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

IF 3.5 4区 医学 Q2 SURGERY
Journal of Investigative Surgery Pub Date : 2025-12-01 Epub Date: 2025-08-26 DOI:10.1080/08941939.2025.2545340
Yanyi Liu, Ning Yang, Ju Mei, Chao Wang, Zhengyu Lin, Yang Zou, Shi Qiu, Fangbao Ding, Zhaolei Jiang
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引用次数: 0

Abstract

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.

一种预测急性心肌梗死手术血运重建术患者术后早期死亡率的新型Nomogram。
背景:尽管外科技术取得了进步,但近期急性心肌梗死(AMI)患者的冠状动脉旁路移植术(CABG)仍然与相对较高的死亡率相关。对这些患者进行风险预测至关重要。本研究的目的是建立一种基于术前临床特征预测AMI手术血运重建术患者术后早期死亡率的nomogram模型。方法:回顾性分析2018年1月至2024年12月我院连续332例AMI冠脉搭桥患者的临床资料。通过单变量和多变量logistic回归模型确定术后早期死亡的独立预测因子。在所有独立预测因子的基础上建立了nomogram预测模型。评估模型的判别能力、校准和临床应用。利用自举方法进行内部验证。结果:nomogram模型纳入了7个独立预测因子:术前心脏停搏、心肌梗死(MI)史、左室射血分数(LVEF) 75岁、血清白蛋白< 35g/L、血清肌酐> 2.0 mg/dL。该模型判别效果良好,受试者工作特征曲线下面积为0.905 (95% CI: 0.832 ~ 0.978),与Hosmer-Lemeshow检验结果拟合良好(χ2 = 3.437, p = 0.944)。决策曲线分析表明,在较宽的阈值概率范围内,与“全操作”或“不操作”策略相比,该模型可以提供更大的临床净效益。结论:结合7项术前临床预测因子的新型nomogram模型,可为AMI手术血运重建术患者术后早期死亡提供准确的术前估计,并具有良好的鉴别和校正效果。
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来源期刊
CiteScore
4.20
自引率
0.00%
发文量
114
审稿时长
6-12 weeks
期刊介绍: Journal of Investigative Surgery publishes peer-reviewed scientific articles for the advancement of surgery, to the ultimate benefit of patient care and rehabilitation. It is the only journal that encompasses the individual and collaborative efforts of scientists in human and veterinary medicine, dentistry, basic and applied sciences, engineering, and law and ethics. The journal is dedicated to the publication of outstanding articles of interest to the surgical research community.
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