ASTRAL Score Predicts 5-Year Dependence and Mortality in Acute Ischemic Stroke.

BACKGROUND AND PURPOSE: The ASTRAL score was externally validated showing remarkable consistency on 3-month outcome prognosis in patients with acute ischemic stroke. The present study aimed to evaluate ASTRAL score's prognostic accuracy to predict 5-year outcome. METHODS: All consecutive patients with acute ischemic stroke registered in the Athens Stroke Registry between January 1, 1998, and December 31, 2010, were included. Patients were excluded if admitted >24 hours after symptom onset or if any ASTRAL score component was missing. End points were 5-year unfavorable functional outcome, defined as modified Rankin Scale 3 to 6, and 5-year mortality. For each outcome, the area under the receiver operating characteristics curve was calculated; also, a multivariate Cox proportional hazards analysis was performed to investigate whether the ASTRAL score was an independent predictor of outcome. The Kaplan-Meier product limit method was used to estimate the probability of 5-year survival for each ASTRAL score quartile. RESULTS: The area under the receiver operating characteristics curve of the score to predict 5-year unfavorable functional outcome was 0.89, 95% confidence interval 0.88 to 0.91. In multivariate Cox proportional hazards analysis, the ASTRAL score was independently associated with 5-year unfavorable functional outcome (hazard ratio, 1.09; 95% confidence interval, 1.08-1.10). The area under the receiver operating characteristics curve for the ASTRAL score's discriminatory power to predict 5-year mortality was 0.81 (95% confidence interval, 0.78-0.83). In multivariate analysis, the ASTRAL score was independently associated with 5-year mortality (hazard ratio, 1.09, 95% confidence interval, 1.08-1.10). During the 5-year follow-up, the probability of survival was significantly lower with increasing ASTRAL score quartiles (log-rank test <0.001). CONCLUSIONS: The ASTRAL score reliably predicts 5-year functional outcome and mortality in patients with acute ischemic stroke.

Growth arrest-specific gene 6 (GAS6) as an intra-hospital mortality predictor for patients in septic shock

Aim: Gas6 is known to be elevated in sepsis, correlating with the severity of infection and organ failure. We aimed to investigate the performance of Gas6 plasma levels at admission to predict the risk of mortality in a cohort of septic patients.Methods: We used prospectively collected data and plasma samples from the 'Sepsis Cohorte Romande'. Gas6 level was measured by ELISA at admission and expressed in percentage relative to its level in a pool of normal plasma.Results: Non-survivors (n = 19) presented higher Gas6 levels than survivors (n = 78; median 287% vs. 158%, IQR 182 and 119 respectively; P = 0.0003). Gas6 correlated positively with different cytokine and was the best mortality predictor, as shown by the ROC curves area (Fig. 1). In patients with septic shock (n = 67), using 249% as a cut-off value, Gas6 measurement had a specificity of 81% and a sensitivity of 68% for predicting mortality. ROC curve area was 0.76. Positive and negative predictive values were 59% and 87%, respectively.Conclusion: Thus, Gas6 plasma level at admission might be a useful tool to predict mortality in patients with septic shock. Nevertheless, independent association of Gas6 level with mortality still needs to be assessed. Although Gas6 hold promise as an early sepsis marker, its precise implication in sepsis remains to be elucidated.

Generalized linear and generalized additive models in studies of species distributions: setting the scene

An important statistical development of the last 30 years has been the advance in regression analysis provided by generalized linear models (GLMs) and generalized additive models (GAMs). Here we introduce a series of papers prepared within the framework of an international workshop entitled: Advances in GLMs/GAMs modeling: from species distribution to environmental management, held in Riederalp, Switzerland, 6-11 August 2001.We first discuss some general uses of statistical models in ecology, as well as provide a short review of several key examples of the use of GLMs and GAMs in ecological modeling efforts. We next present an overview of GLMs and GAMs, and discuss some of their related statistics used for predictor selection, model diagnostics, and evaluation. Included is a discussion of several new approaches applicable to GLMs and GAMs, such as ridge regression, an alternative to stepwise selection of predictors, and methods for the identification of interactions by a combined use of regression trees and several other approaches. We close with an overview of the papers and how we feel they advance our understanding of their application to ecological modeling.

Oxygen uptake kinetics and middle distance swimming performance.

