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A deep learning system for retinal vessel calibre improves cardiovascular risk prediction in Asians with chronic kidney disease

BACKGRAUND: Cardiovascular disease (CVD) and mortality is elevated in chronic kidney disease (CKD). Retinal vessel calibre in retinal photographs is associated with cardiovascular risk and automated measurements may aid CVD risk prediction. METHODS: Retrospective cohort study of 860 Chinese, Malay a...

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Autores principales: Lim, Cynthia Ciwei, Chong, Crystal, Tan, Gavin, Tan, Chieh Suai, Cheung, Carol Y, Wong, Tien Y, Cheng, Ching Yu, Sabanayagam, Charumathi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10689182/
https://www.ncbi.nlm.nih.gov/pubmed/38046002
http://dx.doi.org/10.1093/ckj/sfad227
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author Lim, Cynthia Ciwei
Chong, Crystal
Tan, Gavin
Tan, Chieh Suai
Cheung, Carol Y
Wong, Tien Y
Cheng, Ching Yu
Sabanayagam, Charumathi
author_facet Lim, Cynthia Ciwei
Chong, Crystal
Tan, Gavin
Tan, Chieh Suai
Cheung, Carol Y
Wong, Tien Y
Cheng, Ching Yu
Sabanayagam, Charumathi
author_sort Lim, Cynthia Ciwei
collection PubMed
description BACKGRAUND: Cardiovascular disease (CVD) and mortality is elevated in chronic kidney disease (CKD). Retinal vessel calibre in retinal photographs is associated with cardiovascular risk and automated measurements may aid CVD risk prediction. METHODS: Retrospective cohort study of 860 Chinese, Malay and Indian participants aged 40–80 years with CKD [estimated glomerular filtration rate (eGFR) <60 ml/min/1.73 m(2)] who attended the baseline visit (2004–2011) of the Singapore Epidemiology of Eye Diseases Study. Retinal vessel calibre measurements were obtained by a deep learning system (DLS). Incident CVD [non-fatal acute myocardial infarction (MI) and stroke, and death due to MI, stroke and other CVD] in those who were free of CVD at baseline was ascertained until 31 December 2019. Risk factors (established, kidney, and retinal features) were examined using Cox proportional hazards regression models. Model performance was assessed for discrimination, fit, and net reclassification improvement (NRI). RESULTS: Incident CVD occurred in 289 (33.6%) over mean follow-up of 9.3 (4.3) years. After adjusting for established cardiovascular risk factors, eGFR [adjusted HR 0.98 (95% CI: 0.97–0.99)] and retinal arteriolar narrowing [adjusted HR 1.40 (95% CI: 1.17–1.68)], but not venular dilation, were independent predictors for CVD in CKD. The addition of eGFR and retinal features to established cardiovascular risk factors improved model discrimination with significantly better fit and better risk prediction according to the low (<15%), intermediate (15–29.9%), and high (30% or more) risk categories (NRI 5.8%), and with higher risk thresholds (NRI 12.7%). CONCLUSIONS: Retinal vessel calibre measurements by DLS were significantly associated with incident CVD independent of established CVD risk factors. Addition of kidney function and retinal vessel calibre parameters may improve CVD risk prediction among Asians with CKD.
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spelling pubmed-106891822023-12-02 A deep learning system for retinal vessel calibre improves cardiovascular risk prediction in Asians with chronic kidney disease Lim, Cynthia Ciwei Chong, Crystal Tan, Gavin Tan, Chieh Suai Cheung, Carol Y Wong, Tien Y Cheng, Ching Yu Sabanayagam, Charumathi Clin Kidney J Original Article BACKGRAUND: Cardiovascular disease (CVD) and mortality is elevated in chronic kidney disease (CKD). Retinal vessel calibre in retinal photographs is associated with cardiovascular risk and automated measurements may aid CVD risk prediction. METHODS: Retrospective cohort study of 860 Chinese, Malay and Indian participants aged 40–80 years with CKD [estimated glomerular filtration rate (eGFR) <60 ml/min/1.73 m(2)] who attended the baseline visit (2004–2011) of the Singapore Epidemiology of Eye Diseases Study. Retinal vessel calibre measurements were obtained by a deep learning system (DLS). Incident CVD [non-fatal acute myocardial infarction (MI) and stroke, and death due to MI, stroke and other CVD] in those who were free of CVD at baseline was ascertained until 31 December 2019. Risk factors (established, kidney, and retinal features) were examined using Cox proportional hazards regression models. Model performance was assessed for discrimination, fit, and net reclassification improvement (NRI). RESULTS: Incident CVD occurred in 289 (33.6%) over mean follow-up of 9.3 (4.3) years. After adjusting for established cardiovascular risk factors, eGFR [adjusted HR 0.98 (95% CI: 0.97–0.99)] and retinal arteriolar narrowing [adjusted HR 1.40 (95% CI: 1.17–1.68)], but not venular dilation, were independent predictors for CVD in CKD. The addition of eGFR and retinal features to established cardiovascular risk factors improved model discrimination with significantly better fit and better risk prediction according to the low (<15%), intermediate (15–29.9%), and high (30% or more) risk categories (NRI 5.8%), and with higher risk thresholds (NRI 12.7%). CONCLUSIONS: Retinal vessel calibre measurements by DLS were significantly associated with incident CVD independent of established CVD risk factors. Addition of kidney function and retinal vessel calibre parameters may improve CVD risk prediction among Asians with CKD. Oxford University Press 2023-09-19 /pmc/articles/PMC10689182/ /pubmed/38046002 http://dx.doi.org/10.1093/ckj/sfad227 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of the ERA. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Original Article
Lim, Cynthia Ciwei
Chong, Crystal
Tan, Gavin
Tan, Chieh Suai
Cheung, Carol Y
Wong, Tien Y
Cheng, Ching Yu
Sabanayagam, Charumathi
A deep learning system for retinal vessel calibre improves cardiovascular risk prediction in Asians with chronic kidney disease
title A deep learning system for retinal vessel calibre improves cardiovascular risk prediction in Asians with chronic kidney disease
title_full A deep learning system for retinal vessel calibre improves cardiovascular risk prediction in Asians with chronic kidney disease
title_fullStr A deep learning system for retinal vessel calibre improves cardiovascular risk prediction in Asians with chronic kidney disease
title_full_unstemmed A deep learning system for retinal vessel calibre improves cardiovascular risk prediction in Asians with chronic kidney disease
title_short A deep learning system for retinal vessel calibre improves cardiovascular risk prediction in Asians with chronic kidney disease
title_sort deep learning system for retinal vessel calibre improves cardiovascular risk prediction in asians with chronic kidney disease
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10689182/
https://www.ncbi.nlm.nih.gov/pubmed/38046002
http://dx.doi.org/10.1093/ckj/sfad227
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