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A Higher-Than-Standard-Intensity International Normalized Ratio Goal for Patients Undergoing Mechanical Aortic Valve Replacement With Additional Thrombotic Risk Factors: Protocol for a Systematic Review and Meta-Analysis

A Higher-Than-Standard-Intensity International Normalized Ratio Goal for Patients Undergoing Mechanical Aortic Valve Replacement With Additional Thrombotic Risk Factors: Protocol for a Systematic Review and Meta-Analysis

These features inherently increase the risk of thromboembolism, suggesting that many MAVR recipients may require more intensive anticoagulation [7]. However, balancing thrombotic protection with bleeding risk is critical, and existing evidence is insufficient to guide personalized INR targets.

Myung-Rho Kim, Taha Shaikh, Shawn Wang, Spencer Taylor, Vidhani Goel, Banveet Kaur Khetarpal, Chowdhury Ahsan, Kavita Batra

JMIR Res Protoc 2025;14:e73389

Machine Learning in the Management of Patients Undergoing Catheter Ablation for Atrial Fibrillation: Scoping Review

Machine Learning in the Management of Patients Undergoing Catheter Ablation for Atrial Fibrillation: Scoping Review

While AF substantially impacts patients’ quality of life, it also increases the risk of serious medical conditions [4-7], such as stroke and thromboembolism. This contributes to long-term rises in both morbidity and mortality rates [8] as well as a growing strain on health care costs [9]. Catheter ablation (CA) represents the most effective clinical intervention currently available for AF [10]. When patients receive their first CA treatment, the effectiveness rate can reach 60%-80% within 1 year [11,12].

Aijing Luo, Wei Chen, Hongtao Zhu, Wenzhao Xie, Xi Chen, Zhenjiang Liu, Zirui Xin

J Med Internet Res 2025;27:e60888

Use of Machine Learning for Early Detection of Maternal Cardiovascular Conditions: Retrospective Study Using Electronic Health Record Data

Use of Machine Learning for Early Detection of Maternal Cardiovascular Conditions: Retrospective Study Using Electronic Health Record Data

Following full analysis by HOPE-CAT, patient risk profiles were linked to any outcomes of cardiovascular pregnancy conditions and complications, specifically preeclampsia and eclampsia, cardiomyopathy, myocardial infarction (MI), heart failure, acute kidney disease and failure, cerebral infarction, pulmonary embolism, venous thromboembolism, and HELLP (hemolysis, elevated liver enzymes, and low platelets) syndrome.

Nawar Shara, Roxanne Mirabal-Beltran, Bethany Talmadge, Noor Falah, Maryam Ahmad, Ramon Dempers, Samantha Crovatt, Steven Eisenberg, Kelley Anderson

JMIR Cardio 2024;8:e53091