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Clinical characteristics of glaucoma patients with various risk factors
BACKGROUND: Glaucoma is multifactorial, but the interrelationship between risk factors and structural changes remains unclear. Here, we adjusted for confounding factors in glaucoma patients with differing risk factors, and compared differences in structure and susceptible areas in the optic disc and...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9484257/ https://www.ncbi.nlm.nih.gov/pubmed/36123604 http://dx.doi.org/10.1186/s12886-022-02587-5 |
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author | Omodaka, Kazuko Kikawa, Tsutomu Kabakura, Sayaka Himori, Noriko Tsuda, Satoru Ninomiya, Takahiro Takahashi, Naoki Pak, Kyongsun Takeda, Noriyasu Akiba, Masahiro Nakazawa, Toru |
author_facet | Omodaka, Kazuko Kikawa, Tsutomu Kabakura, Sayaka Himori, Noriko Tsuda, Satoru Ninomiya, Takahiro Takahashi, Naoki Pak, Kyongsun Takeda, Noriyasu Akiba, Masahiro Nakazawa, Toru |
author_sort | Omodaka, Kazuko |
collection | PubMed |
description | BACKGROUND: Glaucoma is multifactorial, but the interrelationship between risk factors and structural changes remains unclear. Here, we adjusted for confounding factors in glaucoma patients with differing risk factors, and compared differences in structure and susceptible areas in the optic disc and macula. METHODS: In 458 eyes with glaucoma, we determined confounding factors for intraocular pressure (IOP), central corneal thickness (CCT), axial length (AL), LSFG-measured ocular blood flow (OBF), which was assessed with laser speckle flowgraphy-measured mean blur rate in the tissue area (MT) of the optic nerve head, biological antioxidant potential (BAP), and systemic abnormalities in diastolic blood pressure (dBP). To compensate for measurement bias, we also analyzed corrected IOP (cIOP; corrected for CCT) and corrected MT (cMT; corrected for age, weighted retinal ganglion cell count, and AL). Then, we determined the distribution of these parameters in low-, middle-, and high-value subgroups and compared them with the Kruskal–Wallis test. Pairwise comparisons used the Steel–Dwass test. RESULTS: The high-cIOP subgroup had significantly worse mean deviation (MD), temporal, superior, and inferior loss of circumpapillary retinal nerve fiber layer thickness (cpRNFLT), and large cupping. The low-CCT subgroup had temporal cpRNFLT loss; the high-CCT subgroup had low cup volume. The high-AL subgroup had macular ganglion cell complex thickness (GCCT) loss; the low-AL subgroup had temporal cpRNFLT loss. The high-systemic-dBP subgroup had worse MD, total, superior, and inferior cpRNFLT loss and macular GCCT loss. The low-BAP subgroup had more male patients, higher dBP, and cpRNFLT loss in the 10 o’clock area. The high-OBF subgroup had higher total, superior and temporal cpRNFLT and macular GCCT. CONCLUSIONS: Structural changes and local susceptibility to glaucomatous damage show unique variations in patients with different risk factors, which might suggest that specific risk factors induce specific types of pathogenesis and corresponding glaucoma phenotypes. Our study may open new avenues for the development of precision medicine for glaucoma. |
format | Online Article Text |
id | pubmed-9484257 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-94842572022-09-20 Clinical characteristics of glaucoma patients with various risk factors Omodaka, Kazuko Kikawa, Tsutomu Kabakura, Sayaka Himori, Noriko Tsuda, Satoru Ninomiya, Takahiro Takahashi, Naoki Pak, Kyongsun Takeda, Noriyasu Akiba, Masahiro Nakazawa, Toru BMC Ophthalmol Research BACKGROUND: Glaucoma is multifactorial, but the interrelationship between risk factors and structural changes remains unclear. Here, we adjusted for confounding factors in glaucoma patients with differing risk factors, and compared differences in structure and susceptible areas in the optic disc and macula. METHODS: In 458 eyes with glaucoma, we determined confounding factors for intraocular pressure (IOP), central corneal thickness (CCT), axial length (AL), LSFG-measured ocular blood flow (OBF), which was assessed with laser speckle flowgraphy-measured mean blur rate in the tissue area (MT) of the optic nerve head, biological antioxidant potential (BAP), and systemic abnormalities in diastolic blood pressure (dBP). To compensate for measurement bias, we also analyzed corrected IOP (cIOP; corrected for CCT) and corrected MT (cMT; corrected for age, weighted retinal ganglion cell count, and AL). Then, we determined the distribution of these parameters in low-, middle-, and high-value subgroups and compared them with the Kruskal–Wallis test. Pairwise comparisons used the Steel–Dwass test. RESULTS: The high-cIOP subgroup had significantly worse mean deviation (MD), temporal, superior, and inferior loss of circumpapillary retinal nerve fiber layer thickness (cpRNFLT), and large cupping. The low-CCT subgroup had temporal cpRNFLT loss; the high-CCT subgroup had low cup volume. The high-AL subgroup had macular ganglion cell complex thickness (GCCT) loss; the low-AL subgroup had temporal cpRNFLT loss. The high-systemic-dBP subgroup had worse MD, total, superior, and inferior cpRNFLT loss and macular GCCT loss. The low-BAP subgroup had more male patients, higher dBP, and cpRNFLT loss in the 10 o’clock area. The high-OBF subgroup had higher total, superior and temporal cpRNFLT and macular GCCT. CONCLUSIONS: Structural changes and local susceptibility to glaucomatous damage show unique variations in patients with different risk factors, which might suggest that specific risk factors induce specific types of pathogenesis and corresponding glaucoma phenotypes. Our study may open new avenues for the development of precision medicine for glaucoma. BioMed Central 2022-09-19 /pmc/articles/PMC9484257/ /pubmed/36123604 http://dx.doi.org/10.1186/s12886-022-02587-5 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Omodaka, Kazuko Kikawa, Tsutomu Kabakura, Sayaka Himori, Noriko Tsuda, Satoru Ninomiya, Takahiro Takahashi, Naoki Pak, Kyongsun Takeda, Noriyasu Akiba, Masahiro Nakazawa, Toru Clinical characteristics of glaucoma patients with various risk factors |
title | Clinical characteristics of glaucoma patients with various risk factors |
title_full | Clinical characteristics of glaucoma patients with various risk factors |
title_fullStr | Clinical characteristics of glaucoma patients with various risk factors |
title_full_unstemmed | Clinical characteristics of glaucoma patients with various risk factors |
title_short | Clinical characteristics of glaucoma patients with various risk factors |
title_sort | clinical characteristics of glaucoma patients with various risk factors |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9484257/ https://www.ncbi.nlm.nih.gov/pubmed/36123604 http://dx.doi.org/10.1186/s12886-022-02587-5 |
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