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August 19, 2025BiomedicinesOpen Access

Machine Learning-Based Prediction of Short-Term Mortality After Coronary Artery Bypass Grafting: A Retrospective Cohort Study

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Authors

ISIslam SalikhanovVRVolker RöthBGBrigitta Gahl

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Overview

Retrospective cohort analysis reveals improved specificity for ML models over EuroSCORE II in predicting short-term mortality.

Key Points

  • ML models incorporating preoperative and postoperative data improve specificity in mortality prediction.
  • The study reported a 30-day mortality rate of 2.5% among 3483 patients undergoing CABG procedures.
  • This retrospective cohort study evaluated multiple predictive models for effectiveness in mortality assessment using AUC.
  • Findings highlight the significance of additional postoperative variables like kidney failure and myocardial infarction.

Cite This Study

Salikhanov et al. (2025) studied this question.

synapsesocial.com/papers/68af35ddcf1dd9ea359e9d30https://doi.org/10.3390/biomedicines13082023
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