Key result
A multivariable model using premature atrial activity, frequency-domain HRV, and heart rate turbulence correctly classified postoperative AF with >90% sensitivity and 70% specificity (C-statistic 0.904).
Why the study?
Can specific electrocardiographic characteristics predict the development of new-onset postoperative atrial fibrillation in cardiac surgery patients?
Observational (n=99)
No
Can specific electrocardiographic characteristics predict the development of new-onset postoperative atrial fibrillation in cardiac surgery patients?
Effect estimate: C-statistic 0.904
Absolute Event Rate: 43.4% vs 56.6%
p-value: p=<0.01
Specific ECG parameters, including premature atrial activity and heart rate variability, can accurately predict the development of postoperative atrial fibrillation in cardiac surgery patients.
May aid ECG-based prediction of postoperative AF; leaves open prospective validation before clinical use.
BACKGROUND: Electrocardiographic (ECG) characteristics were analyzed in postoperative cardiac surgery patients in an attempt to predict development of new-onset postoperative atrial fibrillation (AF). METHODS: Nineteen ECG characteristics were analyzed using computer-based algorithms. The parameters were retrospectively analyzed from ECG signals recorded in postoperative cardiac surgery patients while they were in the cardiovascular intensive care unit (CVICU) at our institution. ECG data from 99 patients (of whom 43 developed postoperative AF) were analyzed. A bootstrap variable selection procedure was applied to select the most important ECG parameters, and a multivariable logistic regression model was developed to classify patients who did and did not develop AF. RESULTS: Premature atrial activity (PAC) was greater in AF patients (P < 0.01). Certain heart rate variability (HRV) and turbulence parameters also differed in patients who did and did not develop AF. In contrast, P-wave morphology was similar in patients with and without AF. Receiver operating curve (ROC) analysis applied to the model produced a C-statistic of 0.904. The model thus correctly classified AF patients with more than a 90% sensitivity and a 70% specificity. CONCLUSION: Among the 19 ECG parameters analyzed, PAC activity, frequency-domain HRV, and heart rate turbulence parameters were the best discriminators for postoperative AF.
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Ovreiu et al. (2008) conducted an observational in Postoperative atrial fibrillation (n=99). Electrocardiographic characteristics (PAC, HRV, turbulence) vs. Patients who did not develop AF was evaluated on Development of new-onset postoperative atrial fibrillation (C-statistic 0.904, p=<0.01). A multivariable model using premature atrial activity, frequency-domain HRV, and heart rate turbulence correctly classified postoperative AF with >90% sensitivity and 70% specificity (C-statistic 0.904).
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