Association Between Kidney Function and Morphology–Voltage–P Wave Duration (MVP) Score: A Cross-Sectional Electrocardiographic Study - Doğan, Ömer; Ebeoğlu, Abdullah Ömer; Ebeoğlu, Şevval İlke and Acar, Ümit and Barman, Hasan Ali (The European Research Journal, 2026)
Objectives: Chronic kidney disease (CKD) is associated with a high burden of atrial arrhythmias, primarily atrial fibrillation (AF), due to structural and electrical remodelling of the atria. The Morphology–Voltage–P wave duration (MVP) score, a composite electrocardiographic parameter derived from surface electrocardiography (ECG), has been proposed as a simple, non-invasive marker of atrial electrical dysfunction. However, its relationship with renal function has not been previously explored. Methods: This single-centre, retrospective, cross-sectional study included 90 adults with varying levels of estimated glomerular filtration rate (eGFR). MVP scores were calculated from standard 12-lead ECGs, and echocardiographic, demographic, and laboratory variables were recorded. Patients were grouped by eGFR (>60, 30–59, and <30 mL/min/1.73 m²). Correlation and multiple linear regression analyses were performed to identify independent predictors of MVP score. Results: MVP score increased across worsening eGFR categories (1.33±0.61, 2.63±1.03, and 4.64±1.26, respectively; P<0.001). A strong inverse correlation was observed between eGFR and MVP score (r = –0.774, P<0.001). In multivariable analysis, eGFR (β = –0.519, P<0.001), left atrial diameter (β=0.396, P<0.001), and male sex (β=0.133, P=0.029) were independent determinants of higher MVP values, explaining 63% of MVP variance. Conclusions: Reduced renal function is independently associated with higher MVP scores, reflecting atrial electrical abnormalities in patients with CKD. The MVP score may serve as a low-cost, easily applicable ECG marker for early detection of subclinical atrial dysfunction and arrhythmia risk in patients with renal impairment. Prospective, multicentre studies integrating MVP with advanced imaging and artificial intelligence–based ECG analysis are warranted to validate its clinical utility.