LAUSR

Abstract Funding Acknowledgements Type of funding sources: Private hospital(s). Main funding source(s): Kyung Hee University Background A study to predict the risk of AF by analyzing the P-wave of the electrocardiogram in detail has been attempted for a long time, and P-wave signal-averaged ECG is also known to be helpful. Recently, the P-wave was analyzed by dividing it into two parts, and when the latter part is extended, it suggests left atrium dilatation or delayed conduction, and it is suggested that this may be a slightly more sensitive parameter. Objective The purpose of this study was to find the best predictor of atrial fibrillation by comparing the characteristics of the P-wave in the subjects with AF and healthy controls using 12-lead ECG and signal-averaged ECG (SAECG). Methods We recruited 58 paroxysmal atrial fibrillation patients in AF group and 57 people in the control group. All subjects underwent 12-lead ECG, P-wave signal-averaged ECG, and transthoracic echocardiography. The total P-wave duration (PWD), the second part of the P-wave were measured with an electronic caliper in lead II. Results The second part of the P-wave was higher in the AF group, which was statistically significant (70.8 ± 20.6 vs. 60.5 ± 12.3ms, respectively, p<0.01). Filtered PWD and the integral of the P-wave were significantly higher in the AF group. The second part of the P-wave, filtered PWD, and the integral of P-wave were univariate and multivariate predictors of AF. The second part of the P-wave showed ROC (Receiver operating characteristic curves) area of 0.635, and the cut-off value was 61.5ms with 59.6% sensitivity and 59.6% of specificity. Of the SAECG parameters, the longer filtered PWD predicted a history of AF with an AUC (Area under the ROC curve) of 0.669. Conclusions We confirmed that second part of the P-wave which reflects the electrophysiological status of the left atrium is a valuable marker for predicting AF. Also, Filtered PWD and the integral of the P-wave among the SAECG parameters were useful predictors of AF. Table 1 & Table 2 Figure 1