Predicting Return to Work in Employees Sick-Listed Due to Minor Mental Disorders

Objective To investigate which factors predict return to work (RTW) after 3 and 6 months in employees sick-listed due to minor mental disorders. Methods Seventy GPs recruited 194 subjects at the start of sick leave due to minor mental disorders. At baseline (T0), 3 and 6 months later (T1 and T2, respectively), subjects received a questionnaire and were interviewed by telephone. Using multivariate logistic regression analyses, we developed three prediction models to predict RTW at T1 and T2. Results The RTW rates were 38% after 3 months (T1) and 61% after 6 months (T2). The main negative predictors of RTW at T1 were: (a) a duration of the problems of more than 3 months before sick leave; and (b) somatisation. The main negative predictors of RTW at T2 were: (a) a duration of the problems of more than 3 months before sick leave; (b) more than 3 weeks of sick leave before inclusion in the study; and (c) anxiety. The main negative predictors of RTW at T2 for those who had not resumed work at T1 were: (a) more than 3 weeks of sick leave before inclusion in the study; and (b) depression at T1. The predictive power of the models was moderate with AUC-values between 0.695 and 0.763. Conclusions The main predictors of RTW were associated with the severity of the problems. A long duration of the problems before the occurrence of sick leave and a long duration of sick leave before seeking help predict a relatively small probability to RTW within 3–6 months. High baseline somatisation and anxiety, and high depression after 3 months make the prospect even worse. Since these predictors are readily assessable with just a few questions and a symptom questionnaire, this opens the opportunity to select high-risk employees for a targeted intervention to prevent long-term absenteeism

Effect of a multidisciplinary stress treatment programme on the return to work rate for persons with work-related stress. A non-randomized controlled study from a stress clinic

<p>Abstract</p> <p>Background</p> <p>In recent years an increasing number of patients have been referred to the medical sector with stress symptoms. Moreover, these conditions imply increased sickness absence. This indicates a need for treatment programmes in general medical practice. The aim of this study was to test the effect of a multidisciplinary stress treatment programme on the return to work (RTW) rate in persons with work-related stress and establish predictive factors for this outcome.</p> <p>Methods</p> <p>During a two-year period 63 out of 73 referrals to the Stress Clinic (a section of a Clinic of Occupational Medicine) completed a stress treatment programme consisted of the following:</p> <p>1) Identification of relevant stressors. 2. Changing the coping strategies of the participants. 3. Evaluating/changes in participant workload and tasks. 4. Relaxation techniques. 5. Physical exercise. 6. Psychiatric evaluation when indicated by depression test score.</p> <p>On average each patient attended six one-hour sessions over the course of four months.</p> <p>A group of 34 employees referred to the Clinic of Occupational Medicine by their general practitioners served as a control group. Each participant had a one-hour consultation at baseline and after four months. A specialist in occupational medicine carried out all sessions.</p> <p>Return To Work (RTW), defined as having a job and not being on sick leave at the census, was used as outcome measure four months after baseline, and after one and two years.</p> <p>Results</p> <p>The level of sick leave in the stress treatment group dropped from 52% to 16% during the first four months of follow-up and remained stable. In the control group, the reduction in sick leave was significantly smaller, ranging from 48% at baseline to 27% after four months and 24% after one year. No statistically significant difference between the two groups was observed after one and two years. Age below 50 years and being a manager increased the odds ratio for RTW after one and two years, while gender and depression had no predictive value.</p> <p>Conclusions</p> <p>The stress treatment programme showed a significant effect on the return to work rate. The stress treatment programme seems feasible for general practitioners.</p> <p>Trial Registration</p> <p>ISRCTN04354658</p

Machine Learning Classification of Females Susceptibility to Visceral Fat Associated Diseases

The problem of classifying subjects into risk categories is a common challenge in medical research. Machine Learning (ML) methods are widely used in the areas of risk prediction and classification. The primary objective of these algorithms is to predict dichotomous responses (e.g. healthy/at risk) based on several features. Similarly to statistical inference models, also ML models are subject to the common problem of class imbalance. Therefore, they are affected by the majority class increasing the false-negative rate. In this paper, we built and evaluated eighteen ML models classifying approximately 4300 female participants from the UK Biobank into three categorical risk statuses based on responses for the discretised visceral adipose tissue values from magnetic resonance imaging. We also examined the effect of sampling techniques on classification modelling when dealing with class imbalance. Results showed that the use of sampling techniques had a significant impact. They not only drove an improvement in predicting patients risk status but also facilitated an increase in the information contained within each variable. Based on domain experts criteria, the three best models for classification were finally identified. These encouraging results will guide further developments of classification models for predicting visceral adipose tissue without the need for a costly scan

Metformin and carotid intima media thickness in never smokers with type 1 diabetes: the REMOVAL trial

