ORIGINAL RESEARCH article
Front. Cardiovasc. Med.
Sec. Clinical and Translational Cardiovascular Medicine
Volume 12 - 2025 | doi: 10.3389/fcvm.2025.1590496
Development and Validation of A New Predictive Model for In-Hospital Postoperative Major Adverse Cardiovascular and Cerebrovascular Events After General Anesthesia in Nonagenarians Undergoing Non-Cardiac Surgery
Provisionally accepted- 1Chongqing Emergency Medical Center, Chongqing, China
- 2Chongqing People‘s Hospital, Chongqing, China
- 3The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China
Select one of your emails
You have multiple emails registered with Frontiers:
Notify me on publication
Please enter your email address:
If you already have an account, please login
You don't have a Frontiers account ? You can register here
Background: Major adverse cardiac and cerebrovascular events (MACCE) following noncardiac surgery are the main cause of perioperative mortality. However, there are few evidence-based prediction models available for predicting the risk of MACCE.We aimed to analyze the risk factors of MACCE in patients aged 90 and older and to construct a prediction model, ultimately leading to the development of a nomogram. Methods: This review study included clinical data from 872 patients aged 90 and older who underwent non-cardiac surgery under general anesthesia between 2015 and 2024. The outcome of interest was in-hospital postoperative MACCE. Logistic regression was employed to identify risk factors and to establish a nomogram for predicting the risk of MACCE. Calibration curves, C-index, and decision curves were used to evaluate the predictive model. An external cohort was used to compare the performance between our model and the widely used revised cardiac risk index (RCRI) score. Results : 112 patients(12.84%) experienced in-hospital MACCE. The final model identified four predictors, including emergency surgery, neutrophil/lymphocyte ratio(NLR) ≥ 11.2, D-dimer ≥ 3.6 mg/L, and postoperative admission to the ICU. The nomogram demonstrated strong discriminative ability with a C statistic of 0.853 and maintained its performance during 10-fold cross-validation with a C statistic of 0.784. Compared to the RCRI score, our predictive model performed better in the validation test (C statistic = 0.853 vs. 0.693). Conclusions : The predictors including NLR, D-dimer, emergency surgery, postoperative 24-hour ICU admission could better predict MACCE than RCRI score in patients greater than 90 years old undergoing non-cardiac surgery undergoing general anesthesia.
Keywords: Major adverse cardiovascular events, Cerebrovascular events, nomogram, Prediction model, Aged
Received: 17 Mar 2025; Accepted: 28 May 2025.
Copyright: © 2025 Feng, Tan, Duan, Zheng, Du, Fu and Ma. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Hong Fu, Chongqing Emergency Medical Center, Chongqing, China
Yu Ma, Chongqing Emergency Medical Center, Chongqing, China
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.