163 papers
This cross-sectional study reveals that EECP-related videos on TikTok generally exhibit low-to-moderate informational quality and limited visibility, with user engagement metrics showing weak or negative correlations with content reliability.
The UK Biobank Cardiac Monitoring Study utilized 14-day patch-based ECG and accelerometer data from 27,658 participants to characterize population-wide heart rhythms and physical activity, revealing significant rates of undiagnosed atrial fibrillation and distinct circadian patterns of arrhythmias linked to activity levels.
This study presents the first peripheral blood transcriptomic map of valvular heart disease-associated atrial fibrillation, revealing a distinct molecular signature characterized by convergent systemic inflammation and epigenetic remodeling that suggests novel therapeutic targets and minimally invasive biomarkers.
This retrospective validation study of the Swedish Registry of Cardiopulmonary Resuscitation (2015–2024) reveals that while unit response times align closely with emergency dispatch data, the registry's total response times are consistently shorter than dispatch records, indicating a systematic underestimation likely due to discrepancies in EMS case number accuracy and timing definitions.
In a blinded comparative study of congenital heart disease illustrations, human-modified images demonstrated superior anatomical accuracy and educational suitability compared to generative AI models, with Gemini NanoBanana outperforming ChatGPT systems yet still falling significantly short of expert-designed standards.
This UK Biobank study reveals that atrial fibrillation and depression share a bidirectional relationship mediated by inflammatory and cardiovascular factors, yet they exhibit distinct, non-additive alterations in central autonomic network structure and function, supporting a systems-level neurocardiac framework for their comorbidity.
This study introduces the TRIAD-HFpEF machine learning framework, which integrates multimodal clinical data to probabilistically diagnose Heart Failure with Preserved Ejection Fraction (HFpEF) in the UK Biobank, thereby enabling a 45-fold expansion of genetic discoveries and the identification of 11 actionable therapeutic targets while distinguishing causal drivers from non-causal biomarkers.
This UK Biobank study demonstrates that AI-detected asymptomatic atrial fibrillation on 12-lead ECGs identifies individuals at significantly elevated risk for incident ischemic stroke and major adverse cardiovascular events, suggesting that machine learning models can uncover subclinical AF-related risks missed by conventional clinical assessment.
This study demonstrates that a haplotype-based genetic model using standard genome-wide data can effectively predict elevated circulating lipoprotein(a) levels across diverse populations, offering a highly efficient strategy for opportunistic screening to address the current gap in clinical testing.
In a nested case-control study of rheumatoid arthritis patients, adding the biomarkers high-sensitivity cardiac troponin T and soluble TNF receptor 1 to clinical risk factors significantly improved the predictive accuracy for future cardiovascular events, though prospective validation is still required before clinical implementation.
This retrospective study of 880 patients undergoing emergency surgery for acute type A aortic dissection reveals that a pre- or intra-operative cardiopulmonary resuscitation duration of 15 minutes or longer is strongly associated with a nearly seven-fold increase in 30-day mortality and significantly higher risks of central nervous system complications, suggesting CPR duration is a critical prognostic indicator for surgical decision-making.
This study demonstrates that specific left ventricular morphological features, particularly the absence of a spiral septal pattern and a more conical shape, can effectively distinguish arrhythmic dilated cardiomyopathy from idiopathic cases and predict adverse arrhythmic outcomes beyond traditional markers like mass, function, or late gadolinium enhancement.
This genetic epidemiological study reveals that while genetically elevated omega-3 levels are initially associated with increased cardiovascular risk due to raised LDL-C, they ultimately exert a protective effect against coronary artery disease when combined with effective lipid management, particularly LDL-C control.
This study demonstrates that specific electrocardiographic parameters, including prolonged PR intervals, increased P-wave dispersion, and a reduced P-wave to PR interval ratio, serve as significant non-invasive digital biomarkers for screening asymptomatic rheumatic heart disease in schoolchildren, offering a viable strategy for early detection in resource-limited settings.
This study demonstrates that while peak high-sensitivity cardiac troponin correlates with late gadolinium enhancement extent in both acute myocardial infarction and acute myocarditis, the former releases significantly more troponin per unit of myocardial injury mass, indicating that troponin-based estimates of injury size are not directly interchangeable between these two conditions.
The paper introduces DELTA, a rigorous N=1 digital health study that integrates lifestyle interventions, dynamic biomarker challenges, and AI-driven analytics to assess and enhance human biological resilience, aiming to extend healthspan and inform future population-level trials.
This study employs a multi-layered approach integrating proteomics, AI-driven network analysis, and human genetics across two clinical trials to identify a multi-system molecular program involving endothelial remodeling, mitochondrial metabolism, and immune modulation that underlies physical function impairment and rehabilitation response in heart failure with preserved ejection fraction.
This systematic review and meta-analysis of 45 randomized controlled trials suggests that vitamin D supplementation may modestly improve key cardiometabolic risk factors, including systolic blood pressure, LDL cholesterol, and glycemic control, with effects that appear to be modulated by the recipient's age and baseline vitamin D status, though the clinical significance of these findings remains uncertain.
The RED-RHD study introduces an AI-based, adaptive multi-regional system that leverages OpenL3 embeddings and a dynamic model selection mechanism to achieve high-precision early detection and classification of Rheumatic Heart Disease murmurs across diverse, noisy clinical datasets.
This retrospective study from Hospital Clinic de Barcelona demonstrates that uncontrolled donation after circulatory death (uDCD) following failed ECPR is a viable source of transplantable organs, particularly kidneys, where shorter warm ischemia times and the central role of perfusionist nurses significantly enhance donation effectiveness.