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欧洲心血管疾病风险评分和一级预防的障碍。

Barriers to cardiovascular disease risk scoring and primary prevention in Europe.

机构信息

Primary Care Clinical Sciences, University of Birmingham, Edgbaston, Birmingham, UK.

出版信息

QJM. 2010 Oct;103(10):727-39. doi: 10.1093/qjmed/hcq122. Epub 2010 Aug 4.

Abstract

The prevalence and burden of cardiovascular disease (CVD) is high, and it remains the leading cause of death worldwide. Unfortunately, many individuals who are at high risk for CVD are not recognized and/or treated. Therefore, programs are available to ensure individuals at risk for CVD are identified through appropriate risk classification and offered optimal preventative interventions. The use of algorithms to determine a global risk score may help to achieve these goals. Such global risk-scoring algorithms takes into account the synergistic effects between individual risk factors, placing increases in individual risk factors into context relative to the overall disease, allowing for a continuum of disease risk to be expressed, and identifying patients most likely to derive benefit from an intervention. The predictive value of risk scoring such as using the Framingham equation is reasonable, analogous to cervical screening, with area under the receiver operated characteristic curve a little over 70%. However, limitations do exist, and as they are identified adjustments can be made to the global risk-scoring algorithms. Limitations include patient-specific issues, such as variations in lifetime risk level, ethnicity or socio-economic strata, and algorithm-specific issues, such as discrepancies between different algorithms arising from varying risk factors evaluated. The use of currently developed algorithms is low in general practice, in part, because of the belief that the assessment may oversimplify the risk and/or lead to medication overuse. Additional hindrances to the use of risk scoring include government or local health policy, patient compliance issues and lack of time. A thorough, easy-to-use, and standardized tool for risk estimation would allow for improvements in the primary prevention of CVD.

摘要

心血管疾病(CVD)的患病率和负担很高,仍然是全球死亡的主要原因。不幸的是,许多患有 CVD 高风险的人没有得到识别和/或治疗。因此,有各种计划可确保通过适当的风险分类识别患有 CVD 高风险的个体,并为他们提供最佳的预防干预措施。使用算法确定全球风险评分可能有助于实现这些目标。这种全球风险评分算法考虑了个体危险因素之间的协同作用,将个体危险因素的增加置于与整体疾病相关的背景下,从而可以表达疾病风险的连续谱,并确定最有可能从干预中受益的患者。使用Framingham 方程等风险评分的预测价值是合理的,类似于宫颈筛查,其接受者操作特征曲线下面积略高于 70%。然而,确实存在局限性,并且随着局限性的发现,可以对全球风险评分算法进行调整。局限性包括患者特定的问题,例如终生风险水平、种族或社会经济阶层的变化,以及算法特定的问题,例如由于评估的风险因素不同,不同算法之间存在差异。一般实践中普遍使用当前开发的算法的比例较低,部分原因是认为评估可能过于简化风险,或者导致过度用药。风险评分使用的其他障碍包括政府或当地卫生政策、患者依从性问题和缺乏时间。一个全面、易于使用且标准化的风险估计工具将有助于改善 CVD 的一级预防。

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