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Electrocardiographic Activity before Onset of Postoperative Atrial Fibrillation in Cardiac Surgery Patients
Author(s) -
OVREIU MIRELA,
NAIR BALA G.,
XU MENG,
BAKRI MOHAMED H.,
LI LIANG,
WAZNI OUSSAMA,
FAHMY TAMER,
PETRE JOHN,
STARR NORMAN J.,
SESSLER DANIEL I.,
BASHOUR C. ALLEN
Publication year - 2008
Publication title -
pacing and clinical electrophysiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.686
H-Index - 101
eISSN - 1540-8159
pISSN - 0147-8389
DOI - 10.1111/j.1540-8159.2008.01198.x
Subject(s) - medicine , heart rate turbulence , atrial fibrillation , receiver operating characteristic , cardiology , logistic regression , intensive care unit , heart rate , heart rate variability , blood pressure
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.