risks of two different treatment modalities. Results: Uncertainties in excess of 100% of the risk were found for almost all organs considered. When applied to treatment plans, the calculated LAR values have uncertainties of the same magnitude. A comparison between cancer risks of different treatment modalities, however, does allow statistically significant conclusions. In the studied cases, the patient averaged LAR ratio of proton and photon treatments was 0.35, 0.56, and 0.59 for brain carcinoma, brain sarcoma, and bone sarcoma, respectively. Their corresponding uncertainties were estimated to be potentially below 5%, depending on uncertainties in dosimetry. Conclusions: The uncertainty in the dose–response curve in cancer risk models makes it currently impractical to predict the risk for an individual external beam treatment. On the other hand, the ratio

  7. Clinical and genetic factors predicting response to therapy in patients with Crohn’s disease

    Science.gov (United States)

    Ferreira, Paula; Sousa, Patricia; Moura-Santos, Paula; Velho, Sonia; Tavares, Lurdes; Deus, João Ramos; Ministro, Paula; da Silva, João Pereira; Correia, Luis; Velosa, Jose; Maio, Rui; Brito, Miguel

    2014-01-01

    Aim To identify clinical and/or genetic predictors of response to several therapies in Crohn’s disease (CD) patients. Methods We included 242 patients with CD (133 females) aged (mean ± standard deviation) 39 ± 12 years and a disease duration of 12 ± 8 years. The single-nucleotide polymorphisms (SNPs) studied were ABCB1 C3435T and G2677T/A, IL23R G1142A, C2370A, and G9T, CASP9 C93T, Fas G670A and LgC844T, and ATG16L1 A898G. Genotyping was performed with real-time PCR with Taqman probes. Results Older patients responded better to 5-aminosalicylic acid (5-ASA) and to azathioprine (OR 1.07, p = 0.003 and OR 1.03, p = 0.01, respectively) while younger ones responded better to biologicals (OR 0.95, p = 0.06). Previous surgery negatively influenced response to 5-ASA compounds (OR 0.25, p = 0.05), but favoured response to azathioprine (OR 2.1, p = 0.04). In respect to genetic predictors, we observed that heterozygotes for ATGL16L1 SNP had a significantly higher chance of responding to corticosteroids (OR 2.51, p = 0.04), while homozygotes for Casp9 C93T SNP had a lower chance of responding both to corticosteroids and to azathioprine (OR 0.23, p = 0.03 and OR 0.08, p = 0.02,). TT carriers of ABCB1 C3435T SNP had a higher chance of responding to azathioprine (OR 2.38, p = 0.01), while carriers of ABCB1 G2677T/A SNP, as well as responding better to azathioprine (OR 1.89, p = 0.07), had a lower chance of responding to biologicals (OR 0.31, p = 0.07), which became significant after adjusting for gender (OR 0.75, p = 0.005). Conclusions In the present study, we were able to identify a number of clinical and genetic predictors of response to several therapies which may become of potential utility in clinical practice. These are preliminary results that need to be replicated in future pharmacogenomic studies. PMID:24918007

  8. STUDY OF CLINICAL AND BIOCHEMICAL PARAMETERS IN PREDICTING THE NEED FOR VENTILATOR SUPPORT IN ORGANOPHOSPHORUS COMPOUND POISONING

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    Rajeev

    2013-12-01

    Full Text Available Organophosphorus compound is used for committing suicidal are on upswing in developing countries A grading system of severity of OP poisoning suggests that most cases can be managed in the ICU which cannot be applied to developing countries, where facilities for ICU management are rather limited. Hence, the pr esent study is undertaken to identify the factors both clinical and biochemical, which help in predicting the need for ventilator support and thus helping to reduce the mortality by timely institution of ventilator support. AIMS OF THE STUDY: To study the clinical and biochemical parameters in organophosphate poisoning, which help to predict the need for ventilator support. MATERIAL AND METHODS: This is a Descriptive Study done at Kempegowda Institute of Medical Sciences, Bangalore, with a sample size of 50 cases. Patients who fulfilled the inclusion criteria are assessed as per proforma specifically designed for the study. RESULTS: In this study population, 12 patients who reached the hospital for treatment > 4 hour of consumption, 11(91.7% required ventil ator support . In this study, out of patients with pinpoint pupils at admission required ventilator support. In this study, all patients ( required ventilator support with a fasciculation score of more than as compared to none with a bsent fasciculation. In this study, lower the Glasgow coma scale at admission, more vulnerable are the patients for ventilator support . In This study, patients with reduced levels of Pseudo cholinesterase i.e. out of patients ( required ventilato r support. CONCLUSION: Clinical and biochemical parameters such as Greater the time lag from consumption of OP poison till getting specific treatment, Lower GCS scoring, Generalized Fasiculations, Low Pseudo cholinesterase levels, Larger initial dose of At ropine required for Atropinization were strong predictors for the need for Assisted Ventilation in OP poisoning. Grading of the degree of the poisoning taking

  9. Ontology-Based Clinical Decision Support System for Predicting High-Risk Pregnant Woman

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    Umar Manzoor

    2015-12-01

    Full Text Available According to Pakistan Medical and Dental Council (PMDC, Pakistan is facing a shortage of approximately 182,000 medical doctors. Due to the shortage of doctors; a large number of lives are in danger especially pregnant woman. A large number of pregnant women die every year due to pregnancy complications, and usually the reason behind their death is that the complications are not timely handled. In this paper, we proposed ontology-based clinical decision support system that diagnoses high-risk pregnant women and refer them to the qualified medical doctors for timely treatment. The Ontology of the proposed system is built automatically and enhanced afterward using doctor’s feedback. The proposed framework has been tested on a large number of test cases; experimental results are satisfactory and support the implementation of the solution.

  10. Incarceration and Unstable Housing Interact to Predict Sexual Risk Behaviors among African American STD Clinic Patients

    Science.gov (United States)

    Widman, Laura; Noar, Seth M.; Golin, Carol E.; Willoughby, Jessica Fitts; Crosby, Richard

    2014-01-01

    Given dramatic racial disparities in rates of HIV/STDs among African Americans, understanding broader structural factors that increase the risk for HIV/STDs is crucial. This study investigated incarceration history and unstable housing as two structural predictors of HIV risk behavior among 293 African Americans (159 men/134 women, Mage=27). Participants were recruited from an urban STD clinic in the southeastern U.S. Approximately half the sample had been incarcerated in their lifetime (54%), and 43% had been unstably housed in the past 6 months. Incarceration was independently associated with number of sex partners and the frequency of unprotected sex. Unstable housing was independently associated with the frequency of unprotected sex. However, these main effects were qualified by significant interactions: individuals with a history of incarceration and more unstable housing had more sex partners and more unprotected sex in the past three months than individuals without these structural barriers. Implications for structural-level interventions are discussed. PMID:24060677

  11. EGFR CA repeat polymorphism predict clinical outcome in EGFR mutation positive NSCLC patients treated with erlotinib

    DEFF Research Database (Denmark)

    Winther Larsen, Anne; Nissen, Peter Henrik; Meldgaard, Peter;

    2014-01-01

    OBJECTIVES: Somatic mutations in the epidermal growth factor receptor (EGFR) are predictors of efficacy for treatment with the EGFR tyrosine kinase inhibitor erlotinib in non-small cell lung cancer (NSCLC). A CA repeat polymorphism in intron 1 of the EGFR gene influences the transcription...... of the EGFR gene. This study evaluates the association between the CA repeat polymorphism and outcome in NSCLC patients treated with erlotinib.MATERIALS AND METHODS: Number of CA repeats in the EGFR gene was evaluated with PCR-fragment length analysis by capillary electrophoresis in 432 advanced NSCLC...... patients treated with erlotinib irrespective of EGFR mutation status. Patients were dichotomized into harboring short allele (CA≤16 in any allele) or long alleles (CA>16 in both alleles). Number of repeats was correlated with clinical characteristic and outcome. A subgroup analysis was performed based...

  12. Hip and fragility fracture prediction by 4-item clinical risk score and mobile heel BMD: a women cohort study

    Directory of Open Access Journals (Sweden)

    Thulesius Hans

    2010-03-01

    Full Text Available Abstract Background One in four Swedish women suffers a hip fracture yielding high morbidity and mortality. We wanted to revalidate a 4-item clinical risk score and evaluate a portable heel bone mineral density (BMD technique regarding hip and fragility fracture risk among elderly women. Methods In a population-based prospective cohort study we used clinical risk factors from a baseline questionnaire and heel BMD to predict a two-year hip and fragility fracture outcome for women, in a fracture preventive program. Calcaneal heel BMD was measured by portable dual X-ray laser absorptiometry (DXL and compared to hip BMD, measured with stationary dual X-ray absorptiometry (DXA technique. Results Seven women suffered hip fracture and 14 women fragility fracture/s (at hip, radius, humerus and pelvis among 285 women; 60% having heel BMD ≤ -2.5 SD. The 4-item FRAMO (Fracture and Mortality Index combined the clinical risk factors age ≥80 years, weight Conclusions In a follow-up study we identified high risk groups for hip and fragility fracture with our plain 4-item risk model. Increased fracture risk was also related to decreasing heel BMD in calcaneal bone, measured with a mobile DXL technique. A combination of high FRAMO Index, prior fragility fracture, and very low BMD restricted the high risk group to 11%, among whom most hip fractures occurred (71%. These practical screening methods could eventually reduce hip fracture incidence by concentrating preventive resources to high fracture risk women.

