Development and internal validation of an OPCABG-specific prediction model for postoperative atrial fibrillation in Chinese patients: a retrospective cohort study

Postoperative atrial fibrillation (POAF) is a common complication after off-pump coronary artery bypass grafting (OPCABG), associated with increased morbidity and healthcare costs. Existing POAF prediction models, developed mainly for Western populations, may not account for genetic, lifestyle, and...

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Published inBMC cardiovascular disorders Vol. 25; no. 1; pp. 316 - 12
Main Authors Zheng, Yihan, Zhou, Min, Lin, Yiting, Zhang, Guican
Format Journal Article
LanguageEnglish
Published England BioMed Central Ltd 24.04.2025
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ISSN1471-2261
1471-2261
DOI10.1186/s12872-025-04780-y

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Abstract Postoperative atrial fibrillation (POAF) is a common complication after off-pump coronary artery bypass grafting (OPCABG), associated with increased morbidity and healthcare costs. Existing POAF prediction models, developed mainly for Western populations, may not account for genetic, lifestyle, and healthcare disparities in Chinese patients. This study aimed to develop and validate a Chinese-specific nomogram for POAF risk stratification in OPCABG patients. A retrospective cohort study was conducted at a single Chinese center, including 456 consecutive OPCABG patients (2018-2022). Patients were divided into a training set (2018-2021, n = 319) and validation set (2022, n = 137). Multivariable logistic regression with LASSO regularization identified predictors of POAF (occurrence within 7 postoperative days). Model performance was evaluated using C-index, calibration curves, decision curve analysis (DCA), and clinical impact curves (CIC). The final nomogram included five independent predictors: age (OR, 1.03), diabetes (OR, 1.85), hypertension (OR, 1.90), previous PCI (OR, 2.51) and last intraoperative blood potassium concentration (OR, 0.30). The model demonstrated excellent discrimination (C-index: 0.809 in training, 0.886 in validation) and good calibration. DCA and CIC showed superior clinical utility compared with existing scores (C2HEST, CHADS2, CHA2DS2-VASc). This OPCABG-specific nomogram outperforms conventional risk scores in predicting POAF in Chinese patients, enabling personalized prophylaxis and resource allocation. External validation in diverse populations is needed to confirm generalizability.
AbstractList Background Postoperative atrial fibrillation (POAF) is a common complication after off-pump coronary artery bypass grafting (OPCABG), associated with increased morbidity and healthcare costs. Existing POAF prediction models, developed mainly for Western populations, may not account for genetic, lifestyle, and healthcare disparities in Chinese patients. This study aimed to develop and validate a Chinese-specific nomogram for POAF risk stratification in OPCABG patients. Methods A retrospective cohort study was conducted at a single Chinese center, including 456 consecutive OPCABG patients (2018-2022). Patients were divided into a training set (2018-2021, n = 319) and validation set (2022, n = 137). Multivariable logistic regression with LASSO regularization identified predictors of POAF (occurrence within 7 postoperative days). Model performance was evaluated using C-index, calibration curves, decision curve analysis (DCA), and clinical impact curves (CIC). Results The final nomogram included five independent predictors: age (OR, 1.03), diabetes (OR, 1.85), hypertension (OR, 1.90), previous PCI (OR, 2.51) and last intraoperative blood potassium concentration (OR, 0.30). The model demonstrated excellent discrimination (C-index: 0.809 in training, 0.886 in validation) and good calibration. DCA and CIC showed superior clinical utility compared with existing scores (C2HEST, CHADS2, CHA2DS2-VASc). Conclusions This OPCABG-specific nomogram outperforms conventional risk scores in predicting POAF in Chinese patients, enabling personalized prophylaxis and resource allocation. External validation in diverse populations is needed to confirm generalizability. Keywords: Postoperative atrial fibrillation, Off-pump coronary artery bypass grafting, Nomogram, Clinical risk factors, Risk models
Postoperative atrial fibrillation (POAF) is a common complication after off-pump coronary artery bypass grafting (OPCABG), associated with increased morbidity and healthcare costs. Existing POAF prediction models, developed mainly for Western populations, may not account for genetic, lifestyle, and healthcare disparities in Chinese patients. This study aimed to develop and validate a Chinese-specific nomogram for POAF risk stratification in OPCABG patients.BACKGROUNDPostoperative atrial fibrillation (POAF) is a common complication after off-pump coronary artery bypass grafting (OPCABG), associated with increased morbidity and healthcare costs. Existing POAF prediction models, developed mainly for Western populations, may not account for genetic, lifestyle, and healthcare disparities in Chinese patients. This study aimed to develop and validate a Chinese-specific nomogram for POAF risk stratification in OPCABG patients.A retrospective cohort study was conducted at a single Chinese center, including 456 consecutive OPCABG patients (2018-2022). Patients were divided into a training set (2018-2021, n = 319) and validation set (2022, n = 137). Multivariable logistic regression with LASSO regularization identified predictors of POAF (occurrence within 7 postoperative days). Model performance was evaluated using C-index, calibration curves, decision curve analysis (DCA), and clinical impact curves (CIC).METHODSA retrospective cohort study was conducted at a single Chinese center, including 456 consecutive OPCABG patients (2018-2022). Patients were divided into a training set (2018-2021, n = 319) and validation set (2022, n = 137). Multivariable logistic regression with LASSO regularization identified predictors of POAF (occurrence within 7 postoperative days). Model performance was evaluated using C-index, calibration curves, decision curve analysis (DCA), and clinical impact curves (CIC).The final nomogram included five independent predictors: age (OR, 1.03), diabetes (OR, 1.85), hypertension (OR, 1.90), previous PCI (OR, 2.51) and last intraoperative blood potassium concentration (OR, 0.30). The model demonstrated excellent discrimination (C-index: 0.809 in training, 0.886 in validation) and good calibration. DCA and CIC showed superior clinical utility compared with existing scores (C2HEST, CHADS2, CHA2DS2-VASc).RESULTSThe final nomogram included five independent predictors: age (OR, 1.03), diabetes (OR, 1.85), hypertension (OR, 1.90), previous PCI (OR, 2.51) and last intraoperative blood potassium concentration (OR, 0.30). The model demonstrated excellent discrimination (C-index: 0.809 in training, 0.886 in validation) and good calibration. DCA and CIC showed superior clinical utility compared with existing scores (C2HEST, CHADS2, CHA2DS2-VASc).This OPCABG-specific nomogram outperforms conventional risk scores in predicting POAF in Chinese patients, enabling personalized prophylaxis and resource allocation. External validation in diverse populations is needed to confirm generalizability.CONCLUSIONSThis OPCABG-specific nomogram outperforms conventional risk scores in predicting POAF in Chinese patients, enabling personalized prophylaxis and resource allocation. External validation in diverse populations is needed to confirm generalizability.
Abstract Background Postoperative atrial fibrillation (POAF) is a common complication after off-pump coronary artery bypass grafting (OPCABG), associated with increased morbidity and healthcare costs. Existing POAF prediction models, developed mainly for Western populations, may not account for genetic, lifestyle, and healthcare disparities in Chinese patients. This study aimed to develop and validate a Chinese-specific nomogram for POAF risk stratification in OPCABG patients. Methods A retrospective cohort study was conducted at a single Chinese center, including 456 consecutive OPCABG patients (2018–2022). Patients were divided into a training set (2018–2021, n = 319) and validation set (2022, n = 137). Multivariable logistic regression with LASSO regularization identified predictors of POAF (occurrence within 7 postoperative days). Model performance was evaluated using C-index, calibration curves, decision curve analysis (DCA), and clinical impact curves (CIC). Results The final nomogram included five independent predictors: age (OR, 1.03), diabetes (OR, 1.85), hypertension (OR, 1.90), previous PCI (OR, 2.51) and last intraoperative blood potassium concentration (OR, 0.30). The model demonstrated excellent discrimination (C-index: 0.809 in training, 0.886 in validation) and good calibration. DCA and CIC showed superior clinical utility compared with existing scores (C2HEST, CHADS2, CHA2DS2-VASc). Conclusions This OPCABG-specific nomogram outperforms conventional risk scores in predicting POAF in Chinese patients, enabling personalized prophylaxis and resource allocation. External validation in diverse populations is needed to confirm generalizability.
BackgroundPostoperative atrial fibrillation (POAF) is a common complication after off-pump coronary artery bypass grafting (OPCABG), associated with increased morbidity and healthcare costs. Existing POAF prediction models, developed mainly for Western populations, may not account for genetic, lifestyle, and healthcare disparities in Chinese patients. This study aimed to develop and validate a Chinese-specific nomogram for POAF risk stratification in OPCABG patients.MethodsA retrospective cohort study was conducted at a single Chinese center, including 456 consecutive OPCABG patients (2018–2022). Patients were divided into a training set (2018–2021, n = 319) and validation set (2022, n = 137). Multivariable logistic regression with LASSO regularization identified predictors of POAF (occurrence within 7 postoperative days). Model performance was evaluated using C-index, calibration curves, decision curve analysis (DCA), and clinical impact curves (CIC).ResultsThe final nomogram included five independent predictors: age (OR, 1.03), diabetes (OR, 1.85), hypertension (OR, 1.90), previous PCI (OR, 2.51) and last intraoperative blood potassium concentration (OR, 0.30). The model demonstrated excellent discrimination (C-index: 0.809 in training, 0.886 in validation) and good calibration. DCA and CIC showed superior clinical utility compared with existing scores (C2HEST, CHADS2, CHA2DS2-VASc).ConclusionsThis OPCABG-specific nomogram outperforms conventional risk scores in predicting POAF in Chinese patients, enabling personalized prophylaxis and resource allocation. External validation in diverse populations is needed to confirm generalizability.
