Jim K Wong1, Robert L Lobato2, Andre Pinesett3, Bryan G Maxwell4, Christina T Mora-Mangano5, Marco V Perez3. 1. Department of Anesthesia, Stanford University School of Medicine, Stanford, CA. Electronic address: wongjk2003@gmail.com. 2. Department of Anesthesia, Cedars Sinai Medical Center, Los Angeles, CA. 3. Department of Cardiology, Stanford University School of Medicine, Stanford, CA. 4. Department of Anesthesia, Johns Hopkins University, Baltimore, MD. 5. Department of Anesthesia, Stanford University School of Medicine, Stanford, CA.
Abstract
OBJECTIVE: To test the hypothesis that including preoperative electrocardiogram (ECG) characteristics with clinical variables significantly improves the new-onset postoperative atrial fibrillation prediction model. DESIGN: Retrospective analysis. SETTING: Single-center university hospital. PARTICIPANTS: Five 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. INTERVENTIONS: Retrospective review of medical records. MEASUREMENTS AND MAIN RESULTS: Baseline 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). CONCLUSION: Several p-wave characteristics are independently associated with postoperative atrial fibrillation. Addition of these parameters improves the postoperative atrial fibrillation prediction model.
OBJECTIVE: To test the hypothesis that including preoperative electrocardiogram (ECG) characteristics with clinical variables significantly improves the new-onset postoperative atrial fibrillation prediction model. DESIGN: Retrospective analysis. SETTING: Single-center university hospital. PARTICIPANTS: Five 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. INTERVENTIONS: Retrospective review of medical records. MEASUREMENTS AND MAIN RESULTS: Baseline 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). CONCLUSION: Several p-wave characteristics are independently associated with postoperative atrial fibrillation. Addition of these parameters improves the postoperative atrial fibrillation prediction model.
Authors: Ahmet Zengin; Mehmet Baran Karataş; Yiğit Çanga; Levent Pay; Semih Eren; Ali Nazmi Çalık; Özge Güzelburç Journal: Ir J Med Sci Date: 2022-01-16 Impact factor: 1.568