A prediction model for new-onset atrial fibrillation following coronary artery bypass graft surgery: A multicenter retrospective study

Abstract

Objective: Developing and assessing a risk prediction model of postoperative atrial fibrillation (POAF) after coronary artery bypass grafting (CABG), and aims to provide a reference for the prediction and prevention. Design: A retrospective case-control study. Setting: Three major urban teaching and university hospitals and tertiary referral centers. Participants: consecutive patients undergoing CABG. Interventions: The study was retrospective and no interventions were administered to patients. Measurements and main results: In the study, the overall new-onset POAF prevalence was approximately 28%. A prediction model for POAF with nine significant indicators was developed, and identified new predictors of POAF: left ventricular end diastolic diameter (LVEDD), intraoperative defibrillation, and intraoperative temporary pacing lead implantation. The model had good discrimination in both the derivation and validation cohorts, with the area under the receiver operating characteristic curves (AUCs) of 0.621 (95% CI = 0.602–0.640) and 0.616 (95% CI = 0.579–0.651), respectively, and showed good calibration. Compared with CHA2DS2-VASc, HATCH score, and the prediction model of POAF after CABG developed based on a small sample of clinical data from a single center in China, the model in this study had better discrimination. Conclusion: We have developed and validated a new prediction model of POAF after CABG using multicenter data that can be used in the clinic for early identification of high-risk patients of POAF, and to help effectively prevent POAF in postoperative patients.

Keywords

• Coronary artery bypass grafting
• Atrial fibrillation
• Prediction