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Abstract #128130 Published in IGR 25-3
Prediction of perimetric progression in ocular hypertension and open angle glaucoma based on corneal biomechanics
Martínez-Sánchez MI; Bolívar G; Dastiridou A; Castaño A; Bertoncini C; Alonso C; Escámez P; Teus MÁEuropean Journal of Ophthalmology 2025; 0: 11206721251340439
PURPOSE: To identify parameters that are significant risk predictors of visual field (VF) progression in patients with ocular hypertension (OHT) or early primary open-angle glaucoma (POAG), using Goldmann applanation tonometry intraocular pressure (IOP-GAT), ultrasound pachymetry and biomechanical indices measured with the Corvis ST and the Ocular Response Analyser (ORA) and create a prediction model. METHODS: A dataset of 65 eyes was analyzed. VF progression was determined using event analysis, the AGIS progression criteria, and experts' opinion. Progression was defined when 2 of the 3 criteria agreed on VF progression. The artificial intelligence training pipeline to predict the consolidated target consisted of an initial outlier removal process, feature selection, and training using the leave-one-out (LOO) cross-validation. Techniques based on decision trees with the XGBoost (Xtreme Gradient Boosting) algorithm were employed. RESULTS: The results reveal that the most accurate predictors were those registered at 1-month follow-up, predicting glaucomatous VF progression with an accuracy of 86.2%. The main variables involved in the prediction were HC dArc length, HC Deflection Time, and the HC Deflection Length 1 month after PG therapy. CONCLUSION: Using AI models, glaucomatous VF progression can be predicted with relatively high accuracy using Corvis ST parameters registered one month after initiating PG treatment. Highest concavity parameters after 1 month of treatment are associated with an increased risk of perimetric progression.
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