Predicting the risk of atrial fibrillation after coronary artery bypass surgery

Abstract

Atrial fibrillation (AF) is the most common arrhythmia, with an incidence of 17-33%, after coronary artery bypass grafting (CABG) and it increases the cost of operative treatment. beta-Blocker therapy reduces markedly the incidence of postoperative AF. The more effective preventive methods, e.g. amiodarone therapy or atrial pacing, are not cost-effective for all the patients. Thus, identification of patients at high risk of AF after CABG would be helpful. This review summarizes the predictors of postoperative AF and the current methods for risk stratification. In summary, identification of the patients at high risk of postoperative AF remains a challenge. The clinical usefulness of most of the conventional factors, e.g. age or history of AF, is low. Even attempts to build logistic regression models based on the pre- and intraoperative variables have failed to provide powerful predictors for postoperative AF after CABG. From the new predictors, the P-wave duration in signal-averaged ECG looks promising. Sensitivity and negative predictive value are high, positive predictive value remains low, which limits its usefulness. Contrary, even detailed analysis of standard 12-lead ECG or measure of heart rate variability has failed to provide useful information for risk stratification. A new method for risk stratification has been developed in our centre. The diagnostic accuracy of high-rate atrial pacing seems to be sufficient to identify a group of patients to whom prophylactic treatment could be proactively targeted. Further experience is, however, warranted to verify significance of this method in everyday clinical practice.