  13. Extraction of Symbolic Rules from Artificial Neural Networks

    CERN Document Server

    Kamruzzaman, S M

    2010-01-01

    Although backpropagation ANNs generally predict better than decision trees do for pattern classification problems, they are often regarded as black boxes, i.e., their predictions cannot be explained as those of decision trees. In many applications, it is desirable to extract knowledge from trained ANNs for the users to gain a better understanding of how the networks solve the problems. A new rule extraction algorithm, called rule extraction from artificial neural networks (REANN) is proposed and implemented to extract symbolic rules from ANNs. A standard three-layer feedforward ANN is the basis of the algorithm. A four-phase training algorithm is proposed for backpropagation learning. Explicitness of the extracted rules is supported by comparing them to the symbolic rules generated by other methods. Extracted rules are comparable with other methods in terms of number of rules, average number of conditions for a rule, and predictive accuracy. Extensive experimental studies on several benchmarks classification ...

  14. The clinical value of hybrid sentinel lymphoscintigraphy to predict metastatic sentinel lymph nodes in breast cancer

    Energy Technology Data Exchange (ETDEWEB)

    Na, Cang Ju; Kim, Jeong Hun; Choi, Se Hun; Han, Yeon Hee; Jeong, Hwan Jeong; Sohn, Myung Hee; Youn, Hyun Jo; Lim, Seok Tae [Chonbuk National University Medical School and Hospital, Jeonju (Korea, Republic of)

    2015-03-15

    Hybrid imaging techniques can provide functional and anatomical information about sentinel lymph nodes in breast cancer. Our aim in this study was to evaluate which imaging parameters on hybrid sentinel lymphoscintigraphy predicted metastatic involvement of sentinel lymph nodes (SLNs) in patients with breast cancer. Among 56 patients who underwent conventional sentinel lymphoscintigraphy, 45 patients (age, 53.1 ± 9.5 years) underwent hybrid sentinel lymphoscintigraphy using a single-photon emission computed tomography (SPECT)/computed tomography (CT) gamma camera. On hybrid SPECT/CT images, we compared the shape and size (long-to-short axis [L/S] ratio) of the SLN, and SLN/periareolar injection site (S/P) count ratio between metastatic and non-metastatic SLNs. Metastatic involvement of sentinel lymph nodes was confirmed by pathological biopsy. Pathological biopsy revealed that 21 patients (46.7 %) had metastatic SLNs, while 24 (53.3 %) had non-metastatic SLNs. In the 21 patients with metastatic SLNs, the SLN was mostly round (57.1 %) or had an eccentric cortical rim (38.1 %). Of 24 patients with non-metastatic SLNs, 13 patients (54.1 %) had an SLN with a C-shape rim or eccentric cortex. L/S ratio was 2.04 for metastatic SLNs and 2.38 for non-metastatic SLNs. Seven (33 %) patients had T1 primary tumors and 14 (66 %) had T2 primary tumors in the metastatic SLN group. In contrast, 18 (75 %) patients had T1 primary tumors and six (25 %) had T2 tumors in the non-metastatic SLN group. S/P count ratio was significantly lower in the metastatic SLN group than the non-metastatic SLN group for those patients with a T1 primary tumor (p = 0.007). Hybrid SPECT/CT offers the physiologic data of SPECT together with the anatomic data of CT in a single image. This hybrid imaging improved the anatomic localization of SLNs in breast cancer patients and predicted the metastatic involvement of SLNs in the subgroup of breast cancer patients with T1 primary tumors.

  15. Peritumoral apparent diffusion coefficients for prediction of lymphovascular invasion in clinically node-negative invasive breast cancer

    Energy Technology Data Exchange (ETDEWEB)

    Mori, Naoko; Mugikura, Shunji; Takasawa, Chiaki; Shimauchi, Akiko; Ota, Hideki; Takase, Kei; Takahashi, Shoki [Tohoku University Graduate School of Medicine, Department of Diagnostic Radiology, Sendai (Japan); Miyashita, Minoru; Ishida, Takanori [Tohoku University Graduate School of Medicine, Department of Surgical Oncology, Sendai (Japan); Kasajima, Atsuko [Tohoku University Graduate School of Medicine, Department of Pathology, Sendai (Japan); Kodama, Tetsuya [Tohoku University Graduate School of Medicine, Department of Biomedical Engineering, Sendai (Japan)

    2016-02-15

    To evaluate whether visual assessment of T2-weighted imaging (T2WI) or an apparent diffusion coefficient (ADC) could predict lymphovascular invasion (LVI) status in cases with clinically node-negative invasive breast cancer. One hundred and thirty-six patients with 136 lesions underwent MRI. Visual assessment of T2WI, tumour-ADC, peritumoral maximum-ADC and the peritumour-tumour ADC ratio (the ratio between them) were compared with LVI status of surgical specimens. No significant relationship was found between LVI and T2WI. Tumour-ADC was significantly lower in the LVI-positive (n = 77, 896 ± 148 x 10{sup -6} mm{sup 2}/s) than the LVI-negative group (n = 59, 1002 ± 163 x 10{sup -6} mm{sup 2}/s; p < 0.0001). Peritumoral maximum-ADC was significantly higher in the LVI-positive (1805 ± 355 x 10{sup -6} mm{sup 2}/s) than the LVI-negative group (1625 ± 346 x 10{sup -6} mm{sup 2}/s; p = 0.0003). Peritumour-tumour ADC ratio was significantly higher in the LVI-positive (2.05 ± 0.46) than the LVI-negative group (1.65 ± 0.40; p < 0.0001). Receiver operating characteristic curve analysis revealed that the area under the curve (AUC) of the peritumour-tumour ADC ratio was the highest (0.81). The most effective threshold for the peritumour-tumour ADC ratio was 1.84, and the sensitivity, specificity, positive predictive value and negative predictive value were 77 % (59/77), 76 % (45/59), 81 % (59/73) and 71 % (45/63), respectively. We suggest that the peritumour-tumour ADC ratio can assist in predicting LVI status on preoperative imaging. (orig.)

  16. The clinical significance of MiR-148a as a predictive biomarker in patients with advanced colorectal cancer.

    Directory of Open Access Journals (Sweden)

    Masanobu Takahashi

    Full Text Available AIM: Development of robust prognostic and/or predictive biomarkers in patients with colorectal cancer (CRC is imperative for advancing treatment strategies for this disease. We aimed to determine whether expression status of certain miRNAs might have prognostic/predictive value in CRC patients treated with conventional cytotoxic chemotherapies. METHODS: We studied a cohort of 273 CRC specimens from stage II/III patients treated with 5-fluorouracil-based adjuvant chemotherapy and stage IV patients subjected to 5-fluorouracil and oxaliplatin-based chemotherapy. In a screening set (n = 44, 13 of 21 candidate miRNAs were successfully quantified by multiplex quantitative RT-PCR. In the validation set comprising of the entire patient cohort, miR-148a expression status was assessed by quantitative RT-PCR, and its promoter methylation was quantified by bisulfite pyrosequencing. Lastly, we analyzed the associations between miR-148a expression and patient survival. RESULTS: Among the candidate miRNAs studied, miR-148a expression was most significantly down-regulated in advanced CRC tissues. In stage III and IV CRC, low miR-148a expression was associated with significantly shorter disease free-survival (DFS, a worse therapeutic response, and poor overall survival (OS. Furthermore, miR-148a methylation status correlated inversely with its expression, and was associated with worse survival in stage IV CRC. In multivariate analysis, miR-148a expression was an independent prognostic/predictive biomarker for advanced CRC patients (DFS in stage III, low vs. high expression, HR 2.11; OS in stage IV, HR 1.93. DISCUSSION: MiR-148a status has a prognostic/predictive value in advanced CRC patients treated with conventional chemotherapy, which has important clinical implications in improving therapeutic strategies and personalized management of this malignancy.

  17. DIAGNOSTIC AND PREDICTIVE VALUES OF PHOTO ALBUMS AND VIDEOCLIPS IN PEDIATRIC NEUROLOGY CLINICS

    Directory of Open Access Journals (Sweden)

    M. Mohammadi MD

    2009-04-01

    Full Text Available Photo-albums and video-clips are simple means for diagnosis of diverseneurologic disorders in children. Most families either own or can borrow a still or video camera. Even when a purchase is required, it is more costeffective than brain imaging as well as other sophisticated studies, and the family has something useful to show for expenditure. On the other hand many families have a photo-album which could be very informative for pediatric neurologists. These useful and simple means are invaluable in:Differentiation of progressive from static diseases of central nervous system in children.Helping in diagnosis of diverse types of seizures in pediatric epileptic patients.Differential diagnosis of epilepsy like disorders (e.g. sleep disorders vs. epilepsy in children.Diagnosis as well as differential diagnosis of movement disorders in children.Therapeutic follow-up in many disorders (i.e. epilepsy, movement and sleep disorders in children.In my review article, I have indicated the importance of photo-albums and video-clips as invaluable means of diagnosis and  prediction in child neurology by giving simple examples in this regard.

