Internal Validation of a Risk Score for Prediction of Postoperative Atrial Fibrillation after Cardiac Surgery

Abstract

Abstract Background: Postoperative atrial fibrillation (POAF) after cardiac surgery has great clinical and economic implications. Many attempts have been made to identify risk factors aiming at a better evaluation of prophylactic treatment strategies. Objective: To perform an internal validation of a risk score for POAF. Methods: A prospective cohort of 1,054 patients who underwent myocardial revascularization and/or valve surgery was included. The risk score model was developed in 448 patients, and its performance was tested in the remaining 606 patients. Variables with a significance level of 5% in the cohort were included and subjected to a multiple logistic regression model with backward selection. Performance statistics was performed using the c-statistic, the chi-square and the Hosmer-Lemeshow (HL) goodness-of-fit, Pearson's correlation coefficient. Results: Four variables were considered predictors of outcome: age (≥ 70 years), mitral valve disease, the non-use or discontinuation of beta-blockers and a positive water balance (> 1,500 mL). The ROC curve was 0.76 (95% confidence interval [CI]: 0.72-0.79). The risk model showed a good ability according to the performance statistics - HL test x(2) = 0.93; p = 0.983 and r = 0.99 (Pearson's coefficient). There was an increase in the frequency of POAF with the increase of the score: very low risk = 0.0%; low risk = 3.9%; intermediate risk = 10.9%; and high risk = 60.0%; p < 0.0001. Conclusion: The predictive variables of POAF allowed us to construct a simplified risk score. This scoring system showed good accuracy and can be used in routine clinical practice.