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Remote patient monitoring in heart failure: A comprehensive meta-analysis of effective programme components for hospitalization and mortality reduction.
Eur J Heart Fail
January 2025
Department of Cardiology, Máxima Medical Centre, Veldhoven, The Netherlands.
Aims: Methods of non-invasive remote patient monitoring (RPM) for heart failure (HF) remain diverse. Understanding factors that influence the effectiveness of RPM on HF-related and all-cause hospitalizations, mortality, and emergency department visits is crucial for developing successful RPM interventions. This meta-analysis aims to synthesize and compare existing literature on RPM components that impact HF-related and all-cause hospitalizations, mortality and emergency department visits in HF patients.
View Article and Find Full Text PDFMachine learning-driven prediction of medical expenses in triple-vessel PCI patients using feature selection.
BMC Health Serv Res
January 2025
Graduate Institute of Business Administration, College of Management, Fu Jen Catholic University, No.510, Zhongzheng Rd., Xinzhuang Dist., New Taipei City, 242062, Taiwan (R.O.C.).
Revascularization therapies, such as percutaneous coronary intervention (PCI) and coronary artery bypass grafting (CABG), alleviate symptoms and treat myocardial ischemia. Patients with multivessel disease, particularly those undergoing 3-vessel PCI, are more susceptible to procedural complications, which can increase healthcare costs. Developing efficient strategies for resource allocation has become a paramount concern due to tightening healthcare budgets and the escalating costs of treating heart conditions.
View Article and Find Full Text PDFKey Concepts in Machine Learning and Clinical Applications in the Cardiac Intensive Care Unit.
Curr Cardiol Rep
January 2025
Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA.
Purpose Of Review: Artificial Intelligence (AI) technology will significantly alter critical care cardiology, from our understanding of diseases to the way in which we communicate with patients and colleagues. We summarize the potential applications of AI in the cardiac intensive care unit (CICU) by reviewing current evidence, future developments and possible challenges.
Recent Findings: Machine Learning (ML) methods have been leveraged to improve interpretation and discover novel uses for diagnostic tests such as the ECG and echocardiograms.
Manipulating Mechanical Forces in the Developing Zebrafish Heart Using Magnetic Beads.
J Vis Exp
January 2025
Department of Bioengineering, Imperial College London; The Francis Crick Institute;
Mechanical forces continuously provide feedback to heart valve morphogenetic programs. In zebrafish, cardiac valve development relies on heart contraction and physical stimuli generated by the beating heart. Intracardiac hemodynamics, driven by blood flow, emerge as fundamental information shaping the development of the embryonic heart.
View Article and Find Full Text PDFTreatment of Cardiogenic Shock: Inotropes, Vasopressors and Machines.
Br J Hosp Med (Lond)
December 2024
Queen Elizabeth Hospital Birmingham, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
Cardiogenic shock (CS) is associated with significant mortality. Advances in pharmacological therapies and mechanical circulatory support (MCS) devices have markedly improved the therapeutic approach to CS, though treatment efficacy and safety vary. The recent DanGer shock trial showed a significant reduction in 6-month mortality for CS patients due to acute myocardial infarction.
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