OBJECTIVE: The aim of this study was to determine whether V˙O(2) kinetics and specifically, the time constant of transitions from rest to heavy (τ(p)H) and severe (τ(p)S) exercise intensities, are related to middle distance swimming performance. DESIGN: Fourteen highly trained male swimmers (mean ± SD: 20.5 ± 3.0 yr; 75.4 ± 12.4 kg; 1.80 ± 0.07 m) performed an discontinuous incremental test, as well as square wave transitions for heavy and severe swimming intensities, to determine V˙O(2) kinetics parameters using two exponential functions. METHODS: All the tests involved front-crawl swimming with breath-by-breath analysis using the Aquatrainer swimming snorkel. Endurance performance was recorded as the time taken to complete a 400 m freestyle swim within an official competition (T400), one month from the date of the other tests. RESULTS: T400 (Mean ± SD) (251.4 ± 12.4 s) was significantly correlated with τ(p)H (15.8 ± 4.8s; r=0.62; p=0.02) and τ(p)S (15.8 ± 4.7s; r=0.61; p=0.02). The best single predictor of 400 m freestyle time, out of the variables that were assessed, was the velocity at V˙O(2max)vV˙O(2max), which accounted for 80% of the variation in performance between swimmers. However, τ(p)H and V˙O(2max) were also found to influence the prediction of T400 when they were included in a regression model that involved respiratory parameters only. CONCLUSIONS: Faster kinetics during the primary phase of the V˙O(2) response is associated with better performance during middle-distance swimming. However, vV˙O(2max) appears to be a better predictor of T400.

Biotic and abiotic variables show little redundancy in explaining tree species distributions

Abiotic factors such as climate and soil determine the species fundamental niche, which is further constrained by biotic interactions such as interspecific competition. To parameterize this realized niche, species distribution models (SDMs) most often relate species occurrence data to abiotic variables, but few SDM studies include biotic predictors to help explain species distributions. Therefore, most predictions of species distributions under future climates assume implicitly that biotic interactions remain constant or exert only minor influence on large-scale spatial distributions, which is also largely expected for species with high competitive ability. We examined the extent to which variance explained by SDMs can be attributed to abiotic or biotic predictors and how this depends on species traits. We fit generalized linear models for 11 common tree species in Switzerland using three different sets of predictor variables: biotic, abiotic, and the combination of both sets. We used variance partitioning to estimate the proportion of the variance explained by biotic and abiotic predictors, jointly and independently. Inclusion of biotic predictors improved the SDMs substantially. The joint contribution of biotic and abiotic predictors to explained deviance was relatively small (similar to 9%) compared to the contribution of each predictor set individually (similar to 20% each), indicating that the additional information on the realized niche brought by adding other species as predictors was largely independent of the abiotic (topo-climatic) predictors. The influence of biotic predictors was relatively high for species preferably growing under low disturbance and low abiotic stress, species with long seed dispersal distances, species with high shade tolerance as juveniles and adults, and species that occur frequently and are dominant across the landscape. The influence of biotic variables on SDM performance indicates that community composition and other local biotic factors or abiotic processes not included in the abiotic predictors strongly influence prediction of species distributions. Improved prediction of species' potential distributions in future climates and communities may assist strategies for sustainable forest management.

HIV-1 Subtype Is an Independent Predictor of Reverse Transcriptase Mutation K65R in HIV-1 Patients Treated with Combination Antiretroviral Therapy Including Tenofovir.

Subtype-dependent selection of HIV-1 reverse transcriptase resistance mutation K65R was previously observed in cell culture and small clinical investigations. We compared K65R prevalence across subtypes A, B, C, F, G, and CRF02_AG separately in a cohort of 3,076 patients on combination therapy including tenofovir. K65R selection was significantly higher in HIV-1 subtype C. This could not be explained by clinical and demographic factors in multivariate analysis, suggesting subtype sequence-specific K65R pathways.

A non-randomized direct comparison of cognitive-behavioral short- and long-term treatment for binge eating disorder

Background: To compare treatment outcomes of a cognitive-behavioral long-term (CBT-L) and short-term (CBT-S) treatment for binge eating disorder (BED) in a non-randomized comparison and to identify moderators of treatment outcome. Methods: 76 female patients with BED participated in the study: 40 in CBT-L and 36 in CBT-S. Outcome values were compared at the end of the active treatment phase (16 sessions for CBT-L, 8 sessions for CBT-S) and at 12-month follow-up. Results: Both treatments produced significant reductions in binge eating. At the end of active treatment, but not at the end of follow-up, effects of primary outcomes (e.g. remission from binge eating, EDE shape concern) were better for CBT-L than for CBT-S. Dropout rates were significantly higher in CBT-L (35%) than in CBT-S (14%). Moderator analyses revealed that treatment efficacy for rapid responders and individuals exhibiting high scores on the mixed dietary negative affect subtype differed between the CBT-L and CBT-S with respect to objective binges, restraint eating and eating concern. Conclusion: Findings suggest that CBT in general represents an effective treatment for BED, but that subgroups of patients might profit more from a prolonged treatment. Short, lessintensive CBT treatments could nevertheless be a viable option in the treatment of BED.

