Abstract
The aim of this study was to create a simple risk index to predict new-onset atrial fibrillation (AF) after coronary artery bypass grafting in patients with histories of AF. AF after coronary artery bypass grafting (referred to here as AF) is associated with increased morbidity and mortality. Identifying patients at high risk for developing AF may help identify a group of patients who might benefit from strategies to prevent postoperative AF. A cohort of 18,517 patients enrolled from January 1, 1996, to December 31, 2009, was used to derive a risk index for AF prediction. A multivariate logistic regression model determined the independent predictive impact of clinical and demographic characteristics on the occurrence of AF. A subset of these variables was used to construct a risk index to predict AF. This risk index was validated in a sequential cohort of 1,378 consecutive patients who underwent coronary artery bypass grafting from January 1, 2010, to June 30, 2011. AF occurred in 3,486 patients in the calibration cohort (18.83%) and in 269 patients in the validation cohort (19.52%). After considering patients' demographics, co-morbid conditions, and severity of illness, advanced age appeared as the most powerful predictor of AF (odds ratio 1.059/year, 95% confidence interval 1.055 to 1.063). Age, height, weight, and the presence of peripheral vascular disease contributed most to the prediction model. An AF risk index including these variables had adequate discriminatory power, with a concordance index of 0.68. In conclusion, using a large cohort of patients, a simple risk index relying only on preoperative clinical variables was developed, which will help predict AF. This risk index can be used clinically to identify patients at high risk for the development of AF.
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