A Novel Nomogram for Preoperative Prediction of Early Postoperative Mortality in Patients Undergoing Surgical Revascularization for Acute Myocardial Infarction

Background Despite advancements in surgical techniques, coronary artery bypass grafting (CABG) for patients with recent acute myocardial infarction (AMI) remains associated with relatively high mortality. Risk prediction in these patients is essential. The aim of this study was to develop a nomogram...

Full description

Saved in:
Bibliographic Details
Main Authors: Yanyi Liu, Ning Yang, Ju Mei, Chao Wang, Zhengyu Lin, Yang Zou, Shi Qiu, Fangbao Ding, Zhaolei Jiang
Format: Article
Language:English
Published: Taylor & Francis Group 2025-12-01
Series:Journal of Investigative Surgery
Subjects:
Online Access:https://www.tandfonline.com/doi/10.1080/08941939.2025.2545340
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Background Despite advancements in surgical techniques, coronary artery bypass grafting (CABG) for patients with recent acute myocardial infarction (AMI) remains associated with relatively high mortality. Risk prediction in these patients is essential. The aim of this study was to develop a nomogram model to predict the early postoperative mortality in patients undergoing surgical revascularization for AMI based on preoperative clinical features.Method We retrospectively analyzed the clinical data of 332 consecutive patients who underwent CABG for AMI at our center from January 2018 to December 2024. Independent predictors for early postoperative death were identified by using univariate and multivariate logistic regression models. A nomogram prediction model was developed based on all independent predictors. Discriminative ability, calibration, and clinical utility of the model were evaluated. Internal validation was performed utilizing the bootstrapping method.Results The nomogram model incorporated seven independent predictors: preoperative cardiac arrest, previous history of myocardial infarction(MI), left ventricular ejection fraction (LVEF) <50%, MI-to-CABG interval ≤ 3d, age > 75 years, serum albumin < 35g/L and serum creatinine > 2.0 mg/dL. The model achieved good discrimination with an area under the receiver operating characteristic curve (AUC) of 0.905 (95% CI: 0.832–0.978), and showed well-fitted calibration curves with Hosmer–Lemeshow test results (χ2 = 3.437, p = 0.944). Decision curve analysis indicated that the model can provide greater clinical net benefits compared to "operate-all" or "operate-none" strategies in a wide range of threshold probability.Conclusions The novel nomogram model combining seven preoperative clinical predictors can provide an accurate preoperative estimation of early postoperative death for AMI patients undergoing surgical revascularization, with satisfactory discrimination and calibration.
ISSN:0894-1939
1521-0553