Scores to predict major bleeding risk during oral anticoagulation therapy: a prospective validation study.

BACKGROUND: Clinical scores may help physicians to better assess the individual risk/benefit of oral anticoagulant therapy. We aimed to externally validate and compare the prognostic performance of 7 clinical prediction scores for major bleeding events during oral anticoagulation therapy. METHODS: We followed 515 adult patients taking oral anticoagulants to measure the first major bleeding event over a 12-month follow-up period. The performance of each score to predict the risk of major bleeding and the physician's subjective assessment of bleeding risk were compared with the C statistic. RESULTS: The cumulative incidence of a first major bleeding event during follow-up was 6.8% (35/515). According to the 7 scoring systems, the proportions of major bleeding ranged from 3.0% to 5.7% for low-risk, 6.7% to 9.9% for intermediate-risk, and 7.4% to 15.4% for high-risk patients. The overall predictive accuracy of the scores was poor, with the C statistic ranging from 0.54 to 0.61 and not significantly different from each other (P=.84). Only the Anticoagulation and Risk Factors in Atrial Fibrillation score performed slightly better than would be expected by chance (C statistic, 0.61; 95% confidence interval, 0.52-0.70). The performance of the scores was not statistically better than physicians' subjective risk assessments (C statistic, 0.55; P=.94). CONCLUSION: The performance of 7 clinical scoring systems in predicting major bleeding events in patients receiving oral anticoagulation therapy was poor and not better than physicians' subjective assessments.

Estimating the risk of developing type 2 diabetes: a comparison of several risk scores: the Cohorte Lausannoise study.

To compare in the Swiss population the results of several scores estimating the risk of developing type 2 diabetes. This was a single-center, cross-sectional study conducted between 2003 and 2006 in Lausanne, Switzerland. Overall, 3,251 women and 2,937 men, aged 35-75 years, were assessed, of which 5,760 (93%) were free from diabetes and included in the current study. The risk of developing type 2 diabetes was assessed using seven different risk scores, including clinical data with or without biological data. Participants were considered to be eligible for primary prevention according to the thresholds provided for each score. The results were then extrapolated to the Swiss population of the same sex and age. The risk of developing type 2 diabetes increased with age in all scores. The prevalence of participants at high risk ranged between 1.6 and 24.9% in men and between 1.1 and 15.7% in women. Extrapolated to the Swiss population of similar age, the overall number of participants at risk, and thus susceptible to intervention, ranged between 46,708 and 636,841. In addition, scores that included the same clinical variables led to a significantly different prevalence of participants at risk (4.2% [95% CI 3.4-5.0] vs. 12.8% [11.5-14.1] in men and 2.9% [2.4-3.6] vs. 6.0% [5.2-6.9] in women). CONCLUSIONS; The prevalence of participants at risk for developing type 2 diabetes varies considerably according to the scoring system used. To adequately prevent type 2 diabetes, risk-scoring systems must be validated for each population considered.

Scores de mesure fonctionnelle articulaire pour le praticien [Joint functional outcome score for the clinician].

The sports clinician faces multiple treatment options when dealing with overload injuries, and it is important to evaluate their outcomes. Multiple scores exist, some clincian rated (CRO), others patient rated (PRO), the latter being currently favoured. This review presents some of these scores and we selected the ones we feel are the most appropriate for a sports clinician. We considered these common problems: tennis elbow, rotator cuff issues, groin pain, patellofemoral pain syndrome, achilles tendinopathy and ankle instability. In addition, an activity level score is useful to weigh the result in the context of return to performance. These scores help to create a common language between therapists and to evaluate treatments objectively.

Prospective, multicenter validation of prediction scores for major bleeding in elderly patients with venous thromboembolism.

