Preoperative Electrocardiogram Score for Predicting New-Onset Postoperative Atrial Fibrillation in Patients Undergoing Cardiac Surgery

• Published in: Journal of cardiothoracic and vascular anesthesia Vol. 31; no. 1; pp. 69 - 76
• Main Authors: Gu, Jiwei, MD, Andreasen, Jan J., MD, PhD, Melgaard, Jacob, MSc, PhD, Lundbye-Christensen, Søren, PhD, Hansen, John, MSc, PhD, Schmidt, Erik B., MD, FESC, PhD, Thorsteinsson, Kristinn, MD, Graff, Claus, MSc, PhD
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.02.2017
• Subjects: Age Factors; Aged; Anesthesia & Perioperative Care; Atrial Fibrillation - diagnosis; Atrial Fibrillation - etiology; cardiac surgery; Cardiac Surgical Procedures - adverse effects; Coronary Artery Bypass - adverse effects; Critical Care; electrocardiogram characteristics; Electrocardiography - methods; Female; Heart Valves - surgery; Humans; Male; Middle Aged; new-onset postoperative atrial fibrillation; Predictive Value of Tests; Preoperative Care - methods; Prognosis; Registries; Retrospective Studies; Risk Factors; ROC Curve; new-onset postoperative atrial fibrillation; cardiac surgery; electrocardiogram characteristics
• ISSN: 1053-0770; 1532-8422
• DOI: 10.1053/j.jvca.2016.05.036

Objective To investigate if electrocardiogram (ECG) markers from routine preoperative ECGs can be used in combination with clinical data to predict new-onset postoperative atrial fibrillation (POAF) following cardiac surgery. Design Retrospective observational case-control study. Setting Single-center university hospital. Participants One hundred consecutive adult patients (50 POAF, 50 without POAF) who underwent coronary artery bypass grafting, valve surgery, or combinations. Interventions Retrospective review of medical records and registration of POAF. Measurements and Main Results Clinical data and demographics were retrieved from the Western Denmark Heart Registry and patient records. Paper tracings of preoperative ECGs were collected from patient records, and ECG measurements were read by two independent readers blinded to outcome. A subset of four clinical variables (age, gender, body mass index, and type of surgery) were selected to form a multivariate clinical prediction model for POAF and five ECG variables (QRS duration, PR interval, P-wave duration, left atrial enlargement, and left ventricular hypertrophy) were used in a multivariate ECG model. Adding ECG variables to the clinical prediction model significantly improved the area under the receiver operating characteristic curve from 0.54 to 0.67 (with cross-validation). The best predictive model for POAF was a combined clinical and ECG model with the following four variables: age, PR-interval, QRS duration, and left atrial enlargement. Conclusion ECG markers obtained from a routine preoperative ECG may be helpful in predicting new-onset POAF in patients undergoing cardiac surgery.