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Applying engineering in healthcare: a proposed computer-assisted mathematical model for atherosclerotic cardiovascular risk assessment

机译:工程技术在医疗保健中的应用:拟议的计算机辅助数学模型用于动脉粥样硬化性心血管疾病风险评估

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Despite major advances in the diagnosis and treatment of atherosclerotic cardiovascular disease (CVD) in the past century, it remains a serious clinical and public health problem. There is a need for a new cardiovascular disease model that includes a wider range of relevant risk factors, in particular lifestyle factors, to aid targeting of interventions and improve population models of the impact of cardiovascular disease and preventive strategies. The model needs to be applicable to a wider population including different ethnic groups, different countries and to those with and without cardiovascular disease. Separate multivariable risk algorithms are commonly used to assess risk of specific atherosclerotic cardiovascular disease events, i.e., coronary heart disease (CHD), cerebrovascular disease, peripheral vascular disease, and heart failure. In recent years a number of algorithms for cardiovascular risk assessment have been proposed to the medical community. These algorithms consider a number of variables and express their results as the percentage risk of developing a major fatal or non-fatal cardiovascular event in the following 10 to 20 years. Decades of evaluation of CVD risk factors by the Framingham Study led to the conclusion that CVD risk evaluation is most fruitfully appraised from the multivariable risk posed by a set of established risk factors. Such assessment is essential because risk factors seldom occur in isolation, and the risk associated with each varies widely depending on the burden of associated risk factors. Multivariable risk stratification is now recognized as essential in efficiently identifying likely candidates for CVD and quantifying the hazard. The present paper aims to propose a computer-assisted model for estimating short-term (10-years) risk for CHD or CHD risk-equivalents based on the steps proposed in the most validated risk-score algorithm, i.e., Third Report of the Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III).
机译:尽管在过去的一个世纪中,动脉粥样硬化性心血管疾病(CVD)的诊断和治疗取得了重大进展,但它仍然是一个严重的临床和公共卫生问题。需要一种新的心血管疾病模型,其包括更广泛的相关危险因素,特别是生活方式因素,以帮助确定干预措施并改善心血管疾病影响和预防策略的人群模型。该模型必须适用于包括不同种族,不同国家以及有或没有心血管疾病的人群。通常使用单独的多变量风险算法来评估特定的动脉粥样硬化性心血管疾病事件的风险,即冠心病(CHD),脑血管疾病,外周血管疾病和心力衰竭。近年来,已经向医学界提出了许多用于心血管风险评估的算法。这些算法考虑了许多变量,并将其结果表示为在接下来的10至20年内发生重大致命或非致命心血管事件的风险百分比。弗雷明汉研究(Framingham Study)对CVD危险因素进行的数十年评估得出的结论是,从一组已确定的危险因素所构成的多变量风险中,可以最有效地评估CVD危险评估。这种评估至关重要,因为风险因素很少单独发生,并且与风险因素相关的风险根据相关风险因素的负担而有很大差异。现在,多变量风险分层对于有效识别可能的CVD候选者和量化危害至关重要。本文旨在基于最有效的风险评分算法(即专家的第三次报告)中提出的步骤,提出一种计算机辅助模型,用于评估冠心病或冠心病风险等价物的短期(10年)风险成人高胆固醇检测,评估和治疗小组(成人治疗小组III)。

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