Glaucoma Prediction Models Based on Ocular and Systemic Findings
Abstract: Introduction: Our aim was to explore the impact of various systemic and ocular findings on predicting the development of glaucoma. Methods: Medical records of 37,692 consecutive patients examined at a single medical center between 2001 and 2020 were analyzed using machine learning algorithms. Systemic and ocular features were included. Univariate and multivariate analyses followed by CatBoost and Light gradient-boosting machine prediction models were performed. Main outcome measures were systemic and ocular features associated with progression to glaucoma. Results: A total of 7,880 patients (mean age 54.7 ± 12.6 years, 5,520 males [70.1%]) were included in a 3-year prediction model, and 314 patients (3.98%) had a final diagnosis of glaucoma. The combined model included 185 systemic and 42 ocular findings, and reached an ROC AUC of 0.84. The associated features were intraocular pressure (48.6%), cup-to-disk ratio (22.7%), age (8.6%), mean corpuscular volume (MCV) of red blood cell trend (5.2%), urinary system disease (3.3%), MCV (2.6%), creatinine level trend (2.1%), monocyte count trend (1.7%), ergometry metabolic equivalent task score (1.7%), dyslipidemia duration (1.6%), prostate-specific antigen level (1.2%), and musculoskeletal disease duration (0.5%). The ocular prediction model reached an ROC AUC of 0.86. Additional features included were age-related macular degeneration (10.0%), anterior capsular cataract (3.3%), visual acuity (2.0%), and peripapillary atrophy (1.3%). Conclusions: Ocular and combined systemic-ocular models can strongly predict the development of glaucoma in the forthcoming 3 years. Novel progression indicators may include anterior subcapsular cataracts, urinary disorders, and complete blood test results (mainly increased MCV and monocyte count).
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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Online-Ressource
- Language
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Englisch
- Bibliographic citation
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Glaucoma Prediction Models Based on Ocular and Systemic Findings ; volume:67 ; number:1 ; year:2023 ; pages:29-38 ; extent:10
Ophthalmic research ; 67, Heft 1 (2023), 29-38 (gesamt 10)
- Creator
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Landau Prat, Daphna
Kapelushnik, Noa
Arazi, Mattan
Zloto, Ofira
Leshno, Ari
Klang, Eyal
Sina, Sigal
Segev, Shlomo
Soudry, Shahar
Ben Simon, Guy J.
- DOI
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10.1159/000535879
- URN
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urn:nbn:de:101:1-2406060158057.915686070033
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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14.08.2025, 10:50 AM CEST
Data provider
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Landau Prat, Daphna
- Kapelushnik, Noa
- Arazi, Mattan
- Zloto, Ofira
- Leshno, Ari
- Klang, Eyal
- Sina, Sigal
- Segev, Shlomo
- Soudry, Shahar
- Ben Simon, Guy J.