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心血管风险评估的艺术。

The art of cardiovascular risk assessment.

作者信息

Khambhati Jay, Allard-Ratick Marc, Dhindsa Devinder, Lee Suegene, Chen John, Sandesara Pratik B, O'Neal Wesley, Quyyumi Arshed A, Wong Nathan D, Blumenthal Roger S, Sperling Laurence S

机构信息

Emory Clinical Cardiovascular Research Institute, Division of Cardiology, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia.

Heart Disease Prevention Program, Division of Cardiology, University of California, Irvine, California.

出版信息

Clin Cardiol. 2018 May;41(5):677-684. doi: 10.1002/clc.22930. Epub 2018 May 10.

Abstract

Cardiovascular disease (CVD) remains the leading cause of death in the United States. Healthcare expenditures have been principally allocated toward treatment of CVD at the end of the health/disease continuum, rather than toward health promotion and disease prevention. A focused effort on both primordial and primary prevention can promote cardiovascular health and reduce the burden of CVD. Risk-factor assessment for predicting atherosclerotic CVD events serves as the foundation of preventive cardiology and has been driven by population-based scoring algorithms based on traditional risk factors. Incorporating individual nontraditional risk factors, biomarkers, and selective use of noninvasive measures may help identify more at-risk patients as well as truly low-risk individuals, allowing for better targeting of treatment intensity. Using a combination of validated population-based atherosclerotic CVD risk-assessment tools, nontraditional risk factors, social health determinants, and novel markers of atherosclerotic disease, we should be able to improve our ability to assess CVD risk. Through scientific evidence, clinical judgment, and discussion between the patient and clinician, we can implement an effective evidence-based strategy to assess and reduce CVD risk.

摘要

心血管疾病(CVD)仍然是美国的主要死因。医疗保健支出主要用于在健康/疾病连续统一体末端治疗CVD,而不是用于健康促进和疾病预防。对初级预防和一级预防的重点努力可以促进心血管健康并减轻CVD的负担。预测动脉粥样硬化性CVD事件的风险因素评估是预防心脏病学的基础,并且一直由基于传统风险因素的人群评分算法驱动。纳入个体非传统风险因素、生物标志物以及选择性使用非侵入性措施可能有助于识别更多高危患者以及真正的低风险个体,从而更好地确定治疗强度的目标。使用经过验证的基于人群的动脉粥样硬化性CVD风险评估工具、非传统风险因素、社会健康决定因素以及动脉粥样硬化疾病的新型标志物的组合,我们应该能够提高评估CVD风险的能力。通过科学证据、临床判断以及患者与临床医生之间的讨论,我们可以实施有效的循证策略来评估和降低CVD风险。

相似文献

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The art of cardiovascular risk assessment.心血管风险评估的艺术。
Clin Cardiol. 2018 May;41(5):677-684. doi: 10.1002/clc.22930. Epub 2018 May 10.
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