BACKGROUND: The Outpatient Bleeding Risk Index (OBRI) and the Kuijer, RIETE and Kearon scores are clinical prognostic scores for bleeding in patients receiving oral anticoagulants for venous thromboembolism (VTE). We prospectively compared the performance of these scores in elderly patients with VTE. METHODS: In a prospective multicenter Swiss cohort study, we studied 663 patients aged ≥ 65 years with acute VTE. The outcome was a first major bleeding at 90 days. We classified patients into three categories of bleeding risk (low, intermediate and high) according to each score and dichotomized patients as high vs. low or intermediate risk. We calculated the area under the receiver-operating characteristic (ROC) curve, positive predictive values and likelihood ratios for each score. RESULTS: Overall, 28 out of 663 patients (4.2%, 95% confidence interval [CI] 2.8-6.0%) had a first major bleeding within 90 days. According to different scores, the rate of major bleeding varied from 1.9% to 2.1% in low-risk, from 4.2% to 5.0% in intermediate-risk and from 3.1% to 6.6% in high-risk patients. The discriminative power of the scores was poor to moderate, with areas under the ROC curve ranging from 0.49 to 0.60 (P = 0.21). The positive predictive values and positive likelihood ratios were low and varied from 3.1% to 6.6% and from 0.72 to 1.59, respectively. CONCLUSION: In elderly patients with VTE, existing bleeding risk scores do not have sufficient accuracy and power to discriminate between patients with VTE who are at a high risk of short-term major bleeding and those who are not.

The association between alcohol screening scores and health status in male veterans.

OBJECTIVES: Alcohol use is associated with self-reported health status. However, little is known about the concurrent association between alcohol screening scores and patient perception of health. We evaluated this association in a sample of primarily older male veterans.METHODS: This secondary, cross-sectional analysis included male general medicine outpatients from 7 VA medical centers who returned mailed questionnaires. Screening scores from the Alcohol Use Disorders Identification Test Consumption (AUDIT-C) questionnaire were divided into 6 categories (0, 1­3, 4­5, 6­7, 8­9, and 10­12). Outcomes included scores on the 8 subscales and 2 component scores of the 36-item Short Form Health Survey (SF-36). Unadjusted and adjusted linear regression models were fit to characterize the association between AUDIT-C categories and SF-36 scores. Models were adjusted for demographic characteristics, smoking, and site?both alone and in combination with 14 self-reported comorbid conditions.RESULTS: Male respondents (n = 24,531; mean age = 63.6 years) represented 69% of those surveyed with the SF-36. After adjustment, a quadratic (inverted U-shaped) relationship was demonstrated between AUDIT-C categories and all SF-36 scores such that patients with AUDIT-C scores 4­5 or 6­7 reported the highest health status, and patients with AUDIT-C scores 0, 8­9, and =10 reported the lowest health status.CONCLUSIONS: Across all measures of health status, patients with the most severe alcohol misuse had significantly poorer health status than those who screened positive for alcohol misuse at mild or moderate levels of severity. The relatively good health status reported by patients with mild-moderate alcohol misuse might interfere with clinicians' acceptance and adoption of guidelines recommending that they counsel these patients about their drinking.

Predicting clinical scores from magnetic resonance scans in Alzheimer's disease.

Machine learning and pattern recognition methods have been used to diagnose Alzheimer's disease (AD) and mild cognitive impairment (MCI) from individual MRI scans. Another application of such methods is to predict clinical scores from individual scans. Using relevance vector regression (RVR), we predicted individuals' performances on established tests from their MRI T1 weighted image in two independent data sets. From Mayo Clinic, 73 probable AD patients and 91 cognitively normal (CN) controls completed the Mini-Mental State Examination (MMSE), Dementia Rating Scale (DRS), and Auditory Verbal Learning Test (AVLT) within 3months of their scan. Baseline MRI's from the Alzheimer's disease Neuroimaging Initiative (ADNI) comprised the other data set; 113 AD, 351 MCI, and 122 CN subjects completed the MMSE and Alzheimer's Disease Assessment Scale-Cognitive subtest (ADAS-cog) and 39 AD, 92 MCI, and 32 CN ADNI subjects completed MMSE, ADAS-cog, and AVLT. Predicted and actual clinical scores were highly correlated for the MMSE, DRS, and ADAS-cog tests (P<0.0001). Training with one data set and testing with another demonstrated stability between data sets. DRS, MMSE, and ADAS-Cog correlated better than AVLT with whole brain grey matter changes associated with AD. This result underscores their utility for screening and tracking disease. RVR offers a novel way to measure interactions between structural changes and neuropsychological tests beyond that of univariate methods. In clinical practice, we envision using RVR to aid in diagnosis and predict clinical outcome.