  18. DIAGNOSTIC AND PREDICTIVE VALUES OF PHOTO ALBUMS AND VIDEOCLIPS IN PEDIATRIC NEUROLOGY CLINICS

    Directory of Open Access Journals (Sweden)

    M. Mohammadi

    2006-10-01

    Full Text Available Photo-albums and video-clips are simple means for diagnosis of diverseneurologic disorders in children. Most families either own or can borrow astill or video camera. Even when a purchase is required, it is more costeffective than brain imaging as well as other sophisticated studies, and thefamily has something useful to show for expenditure. On the other handmany families have a photo-album which could be very informative forpediatric neurologists. These useful and simple means are invaluable in: • Differentiation of progressive from static diseases of central nervoussystem in children. • Helping in diagnosis of diverse types of seizures in pediatric epilepticpatients. • Differential diagnosis of epilepsy like disorders (e.g. sleep disorders vs.epilepsy in children. • Diagnosis as well as differential diagnosis of movement disorders inchildren. • Therapeutic follow-up in many disorders (i.e. epilepsy, movement andsleep disorders in children.In my review article, I have indicated the importance of photo-albums andvideo-clips as invaluable means of diagnosis and prediction in child neurologyby giving simple examples in this regard.

  19. Synuclein gamma predicts poor clinical outcome in colon cancer with normal levels of carcinoembryonic antigen

    Directory of Open Access Journals (Sweden)

    Xing Xiaofang

    2010-07-01

    Full Text Available Abstract Background Synuclein gamma (SNCG, initially identified as a breast cancer specific gene, is aberrantly expressed in many different malignant tumors but rarely expressed in matched nonneoplastic adjacent tissues. In this study, we investigated the prognostic potential of SNCG in colon cancer particularly in the patients with normal carcinoembryonic antigen (CEA levels. Methods SNCG levels were assessed immunohistochemically in cancer tissues from 229 colon adenocarcinoma patients with a mean follow-up of 44 months. Correlations between SNCG levels and clinicopathologic features, preoperative serum CEA level, and clinical outcome were analyzed statistically using SPSS. Results SNCG levels in colon adenocarcinoma were closely associated with intravascular embolus and tumor recurrence but independent of preoperative serum CEA levels. SNCG expression was an independent prognostic factor of a shorter disease-free survival (DFS and overall survival (OS (P P = 0.001, P = 0.001, 0.002 for 97 patients with normal preoperative serum CEA level. Conclusions Our results suggest for the first time that SNCG is a new independent predicator for poor prognosis in patients with colon adenocarcinoma, including those with normal CEA levels. Combination of CEA with SNCG improves prognostic evaluation for patients with colon adenocarcinoma.

  20. Regional MRI Perfusion Measures Predict Motor/Executive Function in Patients with Clinically Isolated Syndrome

    Directory of Open Access Journals (Sweden)

    Efrosini Z. Papadaki

    2014-01-01

    Full Text Available Background. Patients with clinically isolated syndrome (CIS demonstrate brain hemodynamic changes and also suffer from difficulties in processing speed, memory, and executive functions. Objective. To explore whether brain hemodynamic disturbances in CIS patients correlate with executive functions. Methods. Thirty CIS patients and forty-three healthy subjects, matched for age, gender, education level, and FSIQ, were administered tests of visuomotor learning and set shifting ability. Cerebral blood volume (CBV, cerebral blood flow (CBF, and mean transit time (MTT values were estimated in normal-appearing white matter (NAWM and normal-appearing deep gray Matter (NADGM structures, using a perfusion MRI technique. Results. CIS patients showed significantly elevated reaction time (RT on both tasks, while their CBV and MTT values were globally increased, probably due to inflammatory vasodilation. Significantly, positive correlation coefficients were found between error rates on the inhibition condition of the visuomotor learning task and CBV values in occipital, periventricular NAWM and both thalami. On the set shifting condition of the respective task significant, positive associations were found between error rates and CBV values in the semioval center and periventricular NAWM bilaterally. Conclusion. Impaired executive function in CIS patients correlated positively with elevated regional CBV values thought to reflect inflammatory processes.

  1. 基于Cramer法则的区间灰数预测模型参数优化方法研究%Research on the Parameter Optimal Method of Interval Grey Number Prediction Model based on Cramer Rule

    Institute of Scientific and Technical Information of China (English)

    曾波; 石娟娟; 周雪玉

    2015-01-01

    以改善区间灰数预测模型的模拟及预测性能为目的,对区间灰数预测模型的参数优化方法进行研究,应用Cramer法则推导了核序列GM (1,1)模型通用形式的参数无偏估计新方法,从理论上证明了新方法对非齐次指数“核”序列的模拟无偏性,并在此基础上构建了一种新的区间灰数预测模型;通过与优化前的区间灰数预测模型模拟精度进行比较,结果表明新模型具有更为优秀的模拟及预测性能。此研究成果对丰富和完善灰色预测模型方法体系与拓展灰色模型应用范围,具有积极意义。%The parameter optimal method of interval grey number prediction model was studied to improve its simulative and predictive performance in this paper .It applied Cramer rule to deduce the novel unbiased estimation method of GM (1 ,1) model common form for interval grey numbers'kernel sequence , and the simulative unbiasedness of the novel method for nonhomogeneous exponent kernel sequences has been theoretically proven and a new interval grey number prediction model has been established . Comparing the simulative accuracy of the novel model with that of the previous interval grey model without parameter optimization reveals that the novel method has better performances in terms of modeling and prediction . The findings in this paper enrich the literature of grey prediction model and pave the way towards extending the application of grey model .

  2. Drivers of Changes in Product Development Rules

    DEFF Research Database (Denmark)

    Christiansen, John K.; Varnes, Claus J.

    2015-01-01

    regimes. However, the analysis here indicates that there are different drivers, both internal and external, that cause companies to adopt new rules or modify their existing ones, such as changes in organizational structures, organizational conflicts, and changes in ownership or strategy. In addition......, contrary to the predictions in previous research, companies sometimes move back and forth between different generations of rules. Companies that have moved to a more flexible third generation of rules might revert to their second generation rules, or supplement their flexibility with an increased level...... indicate that many factors influence the modification of rules, and that there is no simple linear progression from one generation to another. Organizational learning is one among several other factors that influences the dynamics of rules for managing product development. Further research is needed...

  3. Somatostatin receptor scintigraphy to predict the clinical evolution and therapeutic response of thyroid-associated ophthalmopathy

    Energy Technology Data Exchange (ETDEWEB)

    Nocaudie, M.; Bailliez, A.; Itti, E. [Centre Hospitalier Regional et Universitaire, Lille (France). Service Central de Medecine Nucleaire et Imagerie Fonctionnelle; Bauters, C.; Wemeau, J.L. [Clinique d`Endocrinologie, Centre Hospitalier Regional et Universitaire de Lille (France); Marchandise, X.

    1999-05-01

    Management of thyroid-associated ophthalmopathy remains a topic of controversy. Immunosuppressive treatments have to be applied at peak disease activity and before criteria of severity develop. Expression of somatostatin receptors on activated lymphocytes allows scintigraphic imaging with indium-111 pentetreotide. We conducted a prospective study with 17 patients who presented severe ophthalmopathy (11 Graves` disease, four Hashimoto`s thyroiditis, two isolated in appearance: Means` syndrome). Each patient underwent hormonal (free T{sub 3} and TSH) and immunological (TBII) assessment, an orbital computed tomography scan or magnetic resonance imaging, a visual functional examination and {sup 111}In-pentetreotide orbital scintigraphy before undergoing treatment by steroids and/or radiotherapy, independently of scintigraphic results. At 4 and 24 h after the intravenous injection of 111 MBq of {sup 111}In-pentetreotide, planar imaging centred on the head and neck (anterior and both lateral views) was carried out. Retrobulbar uptake was assessed by visual semi-quantitative analysis (score given by two independent trained observers) and by quantitative analyses (regions of interest, orbit/brain uptake indices). Patients were ophthalmologically followed up for 6 months and then classified as improved or not. Visual semi-quantitative analysis of 4-h/24-h planar images was correlated with the ophthalmological evolution ({chi}{sup 2} test, P<0.01). All ten patients in whom scintigraphy was considered positive were clinically improved at 6 months, and of the seven patients in whom scintigraphy was negative, six were not improved. Nevertheless, objective quantitative analysis did not succeed in confirming these results. We conclude that {sup 111}In-pentetreotide scintigraphy requires further developments, including quantitative single-photon emission tomographic acquisition, if its role as a guide to therapeutic strategy in thyroid-associated ophthalmopathy is to be confirmed

  4. CIAPIN1 nuclear accumulation predicts poor clinical outcome in epithelial ovarian cancer

    Directory of Open Access Journals (Sweden)

    Cai Xiaolan

    2012-06-01

    Full Text Available Abstract Background Epithelial ovarian cancer (EOC is an aggressive disease with poor prognosis. The expression of cytokine-induced apoptosis inhibitor 1 (CIAPIN1 correlates with the malignant progression of several cancers. However, the relationship between the subcellular localization of CIAPIN1 and clinical characteristics in EOC remains unclear. Methods Immunohistochemistry was performed to detect CIAPIN1 expression in 108 EOC tissues. CIAPIN1 expressions in eight fresh EOC tissues were detected by Western blotting. The relationship between CIAPIN1 subcellular expression and patients’ clinicopathological features, including prognosis, was evaluated. Immunohistochemistry and immunofluorescence were employed to assess the CIAPIN1 subcellular localization in the EOC cell lines A2780 and HO8910. In addition, all patients were followed up to assess the prognostic value of CIAPIN1 in patients with EOC. Results CIAPIN1 is highly expressed in EOC, but is present at low levels in paired non-cancerous ovarian epithelial tissues. The results of Western blotting were in accordance with the immunohistochemical results. Poor differentiation of the tumors and EOC cell lines correlated with higher levels of CIAPIN1 nuclear expression. CIAPIN1 nuclear expression significantly correlated with the Federation International of Gynecology and Obstetrics (FIGO stage and histological differentiation (P = 0.034 and P P  Conclusions CIAPIN1 might play a crucial role in the differentiation of EOC cells. Elevated expression of nuclear CIAPIN1 negatively correlated with the survival of EOC patients, suggesting that nuclear CIAPIN1 might serve as a prognostic biomarker for EOC patients.

