Key result
Adding preoperative ECG variables to a clinical prediction model significantly improved the AUC for postoperative atrial fibrillation from 0.71 to 0.78 (p<0.01).
Why the study?
Does adding preoperative ECG characteristics to clinical variables improve the prediction of new-onset postoperative atrial fibrillation in patients undergoing cardiac surgery?
Observational (n=526)
No
Does adding preoperative ECG characteristics to clinical variables improve the prediction of new-onset postoperative atrial fibrillation in patients undergoing cardiac surgery?
Absolute Event Rate: 0.78% vs 0.71%
p-value: p=<0.01
Adding preoperative P-wave characteristics to standard clinical variables significantly improves the prediction of new-onset postoperative atrial fibrillation in patients undergoing cardiac surgery.
May refine postoperative AF risk stratification; leaves open need for prospective validation before clinical use.
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Wong et al. (2014) conducted an observational in Postoperative atrial fibrillation (n=526). Preoperative electrocardiogram (ECG) characteristics (premature atrial contraction, p-wave index, and p-frontal axis) vs. Clinical predictors alone was evaluated on Area under the receiver operating characteristic curve for predicting postoperative atrial fibrillation (p=<0.01). Adding preoperative ECG variables to a clinical prediction model significantly improved the AUC for postoperative atrial fibrillation from 0.71 to 0.78 (p<0.01).
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