Atopic dermatitis and risk of atrial fibrillation or flutter: A 35-year follow-up study.

BACKGROUND: Atopic dermatitis is characterized by chronic inflammation, which is a risk factor for atrial fibrillation. OBJECTIVE: To examine the association between hospital-diagnosed atopic dermatitis and atrial fibrillation. METHODS: Using linked population-based Danish registries, we identified persons with an inpatient or outpatient hospital diagnosis of atopic dermatitis during 1977-2013 and a comparison cohort individually matched to the atopic dermatitis cohort. We followed cohorts until death, emigration, atrial fibrillation diagnosis, or end of study (January 1, 2013). We compared 35-year risk of atrial fibrillation and estimated hazard ratios with 95% confidence intervals using Cox regression, adjusting for birth year and sex. We validated 100 atopic dermatitis diagnoses from a dermatologic department through medical record review. RESULTS: We included 13,126 persons with atopic dermatitis and 124,211 comparators and followed them for a median of 19.3 years. The 35-year risk of atrial fibrillation was 0.81% and 0.67%, respectively. The positive predictive value of atopic dermatitis diagnoses was 99%. The hazard ratio was 1.2 (95% confidence interval 1.0-1.6) and remained increased after adjusting for various atrial fibrillation risk factors. LIMITATIONS: Analyses were limited to persons with moderate-to-severe atopic dermatitis, and we had no lifestyle data. CONCLUSION: Patients with hospital-diagnosed atopic dermatitis have a 20% increased long-term risk of atrial fibrillation, but the absolute risk remains low

Scalable Group Level Probabilistic Sparse Factor Analysis

Many data-driven approaches exist to extract neural representations of functional magnetic resonance imaging (fMRI) data, but most of them lack a proper probabilistic formulation. We propose a group level scalable probabilistic sparse factor analysis (psFA) allowing spatially sparse maps, component pruning using automatic relevance determination (ARD) and subject specific heteroscedastic spatial noise modeling. For task-based and resting state fMRI, we show that the sparsity constraint gives rise to components similar to those obtained by group independent component analysis. The noise modeling shows that noise is reduced in areas typically associated with activation by the experimental design. The psFA model identifies sparse components and the probabilistic setting provides a natural way to handle parameter uncertainties. The variational Bayesian framework easily extends to more complex noise models than the presently considered.Comment: 10 pages plus 5 pages appendix, Submitted to ICASSP 1

25 year trends in first time hospitalisation for acute myocardial infarction, subsequent short and long term mortality, and the prognostic impact of sex and comorbidity: a Danish nationwide cohort study

Objectives To examine 25 year trends in first time hospitalisation for acute myocardial infarction in Denmark, subsequent short and long term mortality, and the prognostic impact of sex and comorbidity

Mortality Risk Among Heart Failure Patients With Depression:A Nationwide Population-Based Cohort Study

BACKGROUND: The prevalence of depression is 4‐ to 5‐fold higher in heart failure patients than in the general population. We examined the influence of depression on all‐cause mortality in patients with heart failure. METHODS AND RESULTS: Using Danish medical registries, this nationwide population‐based cohort study included all patients with a first‐time hospitalization for heart failure (1995–2014). All‐cause mortality risks and 19‐year mortality rate ratios were estimated based on Cox regression analysis, adjusting for age, sex, time period, comorbidity, and socioeconomic status. The analysis included 9636 patients with and 194 887 patients without a diagnosis of depression. Compared with patients without a history of depression, those with depression had higher 1‐year (36% versus 33%) and 5‐year (68% versus 63%) mortality risks. Overall, the adjusted mortality rate ratio was 1.03 (95% CI 1.01–1.06). Compared with no depression, the adjusted mortality rate ratios for mild, moderate, and severe depression, as defined by diagnostic codes, were 1.06 (95% CI 1.00–1.13), 1.03 (95% CI 0.99–1.08), and 1.02 (95% CI 0.96–1.09), respectively. In a subcohort of patients, the mortality rate ratios were modified by left ventricular ejection fraction, with adjusted mortality rate ratios of 1.17 (95% CI, 1.05–1.31) for ≤35%, 0.98 (95% CI 0.81–1.18) for 36% to 49%, and 0.96 (95% CI 0.74–1.25) for ≥50%. Results were consistent after adjustment for alcohol abuse and smoking. CONCLUSIONS: A history of depression was an adverse prognostic factor for all‐cause mortality in heart failure patients with left ventricular ejection fraction ≤35% but not for other heart failure patients

Metabolomic phenotyping of a cloned pig model

<p>Abstract</p> <p>Background</p> <p>Pigs are widely used as models for human physiological changes in intervention studies, because of the close resemblance between human and porcine physiology and the high degree of experimental control when using an animal model. Cloned animals have, in principle, identical genotypes and possibly also phenotypes and this offer an extra level of experimental control which could possibly make them a desirable tool for intervention studies. Therefore, in the present study, we address how phenotype and phenotypic variation is affected by cloning, through comparison of cloned pigs and normal outbred pigs.</p> <p>Results</p> <p>The metabolic phenotype of cloned pigs (n = 5) was for the first time elucidated by nuclear magnetic resonance (NMR)-based metabolomic analysis of multiple bio-fluids including plasma, bile and urine. The metabolic phenotype of the cloned pigs was compared with normal outbred pigs (n = 6) by multivariate data analysis, which revealed differences in the metabolic phenotypes. Plasma lactate was higher for cloned vs control pigs, while multiple metabolites were altered in the bile. However a lower inter-individual variability for cloned pigs compared with control pigs could not be established.</p> <p>Conclusions</p> <p>From the present study we conclude that cloned and normal outbred pigs are phenotypically different. However, it cannot be concluded that the use of cloned animals will reduce the inter-individual variation in intervention studies, though this is based on a limited number of animals.</p

