Predicting post-coronary bypass surgery atrial arrhythmias from the preoperative electrocardiogram

Rod S Passman*, John Beshai, Behzad Pavri, Stephen Kimmel

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

38 Scopus citations

Abstract

Background: Atrial fibrillation (AF) after coronary artery bypass grafting (CABG) is a common occurrence and adds to the morbidity and cost associated with the procedure. Various therapies have been demonstrated to reduce the risk of post-CABG AF, but their use should be targeted to high-risk patients. The purpose of this study was to develop a prediction rule for post-CABG AF on the basis of patient age and the preoperative electrocardiogram (ECG). Methods: The charts of 152 consecutive patients undergoing isolated CABG at one institution were reviewed and the preoperative ECG was analyzed with use of commercially available software. Logistic regression was performed and age-adjusted predictors of the primary end point, any post-CABG AF, were derived. The discriminatory values of the various models were compared by receiver-operating characteristic curves. Results: Sixty-four patients (42.1%) had AF. Multivariable predictors were dichotomized on the basis of variable distribution, and a high-risk patient population was identified by age >65 years, PR interval ≥180 milliseconds (age-adjusted odds ratio [OR] 2.12, P = .05), and a P-wave duration in lead V1 ≥110 milliseconds (age-adjusted OR 2.30, P =.02). Conclusions: This study demonstrates that post-CABG AF can be predicted preoperatively from patient age and evidence of intra-atrial conduction delay on ECG. Such information can be used to guide prophylactic therapy.

Original languageEnglish (US)
Pages (from-to)806-810
Number of pages5
JournalAmerican Heart Journal
Volume142
Issue number5
DOIs
StatePublished - Jan 1 2001

ASJC Scopus subject areas

  • Cardiology and Cardiovascular Medicine

Fingerprint Dive into the research topics of 'Predicting post-coronary bypass surgery atrial arrhythmias from the preoperative electrocardiogram'. Together they form a unique fingerprint.

Cite this