1,721,065 research outputs found
Vitamin D supplementation and COVID-19 disease: safety but unproven efficacy reply to Dr Helga Rhein.
No full textVitamin D and COVID-19 disease: don’t believe everything you read in the papers! Reply to Dr William B. Grant.
No full textCardiovascular magnetic resonance reference ranges from the Healthy Hearts Consortium
No full textBackground: The absence of population-stratified cardiovascular magnetic resonance (CMR) reference ranges from large cohorts is a major shortcoming for clinical care. Objectives: This paper provides age-, sex-, and ethnicity-specific CMR reference ranges for atrial and ventricular metrics from the Healthy Hearts Consortium, an international collaborative comprising 9,088 CMR studies from verified healthy individuals, covering the complete adult age spectrum across both sexes, and with the highest ethnic diversity reported to date. Methods: CMR studies were analyzed using certified software with batch processing capability (cvi42, version 5.14 prototype, Circle Cardiovascular Imaging) by 2 expert readers. Three segmentation methods (smooth, papillary, anatomic) were used to contour the endocardial and epicardial borders of the ventricles and atria from long- and short-axis cine series. Clinically established ventricular and atrial metrics were extracted and stratified by age, sex, and ethnicity. Variations by segmentation method, scanner vendor, and magnet strength were examined. Reference ranges are reported as 95% prediction intervals. Results: The sample included 4,452 (49.0%) men and 4,636 (51.0%) women with average age of 61.1 ± 12.9 years (range: 18-83 years). Among these, 7,424 (81.7%) were from White, 510 (5.6%) South Asian, 478 (5.3%) mixed/other, 341 (3.7%) Black, and 335 (3.7%) Chinese ethnicities. Images were acquired using 1.5-T (n = 8,779; 96.6%) and 3.0-T (n = 309; 3.4%) scanners from Siemens (n = 8,299; 91.3%), Philips (n = 498; 5.5%), and GE (n = 291, 3.2%). Conclusions: This work represents a resource with healthy CMR-derived volumetric reference ranges ready for clinical implementation.</p
Cardiovascular magnetic resonance imaging in the UK Biobank: a major international health research resource
Full text linkThe UK Biobank (UKB) is a health research resource of major international importance, incorporating comprehensive characterisation of over 500,000 men and women recruited between 2006-2010 from across the UK. There is prospective tracking of health outcomes for all participants through linkages with national cohorts (death registers, cancer registers, electronic hospital records, primary care records). The dataset has been enhanced with the UKB imaging study, which aims to scan a subset of 100,000 participants. The imaging protocol includes magnetic resonance imaging of the brain, heart, and abdomen, carotid ultrasound, and whole-body dual x-ray absorptiometry (DXA). Since its launch in 2015, over 48,000 participants have completed the imaging study with scheduled completion in 2023. Repeat imaging of 10,000 participants has been approved and commenced in 2019. The cardiovascular magnetic resonance (CMR) scan provides detailed assessment of cardiac structure and function comprising bright blood anatomic assessment (sagittal, coronal, axial), left and right ventricular cine images (long and short axis), myocardial tagging, native T1 mapping, aortic flow, and imaging of the thoracic aorta. The UKB is an open access resource available to health researchers across all scientific disciplines from both academia and industry with no preferential access or exclusivity. In this paper, we consider how we may best utilise the UKB CMR data to advance cardiovascular research and review notable achievements to date
A Perspective on Explainable Artificial Intelligence Methods: SHAP and LIME
Full text linkeXplainable artificial intelligence (XAI) methods have emerged to convert the black box of machine learning (ML) models into a more digestible form. These methods help to communicate how the model works with the aim of making ML models more transparent and increasing the trust of end-users into their output. SHapley Additive exPlanations (SHAP) and Local Interpretable Model Agnostic Explanation (LIME) are two widely used XAI methods, particularly with tabular data. In this perspective piece, we discuss the way the explainability metrics of these two methods are generated and propose a framework for interpretation of their outputs, highlighting their weaknesses and strengths. Specifically, we discuss their outcomes in terms of model-dependency and in the presence of collinearity among the features, relying on a case study from the biomedical domain (classification of individuals with or without myocardial infarction). The results indicate that SHAP and LIME are highly affected by the adopted ML model and feature collinearity, raising a note of caution on their usage and interpretation
