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CONDITIONS REGARDING CORONARY SURGERY

Clinical prediction rule for atrial fibrillation after coronary artery bypass grafting

David Amar, MD^*,*, Weiji Shi, MS, Charles W. Hogue, Jr, MD, Hao Zhang, MD^*, Rod S. Passman, MD^||, Betsy Thomas, RN, Peter B. Bach, MD, Ralph Damiano, MD and Howard T. Thaler, PhD

^* Departments of Anesthesiology and Critical Care Medicine
Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center and Weill Medical College of Cornell University, New York, New York, USA
Anesthesiology
Cardiac Surgery, Washington University School of Medicine, St. Louis, Missouri, USA
^|| Division of Cardiac Electrophysiology, Northwestern University School of Medicine, Chicago, Illinois, USA

Manuscript received March 23, 2004; revised manuscript received May 4, 2004, accepted May 11, 2004.

^* Reprint requests and correspondence: Dr. David Amar, Professor of Anesthesiology, Memorial Sloan-Kettering Cancer Center, 1275 York Avenue, M-304, New York, New York 10021 (Email: amard{at}mskcc.org).

Presented in part at the 53rd Annual Scientific Session of the American College of Cardiology, March 2004, New Orleans, Louisiana.

OBJECTIVES: 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.

BACKGROUND: Reported prediction rules for postoperative AF have suffered from inconsistent results and controversy surrounding the added predictive value of a prolonged P-wave duration.

METHODS: 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.

RESULTS: 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.

CONCLUSIONS: 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.

Abbreviations and Acronyms   AF = atrial fibrillation/atrial flutter   CABG = coronary artery bypass grafting   CI = confidence interval   ECG = electrocardiographic/electrocardiogram   MI = myocardial infarction   OR = odds ratio   ROC = receiver operating characteristic

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