Postoperative atrial fibrillation (POAF) is a common complication after off-pump coronary artery bypass grafting (OPCABG), associated with increased morbidity and healthcare costs. Existing POAF prediction models, developed mainly for Western populations, may not account for genetic, lifestyle, and healthcare disparities in Chinese patients. This study aimed to develop and validate a Chinese-specific nomogram for POAF risk stratification in OPCABG patients. A retrospective cohort study was conducted at a single Chinese center, including 456 consecutive OPCABG patients (2018-2022). Patients were divided into a training set (2018-2021, n = 319) and validation set (2022, n = 137). Multivariable logistic regression with LASSO regularization identified predictors of POAF (occurrence within 7 postoperative days). Model performance was evaluated using C-index, calibration curves, decision curve analysis (DCA), and clinical impact curves (CIC). The final nomogram included five independent predictors: age (OR, 1.03), diabetes (OR, 1.85), hypertension (OR, 1.90), previous PCI (OR, 2.51) and last intraoperative blood potassium concentration (OR, 0.30). The model demonstrated excellent discrimination (C-index: 0.809 in training, 0.886 in validation) and good calibration. DCA and CIC showed superior clinical utility compared with existing scores (C2HEST, CHADS2, CHA2DS2-VASc). This OPCABG-specific nomogram outperforms conventional risk scores in predicting POAF in Chinese patients, enabling personalized prophylaxis and resource allocation. External validation in diverse populations is needed to confirm generalizability.
Postoperative atrial fibrillation (POAF) is a common complication after off-pump coronary artery bypass grafting (OPCABG), associated with increased morbidity and healthcare costs. Existing POAF prediction models, developed mainly for Western populations, may not account for genetic, lifestyle, and healthcare disparities in Chinese patients. This study aimed to develop and validate a Chinese-specific nomogram for POAF risk stratification in OPCABG patients. A retrospective cohort study was conducted at a single Chinese center, including 456 consecutive OPCABG patients (2018-2022). Patients were divided into a training set (2018-2021, n = 319) and validation set (2022, n = 137). Multivariable logistic regression with LASSO regularization identified predictors of POAF (occurrence within 7 postoperative days). Model performance was evaluated using C-index, calibration curves, decision curve analysis (DCA), and clinical impact curves (CIC). The final nomogram included five independent predictors: age (OR, 1.03), diabetes (OR, 1.85), hypertension (OR, 1.90), previous PCI (OR, 2.51) and last intraoperative blood potassium concentration (OR, 0.30). The model demonstrated excellent discrimination (C-index: 0.809 in training, 0.886 in validation) and good calibration. DCA and CIC showed superior clinical utility compared with existing scores (C2HEST, CHADS2, CHA2DS2-VASc). This OPCABG-specific nomogram outperforms conventional risk scores in predicting POAF in Chinese patients, enabling personalized prophylaxis and resource allocation. External validation in diverse populations is needed to confirm generalizability.
ArticleNumber 316
Audience Academic
Author Zheng, Yihan
Zhang, Guican
Zhou, Min
Lin, Yiting
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Keywords Clinical risk factors
Postoperative atrial fibrillation
Off-pump coronary artery bypass grafting
Risk models
Nomogram
Language English
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Snippet Postoperative atrial fibrillation (POAF) is a common complication after off-pump coronary artery bypass grafting (OPCABG), associated with increased morbidity...
Background Postoperative atrial fibrillation (POAF) is a common complication after off-pump coronary artery bypass grafting (OPCABG), associated with increased...
BackgroundPostoperative atrial fibrillation (POAF) is a common complication after off-pump coronary artery bypass grafting (OPCABG), associated with increased...
Abstract Background Postoperative atrial fibrillation (POAF) is a common complication after off-pump coronary artery bypass grafting (OPCABG), associated with...
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SourceType Open Website
Open Access Repository
Aggregation Database
Index Database
StartPage 316
SubjectTerms Age
Aged
Analysis
Atrial fibrillation
Atrial Fibrillation - diagnosis
Atrial Fibrillation - epidemiology
Atrial Fibrillation - etiology
Blood levels
Bypass
Cardiac arrhythmia
Cardiovascular disease
China - epidemiology
Clinical risk factors
Complications and side effects
Coronary artery
Coronary artery bypass
Coronary Artery Bypass, Off-Pump - adverse effects
Coronary vessels
Decision Support Techniques
Diabetes
Diabetes mellitus
Discrimination in medical care
Disease prevention
East Asian People
Female
Fibrillation
Health care
Health care disparities
Heart attacks
Heart surgery
Humans
Hypertension
Information systems
Male
Medical care, Cost of
Medical prognosis
Medical research
Medicine, Experimental
Middle Aged
Morbidity
Nomogram
Nomograms
Off-pump coronary artery bypass grafting
Patients
Postoperative atrial fibrillation
Potassium
Prediction models
Predictive Value of Tests
Prophylaxis
Reproducibility of Results
Resource allocation
Retrospective Studies
Risk Assessment
Risk Factors
Risk models
Time Factors
Treatment Outcome
Variables
Veins & arteries
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Title Development and internal validation of an OPCABG-specific prediction model for postoperative atrial fibrillation in Chinese patients: a retrospective cohort study
URI https://www.ncbi.nlm.nih.gov/pubmed/40275146
https://www.proquest.com/docview/3201517502
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https://pubmed.ncbi.nlm.nih.gov/PMC12020320
https://doaj.org/article/3a26e42447bc462289ee8a4e4d48ba08
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