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.

Background and Aims: Patients with heart failure with reduced ejection fraction (HFrEF) are among the most challenging patients undergoing coronary artery bypass grafting surgery (CABG). Several surgical risk scores are commonly used to predict the risk in patients undergoing CABG. However, these risk scores do not specifically target HFrEF patients. We aim to develop and validate a new nomogram score to predict the risk of in-hospital mortality among HFrEF patients after CABG.Methods: The study retrospectively enrolled 489 patients who had HFrEF and underwent CABG. The outcome was postoperative in-hospital death. About 70% (n = 342) of the patients were randomly constituted a training cohort and the rest (n = 147) made a validation cohort. A multivariable logistic regression model was derived from the training cohort and presented as a nomogram to predict postoperative mortality in patients with HFrEF. The model performance was assessed in terms of discrimination and calibration. Besides, we compared the model with EuroSCORE-2 in terms of discrimination and calibration.Results: Postoperative death occurred in 26 (7.6%) out of 342 patients in the training cohort, and in 10 (6.8%) out of 147 patients in the validation cohort. Eight preoperative factors were associated with postoperative death, including age, critical state, recent myocardial infarction, stroke, left ventricular ejection fraction (LVEF) ≤35%, LV dilatation, increased serum creatinine, and combined surgery. The nomogram achieved good discrimination with C-indexes of 0.889 (95%CI, 0.839–0.938) and 0.899 (95%CI, 0.835–0.963) in predicting the risk of mortality after CABG in the training and validation cohorts, respectively, and showed well-fitted calibration curves in the patients whose predicted mortality probabilities were below 40%. Compared with EuroSCORE-2, the nomogram had significantly higher C-indexes in the training cohort (0.889 vs. 0.762, p = 0.005) as well as the validation cohort (0.899 vs. 0.816, p = 0.039). Besides, the nomogram had better calibration and reclassification than EuroSCORE-2 both in the training and validation cohort. The EuroSCORE-2 underestimated postoperative mortality risk, especially in high-risk patients.Conclusions: The nomogram provides an optimal preoperative estimation of mortality risk after CABG in patients with HFrEF and has the potential to facilitate identifying HFrEF patients at high risk of in-hospital mortality.

Background:The relationship between abnormal left ventricular (LV) structure and adverse outcomes has been confirmed in diverse patient groups in previous studies. However, it remains uncertain whether LV structure has predictive implications in heart failure with reduced ejection fraction (HFrEF) patients with coronary artery bypass grafting (CABG). Methods: This study retrospectively enrolled patients who had HFrEF and underwent CABG between January 2013 and July 2019. According to LV hypertrophy (LVH) and LV enlargement (LVE) assessed by echocardiography, patients were classified into four LV structure types: (-)LVH/(-)LVE, (+)LVH/(-)LVE, (-)LVH/(+)LVE, and (+)LVH/(+)LVE. Results: A total of 435 consecutive patients (mean age: 59.4 ± 9.6 years; 14.9% female) were enrolled in the present study. Examined independently, either LVH (p < 0.001) or LVE (p < 0.001) was independently associated with postoperative mortality in multivariate analysis. When LVH and LVE were analyzed in combination, the risk of mortality after CABG was lowest in (-)LVH/(-)LVE and increased with (+)LVH/(-)LVE (odds ratio [OR]: 7.525; 95% confidence interval [CI]: 1.827-30.679, p = 0.004), (-)LVH/(+)LVE (OR: 7.253; 95% CI: 1.950-27.185, p = 0.003), and (+)LVH/(+)LVE (OR: 9.547; 95% CI: 2.726-34.805, p < 0.001), independent of other risk factors. Adding LV structural types to the baseline model gained an incremental effect on the predictive value for postoperative mortality (AUC: baseline model, 0.838 vs baseline model + LV structural types, 0.901, p for comparison = 0.010; category-free net reclassification improvement (NRI): 0.764, p < 0.001; integrated discrimination improvement (IDI): 0.061, p = 0.007). Conclusion: LVH and LVE were associated with an increased risk of postoperative mortality after CABG in patients with HFrEF. Categorizing LV structural patterns with LVH and LVE contributes to risk stratification and provides incremental predictive ability. Routine echocardiographic assessment of LVH and LVE is needed in clinical practice.