Relationship between treatment delay and final infarct size in STEMI patients treated with abciximab and primary PCI

Background Studies on the impact of time to treatment on myocardial infarct size have yielded   conflicting results. In this study of ST-Elevation Myocardial Infarction (STEMI) treated   with primary percutaneous coronary intervention (PCI), we set out to investigate the   relationship between the time from First Medical Contact (FMC) to the demonstration   of an open infarct related artery (IRA) and final scar size. Between February 2006 and September 2007, 89 STEMI patients treated with primary PCI   were studied with contrast enhanced magnetic resonance imaging (ceMRI) 4 to 8 weeks   after the infarction. Spearman correlation was computed for health care delay time   (defined as time from FMC to PCI) and myocardial injury. Multiple linear regression   was used to determine covariates independently associated with infarct size. Results An occluded artery (Thrombolysis In Myocardial Infarction, TIMI flow 0-1 at initial   angiogram) was seen in 56 patients (63%). The median FMC-to-patent artery was 89 minutes.   There was a weak correlation between time from FMC-to-patent IRA and infarct size,   r = 0.27, p = 0.01. In multiple regression analyses, LAD as the IRA, smoking and an occluded vessel   at the first angiogram, but not delay time, correlated with infarct size. Conclusions In patients with STEMI treated with primary PCI we found a weak correlation between   health care delay time and infarct size. Other factors like anterior infarction, a   patent artery pre-PCI and effects of reperfusion injury may have had greater influence   on infarct size than time-to-treatment per se

Stress and prevalence of hearing problems in the Swedish working population

<p>Abstract</p> <p>Background</p> <p>Current human and experimental studies are indicating an association between stress and hearing problems; however potential risk factors have not been established. Hearing problems are projected to become among the top ten disabilities according to the WHO in the near future. Therefore a better understanding of the relationships between stress and hearing is warranted. Here we describe the prevalence of two common hearing problems, i.e. hearing complaints and tinnitus, in relation to different work-and health-related stressors.</p> <p>Methods</p> <p>A total of 18,734 individuals were invited to participate in the study, out of which 9,756 (52%) enrolled.</p> <p>Results</p> <p>The results demonstrate a clear and mostly linear relationship between higher prevalence of hearing problems (tinnitus or hearing loss or both) and different stressors, e.g. occupational, poorer self-rated health, long-term illness, poorer sleep quality, and higher burnout scores.</p> <p>Conclusions</p> <p>The present study unambiguously demonstrates associations between hearing problems and various stressors that have not been previously described for the auditory system. These findings will open new avenues for future investigations.</p

The early effects of afforestation on biodiversity of grasslands in Ireland

Abstract The target rate of afforestation in Ireland over the next 30 years is 20,000 ha per year, which would result in an increase of the forest cover from the current 10% to 17%. In order to promote sustainable forest management practices, it is essential to know the composition and conservation value of habitats where afforestation is planned and the effects of subsequent planting upon biodiversity. The objectives of this study were to investigate changes in vegetation composition and diversity of grasslands 5 years after afforestation with Sitka spruce (Picea sitchensis) and determine the primary ecological and management factors responsible for these changes. Species cover, environmental and management data were collected from 16 afforested and unplanted improved and wet grassland site pairs in Ireland. Our results indicate that 5 years after tree planting, there were significant changes in richness, composition, and abundance of species. Competitive and vigorous grasses were more abundant in planted than in unplanted sites, as were generalist species found in both open and wooded habitats, while small-stature shade-sensitive species were less abundant. Vascular plant species richness and Shannon’s diversity index were higher in unplanted wet grassland, than in the planted sites. Bryophyte species richness was higher in planted improved grassland than in unplanted sites. The differences were primarily the result of the exclusion of grazing, ground preparation, changes in nutrient management and drainage for afforestation. Drainage ditches provided a temporary habitat for less competitive species, but the overall effect of drainage was to reduce the diversity of species dependent on wet conditions. Variance partitioning showed differences in the relative influences of environmental and management variables on biodiversity in the two habitats, probably due to the greater pre-afforestation grazing pressure and fertilisation levels in improved grasslands. The differences in biodiversity between planted and unplanted grasslands indicate that afforestation represents a threat to semi-natural habitats where distinctive and highly localised plant communities could potentially occur

Shared genetic risk between eating disorder- and substance-use-related phenotypes: Evidence from genome-wide association studies

Eating disorders and substance use disorders frequently co-occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa and problem alcohol use (genetic correlation [r(g)], twin-based = 0.23-0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome-wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge eating, AN without binge eating, and a bulimia nervosa factor score), and eight substance-use-related phenotypes (drinks per week, alcohol use disorder [AUD], smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder and schizophrenia. Total study sample sizes per phenotype ranged from similar to 2400 to similar to 537 000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism-based genetic correlations between eating disorder- and substance-use-related phenotypes. Significant positive genetic associations emerged between AUD and AN (r(g) = 0.18; false discovery rate q = 0.0006), cannabis initiation and AN (r(g) = 0.23; q < 0.0001), and cannabis initiation and AN with binge eating (r(g) = 0.27; q = 0.0016). Conversely, significant negative genetic correlations were observed between three nondiagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge eating (r(gs) = -0.19 to -0.23; qs < 0.04). The genetic correlation between AUD and AN was no longer significant after co-varying for major depressive disorder loci. The patterns of association between eating disorder- and substance-use-related phenotypes highlights the potentially complex and substance-specific relationships among these behaviors

Analysis of shared heritability in common disorders of the brain

Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology