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Phenotypic clustering of heart failure with preserved ejection fraction reveals different rates of hospitalization.

Journal of cardiovascular medicine (Hagerstown, Md.)
AIMS: Approximately 50% of patients with heart failure have preserved (≥50%) ejection fraction (HFpEF). Improved understanding of the phenotypic heterogeneity of HFpEF might facilitate development of targeted therapies and interventions.

Machine Learning Assessment of Left Ventricular Diastolic Function Based on Electrocardiographic Features.

Journal of the American College of Cardiology
BACKGROUND: Left ventricular (LV) diastolic dysfunction is recognized as playing a major role in the pathophysiology of heart failure; however, clinical tools for identifying diastolic dysfunction before echocardiography remain imprecise.

Early Detection of Heart Failure With Reduced Ejection Fraction Using Perioperative Data Among Noncardiac Surgical Patients: A Machine-Learning Approach.

Anesthesia and analgesia
BACKGROUND: Heart failure with reduced ejection fraction (HFrEF) is a condition imposing significant health care burden. Given its syndromic nature and often insidious onset, the diagnosis may not be made until clinical manifestations prompt further ...

Determinants of In-Hospital Mortality After Percutaneous Coronary Intervention: A Machine Learning Approach.

Journal of the American Heart Association
Background The ability to accurately predict the occurrence of in-hospital death after percutaneous coronary intervention is important for clinical decision-making. We sought to utilize the New York Percutaneous Coronary Intervention Reporting System...

Fully Automated Echocardiogram Interpretation in Clinical Practice.

Circulation
BACKGROUND: Automated cardiac image interpretation has the potential to transform clinical practice in multiple ways, including enabling serial assessment of cardiac function by nonexperts in primary care and rural settings. We hypothesized that adva...

Machine Learning Analysis of Left Ventricular Function to Characterize Heart Failure With Preserved Ejection Fraction.

Circulation. Cardiovascular imaging
BACKGROUND: Current diagnosis of heart failure with preserved ejection fraction (HFpEF) is suboptimal. We tested the hypothesis that comprehensive machine learning (ML) of left ventricular function at rest and exercise objectively captures difference...

Machine Learning Algorithm Predicts Cardiac Resynchronization Therapy Outcomes: Lessons From the COMPANION Trial.

Circulation. Arrhythmia and electrophysiology
BACKGROUND: Cardiac resynchronization therapy (CRT) reduces morbidity and mortality in heart failure patients with reduced left ventricular function and intraventricular conduction delay. However, individual outcomes vary significantly. This study so...

[Perfusion-Metabolic Myocardial Scintigraphy in Prognosis of Left Ventricular Remodeling After Complex Surgical Treatment of Ischemic Cardiomyopathy].

Kardiologiia
PURPOSE: To study capabilities of perfusion-metabolic myocardial scintigraphy for prediction of the left ventricular (LV) reverse remodeling after comprehensive surgical treatment of ischemic cardiomyopathy (ICMP).