Abstract DP049: Predictors for Detecting Paroxysmal Atrial Fibrillation by Implanted Loop Recorders

Background: Extended cardiac monitoring, particularly via implanted loop recorders (ILR), has been shown to increase the odds of detecting paroxysmal atrial fibrillation (PAF). There is, however, a need to identify which patients are more likely to benefit from ILR. Methods: We retrospectively analyzed our experience over the last 45 months using ILR to detect PAF in patients suspected of having cardiogenic brain embolism. Specifically, we used logistic regression to assess the predictive impact of the length of the monitoring interval (LMI) and the following cardiac indices: a) P-axis, b) Left atrial diameter (LAD), c) Left atrial volume (LAV), and d) Left atrial volume index (LAVI). Results: Our cohort includes 159 patients, 76 (47%) of them men, ages ranging from 45 to 89 years (Mean= 68.9). A total of 19 (12%) patients (Group A) had newly detected PAF during the monitoring period, while the remainder (Group B) did not. There were no statistically significant differences in baseline demographics, clinical characteristics, or cardiac indices between groups A and B. Nevertheless, all cardiac indices [z values of -1.33 (LAVI), 1.35 (P Axis), 1.58 (LAD) and 1.74 (LAV)] and LMI (z value = -1.58) showed the strongest impact in predicting the detection of PAF. Conclusions: Our study confirms the predictive impact of the LMI and specific cardiac indices on the likelihood of detecting PAF using ILR. Still, future work should concentrate on the development of a stronger predictive model that incorporates these variables in the most effective forecasting combination.