Work

The impact of perivascular adipose tissue characteristics on incident cardiovascular events in non-dialysis chronic kidney disease patients

Year: 2025

Type: article

Abstract: Introduction Patients with chronic kidney disease (CKD) face a high risk of developing cardiovascular disease. However, the relationship between perivascular adipose tissue characteristics and incident cardiovascular outcomes in non-dialysis patients with CKD remains unclear. Methods This was prospective, observational, cohort study. A total of 220 CKD patients (stages G2–G5) without prior cardiovascular disease were enrolled. Attenuations and volumes of peri-coronary adipose tissue (PCAT), thoracic peri-aortic adipose tissue (TAT), and epicardial adipose tissue (EAT) were measured by ECG-gated non-enhanced computed tomography scans. Total coronary artery (CAC) and thoracic aorta calcification (TAC) were quantified with Agatston scores. Results Lower estimated glomerular filtration rate (eGFR) was associated with higher attenuation of PCAT, TAT, and EAT, but volumes differences across eGFR tertile were not significant. Multivariate analysis indicated that age and body mass index (BMI) were independently associated with PCAT, TAT, and EAT volumes. Smoking and serum phosphorus levels correlated with PCAT attenuation, while proteinuria, BMI, HDL cholesterol, and white blood cell counts were linked to TAT attenuation. EAT attenuations was associated with age, serum creatinine, proteinuria, BMI, smoking, and systolic blood pressure. During a median follow-up of 26.56 months, 23 patients developed cardiovascular events, with high EAT volume (≥129.14 cm3) or TAT volume (≥36.38 cm3) correlating with increased events rates. Cox regression demonstrated EAT volume as an independent predictor of incident cardiovascular outcomes. A multivariable model showed EAT volume enhanced the Framingham risk score's predictive value, achieving an area under the curve (AUC) of 0.76 (95% CI 0.66–0.87). Conclusion These findings suggest EAT volume significantly predicts incident cardiovascular events in non-dialysis CKD patients.

Source: Frontiers in Medicine

DOI: 10.3389/fmed.2025.1547007