Laser treatment in diabetic retinopathy

Diabetic retinopathy is a leading cause of visual impairment and blindness in developed countries due to macular edema and proliferative diabetic retinopathy (PDR). For both complications laser treatment may offer proven therapy: the Diabetic Retinopathy Study demonstrated that panretinal scatter photocoagulation reduces the risk of severe visual loss by >= 50% in eyes with high-risk characteristics. Pan-retinal scatter coagulation may also be beneficial in other PDR and severe nonproliferative diabetic retinopathy (NPDR) under certain conditions. For clinically significant macular edema the Early Treatment of Diabetic Retinopathy Study could show that immediate focal laser photocoagulation reduces the risk of moderate visual loss by at least 50%. When and how to perform laser treatment is described in detail, offering a proven treatment for many problems associated with diabetic retinopathy based on a high evidence level. Copyright (c) 2007 S. Karger AG, Basel

Employers' views on the promotion of workplace health and wellbeing: A qualitative study

Background: The evidence surrounding the value of workplace health promotion in positively influencing employees' health and wellbeing via changes to their health behaviours is growing. The aim of the study was to explore employers' views on the promotion of workplace health and wellbeing and the factors affecting these views. Methods: Using a qualitative phenomenological approach, 10 focus groups were conducted with employers selected from a range of industries and geographical locations within Western Australia. The total sample size was 79. Results: Three factors were identified: employers' conceptualization of workplace health and wellbeing; employers' descriptions of (un)healthy workers and perceptions surrounding the importance of healthy workers; and employers' beliefs around the role the workplace should play in influencing health. Conclusions: Progress may be viable in promoting health and wellbeing if a multifaceted approach is employed taking into account the complex factors influencing employers' views. This could include an education campaign providing information about what constitutes health and wellbeing beyond the scope of occupational health and safety paradigms along with information on the benefits of workplace health and wellbeing aligned with perceptions relating to healthy and unhealthy workers

The PPARGC1A Gly482Ser polymorphism is associated with left ventricular diastolic dysfunction in men

<p>Abstract</p> <p>Background</p> <p>The Gly482Ser polymorphism in peroxisome proliferator-activated receptor gamma coactivator-1 alpha (<it>PPARGC1A</it>) has been demonstrated to be associated with diabetes, obesity and hypertension, all of which are important risk factors for left ventricular diastolic dysfunction.</p> <p>Methods</p> <p>The <it>PPARGC1A </it>Gly482Ser polymorphism was genotyped in a community-based cohort of 499 men and 533 women, who also underwent an echocardiographic examination to determine their left ventricular diastolic function. The association between the polymorphism and the presence of diastolic dysfunction was evaluated using logistic regression models.</p> <p>Results</p> <p>The Ser allele of the <it>PPARGC1A </it>Gly482Ser polymorphism was significantly associated with a lower risk of diastolic dysfunction in men, but not in women. In a model adjusting for potential confounders (age, body mass index, leisure time physical activity, hypertension and diabetes) the results were still significant and substantial (odds ratio 0.13, 95% confidence interval 0.03–0.54, p for trend = 0.004). The results were consistent in a series of models, and they imply a multiplicative, protective effect of the Ser allele, with lower risk of diastolic dysfunction for each copy of the allele.</p> <p>Conclusion</p> <p>The Ser allele of the <it>PPARGC1A </it>Gly482Ser polymorphism was associated with decreased risk of diastolic left ventricular dysfunction in men, but not in women, in our large community-based sample. It was associated with a substantially decreased risk, even after adjustment for potential confounders. The clinical importance of the findings has to be established in further studies.</p

Evidence of causal effect of major depression on alcohol dependence: findings from the psychiatric genomics consortium

BACKGROUND Despite established clinical associations among major depression (MD), alcohol dependence (AD), and alcohol consumption (AC), the nature of the causal relationship between them is not completely understood. We leveraged genome-wide data from the Psychiatric Genomics Consortium (PGC) and UK Biobank to test for the presence of shared genetic mechanisms and causal relationships among MD, AD, and AC. METHODS Linkage disequilibrium score regression and Mendelian randomization (MR) were performed using genome-wide data from the PGC (MD: 135 458 cases and 344 901 controls; AD: 10 206 cases and 28 480 controls) and UK Biobank (AC-frequency: 438 308 individuals; AC-quantity: 307 098 individuals). RESULTS Positive genetic correlation was observed between MD and AD (rgMD−AD = + 0.47, P = 6.6 × 10−10). AC-quantity showed positive genetic correlation with both AD (rgAD−AC quantity = + 0.75, P = 1.8 × 10−14) and MD (rgMD−AC quantity = + 0.14, P = 2.9 × 10−7), while there was negative correlation of AC-frequency with MD (rgMD−AC frequency = −0.17, P = 1.5 × 10−10) and a non-significant result with AD. MR analyses confirmed the presence of pleiotropy among these four traits. However, the MD-AD results reflect a mediated-pleiotropy mechanism (i.e. causal relationship) with an effect of MD on AD (beta = 0.28, P = 1.29 × 10−6). There was no evidence for reverse causation. CONCLUSION This study supports a causal role for genetic liability of MD on AD based on genetic datasets including thousands of individuals. Understanding mechanisms underlying MD-AD comorbidity addresses important public health concerns and has the potential to facilitate prevention and intervention efforts

Evidence for similar structural brain anomalies in youth and adult attention-deficit/hyperactivity disorder: a machine learning analysis

Attention-deficit/hyperactivity disorder (ADHD) affects 5% of children world-wide. Of these, two-thirds continue to have impairing symptoms of ADHD into adulthood. Although a large literature implicates structural brain differences of the disorder, it is not clear if adults with ADHD have similar neuroanatomical differences as those seen in children with recent reports from the large ENIGMA-ADHD consortium finding structural differences for children but not for adults. This paper uses deep learning neural network classification models to determine if there are neuroanatomical changes in the brains of children with ADHD that are also observed for adult ADHD, and vice versa. We found that structural MRI data can significantly separate ADHD from control participants for both children and adults. Consistent with the prior reports from ENIGMA-ADHD, prediction performance and effect sizes were better for the child than the adult samples. The model trained on adult samples significantly predicted ADHD in the child sample, suggesting that our model learned anatomical features that are common to ADHD in childhood and adulthood. These results support the continuity of ADHD’s brain differences from childhood to adulthood. In addition, our work demonstrates a novel use of neural network classification models to test hypotheses about developmental continuity