LV Mass Assessed by Echocardiography and CMR, Cardiovascular Outcomes, and Medical Practice

The authors investigated 3 important areas related to the clinical use of left ventricular mass (LVM): accuracy of assessments by echocardiography and cardiac magnetic resonance (CMR), the ability to predict cardiovascular outcomes, and the comparative value of different indexing methods. The recommended formula for echocardiographic estimation of LVM uses linear measurements and is based on the assumption of the left ventricle (LV) as a prolate ellipsoid of revolution. CMR permits a modeling of the LV free of cardiac geometric assumptions or acoustic window dependency, showing better accuracy and reproducibility. However, echocardiography has lower cost, easier availability, and better tolerability. From the MEDLINE database, 26 longitudinal echocardiographic studies and 5 CMR studies investigating LVM or LV hypertrophy as predictors of death or major cardiovascular outcomes were identified. LVM and LV hypertrophy were reliable cardiovascular risk predictors using both modalities. However, no study directly compared the methods for the ability to predict events, agreement in hypertrophy classification, or performance in cardiovascular risk reclassification. Indexing LVM to body surface area was the earliest normalization process used, but it seems to underestimate the prevalence of hypertrophy in obese and overweight subjects. Dividing LVM by height to the allometric power of 1.7 or 2.7 is the most promising normalization method in terms of practicality and usefulness from a clinical and scientific standpoint for scaling myocardial mass to body size. The measurement of LVM, calculation of LVM index, and classification for LV hypertrophy should be standardized by scientific societies across measurement techniques and adopted by clinicians in risk stratification and therapeutic decision making

Is There an Association between Long-Term Sick Leave and Disability Pension and Unemployment beyond the Effect of Health Status? – A Cohort Study

Background: Studies have shown that long-term sick leave is a strong predictor of disability pension. However, few have aimed to disentangle the effect of sick leave and of health status. The objective of this study was to investigate whether there is an association between long-term sick leave and disability pension and unemployment, when taking health status into account. Methods/Principal Findings: The study was based on the Stockholm Public Health Cohort, restricted to 13,027 employed individuals (45.9 % men) aged 18–59 in 2002 and followed until 2007. Hazard ratios (HR) with 95 % Confidence Interval (CI) were estimated by Cox regression models adjusting for socio-demographic factors and five measures of health status. Having been on long-term sick leave increased the risk of disability pension (HR 4.01; 95 % CI 3.19–5.05) and longterm unemployment (HR 1.45; 95 % CI 1.05–2.00), after adjustment for health status. The analyses of long-term sick leave due to specific illness showed that the increased risk for long-term unemployment was confined to the group on sick leave due to musculoskeletal (HR 1.70 95 % CI 1.00–2.89) and mental illness (HR 1.80 95 % CI 1.13–2.88) and further that there was an increased risk for short-term unemployment in the group on sick leave due to mental illness (HR1.57 95%CI 1.09–2.26). Conclusions/Significance: Long-term sick leave increases the risks of both disability pension and unemployment even when taking health status into account. The results support the hypothesis that long-term sick leave may start a process o

Coordinated and tailored work rehabilitation: a randomized controlled trial with economic evaluation undertaken with workers on sick leave due to musculoskeletal disorders

Introduction In Denmark, the magnitude and impact of work disability on the individual worker and society has prompted the development of a new "coordinated and tailored work rehabilitation" (CTWR) approach. The aim of this study was to compare the effects of CTWR with conventional case management (CCM) on return-to-work of workers on sick leave due to musculoskeletal disorders (MSDs). Methods The study was a randomized controlled trial with economic evaluation undertaken with workers on sick leave for 4-12 weeks due to MSDs. CTWR consists of a work disability screening by an interdisciplinary team followed by the collaborative development of a RTW plan. The primary outcome variable was registered cumulative sickness absence hours during 12 months follow-up. Secondary outcomes were work status as well as pain intensity and functional disability, measured at baseline, 3 and 12 months follow-up. The economic evaluation (intervention costs, productivity loss, and health care utilization costs) was based on administrative data derived from national registries. Results For the time intervals 0-6 months, 6-12 months, and the entire follow-up period, the number of sickness absence hours was significantly lower in the CTWR group as compared to the control group. The total costs saved in CTWR participants compared to controls were estimated at US $1,366 per person at 6 months follow-up and US$ 10,666 per person at 12 months follow-up. Conclusions Workers on sick leave for 4-12 weeks due to MSD who underwent "CTWR" by an interdisciplinary team had fewer sickness absence hours than controls. The economic evaluation showed that-in terms of productivity loss-CTWR seems to be cost saving for the society

Parametric hazard rate models for long-term sickness absence

PURPOSE: In research on the time to onset of sickness absence and the duration of sickness absence episodes, Cox proportional hazard models are in common use. However, parametric models are to be preferred when time in itself is considered as independent variable. This study compares parametric hazard rate models for the onset of long-term sickness absence and return to work. METHOD: Prospective cohort study on sickness absence with four follow-up years of 53,830 employees working in the private sector in the Netherlands. The time to onset of long-term (>6 weeks) sickness absence and return to work were modelled by parametric hazard rate models. RESULTS: The exponential parametric model with a constant hazard rate most accurately described the time to onset of long-term sickness absence. Gompertz-Makeham models with monotonically declining hazard rates best described return to work. CONCLUSIONS: Parametric models offer more possibilities than commonly used models for time-dependent processes as sickness absence and return to work. However, the advantages of parametric models above Cox models apply mainly for return to work and less for onset of long-term sickness absence

