Performance of Cpred/Cobs concentration ratios as a metric reflecting adherence to antidepressant drug therapy

Background: Nonadherence is very common among subjects undergoing pharmacotherapy for schizophrenia and depression. This study aimed to evaluate the performance of the ratio of the nonlinear mixed effects pharmacokinetic model predicted concentration to observed drug concentration (ratio of population predicted to observed concentration (Cpred/Cobs) and ratio of individual predicted to observed concentration (Cipred/Cobs) as a measure of erratic drug exposure, driven primarily by variable execution of the dosage regimen and unknown true dosage history. Methods: Modeling and simulation approaches in conjunction with dosage history information from the Medication Event Monitoring System (MEMS, provided by the "Depression: The search for treatment relevant phenotypes" study), was applied to evaluate the consistency of exposure via simulation studies with scenarios representing a long half-life drug (escitalopram). Adherence rates were calculated based on the percentage of the prescribed doses actually taken correctly during the treatment window of interest. The association between Cpred/Cobs, Cipred/Cobs ratio, and adherence rate was evaluated under various assumptions of known dosing history. Results: Simulations for those scenarios representing a known dosing history were generated from historical MEMS data. Simulations of a long half-life drug exhibited a trend for overprediction of concentrations in patients with a low percentage of doses taken and underprediction of concentrations in patients taking more than their prescribed number of doses. Overall, the ratios did not predict adherence well, except when the true adherence rates were extremely high (greater than 100% of prescribed doses) or extremely low (complete nonadherence). In general, the Cipred/Cobs ratio was a better predictor of adherence rate than the Cpred/Cobs ratio. Correct predictions of extreme (high, low) 7-day adherence rates using Cipred/Cobs were 73.8% and 64.0%. Conclusion: This simulation study demonstrated the limitations of the Cpred/obs and Cipred/obs ratios as metrics for actual dosage intake history, and identified that use of MEMS dosing history monitoring combined with sparse pharmacokinetic sampling is a more reliable approach. © 2011 Feng et al

The role of expertise in dynamic risk assessment: A reflection of the problem-solving strategies used by experienced fireground commanders

Although the concept of dynamic risk assessment has in recent times become more topical in the training manuals of most high risk domains, only a few empirical studies have reported how experts actually carry out this crucial task. The knowledge gap between research and practice in this area therefore calls for more empirical investigation within the naturalistic environment. In this paper, we present and discuss the problem solving strategies employed by sixteen experienced operational firefighters using a qualitative knowledge elicitation tool — the critical decision method. Findings revealed that dynamic risk assessment is not merely a process of weighing the risks of a proposed course of action against its benefits, but rather an experiential and pattern recognition process. The paper concludes by discussing the implications of designing training curriculum for the less experienced officers using the elicited expert knowledge

Varespladib and cardiovascular events in patients with an acute coronary syndrome: the VISTA-16 randomized clinical trial