  5. Mining association rule efficiently based on data warehouse

    Institute of Scientific and Technical Information of China (English)

    陈晓红; 赖邦传; 罗铤

    2003-01-01

    The conventional complete association rule set was replaced by the least association rule set in data warehouse association rule mining process. The least association rule set should comply with two requirements: 1) it should be the minimal and the simplest association rule set; 2) its predictive power should in no way be weaker than that of the complete association rule set so that the precision of the association rule set analysis can be guaranteed.By adopting the least association rule set, the pruning of weak rules can be effectively carried out so as to greatly reduce the number of frequent itemset, and therefore improve the mining efficiency. Finally, based on the classical Apriori algorithm, the upward closure property of weak rules is utilized to develop a corresponding efficient algorithm.

  6. Westgard西格玛规则在临床血液学检验项目室内质量控制规则选择中的应用%Application of Westgard sigma rules in selecting internal quality control rules for clinical hematology tests

    Institute of Scientific and Technical Information of China (English)

    费阳; 王薇; 王治国

    2016-01-01

    目的:利用Westgard西格玛规则帮助某实验室选择适当的临床血液学检验项目室内质量控制(简称室内质控)规则。方法选择1家参加2013年卫生部临床检验中心血细胞计数室间质量评价(简称室间质评)和室内质控计划的实验室,用实验室室内质控累积变异系数(CV)作为测量不精密度的估计值,将该实验室在室间质评计划中的百分差值作为该实验室的偏移估计值,采用生物学变异导出要求、美国临床实验室改进修正法案(CLIA'88)能力验证评价限和我国卫生行业标准WS/T406-2012的允许总误差(TEa)作为质量规范,计算各项目的σ值。根据σ值利用Westgard西格玛规则为实验室血液学检验各项目选择适当的质量控制规则。结果采用生物学变异导出要求的TEa,全血细胞计数各项目σ值均<4,应使用13s/22s/R4s/41s/8x规则;采用美国CLIA'88能力验证评价限,血红蛋白和血小板的σ值分别为5.20和5.13,应使用13s/22s/R4s规则;采用我国卫生行业标准,血红蛋白和血细胞比容的σ值分别为4.35和4.62,应使用13s/22s/R4s/41s规则。结论 Westgard西格玛规则是一种方便、实用的质量控制规则选择工具,实验室可利用它得到正确的质量控制规则和质量控制测定值个数。%Objective To use Westgard sigma rules in selecting suitable internal quality control rules for clinical hematology tests. Methods A laboratory which participated complete blood count external quality assessment and internal quality control of the National Center for Clinical Laboratories in 2013 was enrolled. Accumulated coefficient of variation(CV) in internal quality control was regarded as the estimation value of imprecision,and the percentage difference in external quality assessment was chosen to be the estimation value of bias. The allowable total errors (TEa) based on biological variation, the Clinical Laboratory

  7. Exome mutation burden predicts clinical outcome in ovarian cancer carrying mutated BRCA1 and BRCA2 genes

    DEFF Research Database (Denmark)

    Birkbak, Nicolai Juul; Kochupurakkal, Bose; Gonzalez-Izarzugaza, Jose Maria;

    2013-01-01

    Reliable biomarkers predicting resistance or sensitivity to anti-cancer therapy are critical for oncologists to select proper therapeutic drugs in individual cancer patients. Ovarian and breast cancer patients carrying germline mutations in BRCA1 or BRCA2 genes are often sensitive to DNA damaging...... drugs and relative to non-mutation carriers present a favorable clinical outcome following therapy. Genome sequencing studies have shown a high number of mutations in the tumor genome in patients carrying BRCA1 or BRCA2 mutations (mBRCA). The present study used exome-sequencing and SNP 6 array data...... had either germlines or somatic mutations of BRCA1 or BRCA2 genes. The results revealed that the Nmut was significantly lower in the chemotherapy-resistant mBRCA HGSOC defined by progression within 6 months after completion of first line platinum-based chemotherapy. We found a significant association...

  8. Ictal SPECT Using an Attachable Automated Injector: Clinical Usefulness in the Prediction of Ictal Onset Zone

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Jung-Ju (Dept. of Neurology, Eulji General Hospital, Eulji Univ. College of Medicine, Seoul (Korea)). e-mail. sangunlee@dreamwiz.com; Lee, Sang Kun (Dept. of Neurology, Seoul National Univ. College of Medicine, Seoul (Korea)); Choi, Jang Wuk (Dept. of Neurology, Seoul National Univ. Hospital, Seoul (Korea)) (and others)

    2009-12-15

    Background: Ictal single-photon emission computed tomography (SPECT) is a valuable method for localizing the ictal onset zone in the presurgical evaluation of patients with intractable epilepsy. Conventional methods used to localize the ictal onset zone have problems with time lag from seizure onset to injection. Purpose: To evaluate the clinical usefulness of a method that we developed, which involves an attachable automated injector (AAI), in reducing time lag and improving the ability to localize the zone of seizure onset. Material and Methods: Patients admitted to the epilepsy monitoring unit (EMU) between January 1, 2003, and June 30, 2008, were included. The definition of ictal onset zone was made by comprehensive review of medical records, magnetic resonance imaging (MRI), data from video electroencephalography (EEG) monitoring, and invasive EEG monitoring if available. We comprehensively evaluated the time lag to injection and the image patterns of ictal SPECT using traditional visual analysis, statistical parametric mapping-assisted, and subtraction ictal SPECT coregistered to an MRI-assisted means of analysis. Image patterns were classified as localizing, lateralizing, and nonlateralizing. The whole number of patients was 99: 48 in the conventional group and 51 in the AAI group. Results: The mean (SD) delay time to injection from seizure onset was 12.4+-12.0 s in the group injected by our AAI method and 40.4+-26.3 s in the group injected by the conventional method (P=0.000). The mean delay time to injection from seizure detection was 3.2+-2.5 s in the group injected by the AAI method and 21.4+-9.7 s in the group injected by the conventional method (P=0.000). The AAI method was superior to the conventional method in localizing the area of seizure onset (36 out of 51 with AAI method vs. 21 out of 48 with conventional method, P=0.009), especially in non-temporal lobe epilepsy (non-TLE) patients (17 out of 27 with AAI method vs. 3 out of 13 with conventional

  9. Identification of clinical and simple laboratory variables predicting responsible gastrointestinal lesions in patients with iron deficiency anemia

    Directory of Open Access Journals (Sweden)

    Songul Serefhanoglu, Yahya Buyukasik, Hakan Emmungil, Nilgun Sayinalp, Ibrahim Celalettin Haznedaroglu, Hakan Goker, Salih Aksu, Osman Ilhami Ozcebe

    2011-01-01

    Full Text Available Iron deficiency anemia (IDA is a frequent disorder. Also, it may be a sign of underlying serious diseases. Iron deficiency points to an occult or frank bleeding lesion when occurred in men or postmenopausal women. In this study, we aimed to evaluate the diagnostic yield of endoscopy in patients with IDA and to define predictive factors of gastrointestinal (GI lesions causing IDA. Ninety-one patients (77 women, 14 men; mean age: 43 years who were decided to have esophago-duodenoscopy and/or colonoscopy for iron deficiency anemia were interviewed and responded to a questionnaire that included clinical and biochemical variables. The endoscopic findings were recorded as GI lesions causing IDA or not causing IDA. Endoscopy revealed a source of IDA in 18.6 % of cases. The risk factors for finding GI lesions causing IDA were as follows: male gender (p= 0.004, advanced age (> 50 years (p= 0.010, weight loss (over 20% of total body weight lost in last 6 month (p= 0.020, chronic diarrhea (p= 0.006, change of bowel habits (p= 0.043, epigastric tenderness (p= 0.037, raised carcinoembryonic antigen (CEA level (normal range: 0-7 ng/mL (p= 0.039, < 10 gr/dl hemoglobin (Hb level (p=0.054. None of these risk factors had been present in 21 (23% women younger than 51 years. In this group, no patient had any GI lesion likely to cause IDA (negative predictive value= 100%. In multivariate analysis, advanced age (p=0.017, male gender (p< 0.01 and weight lost (p=0.012 found that associated with GI lesions in all patients. It may be an appropriate clinical approach to consider these risk factors when deciding for gastrointestinal endoscopic evaluation in iron deficiency anemia.

