Japanese journal of ophthalmology · 2025
Role of perfusion-related metrics in visual field progression of primary open-angle and exfoliation glaucoma: a natural language processing approach.
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Akagi Ayumu, Narimoto Kaito, Ueda Kanta, Koizumi Noriko, Okumura Naoki, Tanito Masaki
Аннотация
PURPOSE: To investigate the association between vascular factors affecting optic nerve perfusion and glaucoma progression in a clinical setting with systematic monitoring of blood pressure and intraocular pressure (IOP).
STUDY DESIGN: Retrospective cohort study.
METHODS: This retrospective study analyzed 428 primary open-angle glaucoma (POAG; n=295) and exfoliation glaucoma (EXG; n=133) patients from Shimane University Hospital. We employed a validated Bidirectional Encoder Representations from Transformers (BERT)-based natural language processing system to extract clinical data from electronic medical records of 36,561 visits, including blood pressure measurements, IOP, and medication details across 216 clinical parameters. Mixed-effects regression models were employed to identify factors associated with visual field mean deviation (MD) and the rate of MD decline.
RESULTS: The cohort demonstrated consistent pressure management (median IOP: 13.0 mmHg; median systolic: 138.0 mmHg; median diastolic: 79.0 mmHg). Ocular perfusion pressure (OPP) showed no significant association with either visual field MD or the rate of MD decline. Significant predictors of worse visual field MD included age (coefficient: -0.28, 95% CI -0.33 to -0.23, p<0.001), history of filtration surgery (coefficient: -3.8, 95% CI -5.7 to -1.9, p<0.001), and number of glaucoma medications (coefficient: -0.19, 95% CI -0.35 to -0.030, p=0.020). Factors significantly associated with faster MD decline were age, initial MD severity, and medication burden.
CONCLUSIONS: In a clinical setting with systematic monitoring, OPP provided limited prognostic value for glaucoma progression, while traditional clinical factors were stronger predictors. Our BERT-based approach demonstrates how artificial intelligence (AI)-powered data extraction enables comprehensive analyses of clinical records, offering new insights for routine ophthalmological care.
STUDY DESIGN: Retrospective cohort study.
METHODS: This retrospective study analyzed 428 primary open-angle glaucoma (POAG; n=295) and exfoliation glaucoma (EXG; n=133) patients from Shimane University Hospital. We employed a validated Bidirectional Encoder Representations from Transformers (BERT)-based natural language processing system to extract clinical data from electronic medical records of 36,561 visits, including blood pressure measurements, IOP, and medication details across 216 clinical parameters. Mixed-effects regression models were employed to identify factors associated with visual field mean deviation (MD) and the rate of MD decline.
RESULTS: The cohort demonstrated consistent pressure management (median IOP: 13.0 mmHg; median systolic: 138.0 mmHg; median diastolic: 79.0 mmHg). Ocular perfusion pressure (OPP) showed no significant association with either visual field MD or the rate of MD decline. Significant predictors of worse visual field MD included age (coefficient: -0.28, 95% CI -0.33 to -0.23, p<0.001), history of filtration surgery (coefficient: -3.8, 95% CI -5.7 to -1.9, p<0.001), and number of glaucoma medications (coefficient: -0.19, 95% CI -0.35 to -0.030, p=0.020). Factors significantly associated with faster MD decline were age, initial MD severity, and medication burden.
CONCLUSIONS: In a clinical setting with systematic monitoring, OPP provided limited prognostic value for glaucoma progression, while traditional clinical factors were stronger predictors. Our BERT-based approach demonstrates how artificial intelligence (AI)-powered data extraction enables comprehensive analyses of clinical records, offering new insights for routine ophthalmological care.