TBS (trabecular bone score) and diabetes-related fracture risk.

CONTEXT: Type 2 diabetes is associated with increased fracture risk but paradoxically greater bone mineral density (BMD). Trabecular bone score (TBS) is derived from the texture of the spine dual x-ray absorptiometry (DXA) image and is related to bone microarchitecture and fracture risk, providing information independent of BMD. OBJECTIVE: This study evaluated the ability of lumbar spine TBS to account for increased fracture risk in diabetes. DESIGN AND SETTING: We performed a retrospective cohort study using BMD results from a large clinical registry for the province of Manitoba, Canada. Patients: We included 29,407 women 50 years old and older with baseline DXA examinations, among whom 2356 had diagnosed diabetes. MAIN OUTCOME MEASURES: Lumbar spine TBS was derived for each spine DXA examination blinded to clinical parameters and outcomes. Health service records were assessed for incident nontraumatic major osteoporotic fractures (mean follow-up 4.7 years). RESULTS: Diabetes was associated with higher BMD at all sites but lower lumbar spine TBS in unadjusted and adjusted models (all P < .001). The adjusted odds ratio (aOR) for a measurement in the lowest vs the highest tertile was less than 1 for BMD (all P < .001) but was increased for lumbar spine TBS [aOR 2.61, 95% confidence interval (CI) 2.30-2.97]. Major osteoporotic fractures were identified in 175 women (7.4%) with and 1493 (5.5%) without diabetes (P < .001). Lumbar spine TBS was a BMD-independent predictor of fracture and predicted fractures in those with diabetes (adjusted hazard ratio 1.27, 95% CI 1.10-1.46) and without diabetes (hazard ratio 1.31, 95% CI 1.24-1.38). The effect of diabetes on fracture was reduced when lumbar spine TBS was added to a prediction model but was paradoxically increased from adding BMD measurements. CONCLUSIONS: Lumbar spine TBS predicts osteoporotic fractures in those with diabetes, and captures a larger portion of the diabetes-associated fracture risk than BMD.

Adherence as a predictor of the development of class-specific resistance mutations: the Swiss HIV Cohort Study.

BACKGROUND: Non-adherence is one of the strongest predictors of therapeutic failure in HIV-positive patients. Virologic failure with subsequent emergence of resistance reduces future treatment options and long-term clinical success. METHODS: Prospective observational cohort study including patients starting new class of antiretroviral therapy (ART) between 2003 and 2010. Participants were naïve to ART class and completed ≥1 adherence questionnaire prior to resistance testing. Outcomes were development of any IAS-USA, class-specific, or M184V mutations. Associations between adherence and resistance were estimated using logistic regression models stratified by ART class. RESULTS: Of 314 included individuals, 162 started NNRTI and 152 a PI/r regimen. Adherence was similar between groups with 85% reporting adherence ≥95%. Number of new mutations increased with increasing non-adherence. In NNRTI group, multivariable models indicated a significant linear association in odds of developing IAS-USA (odds ratio (OR) 1.66, 95% confidence interval (CI): 1.04-2.67) or class-specific (OR 1.65, 95% CI: 1.00-2.70) mutations. Levels of drug resistance were considerably lower in PI/r group and adherence was only significantly associated with M184V mutations (OR 8.38, 95% CI: 1.26-55.70). Adherence was significantly associated with HIV RNA in PI/r but not NNRTI regimens. CONCLUSION: Therapies containing PI/r appear more forgiving to incomplete adherence compared with NNRTI regimens, which allow higher levels of resistance, even with adherence above 95%. However, in failing PI/r regimens good adherence may prevent accumulation of further resistance mutations and therefore help to preserve future drug options. In contrast, adherence levels have little impact on NNRTI treatments once the first mutations have emerged.