Scores composites CHC pour la WAIS-IV : normes francophones

Les résultats des recherches contemporaines, montrant notamment l'importance du raisonnement fluide, de la mémoire de travail (IMT) et de la vitesse de traitement (IVT) dans le fonctionnement cognitif, ont conduit les concepteurs de la WAIS-IV à introduire de nouvelles épreuves pour renforcer l'évaluation de ces dimensions cognitives. L'interprétation des scores de la WAIS-IV repose maintenant sur quatre indices factoriels (ICV, IRP, IMT et IVT), ainsi que sur le QIT. Les concepteurs de la WAIS-IV indiquent que l'un des objectifs de la révision consistait à actualiser les fondements théoriques de cette échelle. Pourtant, la structure globale de la WAIS-IV ne correspond que partiellement à celle proposée dans le modèle qui fait consensus aujourd'hui, le modèle de Cattell-Horn-Carroll (CHC). Par exemple, la WAIS-IV ne propose pas d'indice de raisonnement fluide, bien que les constructeurs soulignent l'importance de cette dimension dans le fonctionnement cognitif. Dans cet article, nous proposons, pour la WAIS-IV, les normes francophones de cinq scores composites CHC, à savoir le raisonnement fluide (Gf), compréhension-connaissances (Gc), le traitement visuel (Gv), la mémoire à court terme (Gsm), et l'IVT (Gs). Ces normes ont été établies en utilisant une procédure d'approximation statistique. À l'instar des scores CHC que nous avons proposés pour le WISCIV, ces normes pour la WAIS-IV permettent aux cliniciens de basculer vers une grille d'interprétation basée sur le modèle dominant et d'utiliser les cinq scores composites CHC en complément des quatre indices standard dans le cadre d'analyses normatives et ipsatives.

Test of four colon cancer risk-scores in formalin fixed paraffin embedded microarray gene expression data.

BACKGROUND: Prognosis prediction for resected primary colon cancer is based on the T-stage Node Metastasis (TNM) staging system. We investigated if four well-documented gene expression risk scores can improve patient stratification. METHODS: Microarray-based versions of risk-scores were applied to a large independent cohort of 688 stage II/III tumors from the PETACC-3 trial. Prognostic value for relapse-free survival (RFS), survival after relapse (SAR), and overall survival (OS) was assessed by regression analysis. To assess improvement over a reference, prognostic model was assessed with the area under curve (AUC) of receiver operating characteristic (ROC) curves. All statistical tests were two-sided, except the AUC increase. RESULTS: All four risk scores (RSs) showed a statistically significant association (single-test, P < .0167) with OS or RFS in univariate models, but with HRs below 1.38 per interquartile range. Three scores were predictors of shorter RFS, one of shorter SAR. Each RS could only marginally improve an RFS or OS model with the known factors T-stage, N-stage, and microsatellite instability (MSI) status (AUC gains < 0.025 units). The pairwise interscore discordance was never high (maximal Spearman correlation = 0.563) A combined score showed a trend to higher prognostic value and higher AUC increase for OS (HR = 1.74, 95% confidence interval [CI] = 1.44 to 2.10, P < .001, AUC from 0.6918 to 0.7321) and RFS (HR = 1.56, 95% CI = 1.33 to 1.84, P < .001, AUC from 0.6723 to 0.6945) than any single score. CONCLUSIONS: The four tested gene expression-based risk scores provide prognostic information but contribute only marginally to improving models based on established risk factors. A combination of the risk scores might provide more robust information. Predictors of RFS and SAR might need to be different.

Bias related to body mass index in pediatric echocardiographic z scores.

In pediatric echocardiography, cardiac dimensions are often normalized for weight, height, or body surface area (BSA). The combined influence of height and weight on cardiac size is complex and likely varies with age. We hypothesized that increasing weight for height, as represented by body mass index (BMI) adjusted for age, is poorly accounted for in Z scores normalized for weight, height, or BSA. We aimed to evaluate whether a bias related to BMI was introduced when proximal aorta diameter Z scores are derived from bivariate models (only one normalizing variable), and whether such a bias was reduced when multivariable models are used. We analyzed 1,422 echocardiograms read as normal in children ≤18 years. We computed Z scores of the proximal aorta using allometric, polynomial, and multivariable models with four body size variables. We then assessed the level of residual association of Z scores and BMI adjusted for age and sex. In children ≥6 years, we found a significant residual linear association with BMI-for-age and Z scores for most regression models. Only a multivariable model including weight and height as independent predictors produced a Z score free of linear association with BMI. We concluded that a bias related to BMI was present in Z scores of proximal aorta diameter when normalization was done using bivariate models, regardless of the regression model or the normalizing variable. The use of multivariable models with weight and height as independent predictors should be explored to reduce this potential pitfall when pediatric echocardiography reference values are evaluated.