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Cardiovascular risk

机译:心血管风险

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摘要

Cardiovascular disease is a major, growing, worldwide problem. It is important that individuals at risk of developing cardiovascular disease can be effectively identified and appropriately stratified according to risk. This review examines what we understand by the term risk, traditional and novel risk factors, clinical scoring systems, and the use of risk for informing prescribing decisions. Many different cardiovascular risk factors have been identified. Established, traditional factors such as ageing are powerful predictors of adverse outcome, and in the case of hypertension and dyslipidaemia are the major targets for therapeutic intervention. Numerous novel biomarkers have also been described, such as inflammatory and genetic markers. These have yet to be shown to be of value in improving risk prediction, but may represent potential therapeutic targets and facilitate more targeted use of existing therapies. Risk factors have been incorporated into several cardiovascular disease prediction algorithms, such as the Framingham equation, SCORE and QRISK. These have relatively poor predictive power, and uncertainties remain with regards to aspects such as choice of equation, different risk thresholds and the roles of relative risk, lifetime risk and reversible factors in identifying and treating at-risk individuals. Nonetheless, such scores provide objective and transparent means of quantifying risk and their integration into therapeutic guidelines enables equitable and cost-effective distribution of health service resources and improves the consistency and quality of clinical decision making.
机译:心血管疾病是主要的,正在发展的全球性问题。重要的是,可以有效地识别有患心血管疾病风险的个体,并根据风险对其进行适当分层。这篇综述通过风险,传统和新颖的风险因素,临床评分系统以及使用风险来告知处方决定的术语来理解我们所了解的内容。已经确定了许多不同的心血管危险因素。已确定的传统因素(例如衰老)是不良后果的有力预测因素,在高血压和血脂异常的情况下,这是治疗干预的主要目标。还已经描述了许多新颖的生物标记,例如炎性和遗传标记。这些尚未显示出在改善风险预测中的价值,但可能代表潜在的治疗靶标并促进现有疗法的更有针对性的使用。风险因素已被纳入几种心血管疾病的预测算法中,例如Framingham方程,SCORE和QRISK。这些具有相对较差的预测能力,并且在方程选择,不同风险阈值以及相对风险,一生风险和可逆因素在识别和治疗高风险个体中的作用等方面仍存在不确定性。但是,此类评分提供了客观透明的量化风险的方法,将其整合到治疗指南中可实现公平,经济高效地分配卫生服务资源,并提高临床决策的一致性和质量。

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