Type 1 and 2 diabetes mellitus: comprehensive fracture risk: relationships in UK Biobank
Full text linkWe aimed to investigate associations between diabetes mellitus and incident fracture, stratified by diabetes type (1 or 2), disease duration and microvascular complications of diabetes. This prospective cohort analysis used data from the UK Biobank, a large population-based cohort of participants recruited 2006-2010 at age 40-69 yr. The exposure was type 1 or type 2 diabetes at baseline, with the outcome of first incident osteoporotic fracture. Poisson regression was used to calculate incidence rate ratios (IRRs) for osteoporotic fracture to investigate prospective relationships between diabetes type 1 or 2 and fracture risk independent of traditional clinical risk factors, estimated bone mineral density by heel ultrasound (eBMD), adiposity, and C-reactive protein. The role of diabetic microvascular complications and associations between diabetes duration and fracture risk were studied. There were 498 949 participants (271 882 women, mean age 56 yr; 227 067 men, 57 yr). In fully adjusted models, type 1 and 2 diabetes were associated with increased fracture risk [type 1; IRR: 2.93 (95%CI:2.37,3.62); type 2: 1.25 (1.14,1.38)], similar by sex. The magnitude of risk associated with type 2 diabetes increased with duration of disease. Increasing number of microvascular complications was associated with greater fracture risk [any vs no complications, IRR 2.03 (1.57,2.62)]. Diabetes is associated with increased risk of fracture (magnitude of effect greater in type 1 than type 2 diabetes). Associations were partly independent of traditional risk factors, adiposity, eBMD and CRP. Type 2 diabetes disease duration and the presence of microvascular complications in both types were dose-dependent risk factors for fracture
Bone mineral density and cardiovascular diseases: a two-sample Mendelian randomization study
No full textThe link between BMD and cardiovascular disease (CVD) remains a topic of extensive debate in observational studies, with inconsistent reports regarding the causality of this relationship. This study implements robust methodologies to evaluate the causal relationship between BMD and various CVDs. Two sample Mendelian randomization (MR) method was used to estimate the relationship between genetically predicted BMD and seven key CVDs: atrial fibrillation and flutter, angina, ischemic heart disease, heart failure, hypertension, myocardial infarction, and non-ischemic cardiomyopathy. Data were obtained from independent publicly available genome-wide association studies (GWAS) for BMD and CVDs, using two separate datasets for the cardiovascular outcomes: the UK Biobank cohort (primary analysis) and the FinnGen cohort (validation analysis). The MR Pleiotropy RESidual Sum and Outlier test assessed the heterogeneity and pleiotropy of selected instrumental variables (IVs). We applied the inverse variance weighted model (IVW), weighted median, weighted mode method, and MR-Egger regression model to estimate causal effects. MR results indicate no relationship between BMD and atrial fibrillation and flutter (IVW, beta-estimate: 0.011, SE: 0.03, p =. 73), angina (IVW, beta-estimate: 0.04, SE: 0.03, p =. 17), chronic ischemic heart disease (IVW, beta-estimate: 0.009, SE: 0.03, p =. 74), heart failure (IVW, beta-estimate: 0.004, SE: 0.04, p =. 91), hypertension (IVW, beta-estimate: -0.01, SE: 0.01, p =. 44), myocardial infarction (IVW, beta-estimate: 0.02, SE: 0.03, p =. 36), or non-ischemic cardiomyopathy (IVW, beta-estimate: 0.1, SE: 0.08, p =. 20). These findings remained consistent across all complementary analyses (MR-Egger, weighted median and weighted mode) and were validated using the FinnGen cohort GWAS dataset. This comprehensive analysis identified no evidence for a causal link between genetically predicted BMD and a range of key CVDs. Previously reported observational associations between bone and cardiovascular health likely represent shared risk factors rather than direct causal mechanisms.</p