  10. Secretome Prediction of Two M. tuberculosis Clinical Isolates Reveals Their High Antigenic Density and Potential Drug Targets

    Science.gov (United States)

    Cornejo-Granados, Fernanda; Zatarain-Barrón, Zyanya L.; Cantu-Robles, Vito A.; Mendoza-Vargas, Alfredo; Molina-Romero, Camilo; Sánchez, Filiberto; Del Pozo-Yauner, Luis; Hernández-Pando, Rogelio; Ochoa-Leyva, Adrián

    2017-01-01

    The Excreted/Secreted (ES) proteins play important roles during Mycobacterium tuberculosis invasion, virulence, and survival inside the host and they are a major source of immunogenic proteins. However, the molecular complexity of the bacillus cell wall has made difficult the experimental isolation of the total bacterial ES proteins. Here, we reported the genomes of two Beijing genotype M. tuberculosis clinical isolates obtained from patients from Vietnam (isolate 46) and South Africa (isolate 48). We developed a bioinformatics pipeline to predict their secretomes and observed that ~12% of the genome-encoded proteins are ES, being PE, PE-PGRS, and PPE the most abundant protein domains. Additionally, the Gene Ontology, KEGG pathways and Enzyme Classes annotations supported the expected functions for the secretomes. The ~70% of an experimental secretome compiled from literature was contained in our predicted secretomes, while only the 34–41% of the experimental secretome was contained in the two previously reported secretomes for H37Rv. These results suggest that our bioinformatics pipeline is better to predict a more complete set of ES proteins in M. tuberculosis genomes. The predicted ES proteins showed a significant higher antigenic density measured by Abundance of Antigenic Regions (AAR) value than the non-ES proteins and also compared to random constructed secretomes. Additionally, we predicted the secretomes for H37Rv, H37Ra, and two M. bovis BCG genomes. The antigenic density for BGG and for isolates 46 and 48 was higher than the observed for H37Rv and H37Ra secretomes. In addition, two sets of immunogenic proteins previously reported in patients with tuberculosis also showed a high antigenic density. Interestingly, mice infected with isolate 46 showed a significant lower survival rate than the ones infected with isolate 48 and both survival rates were lower than the one previously reported for the H37Rv in the same murine model. Finally, after a

  11. Extracting Symbolic Rules for Medical Diagnosis Problem

    CERN Document Server

    Kamruzzaman, S M

    2010-01-01

    Neural networks (NNs) have been successfully applied to solve a variety of application problems involving classification and function approximation. Although backpropagation NNs generally predict better than decision trees do for pattern classification problems, they are often regarded as black boxes, i.e., their predictions cannot be explained as those of decision trees. In many applications, it is desirable to extract knowledge from trained NNs for the users to gain a better understanding of how the networks solve the problems. An algorithm is proposed and implemented to extract symbolic rules for medical diagnosis problem. Empirical study on three benchmarks classification problems, such as breast cancer, diabetes, and lenses demonstrates that the proposed algorithm generates high quality rules from NNs comparable with other methods in terms of number of rules, average number of conditions for a rule, and predictive accuracy.

  12. A Case-Control Comparison of Retracted and Non-Retracted Clinical Trials: Can Retraction Be Predicted?

    Directory of Open Access Journals (Sweden)

    R. Grant Steen

    2014-01-01

    Full Text Available Does scientific misconduct severe enough to result in retraction disclose itself with warning signs? We test a hypothesis that variables in the results section of randomized clinical trials (RCTs are associated with retraction, even without access to raw data. We evaluated all English-language RCTs retracted from the PubMed database prior to 2011. Two controls were selected for each case, matching publication journal, volume, issue, and page as closely as possible. Number of authors, subjects enrolled, patients at risk, and patients treated were tallied in cases and controls. Among case RCTs, 17.5% had ≤2 authors, while 6.3% of control RCTs had ≤2 authors. Logistic regression shows that having few authors is associated with retraction (p < 0.03, although the number of subjects enrolled, patients at risk, or treated patients is not. However, none of the variables singly, nor all of the variables combined, can reliably predict retraction, perhaps because retraction is such a rare event. Exploratory analysis suggests that retraction rate varies by medical field (p < 0.001. Although retraction cannot be predicted on the basis of the variables evaluated, concern is warranted when there are few authors, enrolled subjects, patients at risk, or treated patients. Ironically, these features urge caution in evaluating any RCT, since they identify studies that are statistically weaker.

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

    Directory of Open Access Journals (Sweden)

    Panagiotis Bountris

    2014-01-01

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

  14. Functional Activities Questionnaire items that best discriminate and predict progression from clinically normal to mild cognitive impairment

    Science.gov (United States)

    Marshall, Gad A.; Zoller, Amy S.; Lorius, Natacha; Amariglio, Rebecca E.; Locascio, Joseph J.; Johnson, Keith A.; Sperling, Reisa A.; Rentz, Dorene M.

    2015-01-01

    Background Impairment in instrumental activities of daily living (IADL) emerges in the transition from mild cognitive impairment (MCI) to Alzheimer’s disease (AD) dementia. Some IADL scales are sensitive to early deficits in MCI, but none have been validated for detecting subtle functional changes in clinically normal (CN) elderly at risk for AD. Methods Data from 624 subjects participating in the Alzheimer’s Disease Neuroimaging Initiative and 524 subjects participating in the Massachusetts Alzheimer’s Disease Research Center, which are two large cohorts including CN elderly and MCI subjects, were used to determine which Functional Activities Questionnaire items best discriminate between and predict progression from CN to MCI. Results We found that “Remembering appointments” and “assembling tax records” best discriminated between CN and MCI subjects, while worse performance on “paying attention and understanding a TV program”, “paying bills/balancing checkbook”, and “heating water and turning off the stove” predicted greater hazard of progressing from a diagnosis of CN to MCI. Conclusions These results demonstrate that certain questions are especially sensitive in detecting the earliest functional changes in CN elderly at risk for AD. As the field moves toward earlier intervention in preclinical AD, it is important to determine which IADL changes can be detected at that stage and track decline over time. PMID:26017560

  15. Shock Index and Prediction of Traumatic Hemorrhagic Shock 28-Day Mortality: Data from the DCLHb Resuscitation Clinical Trials

    Directory of Open Access Journals (Sweden)

    Edward P. Sloan

    2014-11-01

    Full Text Available Introduction: To assess the ability of the shock index (SI to predict 28-day mortality in traumatic hemorrhagic shock patients treated in the diaspirin cross-linked hemoglobin (DCLHb resuscitation clinical trials. Methods: We used data from two parallel DCLHb traumatic hemorrhagic shock efficacy trials, one in U.S. emergency departments, and one in the European Union prehospital setting to assess the relationship between SI values and 28-day mortality. Results: In the 219 patients, the mean age was 37 years, 64% sustained a blunt injury, 48% received DCLHb, 36% died, and 88% had an SI>1.0 at study entry. The percentage of patients with an SI>1.0 dropped by 57% (88 to 38% from the time of study entry to 120 minutes after study resuscitation (p1.0, 1.4, and 1.8 at any time point were 2.3, 2.7, and 3.1 times, respectively, more likely to die by 28 days than were patients with SI values below these cutoffs (p1.0 were 3.9x times more likely to die by 28 days (40 vs. 15%, p<0.001. Although the distribution of SI values differed based on treatment group, the receiver operator characeristics data showed no difference in SI predictive ability for 28-day mortality in patients treated with DCLHb. Conclusion: In these traumatic hemorrhagic shock patients, the shock index correlates with 28-day mortality, with higher SI values indicating greater mortality risk. Although DCLHb treatment did alter the distribution of SI values, it did not influence the ability of the SI to predict 28-day mortality. [West J Emerg Med. 2014;15(7:–0.

  16. Everyday Cognition scale items that best discriminate between and predict progression from clinically normal to mild cognitive impairment

    Science.gov (United States)

    Marshall, Gad A.; Zoller, Amy S.; Kelly, Kathleen E.; Amariglio, Rebecca E.; Locascio, Joseph J.; Johnson, Keith A.; Sperling, Reisa A.; Rentz, Dorene M.

    2014-01-01

    Background Impairment in instrumental activities of daily living (IADL) starts as individuals with amnestic mild cognitive impairment (MCI) transition to Alzheimer’s disease (AD) dementia. However, most IADL scales have not shown IADL alterations in clinically normal (CN) elderly. The objective of this study was to determine which of the IADL-related Everyday Cognition (ECog) scale items are most sensitive for detection of early functional changes. Methods We assessed 290 CN and 495 MCI participants from the Alzheimer’s Disease Neuroimaging Initiative. We performed logistic regression analyses predicting the probability of CN vs. MCI diagnosis using only the 17 participant-based and 17 informant-based ECog items related to IADL. We then performed Cox regression analyses to predict progression from CN to MCI. All analyses were adjusted for demographic characteristics. Results We found that worse performance on “remembering a few shopping items” (participant and informant-based p<0.0001), “remembering appointments” (participant and informant-based p<0.0001), “developing a schedule in advance of anticipated events” (participant-based p=0.007), “balancing checkbook” (participant-based p=0.02), and “keeping mail and papers organized” (informant-based p=0.002) best discriminated MCI from CN. We found that worse performance on “keeping mail and papers organized” (participant-based Hazard Ratio (HR)=2.27, p=0.07) marginally predicted greater hazard of progressing from CN to MCI. Conclusions Our results indicate that a few simple questions targeting early functional changes, addressed either to the individual or informant, can effectively distinguish between CN elderly and individuals with MCI. Additionally, one of the above questions related to organization suggested which CN individuals are likely to progress to MCI. PMID:25274110

  17. T Cell Receptor Excision Circle (TREC) Monitoring after Allogeneic Stem Cell Transplantation; a Predictive Marker for Complications and Clinical Outcome

    Science.gov (United States)

    Gaballa, Ahmed; Sundin, Mikael; Stikvoort, Arwen; Abumaree, Muhamed; Uzunel, Mehmet; Sairafi, Darius; Uhlin, Michael

    2016-01-01

    Allogeneic hematopoietic stem cell transplantation (HSCT) is a well-established treatment modality for a variety of malignant diseases as well as for inborn errors of the metabolism or immune system. Regardless of disease origin, good clinical effects are dependent on proper immune reconstitution. T cells are responsible for both the beneficial graft-versus-leukemia (GVL) effect against malignant cells and protection against infections. The immune recovery of T cells relies initially on peripheral expansion of mature cells from the graft and later on the differentiation and maturation from donor-derived hematopoietic stem cells. The formation of new T cells occurs in the thymus and as a byproduct, T cell receptor excision circles (TRECs) are released upon rearrangement of the T cell receptor. Detection of TRECs by PCR is a reliable method for estimating the amount of newly formed T cells in the circulation and, indirectly, for estimating thymic function. Here, we discuss the role of TREC analysis in the prediction of clinical outcome after allogeneic HSCT. Due to the pivotal role of T cell reconstitution we propose that TREC analysis should be included as a key indicator in the post-HSCT follow-up. PMID:27727179

  18. Prevalence of delirium among patients at a cancer ward: Clinical risk factors and prediction by bedside cognitive tests.

