Background: Accurate measurement of retinal nerve fiber layer (RNFL) is now possible with the high resolution optical coherence tomography (OCT). Effect of refractive status of the eye on RNFL thickness may be relevant in the diagnosis of glaucoma and other optic nerve diseases.
Aim: To assess the RNFL thickness and compare its correlation with refractive status and axial length of the eye.
Material And Methods: Three hundred eyes of 150 patients were included in this study, who underwent RNFL analysis using TOPCON 3D OCT 2000. Analysis of variance has been used to find the significance of study parameters between the study groups.
Results: The study showed that refractive status/axial length affected the peripapillary RNFL thickness significantly.
Conclusion: The study suggests that the diagnostic accuracy of OCT may be improved by considering refractive status and axial length of the eye when RNFL is measured.
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http://dx.doi.org/10.7860/JCDR/2015/14112.6480 | DOI Listing |
Front Med (Lausanne)
December 2024
Research Unit Vision, Visual Impairments and Blindness, Department of Rehabilitation Sciences, TU Dortmund University, Dortmund, Germany.
Introduction: The increasing prevalence of myopia worldwide is problematic because myopia can result in severe secondary pathologies, and is associated with considerable financial burden. With plenty of prevalence data available for some regions, current data for Europe remain sparse. Yet, information on myopia prevalence and associations is essential for monitoring, preventive and interventive purposes.
View Article and Find Full Text PDFIndian J Ophthalmol
January 2025
Dr. Rajendra Prasad Centre for Ophthalmic Sciences, AIIMS, New Delhi, India.
Scleral-fixated intraocular lens (SFIOL) is a widely used technique for IOL implantation in patients where capsular support is insufficient. Most surgeons have shifted away from sutured to sutureless SFIOL techniques where haptics of a multifocal IOL are inserted in scleral tunnels/flaps. Large-scale publications have shown wide variation in the refractive status of eyes post-SFIOL even in the best of the hands.
View Article and Find Full Text PDFOphthalmic Physiol Opt
December 2024
Optometry and Vision Sciences Research Group, Aston University, Birmingham, UK.
Purpose: To propose a novel artificial intelligence (AI)-based virtual assistant trained on tabular clinical data that can provide decision-making support in primary eye care practice and optometry education programmes.
Method: Anonymised clinical data from 1125 complete optometric examinations (2250 eyes; 63% women, 37% men) were used to train different machine learning algorithm models to predict eye examination classification (refractive, binocular vision dysfunction, ocular disorder or any combination of these three options). After modelling, adjustment, mining and preprocessing (one-hot encoding and SMOTE techniques), 75 input (preliminary data, history, oculomotor test and ocular examinations) and three output (refractive, binocular vision status and eye disease) features were defined.
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