Israel Medical Association Journal

Background: Myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) is a rare autoimmune demyelinating disorder of the central nervous system. Optic neuritis (ON) is the most common clinical manifestation of MOGAD in adults. In 2023, new MOGAD diagnostic criteria were proposed, highlighting the importance of supplemental criteria when MOG-immunoglobulin G (IgG) titers are unavailable.

Objective: To investigate the applicability of the 2023 MOGAD criteria in patients diagnosed with MOGAD and treated before the availability of MOG-IgG titers.

Methods: We conducted a retrospective chart review of patients classified as MOGAD between 2010 and 2023 at Rabin Medical Center. Patient demographics as well as clinical and imaging data were collected, including visual acuity, expanded disability status score, core demyelinating events, antibody status, and brain and optic nerve magnetic resonance imaging data. Patients fulfilling the 2023 MOGAD criteria were reported as definite MOGAD.

Results: Fifteen patients met the 2023 MOGAD diagnostic criteria despite lack of MOG-IgG titer. The most common supplemental criterion meeting the 2023 MOGAD criteria was optic disc edema (n=12, 80%), followed by longitudinal optic nerve involvement (53%), bilateral ON (40%), and perineural optic sheath enhancement (33%).

Conclusions: All patients with a clinical diagnosis of MOG-ON in our cohort fulfilled the 2023 MOGAD criteria despite the lack of antibody titers. The 2023 MOGAD criteria can be reliably applied to Israeli cohorts, prior to availability of MOGAD IgG titers, with particular attention to additional supplemental criteria. Since the 2023 MOGAD criteria were published, MOGAD IgG titers have been added to routine testing at our facility.

Artificial intelligence in ophthalmology is used for automatic diagnosis, data analysis, and predicting responses to possible treatments. The potential challenges in the application and assimilation of artificial intelligence include technical challenges of the algorithms, the ability to explain the algorithm, and the ability to diagnose and manage the medical course of patients. Despite these challenges, artificial intelligence is expected to revolutionize the way ophthalmology will be practiced. In this review, we compiled recent reports on the use and application of deep learning in various fields of ophthalmology, potential challenges in clinical deployment, and future directions.

Background: The coronavirus disease-2019 (COVID-19) pandemic presented a major medical management challenge to ophthalmology departments throughout Israel.

Objectives: To examine the managerial challenges, actions taken, and insights of directors of ophthalmology departments in Israel during the COVID-19 pandemic.

Methods: We conducted a cross sectional survey of directors of ophthalmology departments during the COVID-19 pandemic while the Israeli population was quarantined.

Results: All 21 directors answered the survey. The majority of the COVID-19 admissions were located in the center of Israel (53%) and Jerusalem (30%). E-communication took a central role in coping with the pandemic with 80% of the directors satisfied with this form of communication; 75% reported a reduction in clinical and surgery volume of at least 25%, and 40% reported reallocations of manpower. Most of the medical staff used gloves, a face shield, disposable robe, and a mask with no uniformity across departments. Cross satisfaction was noted regarding a hospital’s ability to equip the departments. Lack of preparation for post-pandemic era was reported by all directors, but one (95%). Directors sought guidelines and uniformity regarding outpatient referral to the hospital (p = 0.035)

Conclusions: Guidelines via safe digital platforms aid in management decisions and uniformity across departments. Advanced preparation is needed to prevent adverse clinical outcomes and to maintain treatment continuum. Our results can be used to guide and help improve the preparedness of ophthalmology departments during COVID-19 and for future pandemics.