From sleep apnea to arrhythmia: p-wave parameters as non-invasive predictors - Lu, Wenjing; He, Ke; Zhang, Jun; Deng, Ying; Lin, Shaopeng; Yang, Demei; Chen, Zhuojun; Li, Xinzhong; Huang, Xiaobo (Frontiers in Cardiovascular Medicine, 2025)
BackgroundNumerous studies have confirmed a significant association between obstructive sleep apnea hypopnea syndrome (OSAHS) and both the increased prevalence and incidence of atrial fibrillation (AF). This study advanced the endpoint event to complex atrial arrhythmias, a group that potentially develops into AF. It innovatively used non-invasive P-wave parameters (PWPs) as predictive indicators for the occurrence of complex atrial arrhythmias in OSAHS, thereby achieving early identification.MethodsA retrospective analysis was performed on the medical records of patients presenting with sleep disorders who were admitted to the Fifth Affiliated Hospital of Sun Yat-sen University between June 2019 and June 2022. Based on their apnea-hypopnea index (AHI), patients were categorized into control, mild, moderate, and severe OSAHS groups. Clinical characteristics, PWPs, occurrences of atrial arrhythmias, and echocardiographic findings were collected for analysis. Using the Kleiger grading method, atrial arrhythmias were classified into simple and complex groups. Analysis of variance (ANOVA) was employed to examine differences among the groups, while independent sample t-tests were used for pairwise comparisons. Logistic regression analysis was applied to identify independent risk factors contributing to complex atrial arrhythmias, and receiver operating characteristic (ROC) curves were generated to evaluate the predictive value of PWPs.ResultsPatients with severe OSAHS exhibited significantly prolonged P-wave duration (PWD) and elevated Macruz Index compared to those with mild or moderate OSAHS (p < 0.01), while the P terminal force in lead V1 (PtfV1) was notably higher in moderate and severe groups relative to the mild and control groups (p < 0.01). Logistic regression analysis identified PtfV1 (odds ratio [OR] = 1.61) and the Macruz Index (OR = 2.95) as independent predictors of complex atrial arrhythmias. Furthermore, ROC curve analysis demonstrated that both PtfV1 and the Macruz Index had moderate predictive value, with area under the curve (AUC) values of 0.701 and 0.681, respectively, for identifying complex atrial arrhythmias.ConclusionPWPs, especially the PtfV1 and Macruz index, provide a powerful non-invasive predictor of atrial arrhythmia risk in patients with OSAHS.