Aim: To determine whether metformin's effects on carotid artery intima-media thickness (cIMT) in type 1 diabetes differ according to smoking status. Methods: Regression model effect estimates for the effect of metformin versus placebo (double-blind) on carotid IMT were calculated as a subgroup analysis of the REMOVAL trial. Results: In 428 randomized participants (227 never-smokers, 201 ever-smokers), averaged mean carotid IMT progression (per year) was reduced by metformin versus placebo in never-smokers (−0.012 mm, 95% CI −0.021 to −0.002; p = .0137) but not in ever-smokers (0.003 mm, 95% CI −0.008 to 0.014; p = .5767); and similarly in non-current smokers (−0.008 mm, 95% CI −0.015 to −0.00001; p = .0497) but not in current smokers (0.013 mm, 95% CI −0.007 to 0.032; p = .1887). Three-way interaction terms (treatment*time*smoking status) were significant for never versus ever smoking (p = .0373, prespecified) and non-current versus current smoking (p = .0496, exploratory). Averaged maximal carotid IMT progression (per year) was reduced by metformin versus placebo in never-smokers (−0.020 mm, 95% CI −0.034 to −0.006; p = .0067) but not in ever-smokers (−0.006 mm, 95% CI −0.020 to 0.008; p = .4067), although this analysis was not supported by a significant three-way interaction term. Conclusions: This subgroup analysis of the REMOVAL trial provides additional support for a potentially wider role of adjunct metformin therapy in cardiovascular risk management in type 1 diabetes, particularly for individuals who have never smoked cigarettes

Quality assessment of clinical practice guidelinesfor Chagas disease

INTRODUCTION: The development of clinical practice guidelines (CPGs) has increased; this study aimed to assess the quality of CPGs for the management of Chagas disease. METHODS: Following a systematic search of the scientific literature, two reviewers assessed the eligible guidelines using the Appraisal of Guidelines Research and Evaluation (AGREE) II instrument. RESULTS: Five CPGs were included. The AGREE domains of scope/purpose, stakeholder involvement, and clarity of presentation were rated well, and the domains of applicability and editorial independence received poor ratings. CONCLUSIONS: The quality of CPGs for Chagas disease is poor, and significant work is required to develop high-quality guidelines

Health care utilization among complementary and alternative medicine users in a large military cohort

<p>Abstract</p> <p>Background</p> <p>Complementary and Alternative Medicine use and how it impacts health care utilization in the United States Military is not well documented. Using data from the Millennium Cohort Study we describe the characteristics of CAM users in a large military population and document their health care needs over a 12-month period. The aim of this study was to determine if CAM users are requiring more physician-based medical services than users of conventional medicine.</p> <p>Methods</p> <p>Inpatient and outpatient medical services were documented over a 12-month period for 44,287 participants from the Millennium Cohort Study. Equal access to medical services was available to anyone needing medical care during this study period. The number and types of medical visits were compared between CAM and non-CAM users. Chi square test and multivariable logistic regression was applied for the analysis.</p> <p>Results</p> <p>Of the 44,287 participants, 39% reported using at least one CAM therapy, and 61% reported not using any CAM therapies. Those individuals reporting CAM use accounted for 45.1% of outpatient care and 44.8% of inpatient care. Individuals reporting one or more health conditions were 15% more likely to report CAM use than non-CAM users and 19% more likely to report CAM use if reporting one or more health symptoms compared to non-CAM users. The unadjusted odds ratio for hospitalizations in CAM users compared to non-CAM users was 1.29 (95% CI: 1.16-1.43). The mean number of days receiving outpatient care for CAM users was 7.0 days and 5.9 days for non-CAM users (<it>p </it>< 0.001).</p> <p>Conclusions</p> <p>Our study found those who report CAM use were requiring more physician-based medical services than users of conventional medicine. This appears to be primarily the result of an increase in the number of health conditions and symptoms reported by CAM users.</p

Should I Stay or Should I Go? A Habitat-Dependent Dispersal Kernel Improves Prediction of Movement

The analysis of animal movement within different landscapes may increase our understanding of how landscape features affect the perceptual range of animals. Perceptual range is linked to movement probability of an animal via a dispersal kernel, the latter being generally considered as spatially invariant but could be spatially affected. We hypothesize that spatial plasticity of an animal's dispersal kernel could greatly modify its distribution in time and space. After radio tracking the movements of walking insects (Cosmopolites sordidus) in banana plantations, we considered the movements of individuals as states of a Markov chain whose transition probabilities depended on the habitat characteristics of current and target locations. Combining a likelihood procedure and pattern-oriented modelling, we tested the hypothesis that dispersal kernel depended on habitat features. Our results were consistent with the concept that animal dispersal kernel depends on habitat features. Recognizing the plasticity of animal movement probabilities will provide insight into landscape-level ecological processes