Clinical prediction rule for atrial fibrillation after coronary artery bypass grafting

David Amar, Weiji Shi, Charles W. Hogue, Hao Zhang, Rod S. Passman, Betsy Thomas, Peter B. Bach, Ralph Damiano, Howard T. Thaler

Research output: Contribution to journalArticlepeer-review

133 Scopus citations

Abstract

This study was designed to devise and validate a practical prediction rule for atrial fibrillation/atrial flutter (AF) after coronary artery bypass grafting (CABG) using easily available clinical and standard electrocardiographic (ECG) criteria. Reported prediction rules for postoperative AF have suffered from inconsistent results and controversy surrounding the added predictive value of a prolonged P-wave duration. In 1,851 consecutive patients undergoing CABG with cardiopulmonary bypass, preoperative clinical characteristics and standard 12-lead ECG data were examined. Patients were continuously monitored for the occurrence of sustained postoperative AF while hospitalized. Multiple logistic regression was used to determine significant predictors of AF and to develop a prediction rule that was evaluated through jackknifing. Atrial fibrillation occurred in 508 of 1,553 patients (33%). Multivariate analysis showed that greater age (odds ratio [OR] 1.1 per year [95% confidence intervals (CI) 1.0 to 1.1], p < 0.0001), prior history of AF (OR 3.7 [95% CI 2.3 to 6.0], p < 0.0001), P-wave duration >110 ms (OR 1.3 [95% CI 1.1 to 1.7], p = 0.02), and postoperative low cardiac output (OR 3.0 [95% CI 1.7 to 5.2], p = 0.0001) were independently associated with AF risk. Using the prediction rule we defined three risk categories for AF: <60 points, 61 of 446 (14%); 60 to 79 points, 330 of 908 (36%); and ≥80 points, 117 of 199 (59%). The area under the receiver-operator characteristic curve for the model was 0.69. These data show that post-CABG AF can be predicted with moderate accuracy using easily available patient characteristics and may prove useful in prognostic and risk stratification of patients after CABG. The presence of intraatrial conduction delay on ECG contributed least to the prediction model.

Original languageEnglish
Pages (from-to)1248-1253
Number of pages6
JournalJournal of the American College of Cardiology
Volume44
Issue number6
DOIs
StatePublished - Sep 15 2004

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