158 papers
This study demonstrates that rare protein-disrupting variants in the CETP gene, which lead to lifelong reduced CETP activity and favorable lipid profiles, are significantly associated with a lower risk of atherosclerotic vascular events and longer disease-free survival.
This systematic review and meta-analysis of five randomized trials indicates that while edoxaban generally offers superior efficacy in reducing stroke and major adverse cardiovascular events compared to warfarin, warfarin remains a critical alternative for specific high-risk subgroups, including patients with prior myocardial infarction, high CHA2DS2-VASc scores, and certain heart failure profiles.
This paper introduces DIA-PINN, a physics-informed neural network framework that accurately and robustly estimates global intrinsic diastolic properties of the left ventricle from instantaneous pressure-volume data, outperforming traditional optimization methods by providing reliable, initialization-insensitive estimates of stiffness, relaxation, and elastic recoil.
This study demonstrates that in a large cohort of acute heart failure patients, artificial intelligence-enabled electrocardiography (AI-ECG) provides universally feasible, scalable diastolic function grading that correlates with hemodynamic severity and independently predicts mortality and rehospitalization, offering a pragmatic solution when echocardiographic assessment is indeterminate or unavailable.
This Danish registry study of over 83,000 people with type 2 diabetes demonstrates that while incorporating trajectory measures of HbA1c, LDL-cholesterol, and eGFR (specifically dispersion and change rather than central tendency) only marginally improves the discrimination of incident cardiovascular disease risk, it offers modest gains in net reclassification, particularly for LDL-cholesterol variability.
This translational study demonstrates that antenatal iron deficiency impairs postpartum cardiac recovery and increases the risk of peripartum cardiomyopathy by causing myocardial iron depletion and dysregulating cardiometabolic pathways, suggesting iron supplementation as a potential preventive strategy.
This prospective cohort study demonstrates that linking national electronic health records in England significantly improves stroke case ascertainment and reveals a rising stroke incidence alongside suboptimal antihypertensive prescribing and socioeconomic disparities in "home-time," thereby validating the utility of integrated data for monitoring and enhancing stroke care quality beyond the pandemic era.
This study developed and validated a scalable, AI-driven toolkit (ECG-ASCVD) that utilizes electrocardiogram data to predict atherosclerotic cardiovascular disease risk across diverse multinational cohorts, offering a solution for risk stratification in patients lacking traditional clinical data.
This study demonstrates that an automated machine learning model applied to routine echocardiographic strain data can successfully identify subtle, pre-symptomatic myocardial abnormalities in individuals carrying the TTR V142I variant, offering a scalable strategy for the early detection of cardiac amyloidosis risk before clinical symptoms appear.
This prospective study of 155 first-time myocardial infarction patients identifies insulin-like growth factor-binding protein 2 (IGFBP-2) as an independent predictor of adverse left ventricular remodeling at 12 months, suggesting its potential to improve risk stratification and guide precision therapies for patients with cardiometabolic dysregulation.
This systematic review and meta-analysis of eight randomized controlled trials demonstrates that exogenous ketone-based therapies significantly improve key hemodynamic markers of cardiac function, including increased left ventricular ejection fraction, cardiac output, and stroke volume, alongside reduced pulmonary capillary wedge pressure, in adults with heart failure or related cardiometabolic risk factors.
This cross-sectional study demonstrates that chronic inhaled combusted cannabis use is associated with proatherogenic changes in monocytes and plasma among healthy young adults, an effect that is further amplified when combined with nicotine electronic cigarette use.
This systematic review and meta-analysis of 65 randomized trials provides firm evidence that remote patient monitoring significantly reduces all-cause mortality and heart failure hospitalizations, while highlighting a critical evidence gap regarding its efficacy in geographically underserved populations due to a lack of rural/urban subgroup data.
In a cohort of Malawian children with rheumatic heart disease, independent predictors of all-cause mortality included living more than 40 km from tertiary care, malnutrition, beta-blocker use, and the presence of pericardial effusion, highlighting the dire prognosis of the disease in under-resourced settings.
This study demonstrates that at least five blood pressure measurements are sufficient to calculate visit-to-visit variability, identifying specific standard deviation, coefficient of variation, and average real variability thresholds that effectively predict cardiovascular disease risk in primary care patients.
This retrospective study of U.S. hospitalizations reveals that ventricular arrhythmias significantly increase in-hospital mortality and complications in acute myocarditis patients, while those undergoing catheter ablation for ventricular tachycardia experienced even higher rates of adverse outcomes, highlighting the need for further research to optimize treatment criteria in this high-risk population.
This study reveals that while anthracycline-induced endothelial injury largely resolves after childhood cancer treatment, long-term cardiovascular risk is driven by impaired endothelial repair mechanisms characterized by depleted and senescent endothelial progenitor cells during remission.
This prospective cohort study demonstrates that incorporating visit-to-visit blood pressure variability into cardiovascular disease risk prediction models significantly enhances their discriminatory accuracy for patients aged 55 and older compared to models relying solely on a single blood pressure measurement.
This study developed and validated the Fuwai-Cardiac Recovery Scale (Fuwai-CRS), a concise 9-item tool designed to effectively assess patient-reported recovery outcomes following cardiac surgery.
By applying machine learning to proteomic data from over 7,000 hypertension patients, researchers identified distinct molecular subtypes characterized by specific protein expression patterns that correlate with varying risks of cardiovascular and renal complications, suggesting a path toward more personalized precision medicine.