Risk factors analysis and prediction models of atrial fibrillation/flutter after esophagectomy

Background Postoperative atrial fibrillation/flutter (POAF) increases postoperative complications and hospitalization time. Identifying those at risk of atrial fibrillation/flutter after major thoracic surgery allows prophylactic therapy to be targeted toward those most likely to benefit. Objective A clinical prediction model for POAF in cancer patients undergoing esophagectomy was developed and validated to identify the incidence and clinical correlates of POAF. Methods 623 patients undergone radical esophagectomy for cancer were included. The POAF prediction models were constructed using a backward selection strategy by starting with factors with p ≤ 0.1 in univariable analyses. Influence factors with a multivariate P < 0.05 were defined as statistically significant. The discrimination of the models was determined by calculating the AUC of the ROC curve. Goodness-of-fit of the model was evaluated by Hosmer–Lemeshow test. Calibrating, nomogram and randomForest algorithm were also applied to develop the prediction model. Results The end point of the study, POAF, occurred in 25.5% of patients (159/623) at a median of 2 days. In univariable analyses, the differential factors associated with atrial fibrillation/flutter including age (median, 67 vs. 64 years; p < 0.0001), male (94% vs. 88%; p = 0.022), hypertension (42% vs. 31%; p = 0.019), FEV1/FVC (median, 74.89 vs. 77.06%; p = 0.010), premature atrial contraction (PAC, 42% vs. 15%; p < 0.0001), left atrial dilation (15% vs. 5%; p = 0.0002), preoperative neutrophilic granulocyte percentage (GRA, median, 65.8 vs. 63.7%; p = 0.013). The AUC of this model is 0.725. Postoperative viables were also included in another model, which prediction efficiency is better than the former. (AUC = 0.736) Conclusion We developed two predictive models identified preoperative and postoperative risk factors and targeted preventive therapy would be administered in selected patients.