    Science.gov (United States)

    Grandahl, Mia Gall; Nielsen, Svend Erik; Koerner, Ejnar Alex; Schultz, Helga Holm; Arnfred, Sidse Marie

    2016-08-01

    Background Delirium is a frequent psychiatric complication to cancer, but rarely recognized by oncologists. Aims 1. To estimate the prevalence of delirium among inpatients admitted at an oncological cancer ward 2. To investigate whether simple clinical factors predict delirium 3. To examine the value of cognitive testing in the assessment of delirium. Methods On five different days, we interviewed and assessed patients admitted to a Danish cancer ward. The World Health Organization International Classification of Diseases Version 10, WHO ICD-10 Diagnostic System and the Confusion Assessment Method (CAM) were used for diagnostic categorization. Clinical information was gathered from medical records and all patients were tested with Mini Cognitive Test, The Clock Drawing Test, and the Digit Span Test. Results 81 cancer patients were assessed and 33% were diagnosed with delirium. All delirious participants were CAM positive. Poor performance on the cognitive tests was associated with delirium. Medical records describing CNS metastases, benzodiazepine or morphine treatment were associated with delirium. Conclusions Delirium is prevalent among cancer inpatients. The Mini Cognitive Test, The Clock Drawing Test, and the Digit Span Test can be used as screening tools for delirium among inpatients with cancer, but even in synergy, they lack specificity. Combining cognitive testing and attention to nurses' records might improve detection, yet further studies are needed to create a more detailed patient profile for the detection of delirium.

  19. The role of LDH serum levels in predicting global outcome in HCC patients undergoing TACE: implications for clinical management.

    Directory of Open Access Journals (Sweden)

    Mario Scartozzi

    Full Text Available In many tumor types serum lactate dehydrogenase (LDH levels is an indirect marker of tumor hypoxia, neo-angiogenesis and worse prognosis. However data about hepatocellular carcinoma (HCC are lacking in the clinical setting of patients undergoing transarterial-chemoembolization (TACE in whom hypoxia and neo-angiogenesis may represent a molecular key to treatment failure. Aim of our analysis was to evaluate the role of LDH pre-treatment levels in determining clinical outcome for patients with HCC receiving TACE. One hundred and fourteen patients were available for our analysis. For all patients LDH values were collected within one month before the procedure. We divided our patients into two groups, according to LDH serum concentration registered before TACE (first: LDH≤450 U/l 84 patients; second: LDH>450 U/l 30 patients. Patients were classified according to the variation in LDH serum levels pre- and post-treatment (increased: 62 patients vs. decreased 52 patients. No statistically significant differences were found between the groups for all clinical characteristics analyzed (gender, median age, performance status ECOG, staging systems. In patients with LDH values below 450 U/l median time to progression (TTP was 16.3 months, whereas it was of 10.1 months in patients above the cut-off (p = 0.0085. Accordingly median overall survival (OS was 22.4 months and 11.7 months (p = 0.0049. In patients with decreased LDH values after treatment median TTP was 12.4 months, and median OS was 22.1 months, whereas TTP was 9.1 months and OS was 9.5 in patients with increased LDH levels (TTP: p = 0.0087; OS: p<0.0001. In our experience, LDH seemed able to predict clinical outcome for HCC patients undergoing TACE. Given the correlation between LDH levels and tumor angiogenesis we can speculate that patients with high LDH pretreatment levels may be optimal candidates for clinical trial exploring a multimodality treatment approach with TACE and anti

  20. Discriminant validity of constructs derived from the self-regulative model for evaluation anxiety for predicting clinical manifestations of test anxiety.

    Science.gov (United States)

    Herzer, Frank; Wendt, Julia; Hamm, Alfons O

    2015-10-01

    Test anxiety is a highly prevalent and impairing syndrome. However, research on clinically relevant manifestations of test anxiety and especially on effective treatment components is still very sparse. In the present study we examined the predictive validity of constructs derived from the self-regulative model for evaluation anxiety proposed by Zeidner and Matthews (2007) for discriminating clinical and non-clinical levels of test anxiety. We compared self-report data from 47 clinically test anxious patients with those from 41 healthy university students. Results showed that learning goals, self-concept of abilities, self-incrimination, elaboration and perfectionism were the constructs that independently separated clinical from non-clinical levels of test anxiety, thus providing the strongest discriminant validity even when controlling for an effect of the global severity of mental health problems. These constructs spread across all three domains proposed in the model, thus providing important implications for possible targets of interventions to reduce clinical levels of test anxiety.

  1. [Clinical application value of prognostic nutritional index for predicting survival in patients with advanced non-small cell lung cancer].

    Science.gov (United States)

    Xu, W J; Kang, Y M; Zhou, L; Chen, F F; Song, Y H; Zhang, C Q

    2017-02-23

    Objective: To explore the clinical application value of prognostic nutritional index(PNI) for predicting overall survival(OS) in patients with advanced non-small cell lung cancer (NSCLC). Methods: 123 patients with histologically confirmed non-small cell lung cancer were enrolled in this study, and their clinical and laboratory data were reviewed. The PNI was calculated as 10×serum albumin value+ 5×total lymphocyte countin peripheral blood.Univariate and multivariate analyses were used to identify the potential prognostic factors for advanced NSCLC. Results: PNI of the 123 NSCLC patients was 46.24±6.56. PNI was significantly associated with age, weight loss and pleural effusion (P0.05). The median OS of the 123 patients was 19.5 months. The median OS in the higher PNI group (PNI≥46.24) and lower PNI group(PNI<46.24) were 25.2 months and 16.4 months, respectively.The 1-year survival rates were 80.6% and 63.9%, and 2-year survival rates were 54.8% and 19.6%, respectively (P<0.01). Univariate analysis showed that PNI, age, dyspnea, and weight loss were related to the OS of the advanced NSCLC patients (P<0.05). Multivariate analysis identified PNI as an independent prognostic factor for OS of advanced NSCLC (P<0.001). Conclusion: PNI can be easily calculated, and may be used as a relatively new prognostic indicator for advanced NSCLC in clinical practice.

  2. Finite element model predicts current density distribution for clinical applications of tDCS and tACS

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    Toralf eNeuling

    2012-09-01

    Full Text Available Transcranial direct current stimulation (tDCS has been applied in numerous scientific studies over the past decade. However, the possibility to apply tDCS in therapy of neuropsychiatric disorders is still debated. While transcranial magnetic stimulation (TMS has been approved for treatment of major depression in the United States by the Food and Drug Administration (FDA, tDCS is not as widely accepted. One of the criticisms against tDCS is the lack of spatial specificity. Focality is limited by the electrode size (35 cm2 are commonly used and the bipolar arrangement. However, a current flow through the head directly from anode to cathode is an outdated view. Finite element (FE models have recently been used to predict the exact current flow during tDCS. These simulations have demonstrated that the current flow depends on tissue shape and conductivity. Toface the challenge to predict the location, magnitude and direction of the current flow induced by tDCS and transcranial alternating current stimulation (tACS, we used a refined realistic FE modeling approach. With respect to the literature on clinical tDCS and tACS, we analyzed two common setups for the location of the stimulation electrodes which target the frontal lobe and the occipital lobe, respectively. We compared lateral and medial electrode configuration with regard to theirusability. We were able to demonstrate that the lateral configurations yielded more focused stimulation areas as well as higher current intensities in the target areas. The high resolution of our simulation allows one to combine the modeled current flow with the knowledge of neuronal orientation to predict the consequences of tDCS and tACS. Our results not only offer a basis for a deeper understanding of the stimulation sites currently in use for clinical applications but also offer a better interpretation of observed effects.

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

    Science.gov (United States)

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

    2016-05-01

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

  4. Bonnet Ruled Surfaces

    Institute of Scientific and Technical Information of China (English)

    Filiz KANBAY

    2005-01-01

    We consider the Bonnet ruled surfaces which admit only one non-trivial isometry that preserves the principal curvatures. We determine the Bonnet ruled surfaces whose generators and orthogonal trajectories form a special net called an A-net.

  5. Cosmological diagrammatic rules

    CERN Document Server

    Giddings, Steven B

    2010-01-01

    A simple set of diagrammatic rules is formulated for perturbative evaluation of ``in-in" correlators, as is needed in cosmology and other nonequilibrium problems. These rules are both intuitive, and efficient for calculational purposes.