Growth arrest-specific gene 6 » (Gas6) as an intra-hospital mortality predictor for patients in septic shock

Aim: Gas6 is known to be elevated in sepsis, correlating with the severity of infection and¦organ failure. We aimed to investigate the performance of Gas6 plasma levels at¦admission to predict the risk of mortality in a cohort of septic patients.¦Methods: We used prospectively collected data and plasma samples from the "Sepsis¦Cohorte Romande". Gas6 level was measured by ELISA at admission and expressed in¦percentage relative to its level in a pool of normal plasma.¦Results: Non-survivors (n=21) presented higher Gas6 levels than survivors (n=73) (median¦258% vs 164%, IQR 194 and 117 respectively) (p=0.0027). Gas6 correlated positively with¦different cytokines and was the best mortality predictor, as shown by the ROC curves area.¦In patients with septic shock (n=66), using 249% as a cut-off value, Gas6 measurement¦had a specificity of 67% and a sensitivity of 81% for predicting mortality. ROC curve area¦was 0.75. Positive and negative predictive values were 57% and 87%, respectively.¦Conclusion: Thus, Gas6 plasma level at admission might be a useful tool to predict¦mortality in patients with septic shock. Although Gas6 hold promise as an early sepsis¦marker, its precise implication in sepsis remains to be elucidated. Our observation should¦be further investigated in larger prospective clinical trials.

Clinical and ultrasonographic predictors of joint replacement for knee osteoarthritis: results from a large, 3-year, prospective EULAR study.

OBJECTIVES: To determine clinical and ultrasonographic predictors of joint replacement surgery across Europe in primary osteoarthritis (OA) of the knee. METHODS: This was a 3-year prospective study of a painful OA knee cohort (from a EULAR-sponsored, multicentre study). All subjects had clinical evaluation, radiographs and ultrasonography (US) at study entry. The rate of knee replacement surgery over the 3-year follow-up period was determined using Kaplan-Meier survival data analyses. Predictive factors for joint replacement were identified by univariate log-rank test then multivariate analysis using a Cox proportional-hazards regression model. Potential baseline predictors included demographic, clinical, radiographic and US features. RESULTS: Of the 600 original patients, 531 (88.5%), mean age 67+/-10 years, mean disease duration 6.1+/-6.9 years, had follow-up data and were analysed. During follow-up (median 3 years; range 0-4 years), knee replacement was done or required for 94 patients (estimated event rate of 17.7%). In the multivariate analysis, predictors of joint replacement were as follows: Kellgren and Lawrence radiographic grade (grade &gt; or =III vs &lt;III, hazards ratio (HR) = 4.08 (95% CI 2.34 to 7.12), p&lt;0.0001); ultrasonographic knee effusion (&gt; or =4 mm vs &lt;4 mm) (HR = 2.63 (95% CI 1.70 to 4.06), p&lt;0.0001); knee pain intensity on a 0-100 mm visual analogue scale (&gt; or =60 vs &lt;60) (HR = 1.81 (95% CI 1.15 to 2.83), p=0.01) and disease duration (&gt; or =5 years vs &lt;5 years) (HR=1.63 (95% CI 1.08 to 2.47), p=0.02). Clinically detected effusion and US synovitis were not associated with joint replacement in the univariate analysis. CONCLUSION: Longitudinal evaluation of this OA cohort demonstrated significant progression to joint replacement. In addition to severity of radiographic damage and pain, US-detected effusion was a predictor of subsequent joint replacement.

Individual responses to converting enzyme inhibitors and calcium antagonists.

This study was designed to assess whether the acute blood pressure response of an individual hypertensive patient to a calcium antagonist or an angiotensin converting enzyme (ACE) inhibitor is a good predictor of the long-term efficacy of these drug classes in this particular patient. The concept that good responses to ACE inhibitors and calcium antagonists may be mutually exclusive was also tested. Sixteen patients were included in a randomized crossover trial of enalapril, 20 mg daily, and diltiazem, 120 mg daily, for 6 weeks each. Blood pressure was measured by ambulatory blood pressure recording. During the washout phase, the acute effect of nifedipine, 10 mg p.o., and enalaprilat, 5 mg i.v., was evaluated. Nifedipine and enalaprilat reduced blood pressure equally well. The long-term blood pressure reduction induced by enalapril and diltiazem was similar. The acute blood pressure response to a given drug was not a good predictor of the result obtained with long-term therapy. No age dependency of the antihypertensive effect of either drug class was apparent. There was no evidence that a good response to one drug excluded a similarly good response to the other.