IMPORTANCE: Secretory phospholipase A2(sPLA2) generates bioactive phospholipid products implicated in atherosclerosis. The sPLA2inhibitor varespladib has favorable effects on lipid and inflammatory markers; however, its effect on cardiovascular outcomes is unknown. OBJECTIVE: To determine the effects of sPLA2inhibition with varespladib on cardiovascular outcomes. DESIGN, SETTING, AND PARTICIPANTS: A double-blind, randomized, multicenter trial at 362 academic and community hospitals in Europe, Australia, New Zealand, India, and North America of 5145 patients randomized within 96 hours of presentation of an acute coronary syndrome (ACS) to either varespladib (n = 2572) or placebo (n = 2573) with enrollment between June 1, 2010, and March 7, 2012 (study termination on March 9, 2012). INTERVENTIONS: Participants were randomized to receive varespladib (500 mg) or placebo daily for 16 weeks, in addition to atorvastatin and other established therapies. MAIN OUTCOMES AND MEASURES: The primary efficacy measurewas a composite of cardiovascular mortality, nonfatal myocardial infarction (MI), nonfatal stroke, or unstable angina with evidence of ischemia requiring hospitalization at 16 weeks. Six-month survival status was also evaluated. RESULTS: At a prespecified interim analysis, including 212 primary end point events, the independent data and safety monitoring board recommended termination of the trial for futility and possible harm. The primary end point occurred in 136 patients (6.1%) treated with varespladib compared with 109 patients (5.1%) treated with placebo (hazard ratio [HR], 1.25; 95%CI, 0.97-1.61; log-rank P = .08). Varespladib was associated with a greater risk of MI (78 [3.4%] vs 47 [2.2%]; HR, 1.66; 95%CI, 1.16-2.39; log-rank P = .005). The composite secondary end point of cardiovascular mortality, MI, and stroke was observed in 107 patients (4.6%) in the varespladib group and 79 patients (3.8%) in the placebo group (HR, 1.36; 95% CI, 1.02-1.82; P = .04). CONCLUSIONS AND RELEVANCE: In patients with recent ACS, varespladib did not reduce the risk of recurrent cardiovascular events and significantly increased the risk of MI. The sPLA2inhibition with varespladib may be harmful and is not a useful strategy to reduce adverse cardiovascular outcomes after ACS. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT01130246. Copyright 2014 American Medical Association. All rights reserved

Correlated Mutations: A Hallmark of Phenotypic Amino Acid Substitutions

Point mutations resulting in the substitution of a single amino acid can cause severe functional consequences, but can also be completely harmless. Understanding what determines the phenotypical impact is important both for planning targeted mutation experiments in the laboratory and for analyzing naturally occurring mutations found in patients. Common wisdom suggests using the extent of evolutionary conservation of a residue or a sequence motif as an indicator of its functional importance and thus vulnerability in case of mutation. In this work, we put forward the hypothesis that in addition to conservation, co-evolution of residues in a protein influences the likelihood of a residue to be functionally important and thus associated with disease. While the basic idea of a relation between co-evolution and functional sites has been explored before, we have conducted the first systematic and comprehensive analysis of point mutations causing disease in humans with respect to correlated mutations. We included 14,211 distinct positions with known disease-causing point mutations in 1,153 human proteins in our analysis. Our data show that (1) correlated positions are significantly more likely to be disease-associated than expected by chance, and that (2) this signal cannot be explained by conservation patterns of individual sequence positions. Although correlated residues have primarily been used to predict contact sites, our data are in agreement with previous observations that (3) many such correlations do not relate to physical contacts between amino acid residues. Access to our analysis results are provided at http://webclu.bio.wzw.tum.de/~pagel/supplements/correlated-positions/

How Does Spatial Study Design Influence Density Estimates from Spatial Capture-Recapture Models?

When estimating population density from data collected on non-invasive detector arrays, recently developed spatial capture-recapture (SCR) models present an advance over non-spatial models by accounting for individual movement. While these models should be more robust to changes in trapping designs, they have not been well tested. Here we investigate how the spatial arrangement and size of the trapping array influence parameter estimates for SCR models. We analysed black bear data collected with 123 hair snares with an SCR model accounting for differences in detection and movement between sexes and across the trapping occasions. To see how the size of the trap array and trap dispersion influence parameter estimates, we repeated analysis for data from subsets of traps: 50% chosen at random, 50% in the centre of the array and 20% in the South of the array. Additionally, we simulated and analysed data under a suite of trap designs and home range sizes. In the black bear study, we found that results were similar across trap arrays, except when only 20% of the array was used. Black bear density was approximately 10 individuals per 100 km2. Our simulation study showed that SCR models performed well as long as the extent of the trap array was similar to or larger than the extent of individual movement during the study period, and movement was at least half the distance between traps. SCR models performed well across a range of spatial trap setups and animal movements. Contrary to non-spatial capture-recapture models, they do not require the trapping grid to cover an area several times the average home range of the studied species. This renders SCR models more appropriate for the study of wide-ranging mammals and more flexible to design studies targeting multiple species

Confusion and Conflict in Assessing the Physical Activity Status of Middle-Aged Men