Multi-modal brain age estimation: a comparative study confirms the importance of microstructure
No full textbrain agin
Age, sex and disease-specific associations between resting heart rate and cardiovascular mortality in the UK BIOBANK
No full textObjective: to define the sex, age, and disease-specific associations of resting heart rate (RHR) with cardiovascular and mortality outcomes in 502,534 individuals from the UK Biobank over 7–12 years of prospective follow-up.Methods: the main outcomes were all-cause, cardiovascular, and ischaemic heart disease mortality. Additional outcomes included incident acute myocardial infarction (AMI), fatal AMI, and cancer mortality. We considered a wide range of confounders and the effects of competing hazards. Results are reported as hazard ratios (HR) for all-cause mortality and sub-distribution hazard ratios (SHR) for other outcomes with corresponding 95% confidence intervals (CI) per 10bpm increment of RHR. Results: in men, for every 10bpm increase of RHR there was 22% (HR 1.22, CI 1.20 to 1.24, p=3×10-123) greater hazard of all-cause and 17% (SHR 1.17, CI 1.13 to 1.21, p=5.6×10-18) greater hazard of cardiovascular mortality; for women, corresponding figures were 19% (HR 1.19, CI 1.16 to 1.22, p=8.9×10-45) and 14% (SHR 1.14, CI 1.07 to 1.22, p=0.00008). Associations between RHR and ischaemic outcomes were of greater magnitude amongst men than women, but with similar magnitude of association for non-cardiovascular cancer mortality [men (SHR 1.18, CI 1.15-1.21, p=5.2×10-46); women 15% (SHR 1.15, CI 1.11-1.18, p=3.1×10-18)]. Associations with all-cause, incident AMI, and cancer mortality were of greater magnitude at younger than older ages.Conclusions: RHR is an independent predictor of mortality, with variation by sex, age, and disease. Ischaemic disease appeared a more important driver of this relationship in men, and associations were more pronounced at younger ages. <br/
Renin-angiotensin-aldosterone system blockers are not associated with coronavirus disease 2019 (COVID-19) hospitalisation: study of 1439 UK biobank cases
No full textBackground: Cardiometabolic morbidity and medications, specifically Angiotensin Converting Enzyme inhibitors (ACEi) and Angiotensin Receptor Blockers (ARBs), have been linked with adverse outcomes from coronavirus disease 2019 (COVID-19). This study aims to investigate, factors associated with COVID-19 positivity in hospital for 1,436 UK Biobank participants; compared with individuals who tested negative, and with the untested, presumed negative, rest of the cohort.Methods: We studied 7,099 participants from the UK Biobank who had been tested for COVID-19 in hospital. We considered the following exposures: age, sex, ethnicity, body mass index (BMI), diabetes, hypertension, hypercholesterolaemia, ACEi/ARB use, prior myocardial infarction (MI), and smoking. We undertook comparisons between 1) COVID-19 positive and COVID-19 negative tested participants; and 2) COVID-19 tested positive and the remaining participants (tested negative plus untested, n=494,838). Logistic regression models were used to investigate univariate and mutually adjusted associations.Results: Among participants tested for COVID-19, Black, Asian, and Minority ethnic (BAME) ethnicity, male sex, and higher BMI were independently associated with a positive result. BAME ethnicity, male sex, greater BMI, diabetes, hypertension, and smoking were independently associated with COVID-19 positivity compared to the remining cohort (test negatives plus untested). However, similar associations were observed when comparing those who tested negative for COVID-19 with the untested cohort; suggesting that these factors associate with general hospitalisation rather than specifically with COVID-19. Conclusions: Among participants tested for COVID-19 with presumed moderate to severe symptoms in a hospital setting, BAME ethnicity, male sex, and higher BMI are associated with a positive result. Other cardiometabolic morbidities confer increased risk of hospitalisation, without specificity for COVID-19. ACE/ARB use did not associate with COVID-19 status
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