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Association between metabolic risk factors and optic disc cupping identified by deep learning method

PURPOSE: This study aims to investigate correlation between metabolic risk factors and optic disc cupping and the development of glaucoma. METHODS: This study is a retrospective, cross-sectional study with over 20-year-old patients that underwent health screening examinations. Intraocular pressure (...

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Autores principales: Shin, Jonghoon, Kang, Min Seung, Park, Keunheung, Lee, Jong Soo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7498045/
https://www.ncbi.nlm.nih.gov/pubmed/32941514
http://dx.doi.org/10.1371/journal.pone.0239071
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author Shin, Jonghoon
Kang, Min Seung
Park, Keunheung
Lee, Jong Soo
author_facet Shin, Jonghoon
Kang, Min Seung
Park, Keunheung
Lee, Jong Soo
author_sort Shin, Jonghoon
collection PubMed
description PURPOSE: This study aims to investigate correlation between metabolic risk factors and optic disc cupping and the development of glaucoma. METHODS: This study is a retrospective, cross-sectional study with over 20-year-old patients that underwent health screening examinations. Intraocular pressure (IOP), fundus photographs, Body Mass Index (BMI), waist circumference (WC), serum triglycerides, serum HDL cholesterol (HDL-C), serum LDL cholesterol (LDL-C), systolic blood pressure (BP), diastolic BP, and serum HbA1c were obtained to analyse correlation between metabolic risk factors and glaucoma. Eye with glaucomatous optic neuropathy(GON) was defined as having an optic disc with either vertical cup-to-disc ratio(VCDR) ≥ 0.7 or a VCDR difference ≥ 0.2 between the right and left eyes by measuring VCDR with deep learning approach. RESULTS: The study comprised 15,585 subjects and 877 subjects were diagnosed as GON. In univariate analyses, age, BMI, systolic BP, diastolic BP, WC, triglyceride, LDL-C, HbA1c, and IOP were significantly and positively correlated with VCDR in the optic nerve head. In linear regression analysis as independent variables, stepwise multiple regression analyses revealed that age, BMI, systolic BP, HbA1c, and IOP showed positive correlation with VCDR. In multivariate logistic analyses of risk factors and GON, higher age (odds ratio [OR], 1.054; 95% confidence interval [CI], 1.046–1.063), male gender (OR, 0.730; 95% CI, 0.609–0.876), more obese (OR, 1.267; 95% CI, 1.065–1.507), and diabetes (OR, 1.575; 95% CI, 1.214–2.043) remained statistically significant correlation with GON. CONCLUSIONS: Among the metabolic risk factors, obesity and diabetes as well as older age and male gender are risk factors of developing GON. The glaucoma screening examinations should be considered in the populations with these indicated risk factors.
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spelling pubmed-74980452020-09-24 Association between metabolic risk factors and optic disc cupping identified by deep learning method Shin, Jonghoon Kang, Min Seung Park, Keunheung Lee, Jong Soo PLoS One Research Article PURPOSE: This study aims to investigate correlation between metabolic risk factors and optic disc cupping and the development of glaucoma. METHODS: This study is a retrospective, cross-sectional study with over 20-year-old patients that underwent health screening examinations. Intraocular pressure (IOP), fundus photographs, Body Mass Index (BMI), waist circumference (WC), serum triglycerides, serum HDL cholesterol (HDL-C), serum LDL cholesterol (LDL-C), systolic blood pressure (BP), diastolic BP, and serum HbA1c were obtained to analyse correlation between metabolic risk factors and glaucoma. Eye with glaucomatous optic neuropathy(GON) was defined as having an optic disc with either vertical cup-to-disc ratio(VCDR) ≥ 0.7 or a VCDR difference ≥ 0.2 between the right and left eyes by measuring VCDR with deep learning approach. RESULTS: The study comprised 15,585 subjects and 877 subjects were diagnosed as GON. In univariate analyses, age, BMI, systolic BP, diastolic BP, WC, triglyceride, LDL-C, HbA1c, and IOP were significantly and positively correlated with VCDR in the optic nerve head. In linear regression analysis as independent variables, stepwise multiple regression analyses revealed that age, BMI, systolic BP, HbA1c, and IOP showed positive correlation with VCDR. In multivariate logistic analyses of risk factors and GON, higher age (odds ratio [OR], 1.054; 95% confidence interval [CI], 1.046–1.063), male gender (OR, 0.730; 95% CI, 0.609–0.876), more obese (OR, 1.267; 95% CI, 1.065–1.507), and diabetes (OR, 1.575; 95% CI, 1.214–2.043) remained statistically significant correlation with GON. CONCLUSIONS: Among the metabolic risk factors, obesity and diabetes as well as older age and male gender are risk factors of developing GON. The glaucoma screening examinations should be considered in the populations with these indicated risk factors. Public Library of Science 2020-09-17 /pmc/articles/PMC7498045/ /pubmed/32941514 http://dx.doi.org/10.1371/journal.pone.0239071 Text en © 2020 Shin et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Shin, Jonghoon
Kang, Min Seung
Park, Keunheung
Lee, Jong Soo
Association between metabolic risk factors and optic disc cupping identified by deep learning method
title Association between metabolic risk factors and optic disc cupping identified by deep learning method
title_full Association between metabolic risk factors and optic disc cupping identified by deep learning method
title_fullStr Association between metabolic risk factors and optic disc cupping identified by deep learning method
title_full_unstemmed Association between metabolic risk factors and optic disc cupping identified by deep learning method
title_short Association between metabolic risk factors and optic disc cupping identified by deep learning method
title_sort association between metabolic risk factors and optic disc cupping identified by deep learning method
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7498045/
https://www.ncbi.nlm.nih.gov/pubmed/32941514
http://dx.doi.org/10.1371/journal.pone.0239071
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