Candidate markers for stratification and classification in rheumatoid arthritis

Rheumatoid arthritis (RA) is a chronic autoimmune, inflammatory disease, characterized by synovitis in small- and medium-sized joints and, if not treated early and efficiently, joint damage, and destruction. RA is a heterogeneous disease with a plethora of treatment options. The pro-inflammatory cytokine tumor necrosis factor (TNF) plays a central role in the pathogenesis of RA, and TNF inhibitors effectively repress inflammatory activity in RA. Currently, treatment decisions are primarily based on empirics and economic considerations. However, the considerable interpatient variability in response to treatment is a challenge. Markers for a more exact patient classification and stratification are lacking. The objective of this study was to identify markers in immune cell populations that distinguish RA patients from healthy donors with an emphasis on TNF signaling. We employed mass cytometry (CyTOF) with a panel of 13 phenotyping and 10 functional markers to explore signaling in unstimulated and TNF-stimulated peripheral blood mononuclear cells from 20 newly diagnosed, untreated RA patients and 20 healthy donors. The resulting high-dimensional data were analyzed in three independent analysis pipelines, characterized by differences in both data clean-up, identification of cell subsets/clustering and statistical approaches. All three analysis pipelines identified p-p38, IkBa, p-cJun, p-NFkB, and CD86 in cells of both the innate arm (myeloid dendritic cells and classical monocytes) and the adaptive arm (memory CD4+ T cells) of the immune system as markers for differentiation between RA patients and healthy donors. Inclusion of the markers p-Akt and CD120b resulted in the correct classification of 18 of 20 RA patients and 17 of 20 healthy donors in regression modeling based on a combined model of basal and TNF-induced signal. Expression patterns in a set of functional markers and specific immune cell subsets were distinct in RA patients compared to healthy individuals. These signatures may support studies of disease pathogenesis, provide candidate markers for response, and non-response to TNF inhibitor treatment, and aid the identification of future therapeutic targets.publishedVersio

Factors associated with first return to work and sick leave durations in workers with common mental disorders

Background: Associations are examined between socio-demographic, medical, work-related and organizational factors and the moment of first return to work (RTW) (within or after 6 weeks of sick leave) and total sick leave duration in sick leave spells due to common mental disorders. Methods: Data are derived from a Dutch database, build to provide reference data for sick leave duration for various medical conditions. The cases in this study were entered in 2004 and 2005 by specially trained occupational health physicians, based on the physician's assessment of medical and other factors. Odds ratios for first RTW and sick leave durations are calculated in logistic regression models. Results: Burnout, depression and anxiety disorder are associated with longer sick leave duration. Similar, but weaker associations were found for female sex, being a teacher, small company size and moderate or high psychosocial hazard. Distress is associated with shorter sick leave duration. Medical factors, psychosocial hazard and company size are also and analogously associated with first RTW. Part-time work is associated with delayed first RTW. The strength of the associations varies for various factors and for different sick leave durations. Conclusion: The medical diagnosis has a strong relation with the moment of first RTW and the duration of sick leave spells in mental disorders, but the influence of demographic and work-related factors should not be neglected

Sick-leave track record and other potential predictors of a disability pension. A population based study of 8,218 men and women followed for 16 years

<p>Abstract</p> <p>Background</p> <p>A number of previous studies have investigated various predictors for being granted a disability pension. The aim of this study was to test the efficacy of sick-leave track record as a predictor of being granted a disability pension in a large dataset based on subjects sampled from the general population and followed for a long time.</p> <p>Methods</p> <p>Data from five ongoing population-based Swedish studies was used, supplemented with data on all compensated sick leave periods, disability pensions granted, and vital status, obtained from official registers. The data set included 8,218 men and women followed for 16 years, generated 109,369 person years of observation and 97,160 sickness spells. Various measures of days of sick leave during follow up were used as independent variables and disability pension grant was used as outcome.</p> <p>Results</p> <p>There was a strong relationship between individual sickness spell duration and annual cumulative days of sick leave on the one hand and being granted a disability pension on the other, among both men and women, after adjustment for the effects of marital status, education, household size, smoking habits, geographical area and calendar time period, a proxy for position in the business cycle. The interval between sickness spells showed a corresponding inverse relationship. Of all the variables studied, the number of days of sick leave per year was the most powerful predictor of a disability pension. For both men and women 245 annual sick leave days were needed to reach a 50% probability of transition to disability. The independent variables, taken together, explained 96% of the variation in disability pension grantings.</p> <p>Conclusion</p> <p>The sick-leave track record was the most important predictor of the probability of being granted a disability pension in this study, even when the influences of other variables affecting the outcome were taken into account.</p