Scleral burn and perforation following transscleral cyclophotocoagulation.

Purpose: This case report highlights scleral perforation as a complication of diode laser transscleral cyclophotocoagulation in the treatment of refractory primary open-angle glaucoma, as well as the management of this complication. Observations: A 78-year-old woman with primary open-angle glaucoma refractory to medication had transscleral cyclophotocoagulation performed in her left eye. During the procedure, it was noted that conjunctival burns and scleral perforation had occurred, at which point the procedure was aborted. Limited peritomy and patch graft with split-thickness donor cornea was done in the area of the scleral thinning and perforation. The patient had a good outcome with an intraocular pressure of 8 mm Hg, appropriate integration of the patch graft, and no significant conjunctival inflammation at the 2-month post-operative visit. Conclusions and importance: This patient, without any known risk factors for scleral thinning or necrosis, experienced conjunctival burn as well as scleral perforation during transscleral cyclophotocoagulation, underscoring this possible complication of the procedure. Additionally, split-thickness donor cornea was used to patch graft the area of scleral thinning and perforation, which is a method of managing this complication that had not been previously reported.

Application of Artificial Intelligence in the Early Detection of Retinopathy of Prematurity: Review of the Literature.

Retinopathy of prematurity (ROP) is a potentially blinding disease in premature neonates that requires a skilled workforce for diagnosis, monitoring, and treatment. Artificial intelligence is a valuable tool that clinicians employ to reduce the screening burden on ophthalmologists and neonatologists and improve the detection of treatment-requiring ROP. Neural networks such as convolutional neural networks and deep learning (DL) systems are used to calculate a vascular severity score (VSS), an important component of various risk models. These DL systems have been validated in various studies, which are reviewed here. Most importantly, we discuss a promising study that validated a DL system that could predict the development of ROP despite a lack of clinical evidence of disease on the first retinal examination. Additionally, there is promise in utilizing these systems through telemedicine in more rural and resource-limited areas. This review highlights the value of these DL systems in early ROP diagnosis.