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

BackgroundMajor 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...

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Main Authors: Lan Feng, Xuemei Tan, Xiaoxia Duan, Jiang Zheng, Xiaohui Du, Hong Fu, Yu Ma
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-06-01
Series:Frontiers in Cardiovascular Medicine
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Online Access:https://www.frontiersin.org/articles/10.3389/fcvm.2025.1590496/full
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author Lan Feng
Xuemei Tan
Xiaoxia Duan
Jiang Zheng
Xiaohui Du
Hong Fu
Yu Ma
author_facet Lan Feng
Xuemei Tan
Xiaoxia Duan
Jiang Zheng
Xiaohui Du
Hong Fu
Yu Ma
author_sort Lan Feng
collection DOAJ
description BackgroundMajor 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.MethodsThis 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.Results112 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).ConclusionsThe 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.
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spelling doaj-art-fb3f1624aaf145d0bf0ac7d3314b044b2025-08-20T03:44:57ZengFrontiers Media S.A.Frontiers in Cardiovascular Medicine2297-055X2025-06-011210.3389/fcvm.2025.15904961590496Development 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 surgeryLan Feng0Xuemei Tan1Xiaoxia Duan2Jiang Zheng3Xiaohui Du4Hong Fu5Yu Ma6Department of Anesthesiology, Chongqing Emergency Medical Center, Chongqing University Central Hospital, School of Medicine, Chongqing University, Chongqing, ChinaDepartment of Anesthesiology, Chongqing General Hospital, Chongqing University, Chongqing, ChinaDepartment of Anesthesiology, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, ChinaDepartment of Anesthesiology, Chongqing Emergency Medical Center, Chongqing University Central Hospital, School of Medicine, Chongqing University, Chongqing, ChinaDepartment of Anesthesiology, Chongqing Emergency Medical Center, Chongqing University Central Hospital, School of Medicine, Chongqing University, Chongqing, ChinaDepartment of Anesthesiology, Chongqing Emergency Medical Center, Chongqing University Central Hospital, School of Medicine, Chongqing University, Chongqing, ChinaDepartment of Intensive Care Unit, Chongqing Emergency Medical Center, Chongqing University Central Hospital, School of Medicine, Chongqing University, Chongqing, ChinaBackgroundMajor 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.MethodsThis 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.Results112 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).ConclusionsThe 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.https://www.frontiersin.org/articles/10.3389/fcvm.2025.1590496/fullmajor adverse cardiovascular eventscerebrovascular eventsnomogramprediction modelaged
spellingShingle Lan Feng
Xuemei Tan
Xiaoxia Duan
Jiang Zheng
Xiaohui Du
Hong Fu
Yu Ma
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
Frontiers in Cardiovascular Medicine
major adverse cardiovascular events
cerebrovascular events
nomogram
prediction model
aged
title 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
title_full 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
title_fullStr 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
title_full_unstemmed 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
title_short 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
title_sort 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
topic major adverse cardiovascular events
cerebrovascular events
nomogram
prediction model
aged
url https://www.frontiersin.org/articles/10.3389/fcvm.2025.1590496/full
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