The TAG P2 score predicts low voltage areas in patients with atrial fibrillation - a novel prediction model

Abstract Background Atrial fibrillation (AF) is a common cardiac arrhythmia associated with morbidity and mortality. One of the mainstays of AF treatment is the interventional isolation of the pulmonary veins. However, the presence of low voltage areas (LVAs) in the left atrium is associated with a worse outcome after catheter ablation. Therefore, identifying LVAs prior to intervention is important for tailoring individualized treatment approaches. Although several prediction models for LVAs exist, none of them incorporate electrocardiographical parameters. Therefore, this study aimed to develop and evaluate the predictive value of a novel LVAs prediction score that incorporates a novel ECG parameter, prospectively validate the score, and compare it with existing prediction scores. Methods The study enrolled 264 patients with AF undergoing catheter ablation. LVAs were determined using high-density maps, which were defined as areas of low voltage amplitude (<0.5 mV). Before intervention, all patients underwent cardiovascular magnetic resonance imaging to measure left atrial dimensions. A novel LVAs prediction score (TAG P²) was established, which included a parameter of cumulative atrial electrical forces in relation to left atrial area (PWAi<0.478 msec * mV * m²/cm² – 2pts), along with type of AF (persistent – 1pt.), age (>70 years - apt.), and gender (female – 1pt.). The score was prospectively validated in a cohort of 126 patients. Results The TAG P² score was effective in predicting LVAs in the study population (AUC: 0.918; 95%CI [0.884 to 0.951]; p<0.001) and the results were confirmed in the validation cohort (AUC: 0.884; 95%CI [0.826 to 0.943]; p<0.001). The TAG P² score outperformed existing prediction scores, such as the DR-FLASH (AUC: 0.788; 95%CI [0.685 to 0.891]) and APPLE scores (AUC: 0.764; 95%CI [0.671 to 0.856]). Conclusion The TAG P² score, which incorporates a novel ECG parameter (PWAi) effectively predicts LVAs in patients undergoing catheter ablation for AF.