Electrocardiographic Findings of Atrial Abnormality as a Predictor of Major Adverse Cardiovascular Events in Non-Dialysis Chronic Kidney Disease
Year: 2025
Type: article
Study design: Observational Study
Abstract: Background: Electrocardiographic (ECG) evidence of atrial abnormality indicated by the abnormal P wave indices have been shown to be associated with an increased mortality in various cohorts. However, data in chronic kidney disease (CKD) patients are scarce. Objective: To examine whether ECG findings of atrial abnormality can predict all-cause mortality in non-dialysis CKD patients. Materials and Methods: The authors analyzed data from CORE-CKD (Thailand) Registry that enrolled patients with pre-dialysis CKD. All baseline ECG were reviewed to determine the pertinent ECG parameters such as atrial flutter or atrial fibrillation, P wave terminal force in lead V1 (PTFV1), maximal P wave duration, complete interatrial block, P wave axis, and PR interval. Cox regression analysis was utilized to estimate the prognostic value of all relevant ECG parameters for long-term survival. Results: There were 253 patients who had interpretable baseline ECG and completed long-term outcome data. Median age was 65 years old and 60.8% were male. Median estimated glomerular filtration rate (eGFR) was 36.35 mL/minute/1.73 m², mostly were in CKD stage 3 or 4, and the major cause of CKD was diabetic nephropathy in 46.2%. During median follow-up of 58.4 months, 13 patients, or 5.1%, died. Cox regression analysis demonstrated that atrial arrhythmias or P wave indices such as PTFV1, maximal P wave duration, complete interatrial block, P wave axis, and PR interval, were not associated with increased risk of all-cause mortality. Conclusion: The authors demonstrated that the ECG parameters indicating atrial abnormalities were not associated with increased risk of mortality in pre-dialysis CKD patients.
Language: English
Subfield: Cardiology and Cardiovascular Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: bronze
Funder: Chiang Mai University
OpenAlex ID: W4408876608