Evaluation of the PREVENT risk assessment tool and visceral adiposity: Insights from the UK Biobank.

BACKGROUND: Visceral adipose tissue (VAT) is a metabolically active fat depot strongly associated with cardiometabolic diseases. Current cardiovascular risk models, including the PREVENT equation, do not incorporate direct measures of visceral fat. This study evaluates whether MRI-derived VAT enhances the discrimination and calibration of the PREVENT model for atherosclerotic cardiovascular disease (ASCVD), heart failure (HF), and total cardiovascular disease (CVD) in a large, population-based cohort. METHODS: We included 38,373 UK Biobank participants who underwent abdominal MRI and had no known CVD at baseline. VAT volume was quantified using standardized MRI protocols. We assessed whether adding VAT to the PREVENT model improved model performance for incident ASCVD, HF, and total CVD, using C-statistics and net reclassification improvement (NRI). RESULTS: The mean age was 54.86 years (SD 7.49), and 52 % of participants were female. The median VAT volume was 3.58 L (IQR:2.14-5.33). Using the overall median VAT value as the threshold, higher visceral adiposity (>3.58 L) was associated with significantly increased risk of ASCVD (HR: 1.32, 95 % CI: 1.15-1.51), heart failure (HR: 1.55, 95 % CI: 1.27-1.89), and total CVD (HR: 1.38, 95 % CI: 1.23-1.55) adjusting for age and sex. Adding VAT to the PREVENT model did not significantly improve discrimination for ASCVD (C-statistic 0.731 vs. 0.729, p = 0.85), nor for HF or total CVD. However, VAT significantly improved reclassification: NRI for ASCVD was 0.37 (95 % CI: 0.30-0.33), for HF was 0.48 (95 % CI: 0.35-0.61), and for total CVD was 0.37 (95 % CI: 0.28-0.46). The association between VAT and all outcomes remained robust after adjustment for age and sex. CONCLUSIONS: MRI-derived visceral adiposity is associated with increased risk of ASCVD, HF, and total CVD. While VAT did not improve overall discrimination of the PREVENT model, it significantly enhanced reclassification, particularly for HF risk. This suggests that VAT may improve individualized cardiovascular risk stratification and inform targeted preventive strategies.

Duke Scholars

Author Neha Pagidipati Medicine, Cardiology