Key result
The Joint British Societies' risk calculator (RiskJBS) provided the most accurate CV risk estimation, demonstrating the best correlation with CIMT (rho=0.45) and CCS (rho=0.46) (all p<0.001).
Why the study?
Which cardiovascular risk assessment algorithm best correlates with subclinical atherosclerosis measures (CIMT and CCS) in an Indian population?
Cross-Sectional (n=194)
No
Which cardiovascular risk assessment algorithm best correlates with subclinical atherosclerosis measures (CIMT and CCS) in an Indian population?
Effect estimate: Spearman rho 0.45 (CIMT) and 0.46 (CCS) for RiskJBS
p-value: p=< 0.001
In an Indian population, the Joint British Societies' risk calculator (JBS3) provided the most accurate estimation of CV risk and best correlated with subclinical atherosclerosis measures (CIMT and CCS).
RiskJBS may best estimate CV risk among Indian patients; leaves open need for prospective validation before wider use.
BACKGROUND: Relative accuracy of the various currently available cardiovascular (CV) risk assessment algorithms in Indian patients is not known. METHODS: This study included 194 consecutive patients (mean age 49.6 ± 10.3 years, 84.5% males) attending a CV disease prevention clinic at a tertiary center in north India. Four risk assessment models [Framingham Risk score (RiskFRS), American College of Cardiology/American Heart Association pooled cohort equations (RiskACC/AHA), the 3rd iteration of Joint British Societies' risk calculator (RiskJBS) and the World Health Organization/International Society of Hypertension risk prediction charts (RiskWHO)] were applied. The estimated risk scores were correlated with carotid intima-media thickness (CIMT) and coronary calcium score (CCS) using nonparametric statistics (Chi-square test, Kruskal-Wallis test and Spearman rank correlation). RESULTS: Overall, RiskACC/AHA and RiskWHO significantly underestimated CV risk as compared to RiskJBS and RiskFRS, with RiskJBS being the least likely to underestimate the risk (patients with coronary artery disease who were found to have ≥20% CV risk- 21.4% with RiskACC/AHA, 17.9% with RiskWHO, 41.4% with RiskFRS, and 58.6% with RiskJBS). Further, only RiskJBS and RiskFRS, but not RiskACC/AHA and RiskWHO, demonstrated consistent relationship with CIMT and CCS (Spearman rho 0.45 and 0.46 for RiskJBS and 0.39 and 0.36 for RiskFRS for CIMT and CCS respectively, all p values < 0.001). CONCLUSIONS: The present study shows that in Indian subjects RiskJBS appears to provide the most accurate estimation of CV risk. It least underestimates the risk and has the best correlation with CIMT and CCS. However, large-scale prospective studies are needed to confirm these findings.
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Bansal et al. (2015) conducted a cross-sectional in Cardiovascular risk (n=194). Cardiovascular risk assessment algorithms (RiskJBS, RiskFRS, RiskACC/AHA, RiskWHO) was evaluated on Correlation with carotid intima-media thickness (CIMT) and coronary calcium score (CCS) (Spearman rho 0.45 (CIMT) and 0.46 (CCS) for RiskJBS, p=< 0.001). The Joint British Societies' risk calculator (RiskJBS) provided the most accurate CV risk estimation, demonstrating the best correlation with CIMT (rho=0.45) and CCS (rho=0.46) (all p<0.001).
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