Big Data Analysis of Glaucoma Prevalence in Israel

Abstract

Précis: The prevalence of glaucoma in the adult population included in this study was 2.3%. Normal values of routine eye examinations are provided including age and sex variations. Purpose: To analyze the prevalence of glaucoma in a very large database. Methods: Retrospective analysis of medical records of patients examined at the Medical Survey Institute of a tertiary care university referral center between 2001-2020. An NLP algorithm identified patients with a diagnosis of glaucoma. Main outcome measures included the prevalence and age distribution of glaucoma. The secondary outcome measures included the prevalence and distribution of VA, IOP, and CDR. Results: Data were derived from 184,589 visits of 36,762 patients (mean age 52 y, 68% males). The NLP model was highly sensitive in identifying glaucoma, achieving an accuracy of 94.98% (AUC 93.85%), and 633 of 27517 patients (2.3%) were diagnosed as having glaucoma with increasing prevalence in older age. The mean VA was 20/21, IOP 14.4±2.84 mmHg, and CDR 0.28±0.16, higher in males. The VA decreased with age, while the IOP and CDR increased with age. Conclusions: The prevalence of glaucoma in the adult population included in this study was 2.3%. Normal values of routine eye examinations are provided including age and sex variations. We proved the validity and accuracy of the NLP model in identifying glaucoma.

Prevalence of common and rare ophthalmic findings in adults attending a medical survey institute

“…The retrieved data on the comprehensive ophthalmic examination findings included those of the anterior and posterior segments. The prevalence of glaucoma mentioned in the results section was extracted from the database using artificial intelligence analysis, as detailed in a previous study [ 7 ].…”