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476 POST-OPERATIVE ATRIAL ELECTROGRAM ANALYSIS TO PREDICT ATRIAL FIBRILLATION AFTER CARDIAC SURGERY P Pagé, A Vinet, Y Yin, A Armour, M Pagé, R Cardinal Several clinical and electrocardiographic parameters have been evaluated to predict the risk of post-operative atrial fibrillation (AF) but no online predictor of AF exists to date.
Montreal, Quebec
METHODS AND ANALYSES: In 30 patients (pts) undergoing isolated coronary artery bypass surgery, the characteristics of atrial unipolar electrograms were assessed using continuous recordings during 4 post-operative days (starting 24 hours after surgery). Electrogram integrals, dV/dt of activation complexes, AA intervals, inter-atrial and AV conduction times were extracted from atrial signals recorded from 3 epicardial temporary wire electrodes sutured on the right atrial free wall (1) and the posterior left atrium (2). AF occurred at 2.8 ± 1.2 days postoperatively in 15 pts (Group I, mean age 67 yrs). Measurements in Group I pts data sets were made on a beat-to-beat basis over 2-hour intervals preceding AF episodes and compared to randomly selected 2-hour intervals in 15 pts without postoperative AF (Group II, mean age 63 yrs). The parameters were grouped in pairs to assess their correlation throughout the study intervals, thus forming a set of 27 variables. The temporal stability of each correlation variable (expressed as a probability) was tested using a non parametric method with reference to time series consisting of random permutations.
RESULTS: At least one study parameter was found to be significantly modified 20 to 60 min preceding the onset of AF in all Group I pts but no single parameter could be identified by multivariate analysis as a significant predictor of the upcoming AF episodes. In the correlation stability studies, cluster analysis of correlation variables showed significantly less stability of values in Group I than in Group II time series throughout the 2 hrs data set (100% discrimination power).
CONCLUSION: No specific atrial electrogram characteristic can be used alone as a reproducible predictor of postoperative AF whereas the correlation stability test of atrial electrophysiologic variables has the potential to discriminate atrial behavioral patterns prone to AF. It is expected that this method, when coupled with the real time assessment of atrial ectopic activity will form the basis for the development of a monitoring algorithm that will become an online predictor of AF episodes after cardiac surgery.
DNC
Canadian Institute of Health Research