Rudnicka, AR; Welikala, R; Barman, S; Foster, PJ; Luben, R; Hayat, S; Khaw, K-T; Whincup, P; Strachan, D; Owen, CG
(2022)
Artificial intelligence-enabled retinal vasculometry for prediction of circulatory mortality, myocardial infarction and stroke.
Br J Ophthalmol, 106 (12).
pp. 1722-1729.
ISSN 1468-2079
https://doi.org/10.1136/bjo-2022-321842
SGUL Authors: Owen, Christopher Grant Rudnicka, Alicja Regina
Abstract
AIMS: We examine whether inclusion of artificial intelligence (AI)-enabled retinal vasculometry (RV) improves existing risk algorithms for incident stroke, myocardial infarction (MI) and circulatory mortality. METHODS: AI-enabled retinal vessel image analysis processed images from 88 052 UK Biobank (UKB) participants (aged 40-69 years at image capture) and 7411 European Prospective Investigation into Cancer (EPIC)-Norfolk participants (aged 48-92). Retinal arteriolar and venular width, tortuosity and area were extracted. Prediction models were developed in UKB using multivariable Cox proportional hazards regression for circulatory mortality, incident stroke and MI, and externally validated in EPIC-Norfolk. Model performance was assessed using optimism adjusted calibration, C-statistics and R2 statistics. Performance of Framingham risk scores (FRS) for incident stroke and incident MI, with addition of RV to FRS, were compared with a simpler model based on RV, age, smoking status and medical history (antihypertensive/cholesterol lowering medication, diabetes, prevalent stroke/MI). RESULTS: UKB prognostic models were developed on 65 144 participants (mean age 56.8; median follow-up 7.7 years) and validated in 5862 EPIC-Norfolk participants (67.6, 9.1 years, respectively). Prediction models for circulatory mortality in men and women had optimism adjusted C-statistics and R2 statistics between 0.75-0.77 and 0.33-0.44, respectively. For incident stroke and MI, addition of RV to FRS did not improve model performance in either cohort. However, the simpler RV model performed equally or better than FRS. CONCLUSION: RV offers an alternative predictive biomarker to traditional risk-scores for vascular health, without the need for blood sampling or blood pressure measurement. Further work is needed to examine RV in population screening to triage individuals at high-risk.
Item Type: |
Article
|
Additional Information: |
© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ. https://creativecommons.org/licenses/by/4.0/
This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/. |
Keywords: |
Diagnostic tests/Investigation, Epidemiology, Imaging, Public health, Retina, 1103 Clinical Sciences, 1113 Opthalmology and Optometry, 1117 Public Health and Health Services, Ophthalmology & Optometry |
SGUL Research Institute / Research Centre: |
Academic Structure > Population Health Research Institute (INPH) |
Journal or Publication Title: |
Br J Ophthalmol |
ISSN: |
1468-2079 |
Language: |
eng |
Dates: |
Date | Event |
---|
22 November 2022 | Published | 4 October 2022 | Published Online | 3 August 2022 | Accepted |
|
Publisher License: |
Creative Commons: Attribution 4.0 |
Projects: |
|
PubMed ID: |
36195457 |
![](http://static.pubmed.gov/portal/portal3rc.fcgi/2745237/img/27842) |
Go to PubMed abstract |
URI: |
https://openaccess.sgul.ac.uk/id/eprint/114902 |
Publisher's version: |
https://doi.org/10.1136/bjo-2022-321842 |
Statistics
Item downloaded times since 11 Oct 2022.
Actions (login required)
![Edit Item](/style/images/action_view.png) |
Edit Item |