Rethinking automated P-wave analysis: A perspective on methodological limitations and future directions

P-wave indices derived from the surface electrocardiogram are increasingly used as markers of atrial cardiomyopathy and predictors of atrial fibrillation and stroke. Their widespread adoption has been driven by automated ECG analysis, enabling large-scale studies and integration into clinical workflows. However, this expansion has occurred without sufficient scrutiny of the methodological assumptions underlying automated measurement and interpretation. In this review, the current approaches to P-wave analysis are reviewed with focus on the most common P-wave indices used in large-scale studies, the issues associated with the use of fully automatic ECG processing, inconsistent definitions, the use of fixed thresholds, and analytical treatment of inherently non-linear variables as continuous measures. These limitations hamper the validity and reproducibility of findings and may hinder their clinical translation, thus highlighting the need for a shift toward physiologically informed, integrative approaches that move beyond rigid thresholds and isolated indices.