AI-Driven Kidney Risk Prediction During Cardiac Surgery

Predicting Kidney Injury After Cardiac Surgery With Cardiopulmonary Bypass Using Machine Learning

This study evaluates a machine learning (ML) model using electronic health record (EHR) data to predict acute kidney injury (AKI) after cardiac surgery. In 130 patients, the AI achieved strong predictive performance (AUROC 0.79 for AKI, 0.83 for 30-day kidney disease). The model enables early, automated risk stratification, offering a practical tool for proactive perioperative management and improved patient outcomes.

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Equity in Cardiac Surgery: Bridging the Gap in Mitral Valve Care

Sex-Based Differences in Outcomes Following Mitral Valve Surgery: A Contemporary Analysis From 2 Institutions

This retrospective study of 3,313 patients undergoing mitral valve surgery found that women presented older, with more advanced heart failure, and were less likely to receive valve repair. Despite these differences, operative mortality did not significantly differ between sexes after adjustment. Women experienced longer ICU and hospital stays, highlighting disparities in recovery rather than survival outcomes. 

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Anticoagulation Management and Monitoring in ECMO

Anticoagulation Management and Monitoring in ECMO: An International Survey From the ISTH SSC Subcommittee on Pediatric and Neonatal Thrombosis and Hemostasis

This international survey evaluates anticoagulation strategies in ECMO patients across 17 countries. Findings show unfractionated heparin remains the primary anticoagulant, while bivalirudin use is rising. Despite widespread protocol use, significant variability persists in dosing, monitoring, and transfusion practices. Hematology involvement is often limited to complex cases, highlighting the need for standardized, collaborative approaches to improve ECMO outcomes.

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