Ophthalmology
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Randomized Controlled Trial
Efficacy, Safety, and Durability of Voretigene Neparvovec-rzyl in RPE65 Mutation-Associated Inherited Retinal Dystrophy: Results of Phase 1 and 3 Trials.
To report the durability of voretigene neparvovec-rzyl (VN) adeno-associated viral vector-based gene therapy for RPE65 mutation-associated inherited retinal dystrophy (IRD), including results of a phase 1 follow-on study at year 4 and phase 3 study at year 2. ⋯ After VN gene augmentation therapy, there was a favorable benefit-to-risk profile with similar improvement demonstrated in navigational ability and light sensitivity among 3 groups of subjects with RPE65 mutation-associated IRD, a degenerative disease that progresses to complete blindness. The safety profile is consistent with the administration procedure. These data suggest that this effect, which is nearly maximal by 30 days after VN administration, is durable for 4 years, with observation ongoing.
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Randomized Controlled Trial Multicenter Study
Postoperative Endothelial Cell Density Is Associated with Late Endothelial Graft Failure after Descemet Stripping Automated Endothelial Keratoplasty.
To determine whether preoperative endothelial cell density (ECD) and postoperative ECD after Descemet stripping automated endothelial keratoplasty (DSAEK) are associated with late endothelial graft failure (LEGF) in the Cornea Preservation Time Study (CPTS). ⋯ In eyes undergoing DSAEK, preoperative ECD is unrelated to LEGF, whereas lower ECD at 6 months is associated with LEGF. Early endothelial cell loss after DSAEK and intraoperative complications should be minimized to improve graft survival.
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With the current wide adoption of electronic health records (EHRs) by ophthalmologists, there are widespread concerns about the amount of time spent using the EHR. The goal of this study was to examine how the amount of time spent using EHRs as well as related documentation behaviors changed 1 decade after EHR adoption. ⋯ After 1 decade of use, providers spend more time using the EHR for an office visit, generate longer notes, and close the chart faster. These changes are likely to represent increased time and documentation pressure for providers. Electronic health record redesign and new documentation regulations may help to address these issues.
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Previous approaches using deep learning (DL) algorithms to classify glaucomatous damage on fundus photographs have been limited by the requirement for human labeling of a reference training set. We propose a new approach using quantitative spectral-domain (SD) OCT data to train a DL algorithm to quantify glaucomatous structural damage on optic disc photographs. ⋯ We introduced a novel DL approach to assess fundus photographs and provide quantitative information about the amount of neural damage that can be used to diagnose and stage glaucoma. In addition, training neural networks to predict SD OCT data objectively represents a new approach that overcomes limitations of human labeling and could be useful in other areas of ophthalmology.