{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T12:06:54Z","timestamp":1773403614348,"version":"3.50.1"},"reference-count":71,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2023,3,25]],"date-time":"2023-03-25T00:00:00Z","timestamp":1679702400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000925","name":"National Health and Medical Research Council","doi-asserted-by":"publisher","award":["1186915"],"award-info":[{"award-number":["1186915"]}],"id":[{"id":"10.13039\/501100000925","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Ophthalmic Physiologic Optic"],"published-print":{"date-parts":[[2023,7]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>To determine whether there are quantifiable structural or functional differences that can distinguish between high\u2010tension glaucoma (HTG; intraocular pressure [IOP]\u2009&gt;\u200921\u2009mm Hg) and low\u2010tension glaucoma (LTG; IOP\u2009\u2264\u200921\u2009mm Hg) at diagnosis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Method<\/jats:title>\n                    <jats:p>\n                      This was a retrospective, cross\u2010sectional study. Clinical results of one eye from 90 newly diagnosed HTG and 319 newly diagnosed LTG patients (117 with very\u2010low\u2010tension glaucoma [vLTG; \u226415\u2009mm\u2009Hg] and 202 with middling LTG [mLTG; &gt;15\u2009mm\u2009Hg, \u226421\u2009mm\u2009Hg]) were extracted, which included relevant demographic covariates of glaucoma, quantitative optical coherence tomography (including the optic nerve head, retinal nerve fibre layer and ganglion cell\u2010inner plexiform layer) measurements and standard automated perimetry global metrics. We used binary logistic regression analysis to identify statistically significant clinical parameters distinguishing between phenotypic groups for inclusion in principal component (PC) (factor) analysis (PCA). The separability between each centroid for each cohort was calculated using the Euclidean distance (\n                      <jats:italic>d<\/jats:italic>\n                      (\n                      <jats:italic>x<\/jats:italic>\n                      ,\n                      <jats:italic>y<\/jats:italic>\n                      )).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The binary logistic regression comparing HTG and all LTG identified eight statistically significant clinical parameters. Subsequent PCA results included three PCs with an eigenvalue &gt;1. PCs 1 and 2 accounted for 21.2% and 20.2% of the model, respectively, with a d(\n                      <jats:italic>x<\/jats:italic>\n                      ,\n                      <jats:italic>y<\/jats:italic>\n                      )\u00a0=\u00a00.468, indicating low separability between HTG and LTG. The analysis comparing vLTG, mLTG and HTG identified 15 significant clinical parameters, which were subsequently grouped into five PCs. PCs 1 and 2 accounted for 24.1% and 17.8%, respectively. The largest separation was observed between vLTG and HTG (d(\n                      <jats:italic>x<\/jats:italic>\n                      ,\n                      <jats:italic>y<\/jats:italic>\n                      )\u00a0=\u00a00.581), followed by vLTG and mLTG (d(\n                      <jats:italic>x<\/jats:italic>\n                      ,\n                      <jats:italic>y<\/jats:italic>\n                      )\u00a0=\u00a00.435) and lastly mLTG and HTG (d(\n                      <jats:italic>x<\/jats:italic>\n                      ,\n                      <jats:italic>y<\/jats:italic>\n                      )\u00a0=\u00a00.210).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Conventional quantitative structural or functional parameters could not distinguish between pressure\u2010defined glaucoma phenotypes at the point of diagnosis and are therefore not contributory to separating cohorts. The overlap in findings highlights the heterogeneity of the primary open\u2010angle glaucoma clinical presentations among pressure\u2010defined groups at the cohort level.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/opo.13129","type":"journal-article","created":{"date-parts":[[2023,3,25]],"date-time":"2023-03-25T15:34:46Z","timestamp":1679758486000},"page":"771-787","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Visualising structural and functional characteristics distinguishing between newly diagnosed high\u2010tension and low\u2010tension glaucoma patients"],"prefix":"10.1007","volume":"43","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2393-7771","authenticated-orcid":false,"given":"Daniel","family":"Rafla","sequence":"first","affiliation":[{"name":"Centre for Eye Health The University of New South Wales  Sydney New South Wales Australia"},{"name":"School of Optometry and Vision Science The 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