BACKGROUND: Physical activity (including exercise) is prescribed for health and there are various recommendations that can be used to gauge physical activity status. The objective of the current study was to determine whether twelve commonly-used physical activity recommendations similarly classified middle-aged men as sufficiently active for general health. METHODS AND FINDINGS: We examined the commonality in the classification of physical activity status between twelve variations of physical activity recommendations for general health in ninety men aged 45-64 years. Physical activity was assessed using synchronised accelerometry and heart rate. Using different guidelines but the same raw data, the proportion of men defined as active ranged from to 11% to 98% for individual recommendations (median 73%, IQR 30% to 87%). There was very poor absolute agreement between the recommendations, with an intraclass correlation coefficient (A,1) of 0.24 (95% CI, 0.15 to 0.34). Only 8% of men met all 12 recommendations and would therefore be unanimously classified as active and only one man failed to meet every recommendation and would therefore be unanimously classified as not sufficiently active. The wide variability in physical activity classification was explained by ostensibly subtle differences between the 12 recommendations for thresholds related to activity volume (time or energy), distribution (e.g., number of days of the week), moderate intensity cut-point (e.g., 3 vs. 4 metabolic equivalents or METs), and duration (including bout length). CONCLUSIONS: Physical activity status varies enormously depending on the physical activity recommendation that is applied and even ostensibly small differences have a major impact. Approximately nine out of every ten men in the present study could be variably described as either active or not sufficiently active. Either the effective dose or prescription that underlies each physical activity recommendation is different or each recommendation is seeking the same prescriptive outcome but with variable success

Discovering Argumentative Patterns in Energy Polylogues: A Macroscope for Argument Mining

A macroscope is proposed and tested here for the discovery of the unique argumentative footprint that characterizes how a collective (e.g., group, online community) manages differences and pursues disagreement through argument in a polylogue. The macroscope addresses broader analytic problems posed by various conceptualizations of large-scale argument, such as fields, spheres, communities, and institutions. The design incorporates a two-tier methodology for detecting argument patterns of the arguments performed in arguing by an interactive collective that produces views, or topographies, of the ways that issues are generated in the making and defending of standpoints. The design premises for the macroscope build on insights about argument patterns from pragma-dialectical theory by incorporating research and theory on disagreement management and the Argumentum Model of Topics. The design reconceptualizes prototypical and stereotypical argument patterns for characterizing large-scale argumentation. A prototype of the macroscope is tested on data drawn from six threads about oil-drilling and fracking from the subreddit Changemyview. The implementation suggests the efficacy of the macroscope’s design and potential for identifying what communities make controversial and how the disagreement space in a polylogue is managed through stereotypical argument patterns in terms of claims/premises, inferential relations, and presentational devices

Clustering of Unhealthy Behaviors in the Aerobics Center Longitudinal Study

Background Clustering of unhealthy behaviors has been reported in previous studies; however the link with all-cause mortality and differences between those with and without chronic disease requires further investigation. Objectives To observe the clustering effects of unhealthy diet, fitness, smoking, and excessive alcohol consumption in adults with and without chronic disease and to assess all-cause mortality risk according to the clustering of unhealthy behaviors. Methods Participants were 13,621 adults (aged 20–84) from the Aerobics Center Longitudinal Study. Four health behaviors were observed (diet, fitness, smoking, and drinking). Baseline characteristics of the study population and bivariate relations between pairs of the health behaviors were evaluated separately for those with and without chronic disease using cross-tabulation and a chi-square test. The odds of partaking in unhealthy behaviors were also calculated. Latent class analysis (LCA) was used to assess clustering. Cox regression was used to assess the relationship between the behaviors and mortality. Results The four health behaviors were related to each other. LCA results suggested that two classes existed. Participants in class 1 had a higher probability of partaking in each of the four unhealthy behaviors than participants in class 2. No differences in health behavior clustering were found between participants with and without chronic disease. Mortality risk increased relative to the number of unhealthy behaviors participants engaged in. Conclusion Unhealthy behaviors cluster together irrespective of chronic disease status. Such findings suggest that multi-behavioral intervention strategies can be similar in those with and without chronic disease