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.
| Original language | English |
|---|---|
| Article number | 6545 |
| Journal | Scientific Reports |
| Volume | 12 |
| Issue number | 1 |
| Early online date | 21 Apr 2022 |
| DOIs | |
| Publication status | Published online - 21 Apr 2022 |
Bibliographical note
Publisher Copyright:© 2022, The Author(s).
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Conjunctiva
- Atherosclerosis
- Biomarkers
- Microcirculation
- Cardiovascular disease
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Mailey , J. A. (Author), Nesbit, A. (Supervisor), Moore, T. (Supervisor) & Spence, M. (Supervisor), Sept 2022Student thesis: Doctoral Thesis
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