AUTHOR=Huang Taiyuan , Schurr Patrick , Muller-Edenborn Bjoern , Pilia Nicolas , Mayer Louisa , Eichenlaub Martin , Allgeier Juergen , Heidenreich Marie , Ahlgrim Christoph , Bohnen Marius , Lehrmann Heiko , Trenk Dietmar , Neumann Franz-Josef , Westermann Dirk , Arentz Thomas , Jadidi Amir 

TITLE=Analysis of the amplified p-wave enables identification of patients with atrial fibrillation during sinus rhythm

JOURNAL=Frontiers in Cardiovascular Medicine

VOLUME=Volume 10 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/cardiovascular-medicine/articles/10.3389/fcvm.2023.1095931

DOI=10.3389/fcvm.2023.1095931

ISSN=2297-055X

ABSTRACT=Aim: This study sought to develop and validate diagnostic models to identify individuals with atrial fibrillation (AF) using amplified sinus-p-wave analysis.
Methods: 1492 patients (491 healthy controls, 499 with paroxysmal AF and 502 with persistent AF) underwent digital 12-lead-ECG recording during sinus rhythm. The patient cohort was divided into training and validation set in a 3:2 ratio. P-wave indices (PWI) including duration of standard p-wave (standard PWD; scale at 10mm/mV, sweep speed at 25mm/sec) and amplified sinus-p-wave (APWD, scale at 60-120mm/mV, sweep speed at 100mm/sec) and advanced inter-atrial block (aIAB) along with other clinical parameters were used to develop diagnostic models using logistic regression. Each model was developed from the training set and further tested in both training and validation sets for its diagnostic performance in identifying individuals with AF. 
Results: Compared to standard PWD (Reference model), which achieved an AUC of 0.637 and 0.632, for training and validation set, respectively, APWD (Basic model) importantly improved the accuracy to identify individuals with AF (AUC=0.86 and 0.866). The PWI-based model combining APWD, aIAB and body surface area (BSA) further improved the diagnostic performance for AF (AUC=0.892 and 0.885). The integrated model, which further combined left atrial diameter (LAD) with parameters of the PWI-based model, achieved optimal diagnostic performance (AUC=0.916 and 0.902).
Conclusions: Analysis of amplified p-wave during sinus rhythm allows identification of individuals with atrial fibrillation.