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Background <p>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.</p> Methods <p>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, <i>n</i> = 319) and validation set (2022, <i>n</i> = 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).</p> Results <p>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).</p> Conclusions <p>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.</p>

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

  • 期刊论文

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  • 发表日期：

    2025年4月24日

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  • Yihan Zheng,
  • Min Zhou,
  • Yiting Lin,
  • Guican Zhang

摘要

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.