瑞士和欧洲心血管预防风险算法比较。

Comparison of Swiss and European risk algorithms for cardiovascular prevention in Switzerland.

机构信息

Service of Internal Medicine, Lausanne University Hospital, Switzerland.

Center for Primary Care and Public Health (Unisanté), University of Lausanne, Switzerland.

出版信息

Eur J Prev Cardiol. 2021 Apr 10;28(2):204–210. doi: 10.1177/2047487320906305. Epub 2020 Feb 23.

DOI:10.1177/2047487320906305

PMID:33838036

Abstract

BACKGROUND

In Switzerland, two distinct algorithms are recommended for cardiovascular prevention: (a) Arbeitsgruppe Lipide und Atherosklerose (AGLA); and (b) European Society of Cardiology (ESC). We validated and determined which algorithm better predicts incident atherosclerotic cardiovascular disease and assessed statin eligibility in Switzerland.

DESIGN

A prospective population-based cohort.

METHODS

We employed longitudinal data of the CoLaus study involving 6733 individuals, aged 35-75 years, with a 10-year follow-up. Using discrimination and calibration, we evaluated the predictive performance of the AGLA and ESC algorithms for the prediction of atherosclerotic cardiovascular disease.

RESULTS

From the 6733 initial participants, 5529 were analysed with complete baseline and follow-up data. Mean age (SD) was 52.4 (10.6) years and 54% were women. During an average follow-up (SD) of 10.2 years (1.7), 370 (6.7%) participants developed an incident atherosclerotic cardiovascular disease. The sensitivity of AGLA and ESC algorithms to predict atherosclerotic cardiovascular disease was 51.6% (95% confidence interval (CI) 46.4-56.8) and 58.6% (53.4-63.7), respectively. Discrimination and calibration were similar between the AGLA and ESC algorithms, with area under the receiver operating characteristic curve values of 0.78 (95% CI 0.76-0.80) and 0.79 (0.76-0.81), and Brier scores of 0.059 and 0.041, respectively. Among 370 individuals developing incident atherosclerotic cardiovascular disease, only 278 (75%) were eligible for statin therapy at baseline, including 210 (57%) according to both algorithms, 4 (1%) to AGLA only and 64 (17%) to ESC only.

CONCLUSION

AGLA and ESC algorithms presented similar accuracy to predict atherosclerotic cardiovascular disease in Switzerland. A quarter of adults developing atherosclerotic cardiovascular disease were not identified by preventive algorithms to be eligible for statin therapy.

摘要

背景

在瑞士，有两种不同的心血管预防算法被推荐使用：（a）脂质和动脉粥样硬化工作组（AGLA）；（b）欧洲心脏病学会（ESC）。我们验证了这两种算法，并确定了哪种算法能更好地预测动脉粥样硬化性心血管疾病的发生，并评估了瑞士使用他汀类药物的资格。

设计

一项前瞻性的基于人群的队列研究。

方法

我们使用了科劳斯研究的纵向数据，涉及 6733 名年龄在 35-75 岁之间、随访 10 年的个体。我们使用区分度和校准度评估了 AGLA 和 ESC 算法对动脉粥样硬化性心血管疾病的预测能力。

结果

在最初的 6733 名参与者中，有 5529 名参与者具有完整的基线和随访数据。平均年龄（标准差）为 52.4（10.6）岁，54%为女性。在平均 10.2 年（1.7）的随访期间，370 名（6.7%）参与者发生了动脉粥样硬化性心血管疾病事件。AGLA 和 ESC 算法预测动脉粥样硬化性心血管疾病的敏感性分别为 51.6%（95%置信区间[CI]为 46.4-56.8）和 58.6%（53.4-63.7）。AGLA 和 ESC 算法的区分度和校准度相似，受试者工作特征曲线下面积分别为 0.78（95%CI为 0.76-0.80）和 0.79（0.76-0.81），Brier 评分分别为 0.059 和 0.041。在 370 名发生动脉粥样硬化性心血管疾病事件的个体中，只有 278 名（75%）在基线时符合他汀类药物治疗的条件，其中根据两种算法均符合条件的有 210 名（57%），仅根据 AGLA 符合条件的有 4 名（1%），仅根据 ESC 符合条件的有 64 名（17%）。