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Importance of confounding risk factors for newly occurring atrial fibrillation after coronary artery bypass grafting.
Gen Thorac Cardiovasc Surg
January 2025
Department of Perfusion, Faculty of Health Sciences, Harran University, Sanliurfa, Türkiye.
Coronary Artery Calcium Scoring Improves Allocation of the GLP-1 Receptor Agonist Semaglutide.
JACC Cardiovasc Imaging
January 2025
Department of Medicine, Lundquist Institute at Harbor-UCLA, Torrance, California, USA.
Allocation of Semaglutide According to Coronary Artery Calcium and BMI: Applying the SELECT Trial to MESA.
JACC Cardiovasc Imaging
January 2025
Ciccarone Center for the Prevention of Cardiovascular Disease, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. Electronic address:
Background: Implementation of semaglutide weight loss therapy has been challenging due to drug supply and cost, underscoring a need to identify those who derive the greatest absolute benefit.
Objectives: Allocation of semaglutide was modeled according to coronary artery calcium (CAC) among individuals without diabetes or established atherosclerotic cardiovascular disease (CVD).
Methods: In this analysis, 3,129 participants in the MESA (Multi-Ethnic Study of Atherosclerosis) without diabetes or clinical CVD met body mass index criteria for semaglutide and underwent CAC scoring on noncontrast cardiac computed tomography.
Concordance and Accuracy of Pressure Wire-Derived Indices in Left Main Coronary Artery Disease.
JACC Cardiovasc Interv
December 2024
British Heart Foundation Centre of Research Excellence at the School of Cardiovascular Medicine and Sciences, King's College London, United Kingdom; Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom. Electronic address:
Comparative Evaluation of Chatbot Responses on Coronary Artery Disease.
Turk Kardiyol Dern Ars
January 2025
Department of Cardiology, Dr Siyami Ersek Thoracic and Cardiovascular Surgery Training Hospital, İstanbul, Türkiye.
Objective: Coronary artery disease (CAD) is the leading cause of morbidity and mortality globally. The growing interest in natural language processing chatbots (NLPCs) has driven their inevitable widespread adoption in healthcare. The purpose of this study was to evaluate the accuracy and reproducibility of responses provided by NLPCs, such as ChatGPT, Gemini, and Bing, to frequently asked questions about CAD.
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