96 papers
Cardiovascular medicine focuses on the heart and blood vessels, exploring how to prevent, diagnose, and treat conditions that affect our circulation. This vital field ranges from understanding high blood pressure and heart failure to investigating the latest breakthroughs in surgical techniques and lifestyle interventions. Because these discoveries directly impact public health, staying informed about emerging research is more important than ever for both specialists and curious readers.
At Gist.Science, we process every new preprint in this category as it appears on medRxiv, ensuring you have immediate access to the latest findings before they undergo formal peer review. For each study, we provide both a plain-language explanation to clarify the core concepts and a detailed technical summary for those seeking deeper scientific context. Below are the latest papers in cardiovascular medicine, organized to help you navigate the most recent developments shaping the future of heart health.
This study demonstrates that fully automated, multi-view deep neural networks can accurately detect mitral valve prolapse and clinically significant mitral regurgitation from echocardiographic videos, achieving high performance in both internal and external validation cohorts.
This study of NHANES III participants demonstrates that subclinical myocardial injury partially mediates the association between elevated resting heart rate and increased long-term mortality, suggesting that ECG-based assessment of such injury can improve risk stratification for individuals with tachycardia.
This study demonstrates that a data-driven approach using principal component analysis to generate synthetic cerebral aneurysm geometries effectively reveals how specific morphological variations, particularly aneurysm height and dome width, systematically govern intra-aneurysmal hemodynamics and wall shear stress patterns.
This qualitative study utilized the COM-B and TDF frameworks to analyze interviews with 54 ACHD patients and clinicians, resulting in a novel, theory-driven engagement framework that identifies six interdependent categories of determinants to guide the development of future interventions for improving specialized adult congenital heart disease care.
This cross-sectional study at Mwananyamala Hospital in Tanzania reveals a 32.8% prevalence of hypertension among people living with HIV on antiretroviral therapy, identifying older age, cigarette smoking, and longer duration since HIV diagnosis as significant risk factors while highlighting the need for integrated screening and education to address this growing comorbidity.
The SOLO study demonstrates that promoting single-pill combination therapy through a targeted care improvement project in a disadvantaged, multi-ethnic primary care setting significantly increased treatment initiation and improved blood pressure control compared to usual care.
This study demonstrates that an explainable advanced electrocardiography (A-ECG) model, derived from standard 12-lead ECG features, provides modest but externally reproducible discrimination for detecting coronary artery disease on CT angiography and independently predicts future cardiovascular events in a large population cohort.
This study utilizes Mendelian randomization to demonstrate that triglyceride-rich lipoproteins are at least three times more aneurysmogenic than low-density lipoproteins on a per-particle basis, suggesting that therapeutic strategies targeting TRL pathways, particularly APOC3 and LPL, should be prioritized for abdominal aortic aneurysm prevention.
This research demonstrates that a Temporal Convolutional Network (TCN) architecture outperforms other deep learning models in predicting structural heart disease from ECG and clinical data, offering statistically significant, stable, and computationally efficient performance suitable for fair healthcare applications.
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.