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印度人群中不同心血管风险评分与亚临床动脉粥样硬化指标之间的关系。

Relationship between different cardiovascular risk scores and measures of subclinical atherosclerosis in an Indian population.

作者信息

Bansal Manish, Kasliwal Ravi R, Trehan Naresh

机构信息

Senior Consultant, Cardiology, Medanta - The Medicity, Gurgaon, India.

Chairman, Clinical and Preventive Cardiology, Medanta - The Medicity, Gurgaon, India.

出版信息

Indian Heart J. 2015 Jul-Aug;67(4):332-40. doi: 10.1016/j.ihj.2015.04.017. Epub 2015 May 15.

Abstract

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.

摘要

背景

目前各种可用的心血管(CV)风险评估算法在印度患者中的相对准确性尚不清楚。

方法

本研究纳入了194例连续就诊于印度北部一家三级中心心血管疾病预防门诊的患者(平均年龄49.6±10.3岁,84.5%为男性)。应用了四种风险评估模型[弗雷明汉风险评分(RiskFRS)、美国心脏病学会/美国心脏协会合并队列方程(RiskACC/AHA)、英国联合学会风险计算器第3版(RiskJBS)和世界卫生组织/国际高血压学会风险预测图表(RiskWHO)]。使用非参数统计(卡方检验、Kruskal-Wallis检验和Spearman等级相关性)将估计的风险评分与颈动脉内膜中层厚度(CIMT)和冠状动脉钙化评分(CCS)进行关联。

结果

总体而言,与RiskJBS和RiskFRS相比,RiskACC/AHA和RiskWHO显著低估了心血管风险,其中RiskJBS最不可能低估风险(患有冠状动脉疾病且心血管风险≥20%的患者——RiskACC/AHA为21.4%,RiskWHO为17.9%,RiskFRS为41.4%,RiskJBS为58.6%)。此外,只有RiskJBS和RiskFRS,而不是RiskACC/AHA和RiskWHO,与CIMT和CCS表现出一致的关系(RiskJBS的CIMT和CCS的Spearman相关系数分别为0.45和0.46,RiskFRS分别为0.39和0.36,所有p值<0.001)。

结论

本研究表明,在印度受试者中,RiskJBS似乎能提供最准确的心血管风险估计。它最不容易低估风险,并且与CIMT和CCS的相关性最好。然而,需要大规模的前瞻性研究来证实这些发现。

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