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Application of cardiovascular disease risk prediction models and the relevance of novel biomarkers to risk stratification in Asian Indians

机译:心血管疾病风险预测模型的应用以及新型生物标志物与亚洲印第安人风险分层的相关性

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The increasing pressure on health resources has led to the emergence of risk assessment as an essential tool in the management of cardiovascular disease (CVD). Concern exists regarding the validity of their generalization to all populations. Existing risk scoring models do not incorporate emerging ‘novel’ risk factors. In this context, the aim of the study was to examine the relevance of British, European, and Framingham predictive CVD risk scores to the asymptomatic high risk Indian population. Blood samples drawn from the participants were analyzed for various ‘traditional’ and ‘novel’ biomarkers, and their CVD risk factor profiling was also done. The Framingham model defined only 5% of the study cohort to be at high risk, which appears to be an underestimation of CVD risk in this genetically predisposed population. These subjects at high risk had significantly elevated levels of lipid, pro-inflammatory, pro-thrombotic, and serological markers. It is more relevant to develop risk predictive scores for application to the Indian population. This study substantiates the argument that alternative approaches to risk stratification are required in order to make them more adaptable and applicable to different populations with varying risk factor and disease patterns.
机译:对健康资源的压力越来越大,导致风险评估已成为心血管疾病(CVD)管理中必不可少的工具。人们担心将其推广到所有人群的有效性。现有的风险评分模型并未纳入新兴的“新颖”风险因素。在这种情况下,该研究的目的是检验英国,欧洲和弗雷明汉的CVD预测性危险评分与无症状高危印度人群的相关性。从参与者抽取的血液样本中分析了各种“传统”和“新”生物标志物,并对他们的CVD危险因素进行了分析。 Framingham模型仅将研究队列中的5%定义为高危人群,这似乎低估了这种遗传易感人群中CVD的风险。这些高危受试者的脂质,促炎,血栓形成和血清学标志物水平明显升高。制定适用于印度人口的风险预测分数更为重要。这项研究证实了这样的论点,即需要采取风险分层的替代方法,以使其更具适应性,并适用于具有不同风险因素和疾病模式的不同人群。

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