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Barriers to cardiovascular disease risk scoring and primary prevention in Europe

机译:欧洲心血管疾病风险评分和一级预防的障碍

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摘要

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.
机译:心血管疾病(CVD)的患病率和负担很高,并且仍然是全球范围内主要的死亡原因。不幸的是,许多患有CVD的高风险个体没有得到认可和/或治疗。因此,可以使用程序来确保通过适当的风险分类来识别有CVD风险的个体,并提供最佳的预防干预措施。使用算法确定总体风险评分可能有助于实现这些目标。这样的全局风险评分算法考虑了个体风险因素之间的协同效应,将个体风险因素的增加置于相对于整体疾病的背景下,允许连续表达疾病风险,并确定最有可能受益的患者来自干预。类似于使用子宫颈筛查,使用Framingham方程等风险评分的预测值是合理的,接受者操作特征曲线下方的面积略超过70%。但是,确实存在局限性,并且在确定局限性之后,可以对全局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差异,以及算法特定的问题,例如因评估的风险因素不同而导致的不同算法之间的差异。在一般实践中,当前开发的算法的使用率很低,部分原因是因为认为评估可能会过度简化风险和/或导致药物滥用。使用风险评分的其他障碍包括政府或地方卫生政策,患者依从性问题和时间不足。全面,易于使用且标准化的风险评估工具将有助于改善CVD的一级预防。

著录项

  • 来源
    《QJM》 |2010年第10期|p.727-739|共13页
  • 作者

    A.L. Catapano;

  • 作者单位
  • 收录信息 美国《科学引文索引》(SCI);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-18 01:07:07

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