Postoperative atrial fibrillation prediction following isolated surgical aortic valve replacement

Özet

Objective: Postoperative atrial fibrillation (POAF) is the most common complication following cardiac surgery, with increased risk of stroke andhigh mortality. Our aim was to identify patients at risk and to design a model that could predict POAF.Methods: In this single center study, we evaluated 1191 patients requiring isolated surgical aortic valve replacement between January 2000 andJune 2014. The patients were followed during the early postoperative period until discharge.Results: AF occurred in 342 patients (28.71%). Six variables associated with high arrhythmic risk [advanced age, body mass index, tricuspidregurgitation, prolonged ventilation, longer intensive care unit stay, and dilated left atrium (LA; volume ≥35 ml/m2)] were selected to create amultivariate prediction model. This model predicted POAF in 64.7% of cases, with a moderate discriminative power (AUC=0.65; p=0.001; 95% CI,0.571-0.771). We also developed the CHAID (Chi-square automatic interaction detection) model showing multilevel interactions among risk factorsfor POAF. Age had the greatest discriminative power, with patients aged >68 years at a higher risk for POAF. In low-risk patients, the subgroupwith dilated LA (volume ≥40 ml) was more prone to develop POAF. For the intermediate-risk group, history of AF was the next deciding variable,whereas for the high-risk group, it was tricuspid regurgitation (at least moderate).Conclusion: The multivariate logistic model has an acceptable predictive value. CHAID-derived model is a new tool that could be easily appliedto identify patients requiring prophylactic regimens.