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基层医疗中的心血管风险算法:DETECT 研究结果。

Cardiovascular risk algorithms in primary care: Results from the DETECT study.

机构信息

University of Heidelberg, Mannheim Medical Faculty, Mannheim Institute of Public Health, Social and Preventive Medicine, Mannheim, Germany.

University of Heidelberg, Mannheim Medical Faculty, Department of Internal Medicine V (Nephrology, Hypertensiology, Rheumatology, Endocrinology, Diabetology), Mannheim, Germany.

出版信息

Sci Rep. 2019 Jan 31;9(1):1101. doi: 10.1038/s41598-018-37092-7.

DOI:10.1038/s41598-018-37092-7
PMID:30705337
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6355969/
Abstract

Guidelines for prevention of cardiovascular diseases use risk scores to guide the intensity of treatment. A comparison of these scores in a German population has not been performed. We have evaluated the correlation, discrimination and calibration of ten commonly used risk equations in primary care in 4044 participants of the DETECT (Diabetes and Cardiovascular Risk Evaluation: Targets and Essential Data for Commitment of Treatment) study. The risk equations correlate well with each other. All risk equations have a similar discriminatory power. Absolute risks differ widely, in part due to the components of clinical endpoints predicted: The risk equations produced median risks between 8.4% and 2.0%. With three out of 10 risk scores calculated and observed risks well coincided. At a risk threshold of 10 percent in 10 years, the ACC/AHA atherosclerotic cardiovascular disease (ASCVD) equation has a sensitivity to identify future CVD events of approximately 80%, with the highest specificity (69%) and positive predictive value (17%) among all the equations. Due to the most precise calibration over a wide range of risks, the large age range covered and the combined endpoint including non-fatal and fatal events, the ASCVD equation provides valid risk prediction for primary prevention in Germany.

摘要

心血管疾病预防指南使用风险评分来指导治疗强度。尚未对德国人群中的这些评分进行比较。我们在 DETECT(糖尿病和心血管风险评估:治疗承诺的目标和基本数据)研究的 4044 名参与者中评估了十种常用风险方程在初级保健中的相关性、区分度和校准度。这些风险方程彼此之间相关性良好。所有风险方程的区分能力相似。绝对风险差异很大,部分原因是预测的临床终点组成部分不同:风险方程产生的中位数风险在 8.4%至 2.0%之间。使用其中 3 种风险评分计算出的计算风险和观察风险非常吻合。在 10 年内风险阈值为 10%的情况下,ACC/AHA 动脉粥样硬化性心血管疾病(ASCVD)方程对未来 CVD 事件的敏感性约为 80%,在所有方程中具有最高的特异性(69%)和阳性预测值(17%)。由于在广泛的风险范围内具有最精确的校准、涵盖的年龄范围较大以及包括非致命和致命事件的联合终点,ASCVD 方程为德国的一级预防提供了有效的风险预测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ab7/6355969/99ea84cabcdb/41598_2018_37092_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ab7/6355969/b98e88a14144/41598_2018_37092_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ab7/6355969/8ac25665af0d/41598_2018_37092_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ab7/6355969/99ea84cabcdb/41598_2018_37092_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ab7/6355969/b98e88a14144/41598_2018_37092_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ab7/6355969/8ac25665af0d/41598_2018_37092_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ab7/6355969/99ea84cabcdb/41598_2018_37092_Fig3_HTML.jpg

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