Abstract
OBJECTIVE: To select variables associated with new-onset postoperative atrial fibrillation (POAF) following isolated coronary artery bypass grafting (CABG) and develop a nomogram for risk prediction in a Chinese population. METHODS: The study retrospectively enrolled 4854 consecutive patients undergoing isolated CABG from February 2018 to September 2019, they were divided into derivation cohort and validation cohort with a 3:1 ratio according to the order of operation date. In the derivation cohort, significant variables were selected by use of the multivariate logistic backward stepwise regression analysis and a nomogram model was built on the strength of the results. The model performance was assessed in terms of discrimination and calibration. Besides, we compared the discriminative ability for POAF of the nomogram with established prediction models (CHA2DS2-VASc and HATCH scores) in the two cohorts. RESULTS: POAF occurred in 1025 (28.2%) out of 3641 patients in the derivation cohort, and in 337 (27.8%) out of 1213 patients in the validation cohort. A nomogram, composed of eight prognostic variables, namely age, sex, heart rate, hypertension, left ventricular ejection fraction (LVEF) <50%, left atrial diameter (LAD) > 40mm, estimated glomerular filtration rate (eGFR) level, and on-pump surgery, was constructed from the derivation cohort. The nomogram had substantial discriminative ability in derivation and validation cohorts with the area under the receiver operating characteristic curves (AUCs) of 0.661 (95% confidence interval, 0.642-0.681) and 0.665 (95% confidence interval, 0.631-0.699), respectively, and showed well-fitted calibration curves. Compared with CHA2DS2-VASc, HATCH and POAF scores, respectively, the nomogram had superior discrimination performance. CONCLUSION: We constructed a novel nomogram with improved accuracy for predicting the risk of POAF following isolated CABG, which might help clinicians predict individual probability of POAF and achieve effective prophylaxis.