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Scheimpflug-Based Corneal Biomechanical Analysis As A Predictor of Glaucoma in Eyes With High Myopia.
PURPOSE: To address if corneal biomechanical behavior has a predictive value for the presence of glaucomatous optical neuropathy in eyes with high myopia.
PATIENTS AND METHODS: This observational cross-sectional study included 209 eyes from 108 consecutive patients, divided into four groups: high myopia and primary open-angle glaucoma (POAG) - HMG, n = 53; high myopia without POAG - HMNG, n = 53; non-myopic with POAG - POAG, n = 50; non-myopic and non-POAG- NMNG, n = 53. Biomechanical assessment was made through a Scheimpflug-camera-based technology. Receiver operating characteristic curves were made for the discrimination between groups. Multivariable logistic regression models were performed to address the predictive value of corneal biomechanics for the presence of glaucoma.
RESULTS: Areas Under the Receiver Operating Characteristic (AUROCs) above 0.6 were found in 6 parameters applied to discriminate between HMG and HMNG and six parameters to discriminate between POAG and NMNG. The biomechanical models with the highest power of prediction for the presence of glaucoma included 5 parameters with an AUROC of 0.947 for eyes with high myopia and 6 parameters with an AUROC of 0.857 for non-myopic eyes. In the final model, including all eyes, and adjusted for the presence of high myopia, the highest power of prediction for the presence of glaucoma was achieved including eight biomechanical parameters, with an AUROC of 0.917.
CONCLUSION: Corneal biomechanics demonstrated differences in eyes with glaucoma and mainly in myopic eyes. A biomechanical model based on multivariable logistic regression analysis and adjusted for high myopia was built, with an overall probability of 91.7% for the correct prediction of glaucomatous damage.
PATIENTS AND METHODS: This observational cross-sectional study included 209 eyes from 108 consecutive patients, divided into four groups: high myopia and primary open-angle glaucoma (POAG) - HMG, n = 53; high myopia without POAG - HMNG, n = 53; non-myopic with POAG - POAG, n = 50; non-myopic and non-POAG- NMNG, n = 53. Biomechanical assessment was made through a Scheimpflug-camera-based technology. Receiver operating characteristic curves were made for the discrimination between groups. Multivariable logistic regression models were performed to address the predictive value of corneal biomechanics for the presence of glaucoma.
RESULTS: Areas Under the Receiver Operating Characteristic (AUROCs) above 0.6 were found in 6 parameters applied to discriminate between HMG and HMNG and six parameters to discriminate between POAG and NMNG. The biomechanical models with the highest power of prediction for the presence of glaucoma included 5 parameters with an AUROC of 0.947 for eyes with high myopia and 6 parameters with an AUROC of 0.857 for non-myopic eyes. In the final model, including all eyes, and adjusted for the presence of high myopia, the highest power of prediction for the presence of glaucoma was achieved including eight biomechanical parameters, with an AUROC of 0.917.
CONCLUSION: Corneal biomechanics demonstrated differences in eyes with glaucoma and mainly in myopic eyes. A biomechanical model based on multivariable logistic regression analysis and adjusted for high myopia was built, with an overall probability of 91.7% for the correct prediction of glaucomatous damage.
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