• Jim K Wong, Robert L Lobato, Andre Pinesett, Bryan G Maxwell, Christina T Mora-Mangano, and Marco V Perez.
• Department of Anesthesia, Stanford University School of Medicine, Stanford, CA. Electronic address: wongjk2003@gmail.com.
• J. Cardiothorac. Vasc. Anesth.. 2014 Dec 1;28(6):1497-504.

ObjectiveTo test the hypothesis that including preoperative electrocardiogram (ECG) characteristics with clinical variables significantly improves the new-onset postoperative atrial fibrillation prediction model.DesignRetrospective analysis.SettingSingle-center university hospital.ParticipantsFive hundred twenty-six patients, ≥ 18 years of age, who underwent coronary artery bypass grafting, aortic valve replacement, mitral valve replacement/repair, or a combination of valve surgery and coronary artery bypass grafting requiring cardiopulmonary bypass.InterventionsRetrospective review of medical records.Measurements And Main ResultsBaseline characteristics and cardiopulmonary bypass times were collected. Digitally-measured timing and voltages from preoperative electrocardiograms were extracted. Postoperative atrial fibrillation was defined as atrial fibrillation requiring therapeutic intervention. Two hundred eight (39.5%) patients developed postoperative atrial fibrillation. Clinical predictors were age, ejection fraction<55%, history of atrial fibrillation, history of cerebral vascular event, and valvular surgery. Three ECG parameters associated with postoperative atrial fibrillation were observed: Premature atrial contraction, p-wave index, and p-frontal axis. Adding electrocardiogram variables to the prediction model with only clinical predictors significantly improved the area under the receiver operating characteristic curve, from 0.71 to 0.78 (p<0.01). Overall net reclassification improvement was 0.059 (p = 0.09). Among those who developed postoperative atrial fibrillation, the net reclassification improvement was 0.063 (p = 0.03).ConclusionSeveral p-wave characteristics are independently associated with postoperative atrial fibrillation. Addition of these parameters improves the postoperative atrial fibrillation prediction model.Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

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