Mariam Kashani, DNP, CRNP Doctor of Nursing Program (DNP) Student, School of Nursing, Johns Hopkins University, Baltimore; Director, Clinical Operations, Integrative Cardiac Health Project, Walter Reed National Military Medical Center, Bethesda, Maryland. Arn Eliasson, MD Senior Physician Research Consultant, Integrative Cardiac Health Project, Walter Reed National Military Medical Center, Bethesda, Maryland. Marina Vernalis, DO Executive Medical Director, Integrative Cardiac Health Project, Walter Reed National Military Medical Center, Bethesda, Maryland. Linda Costa, PhD, RN Associate Professor, School of Nursing, Johns Hopkins University, Baltimore, Maryland. Mary Terhaar, DNSc, RN Director, DNP Program, and Associate Professor, School of Nursing, Johns Hopkins University, Baltimore, Maryland.
J Cardiovasc Nurs. 2013 Nov-Dec;28(6):E18-27. doi: 10.1097/JCN.0b013e318294b206.
Cardiovascular disease (CVD) is the number one killer in the United States. Although the causes of CVD are multifactorial, including genetic and environmental influences, it is largely a preventable disease. The cornerstone of CVD prevention is accuracy in risk prediction to identify patients who will benefit from interventions aimed at reducing risk. Nurse practitioners commonly perform CVD risk assessments and are well positioned to impact preventive therapy. Cardiovascular disease risk scoring systems currently in use substantially underestimate risk in large part because these do not include family history of premature CVD as a high-risk factor.
We sought to examine the state of evidence for the use of family history as a predictor in CVD risk stratification.
A comprehensive literature search using the Medical Subject Headings terms of family history of CVD, family history of premature CVD, risk assessment, and risk estimation displayed 416 articles; a review of the titles and subsequent evaluation of the articles eliminated 392 references, leaving 24 for review. By incorporating family history in risk assessment, categorization of CVD risk improves substantially. The evidence demonstrates that family history is an independent contributor to risk appraisal and unequivocally supports its incorporation to improve accuracy in global CVD risk estimation.
Underestimation of CVD risk leaves patients and providers misinformed, promoting the ongoing epidemic of chronic disease. Translating this evidence into practice by establishing a clinical algorithm that incorporates family history into risk prediction will standardize CVD risk assessment, improve the identification of high-risk patients, and provide the indicated aggressive care to prevent CVD.
心血管疾病(CVD)是美国的头号杀手。尽管 CVD 的病因是多因素的,包括遗传和环境影响,但它在很大程度上是一种可预防的疾病。CVD 预防的基石是准确预测风险,以确定将从旨在降低风险的干预措施中受益的患者。护士从业者通常进行 CVD 风险评估,并且处于能够影响预防性治疗的有利位置。目前使用的 CVD 风险评分系统在很大程度上低估了风险,部分原因是这些系统不将家族史作为高风险因素包括在内。
我们旨在检查家族史作为 CVD 风险分层预测因子的使用证据状况。
使用 CVD 家族史、早发性 CVD 家族史、风险评估和风险估计的医学主题词术语进行全面文献检索显示出 416 篇文章;对标题进行审查,随后对文章进行评估,排除了 392 篇参考文献,留下 24 篇进行审查。通过将家族史纳入风险评估,CVD 风险的分类得到了极大的改善。证据表明,家族史是风险评估的独立贡献者,并明确支持将其纳入以提高全球 CVD 风险估计的准确性。
CVD 风险的低估会使患者和提供者产生误解,从而促进慢性疾病的持续流行。通过建立一种将家族史纳入风险预测的临床算法,将这一证据转化为实践,将标准化 CVD 风险评估,提高高危患者的识别,并提供所需的积极护理,以预防 CVD。