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Predicting post-coronary bypass surgery atrial arrhythmias from the preoperative electrocardiogram
1Feinberg Cardiovascular Research Institute and the Departments of Medicine and Preventive Medicine, Division of Cardiology, Northwestern University Medical School, Chicago, IL, USA. r-passman@northwestern.edu
Insights
Post-coronary artery bypass grafting (CABG) atrial fibrillation (AF) risk can be predicted using patient age and preoperative electrocardiogram (ECG) findings. This helps target prophylactic therapy to high-risk individuals.
Area of Science:
- Cardiology
- Cardiac Surgery
- Electrophysiology
Background:
- Post-coronary artery bypass grafting (CABG) atrial fibrillation (AF) is a frequent complication.
- AF increases morbidity and healthcare costs following CABG surgery.
- Targeted prophylactic therapies are needed for high-risk patients.
Purpose of the Study:
- To develop a predictive rule for post-CABG AF.
- To utilize patient age and preoperative electrocardiogram (ECG) data for prediction.
Main Methods:
- Retrospective review of 152 isolated CABG patient charts.
- Analysis of preoperative ECGs using commercial software.
- Logistic regression and receiver-operating characteristic curve analysis.
Main Results:
- 42.1% of patients developed post-CABG AF.
- High-risk predictors identified: age >65 years, PR interval ≥180 ms (OR 2.12), and P-wave duration in V1 ≥110 ms (OR 2.30).
Conclusions:
- Preoperative ECG and patient age can predict post-CABG AF.
- Intra-atrial conduction delays on ECG are significant predictors.
- This prediction tool can guide prophylactic treatment strategies.
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.
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