Association between the A-2518G polymorphism in the monocyte chemoattractant protein-1 gene and insulin resistance and Type 2 diabetes mellitus.

AIMS/HYPOTHESIS: The molecular mechanisms of obesity-related insulin resistance are incompletely understood. Macrophages accumulate in adipose tissue of obese individuals. In obesity, monocyte chemoattractant protein-1 (MCP-1), a key chemokine in the process of macrophage accumulation, is overexpressed in adipose tissue. MCP-1 is an insulin-responsive gene that continues to respond to exogenous insulin in insulin-resistant adipocytes and mice. MCP-1 decreases insulin-stimulated glucose uptake into adipocytes. The A-2518G polymorphism in the distal regulatory region of MCP-1 may regulate gene expression. The aim of this study was to investigate the impact of this gene polymorphism on insulin resistance. METHODS: We genotyped the Ludwigshafen Risk and Cardiovascular Health (LURIC) cohort ( n=3307). Insulin resistance, estimated by homeostasis model assessment, and Type 2 diabetes were diagnosed in 803 and 635 patients respectively. RESULTS: Univariate analysis revealed that plasma MCP-1 levels were significantly and positively correlated with WHR ( p=0.011), insulin resistance ( p=0.0097) and diabetes ( p<0.0001). Presence of the MCP-1 G-2518 allele was associated with decreased plasma MCP-1 ( p=0.017), a decreased prevalence of insulin resistance (odds ratio [OR]=0.82, 95% CI: 0.70-0.97, p=0.021) and a decreased prevalence of diabetes (OR=0.80, 95% CI: 0.67-0.96, p=0.014). In multivariate analysis, the G allele retained statistical significance as a negative predictor of insulin resistance (OR=0.78, 95% CI: 0.65-0.93, p=0.0060) and diabetes (OR=0.80, 95% CI: 0.66-0.96, p=0.018). CONCLUSIONS/INTERPRETATION: In a large cohort of Caucasians, the MCP-1 G-2518 gene variant was significantly and negatively correlated with plasma MCP-1 levels and the prevalence of insulin resistance and Type 2 diabetes. These results add to recent evidence supporting a role for MCP-1 in pathologies associated with hyperinsulinaemia.

Resting metabolic rate in six- to ten-year-old obese and nonobese children.

The resting metabolic rate (RMR) and body composition of 130 obese and nonobese prepubertal children, aged 6 to 10 years, were assessed by indirect calorimetry and skin-fold thickness, respectively. The mean (+/- SD) RMR was 4619 +/- 449 kJ.day-1 (164 +/- 31 kJ.kg body weight-1 x day-1) in the 62 boys and 4449 +/- 520 kJ.day-1 (147 +/- 32 kJ.kg body weight-1 x day-1) in the 68 girls. Fat-free mass was the best single predictor of RMR (R2 = 0.64; p < 0.001). Step-down multiple regression analysis, with independent variables such as age, gender, weight, and height, allowed several RMR predictive equations to be developed. An equation for boys is as follows: RMR (kJ.day-1) = 1287 + 28.6 x Weight(kg) + 23.6 x Height(cm) - 69.1 x Age(yr) (R2 = 0.58; p < 0.001). An equation for girls is as follows: RMR (kJ.day-1 = 1552 + 35.8 x Weight (kg) + 15.6 x Height (cm) - 36.3 x Age (yr) (R2 = 0.69; p < 0.001). Comparison between the measured RMR and that predicted by currently used formulas showed that most of these equations tended to overestimate the RMR of both genders, especially in overweight children.

The influence of environmental conditions on immune responses, morphology and recapture probability of nestling house martins (Delichon urbica)

Nestling birds produced later in the season are hypothesized to be of poor quality with a low probability of survival and recruitment. In a Spanish population of house martins (Delichon urbica), we first compared reproductive success, immune responses and morphological traits between the first and the second broods. Second, we investigated the effects of an ectoparasite treatment and breeding date on the recapture rate the following year. Due probably to a reverse situation in weather conditions during the experiment, with more rain during rearing of the first brood, nestlings reared during the second brood were in better condition and had stronger immune responses compared with nestlings from the first brood. Contrary to other findings on house martins, we found a similar recapture rate for chicks reared during the first and the second brood. Furthermore, ectoparasitic house martin bugs had no significant effect on the recapture rate. Recaptured birds had similar morphology but higher immunoglobulin levels when nestlings compared with non-recaptured birds. This result implies that a measure of immune function is a better predictor of survival than body condition per se.