The increasing global prevalence of myopia presents a significant public health concern, and growing evidence has demonstrated that myopia is a major risk factor for the development of open-angle glaucoma. Therefore, timely detection and management of glaucoma in myopic patients are crucial; however, identifying the structural alterations of glaucoma in the optic nerve head (ONH) and retinal tissues of myopic eyes using standard diagnostic tools such as fundus photography, optical coherence tomography (OCT), and OCT angiography (OCTA) presents challenges. Additionally, myopia-related perimetric defects can be confounded with glaucoma-related defects.
View Article and Find Full Text PDFBackground: To evaluate the impact of testing frequency on the time required to detect statistically significant glaucoma progression for ganglion cell complex (GCC) with optical coherence tomography (OCT).
Materials And Methods: From multicentre glaucoma registries, 332 eyes of 201 glaucoma patients were enrolled over an average of 4.4 years.
Purpose: To evaluate RETFound, a foundation artificial intelligence model, using a diverse clinical research dataset to assess its accuracy in detecting glaucoma using optic disc photographs. The model's accuracy for glaucoma detection was evaluated across race, age, glaucoma severity, and various training cycles (epochs) and dataset sample sizes.
Design: Evaluation of a diagnostic technology.
Purpose: To evaluate the diagnostic accuracy of retinal nerve fiber layer thickness (RNFLT) by spectral-domain optical coherence tomography (OCT) in primary open-angle glaucoma (POAG) in eyes of African (AD) and European descent (ED).
Design: Comparative diagnostic accuracy analysis by race.
Participants: 379 healthy eyes (125 AD and 254 ED) and 442 glaucomatous eyes (226 AD and 216 ED) from the Diagnostic Innovations in Glaucoma Study and the African Descent and Glaucoma Evaluation Study.