  6. Cosmological diagrammatic rules

    Energy Technology Data Exchange (ETDEWEB)

    Giddings, Steven B. [Department of Physics, University of California, Santa Barbara, CA 93106 (United States); Sloth, Martin S., E-mail: giddings@physics.ucsb.edu, E-mail: sloth@cern.ch [CERN, Physics Department, Theory Unit, CH-1211 Geneva 23 (Switzerland)

    2010-07-01

    A simple set of diagrammatic rules is formulated for perturbative evaluation of ''in-in'' correlators, as is needed in cosmology and other nonequilibrium problems. These rules are both intuitive, and efficient for calculational purposes.

  7. Parton model sum rules

    CERN Document Server

    Hinchliffe, Ian; Hinchliffe, Ian; Kwiatkowski, Axel

    1996-01-01

    This review article discusses the experimental and theoretical status of various Parton Model sum rules. The basis of the sum rules in perturbative QCD is discussed. Their use in extracting the value of the strong coupling constant is evaluated and the failure of the naive version of some of these rules is assessed.

  8. The Applicability of the Density Rule of Pathwardhan and Kumer and the Rule Based on Linear Isopiestic Relation

    Institute of Scientific and Technical Information of China (English)

    胡玉峰

    2001-01-01

    The applicability of the density rule of Pathwardhan and Kumer and the rule based on the linear isopiestic relation is studied by comparison with experimental density data in the literature. Predicted and measured values for 18 electrolyte mixtures are compared. The two rules are good for mixtures with and without common ions, including those containing associating ions. The deviations of the rule based on the linear isopiestic relation are slightly higher for the mixtures involving very strong ion complexes, but the predictions are still quite satisfactory.The density rule of Pathwardhan and Kumer is more accurate for these mixtures. However, it is not applicable for mixtures containing non-electrolytes. The rule based on the linear isopiestic relation is extended to mixtures involving non-electrolytes. The predictions for the mixtures containing both electrolytes and non-electrolytes and the non-electrolyte mixtures are accurate. All these results indicate that this rule is a widely avvlicable approach.

  9. The Applicability of the Density Rule of Pathwardhan and Kumer and the Rule Based on Linear Isopiestic Relation

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    The applicability of the density rule of Pathwardhan and Kumer and the rule based on the linear isopiestic relation is studied by comparison with experimental density data in the literature. Predicted and measured values for 18 electrolyte mixtures are compared. The two rules are good for mixtures with and without common ions, including those containing associating ions. The deviations of the rule based on the linear isopiestic relation are slightly higher for the mixtures involving very strong ion complexes, but the predictions are still quite satisfactory. The density rule of Pathwardhan and Kumer is more accurate for these mixtures. However, it is not applicable for mixtures containing non-electrolytes. The rule based on the linear isopiestic relation is extended to mixtures involving non-electrolytes. The predictions for the mixtures containing both electrolytes and non-electrolytes and the non-electrolyte mixtures are accurate. All these results indicate that this rule is a widely applicable approach.

  10. Predicting clinically significant response to cognitive behavior therapy for chronic insomnia in general medical practice: analysis of outcome data at 12 months posttreatment.

    Science.gov (United States)

    Espie, C A; Inglis, S J; Harvey, L

    2001-02-01

    The clinical efficacy of cognitive behavior therapy (CBT) for chronic insomnia has been established, yet clinical effectiveness is less clear. This study presents data on 109 patients from general practice during a formal evaluation of clinical effectiveness. Two thirds achieved normative values of or =50%. Logistic regression revealed that initial severity did not contraindicate good outcome. Rather, greater sleep disturbance was positively associated with large symptom reduction, although lower endpoint scores were less likely. Similarly, symptoms of anxiety, depression, and thinking errors positively predicted good outcome. Hypnotic using patients responded equally well to CBT, and demographic factors were of no significant predictive value. It is concluded that CBT is clinically and durably effective for persistent insomnia in routine practice.

  11. The value of integrating pre-clinical data to predict nausea and vomiting risk in humans as illustrated by AZD3514, a novel androgen receptor modulator.

    Science.gov (United States)

    Grant, Claire; Ewart, Lorna; Muthas, Daniel; Deavall, Damian; Smith, Simon A; Clack, Glen; Newham, Pete

    2016-04-01

    Nausea and vomiting are components of a complex mechanism that signals food avoidance and protection of the body against the absorption of ingested toxins. This response can also be triggered by pharmaceuticals. Predicting clinical nausea and vomiting liability for pharmaceutical agents based on pre-clinical data can be problematic as no single animal model is a universal predictor. Moreover, efforts to improve models are hampered by the lack of translational animal and human data in the public domain. AZD3514 is a novel, orally-administered compound that inhibits androgen receptor signaling and down-regulates androgen receptor expression. Here we have explored the utility of integrating data from several pre-clinical models to predict nausea and vomiting in the clinic. Single and repeat doses of AZD3514 resulted in emesis, salivation and gastrointestinal disturbances in the dog, and inhibited gastric emptying in rats after a single dose. AZD3514, at clinically relevant exposures, induced dose-responsive "pica" behaviour in rats after single and multiple daily doses, and induced retching and vomiting behaviour in ferrets after a single dose. We compare these data with the clinical manifestation of nausea and vomiting encountered in patients with castration-resistant prostate cancer receiving AZD3514. Our data reveal a striking relationship between the pre-clinical observations described and the experience of nausea and vomiting in the clinic. In conclusion, the emetic nature of AZD3514 was predicted across a range of pre-clinical models, and the approach presented provides a valuable framework for predicition of clinical nausea and vomiting.

  12. Which clinical parameters predict a positive CSF diagnosis of meningitis in a population with high HIV prevalence?

    Directory of Open Access Journals (Sweden)

    Will Loughborough

    2014-05-01

    Full Text Available Background. The HIV epidemic has changed the aetiology of meningitis in sub-Saharan Africa, and frontline clinicians are faced with a variety of meningitic presentations. Doctors working in resource-limited settings have the challenge of appropriately selecting patients for lumbar puncture (LP, a potentially risky procedure that requires laboratory analysis. Methods. In a rural South African hospital, the practice of performing LPs was audited against local guidelines. Data were collected retrospectively between February and June 2013. Symptoms and signs of meningitis, HIV status, investigations performed prior to LP and cerebrospinal fluid (CSF results were recorded. With the aim of determining statistically significant clinical predictors of meningitis, parameters were explored using univariate and multivariate logistic regression analyses.Results. A total of 107 patients were included, of whom 43% had an abnormal CSF result. The majority (76% of patients were HIV-positive (CD4+ cell count <200 cells/µl in 46%. Cryptococcal meningitis (CCM was the most prevalent microbiological diagnosis, confirmed in 10 out of 12 patients. Of the non-microbiological diagnoses, lymphocytic predominance was the most common abnormality, present in 17 out of 33 patients. Confusion (p=0.011 was the most statistically significant predictor of an abnormal CSF result. Headache (p=0.355, fever (p=0.660 and photophobia (p=0.634 were not statistically predictive.Conclusion. The high incidence of CCM correlates with previous data from sub-Saharan Africa. In populations with high HIV prevalence, the classic meningitic symptoms of headache, fever and photophobia, while common presenting symptoms, are significantly less predictive of a meningitis diagnosis than confusion.

  13. Utility of clinical assessment, imaging, and cryptococcal antigen titer to predict AIDS-related complicated forms of cryptococcal meningitis

    Directory of Open Access Journals (Sweden)

    Kandel Sean

    2010-08-01

    Full Text Available Abstract Background This study aimed to evaluate the prevalence and predictors of AIDS-related complicated cryptococcal meningitis. The outcome was complicated cryptococcal meningitis: prolonged (≥ 14 days altered mental status, persistent (≥ 14 days focal neurologic findings, cerebrospinal fluid (CSF shunt placement or death. Predictor variable operating characteristics were estimated using receiver operating characteristic curve (ROC analysis. Multivariate analysis identified independent predictors of the outcome. Results From 1990-2009, 82 patients with first episode of cryptococcal meningitis were identified. Of these, 14 (17% met criteria for complicated forms of cryptococcal meningitis (prolonged altered mental status 6, persistent focal neurologic findings 7, CSF surgical shunt placement 8, and death 5. Patients with complicated cryptococcal meningitis had higher frequency of baseline focal neurological findings, head computed tomography (CT abnormalities, mean CSF opening pressure, and cryptococcal antigen (CRAG titers in serum and CSF. ROC area of log2 serum and CSF CRAG titers to predict complicated forms of cryptococcal meningitis were comparable, 0.78 (95%CI: 0.66 to 0.90 vs. 0.78 (95% CI: 0.67 to 0.89, respectively (χ2, p = 0.95. The ROC areas to predict the outcomes were similar for CSF pressure and CSF CRAG titers. In a multiple logistic regression model, the following were significant predictors of the outcome: baseline focal neurologic findings, head CT abnormalities and log2 CSF CRAG titer. Conclusions During initial clinical evaluation, a focal neurologic exam, abnormal head CT and large cryptococcal burden measured by CRAG titer are associated with the outcome of complicated cryptococcal meningitis following 2 weeks from antifungal therapy initiation.