Data management and data analysis techniques in pharmacoepidemiological studies using a pre-planned multi-database approach : a systematic literature review

PurposeTo identify pharmacoepidemiological multi-database studies and to describe data management and data analysis techniques used for combining data. MethodsSystematic literature searches were conducted in PubMed and Embase complemented by a manual literature search. We included pharmacoepidemiological multi-database studies published from 2007 onwards that combined data for a pre-planned common analysis or quantitative synthesis. Information was retrieved about study characteristics, methods used for individual-level analyses and meta-analyses, data management and motivations for performing the study. ResultsWe found 3083 articles by the systematic searches and an additional 176 by the manual search. After full-text screening of 75 articles, 22 were selected for final inclusion. The number of databases used per study ranged from 2 to 17 (median=4.0). Most studies used a cohort design (82%) instead of a case-control design (18%). Logistic regression was most often used for individual-level analyses (41%), followed by Cox regression (23%) and Poisson regression (14%). As meta-analysis method, a majority of the studies combined individual patient data (73%). Six studies performed an aggregate meta-analysis (27%), while a semi-aggregate approach was applied in three studies (14%). Information on central programming or heterogeneity assessment was missing in approximately half of the publications. Most studies were motivated by improving power (86%). ConclusionsPharmacoepidemiological multi-database studies are a well-powered strategy to address safety issues and have increased in popularity. To be able to correctly interpret the results of these studies, it is important to systematically report on database management and analysis techniques, including central programming and heterogeneity testing. (c) 2015 The Authors. Pharmacoepidemiology and Drug Safety published by John Wiley & Sons, Ltd.Peer reviewe

Cancer risk among insulin users : comparing analogues with human insulin in the CARING five-country cohort study

Aims/hypothesis The aim of this work was to investigate the relationship between use of certain insulins and risk for cancer, when addressing the limitations and biases involved in previous studies. Methods National Health Registries from Denmark (1996-2010), Finland (1996-2011), Norway (2005-2010) and Sweden (2007-2012) and the UK Clinical Practice Research Datalink database (1987-2013) were used to conduct a cohort study on new insulin users (N = 327,112). By using a common data model and semi-aggregate approach, we pooled individual-level records from five cohorts and applied Poisson regression models. For each of ten cancer sites studied, we estimated the rate ratios (RRs) by duration (6 years) of cumulative exposure to insulin glargine or insulin detemir relative to that of human insulin. Results A total of 21,390 cancer cases occurred during a mean follow-up of 4.6 years. No trend with cumulative treatment time for insulin glargine relative to human insulin was observed in risk for any of the ten studied cancer types. Of the 136 associations tested in the main analysis, only a few increased and decreased risks were found: among women, a higher risk was observed for colorectal (RR 1.54, 95% CI 1.06, 2.25) and endometrial cancer (RR 1.78, 95% CI 1.07, 2.94) for 6 years (RR 0.22, 95% CI 0.05, 0.92). Comparisons of insulin detemir with human insulin also showed no consistent differences. Conclusions/interpretation The present multi-country study found no evidence of consistent differences in risk for ten cancers for insulin glargine or insulin detemir use compared with human insulin, at follow-up exceeding 5 years.Peer reviewe

Lack of cardioprotection from subcutaneously and preischemic administered Liraglutide in a closed chest porcine ischemia reperfusion model

<p>Abstract</p> <p>Background</p> <p>Glucagon-like peptide 1 (GLP1) analogues are promising new treatment options for patients with type 2 diabetes, but may have both potentially beneficial and harmful cardiovascular effects. This may also be the case for the analogues of GLP1 for clinical use. The present study examined the effect of treatment with Liraglutide, a long-acting GLP1 analogue, on myocardial ischemia and reperfusion in a porcine model.</p> <p>Methods</p> <p>Danish Landrace Pigs (70–80 kg) were randomly assigned to Liraglutide (10 μg/kg) or control treatment given daily for three days before ischemia-reperfusion. Ischemia was induced by balloon occlusion of the left anterior descending artery for 40 minutes followed by 2.5 hours of reperfusion. The primary outcome parameter was infarct size in relation to the ischemic region at risk. Secondary endpoints were the hemodynamic parameters mean pulmonary pressure, cardiac output, pulmonary capillary wedge pressure as measured by a Swan-Ganz catheter as well as arterial pressure and heart rate.</p> <p>Results</p> <p>The infarct size in relation to ischemic risk region in the control versus the Liraglutide group did not differ significantly: 0.46 ± 0.14 and 0.54 ± 0.12) (mean and standard deviation (SD), p = 0.21). Heart rate was significantly higher in the Liraglutide group during the experiment, while the other hemodynamic parameters did not differ significantly.</p> <p>Conclusion</p> <p>Liraglutide has a neutral effect on myocardial infarct size in a porcine ischemia-reperfusion model.</p