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A Novel Nomogram for Preoperative Prediction of Early Postoperative Mortality in Patients Undergoing Surgical

Yanyi Liu1, Ning Yang1, Ju Mei1

  • 1Department of Cardiothoracic Surgery, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, P. R. China.

Journal of Investigative Surgery : the Official Journal of the Academy of Surgical Research
|August 26, 2025
PubMed

Insights

A new nomogram predicts early death risk in acute myocardial infarction (AMI) patients undergoing coronary artery bypass grafting (CABG). This tool uses seven preoperative factors to improve risk assessment for surgical revascularization.

Area of Science:

  • Cardiology
  • Cardiovascular Surgery
  • Medical Informatics

Background:

  • Coronary artery bypass grafting (CABG) for acute myocardial infarction (AMI) has high mortality.
  • Accurate risk prediction is crucial for these high-risk patients.
  • Current prediction models may not fully capture early postoperative mortality risks.

Purpose of the Study:

  • Develop and validate a nomogram model.
  • Predict early postoperative mortality in AMI patients undergoing surgical revascularization.
  • Utilize preoperative clinical features for risk stratification.

Main Methods:

  • Retrospective analysis of 332 consecutive AMI patients undergoing CABG.
  • Identification of independent predictors using logistic regression.
  • Development and validation of a nomogram using bootstrapping.
  • Evaluation of model discrimination, calibration, and clinical utility.

Main Results:

  • A nomogram incorporating seven predictors was developed: preoperative cardiac arrest, prior MI, LVEF <50%, MI-to-CABG interval ≤3d, age >75 years, serum albumin <35g/L, and serum creatinine >2.0mg/dL.
  • The model demonstrated excellent discrimination (AUC=0.905) and calibration (p=0.944).
  • Decision curve analysis confirmed clinical utility over "operate-all" or "operate-none" strategies.

Conclusions:

  • A novel nomogram accurately predicts early postoperative death in AMI patients undergoing CABG.
  • The model integrates seven preoperative clinical predictors for improved risk estimation.
  • The nomogram offers satisfactory discrimination and calibration for clinical decision-making.
Abstract

Keywords:
acute myocardial infarctioncoronary artery bypass graftingmortalitynomogramsurgical revascularization

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