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一种基于结膜微循环参数和血液生物标志物的心血管筛查新算法。

A novel algorithm for cardiovascular screening using conjunctival microcirculatory parameters and blood biomarkers.

机构信息

Biomedical Sciences Research Institute, Ulster University, Cromore Road, Coleraine, BT52 1SA, UK.

Clinical Studies Group, Randox Laboratories Ltd, 55 Diamond Road, Crumlin, BT29 4QY, UK.

出版信息

Sci Rep. 2022 Apr 21;12(1):6545. doi: 10.1038/s41598-022-10491-7.

Abstract

Microvascular haemodynamic alterations are associated with coronary artery disease (CAD). The conjunctival microcirculation can easily be assessed non-invasively. However, the microcirculation of the conjunctiva has not been previously explored in clinical algorithms aimed at identifying patients with CAD. This case-control study involved 66 patients with post-myocardial infarction and 66 gender-matched healthy controls. Haemodynamic properties of the conjunctival microcirculation were assessed with a validated iPhone and slit lamp-based imaging tool. Haemodynamic properties were extracted with semi-automated software and compared between groups. Biomarkers implicated in the development of CAD were assessed in combination with conjunctival microcirculatory parameters. The conjunctival blood vessel parameters and biomarkers were used to derive an algorithm to aid in the screening of patients for CAD. Conjunctival blood velocity measured in combination with the blood biomarkers (N-terminal pro-brain natriuretic peptide and adiponectin) had an area under receiver operator characteristic curve (AUROC) of 0.967, sensitivity 93.0%, specificity 91.5% for CAD. This study demonstrated that the novel algorithm which included a combination of conjunctival blood vessel haemodynamic properties, and blood-based biomarkers could be used as a potential screening tool for CAD and should be validated for potential utility in asymptomatic individuals.

摘要

微血管血液动力学改变与冠状动脉疾病(CAD)有关。结膜微循环可以很容易地进行非侵入性评估。然而,结膜的微循环在以前用于识别 CAD 患者的临床算法中尚未得到探索。这项病例对照研究涉及 66 名心肌梗死后患者和 66 名性别匹配的健康对照者。使用经过验证的 iPhone 和裂隙灯成像工具评估结膜微循环的血液动力学特性。使用半自动软件提取血液动力学特性,并在组间进行比较。结合结膜微循环参数评估与 CAD 发展相关的生物标志物。使用算法将结膜血管参数和生物标志物结合起来,以帮助筛选 CAD 患者。结合血液生物标志物(N 端脑利钠肽前体和脂联素)测量的结膜血流速度的受试者工作特征曲线(AUROC)为 0.967,对 CAD 的敏感性为 93.0%,特异性为 91.5%。这项研究表明,包括结膜血管血液动力学特性和基于血液的生物标志物的新算法可作为 CAD 的潜在筛查工具,应验证其在无症状个体中的潜在效用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0b2/9023476/a8b61aa96776/41598_2022_10491_Fig1_HTML.jpg

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