  14. Country, Sex, EDSS Change and Therapy Choice Independently Predict Treatment Discontinuation in Multiple Sclerosis and Clinically Isolated Syndrome

    Science.gov (United States)

    Jokubaitis, Vilija G.; Trojano, Maria; Izquierdo, Guillermo; Grand’Maison, François; Oreja-Guevara, Celia; Boz, Cavit; Lugaresi, Alessandra; Girard, Marc; Grammond, Pierre; Iuliano, Gerardo; Fiol, Marcela; Cabrera-Gomez, Jose Antonio; Fernandez-Bolanos, Ricardo; Giuliani, Giorgio; Lechner-Scott, Jeannette; Cristiano, Edgardo; Herbert, Joseph; Petkovska-Boskova, Tatjana; Bergamaschi, Roberto; van Pesch, Vincent; Moore, Fraser; Vella, Norbert; Slee, Mark; Santiago, Vetere; Barnett, Michael; Havrdova, Eva; Young, Carolyn; Sirbu, Carmen-Adella; Tanner, Mary; Rutherford, Michelle; Butzkueven, Helmut

    2012-01-01

    Objectives We conducted a prospective study, MSBASIS, to assess factors leading to first treatment discontinuation in patients with a clinically isolated syndrome (CIS) and early relapsing-remitting multiple sclerosis (RRMS). Methods The MSBASIS Study, conducted by MSBase Study Group members, enrols patients seen from CIS onset, reporting baseline demographics, cerebral magnetic resonance imaging (MRI) features and Expanded Disability Status Scale (EDSS) scores. Follow-up visits report relapses, EDSS scores, and the start and end dates of MS-specific therapies. We performed a multivariable survival analysis to determine factors within this dataset that predict first treatment discontinuation. Results A total of 2314 CIS patients from 44 centres were followed for a median of 2.7 years, during which time 1247 commenced immunomodulatory drug (IMD) treatment. Ninety percent initiated IMD after a diagnosis of MS was confirmed, and 10% while still in CIS status. Over 40% of these patients stopped their first IMD during the observation period. Females were more likely to cease medication than males (HR 1.36, p = 0.003). Patients treated in Australia were twice as likely to cease their first IMD than patients treated in Spain (HR 1.98, p = 0.001). Increasing EDSS was associated with higher rate of IMD cessation (HR 1.21 per EDSS unit, p<0.001), and intramuscular interferon-β-1a (HR 1.38, p = 0.028) and subcutaneous interferon-β-1a (HR 1.45, p = 0.012) had higher rates of discontinuation than glatiramer acetate, although this varied widely in different countries. Onset cerebral MRI features, age, time to treatment initiation or relapse on treatment were not associated with IMD cessation. Conclusion In this multivariable survival analysis, female sex, country of residence, EDSS change and IMD choice independently predicted time to first IMD cessation. PMID:22768046

  15. Country, sex, EDSS change and therapy choice independently predict treatment discontinuation in multiple sclerosis and clinically isolated syndrome.

    Directory of Open Access Journals (Sweden)

    Claire Meyniel

    Full Text Available OBJECTIVES: We conducted a prospective study, MSBASIS, to assess factors leading to first treatment discontinuation in patients with a clinically isolated syndrome (CIS and early relapsing-remitting multiple sclerosis (RRMS. METHODS: The MSBASIS Study, conducted by MSBase Study Group members, enrols patients seen from CIS onset, reporting baseline demographics, cerebral magnetic resonance imaging (MRI features and Expanded Disability Status Scale (EDSS scores. Follow-up visits report relapses, EDSS scores, and the start and end dates of MS-specific therapies. We performed a multivariable survival analysis to determine factors within this dataset that predict first treatment discontinuation. RESULTS: A total of 2314 CIS patients from 44 centres were followed for a median of 2.7 years, during which time 1247 commenced immunomodulatory drug (IMD treatment. Ninety percent initiated IMD after a diagnosis of MS was confirmed, and 10% while still in CIS status. Over 40% of these patients stopped their first IMD during the observation period. Females were more likely to cease medication than males (HR 1.36, p = 0.003. Patients treated in Australia were twice as likely to cease their first IMD than patients treated in Spain (HR 1.98, p = 0.001. Increasing EDSS was associated with higher rate of IMD cessation (HR 1.21 per EDSS unit, p<0.001, and intramuscular interferon-β-1a (HR 1.38, p = 0.028 and subcutaneous interferon-β-1a (HR 1.45, p = 0.012 had higher rates of discontinuation than glatiramer acetate, although this varied widely in different countries. Onset cerebral MRI features, age, time to treatment initiation or relapse on treatment were not associated with IMD cessation. CONCLUSION: In this multivariable survival analysis, female sex, country of residence, EDSS change and IMD choice independently predicted time to first IMD cessation.

  16. Current methods of assessing the accuracy of three-dimensional soft tissue facial predictions: technical and clinical considerations.

    Science.gov (United States)

    Khambay, B; Ullah, R

    2015-01-01

    Since the introduction of three-dimensional (3D) orthognathic planning software, studies have reported on their predictive ability. The aim of this study was to highlight the limitations of the current methods of analysis. The predicted 3D soft tissue image was compared to the postoperative soft tissue. For the full face, the maximum and 95th and 90th percentiles, the percentage of 3D mesh points ≤ 2 mm, and the root mean square (RMS) error, were calculated. For specific anatomical regions, the percentage of 3D mesh points ≤ 2 mm and the distance between the two meshes at 10 landmarks were determined. For the 95th and 90th percentiles, the maximum difference ranged from 7.7 mm to 2.2 mm and from 3.7 mm to 1.5 mm, respectively. The absolute mean distance ranged from 0.98 mm to 0.56 mm and from 0.91 mm to 0.50 mm, respectively. The percentage of mesh with ≤ 2 mm for the full face was 94.4-85.2% and 100-31.3% for anatomical regions. The RMS error ranged from 2.49 mm to 0.94 mm. The majority of mean linear distances between the surfaces were ≤ 0.8 mm, but increased for the mean absolute distance. At present the use of specific anatomical regions is more clinically meaningful than the full face. It is crucial to understand these and adopt a protocol for conducting such studies.

  17. A predictive genetic signature for response to fluoropyrimidine-based neoadjuvant chemoradiation in clinical Stage II and III rectal cancer

    Directory of Open Access Journals (Sweden)

    Jason eChan

    2013-11-01

    Full Text Available PurposePreoperative chemoradiation is currently the standard of care for patients with clinical stage II and III rectal cancer but only about 45% of patients achieve tumor downstaging and less than 20% of patients achieve a pathologic complete response. Better methods to stratify patients according to potential neoadjuvant treatment response are needed. We used microarray analysis to identify a genetic signature that correlates with a pathological complete response to neoadjuvant chemoradiation. We performed a gene network analysis to identify potential signaling pathways involved in determining response to neoadjuvant treatment.Patients and MethodsWe identified 31 T3-4 N0-1 rectal cancer patients who were treated with neoadjuvant fluorouracil-based chemoradiation. 8 patients were identified to have achieved a pathological complete response to treatment while 23 patients did not. mRNA expression was analyzed using cDNA microarrays. The correlation between mRNA expression and pathological complete response from pre-treatment tumor biopsies was determined. Gene network analysis was performed for the genes represented by the predictive signature.ResultsA genetic signature represented by expression levels of the 3 genes EHBP1, STAT1, and GAPDH was found to correlate with a pathological complete response to neoadjuvant treatment. The difference in expression levels between patients who achieved a pathological complete response and those who did not was greatest for EHBP1. Gene network analysis showed that the 3 genes can be connected by the gene UBC. ConclusionThis study identifies a 3-gene signature expressed in pre-treatment tumor biopsies that correlates with a pathological complete response to neoadjuvant chemoradiation in patients with clinical stage II and III rectal cancer. These 3 genes can be connected by the gene UBC, suggesting that ubiquination is a molecular mechanism involved in determining response to treatment. Validating this genet

  18. The prognostic blood biomarker proadrenomedullin for outcome prediction in patients with chronic obstructive pulmonary disease (COPD): a qualitative clinical review.

    Science.gov (United States)

    Schuetz, Philipp; Marlowe, Robert J; Mueller, Beat

    2015-03-01

    Plasma proadrenomedullin (ProADM) is a blood biomarker that may aid in multidimensional risk assessment of patients with chronic obstructive pulmonary disease (COPD). Co-secreted 1:1 with adrenomedullin (ADM), ProADM is a less biologically active, more chemically stable surrogate for this pluripotent regulatory peptide, which due to biological and ex vivo physical characteristics is difficult to reliably directly quantify. Upregulated by hypoxia, inflammatory cytokines, bacterial products, and shear stress and expressed widely in pulmonary cells and ubiquitously throughout the body, ADM exerts or mediates vasodilatory, natriuretic, diuretic, antioxidative, anti-inflammatory, antimicrobial, and metabolic effects. Observational data from four separate studies totaling 1366 patients suggest that as a single factor, ProADM is a significant independent, and accurate, long-term all-cause mortality predictor in COPD. This body of work also suggests that combined with different groups of demographic/clinical variables, ProADM provides significant incremental long-term mortality prediction power relative to the groups of variables alone. Additionally, the literature contains indications that ProADM may be a global cardiopulmonary stress marker, potentially supplying prognostic information when cardiopulmonary exercise testing results such as 6-min walk distance are unavailable due to time or other resource constraints or to a patient's advanced disease. Prospective, randomized, controlled interventional studies are needed to demonstrate whether ProADM use in risk-based guidance of site-of-care, monitoring, and treatment decisions improves