D’Souza, Haley S.

Purpose: To assess the prevalence, associated conditions, diagnostic and treatment modalities, and provider education regarding the diagnosis and management of keratoconus (KCN) in sub-Saharan Africa (SSA) based on the currently available body of literature. Methods: Peer-reviewed publications from any year and any language were included. The databases included Cochrane Database of Systematic Reviews, Embase, and Ovid. A separate search of African Journals Online was conducted using the same Medical Subject Heading (MeSH) terms as the database search. Additional publications were identified in the references during full-text extraction. The abstracts of all publications were evaluated by two reviewers. The full text was then examined by one reviewer for inclusion. A data extraction tool was used by a single reviewer to document the findings. Results: Sixty-two publications were included in data extraction. Fourteen countries in SSA were represented. Prevalence was reported in eight SSA countries and ranged from 0% to 2.8%. The highest prevalence of 1.2% was found in a cross-sectional study in Banjul, Gambia. Diagnosis in urban areas is often made using slit lamps, although some sites had access to keratometry and/or topography, whereas rural areas use penlight exams alone. Penetrating keratoplasty was reported as an available treatment in 14 manuscripts, glasses and hard contact lenses in 10, and corneal cross-linking in two. Publications discussing provider education reported a knowledge gap. Conclusions: There is a need for increased data on KCN in SSA to better inform public health policy to improve KCN patients’ access to care and quality of life.

ImportanceSpecialized ophthalmology terminology limits comprehension for nonophthalmology clinicians and professionals, hindering interdisciplinary communication and patient care. The clinical implementation of large language models (LLMs) into practice has to date been relatively unexplored.ObjectiveTo evaluate LLM–generated plain language summaries (PLSs) integrated into standard ophthalmology notes (SONs) in improving diagnostic understanding, satisfaction, and clarity.Design, Setting, and ParticipantsRandomized quality improvement study conducted from February 1, 2024, to May 31, 2024, including data from inpatient and outpatient encounters in a single tertiary academic center. Participants were nonophthalmology clinicians and professionals and ophthalmologists. The single inclusion criterion was any encounter note generated by an ophthalmologist during the study dates. Exclusion criteria were (1) lack of established nonophthalmology clinicians and professionals for outpatient encounters and (2) procedure-only patient encounters.InterventionAddition of LLM-generated plain language summaries to ophthalmology notes.Main Outcomes and MeasuresThe primary outcome was survey responses from nonophthalmology clinicians and professionals assessing understanding, satisfaction, and clarity of ophthalmology notes. Secondary outcomes were survey responses from ophthalmologists evaluating PLS in terms of clinical workflow and accuracy, objective measures of semantic quality, and safety analysis.ResultsA total of 362 (85%) nonophthalmology clinicians and professionals (33.0% response rate) preferred the PLS to SON. Demographic data on age, race and ethnicity, and sex were not collected. Nonophthalmology clinicians and professionals reported enhanced diagnostic understanding (percentage point increase, 9.0; 95% CI, 0.3-18.2; P = .01), increased note detail satisfaction (percentage point increase, 21.5; 95% CI, 11.4-31.5; P < .001), and improved explanation clarity (percentage point increase, 23.0; 95% CI, 12.0-33.1; P < .001) for notes containing a PLS. The addition of a PLS was associated with reduced comprehension gaps between clinicians who were comfortable and uncomfortable with ophthalmology terminology (from 26.1% [95% CI, 13.7%-38.6%; P < .001] to 14.4% [95% CI, 4.3%-24.6%; P > .06]). PLS semantic analysis found high meaning preservation (bidirectional encoder representations from transformers score mean F1 score: 0.85) with greater readability than SONs (Flesch Reading Ease: 51.8 vs 43.6; Flesch-Kincaid Grade Level: 10.7 vs 11.9). Ophthalmologists (n = 489; 84% response rate) reported high PLS accuracy (90% [320 of 355] a great deal) with minimal review time burden (94.9% [464 of 489] ≤1 minute). PLS error rate on ophthalmologist review was 26% (126 of 489). A total of 83.9% (104 of 126) of errors were deemed low risk for harm and none had a risk of severe harm or death.Conclusions and RelevanceIn this study, use of LLM-generated PLSs was associated with enhanced comprehension and satisfaction among nonophthalmology clinicians and professionals, which might aid interdisciplinary communication. Careful implementation and safety monitoring are recommended for clinical integration given the persistence of errors despite physician review.

Purpose of review Large language models (LLMs) are rapidly entering the landscape of medicine in areas from patient interaction to clinical decision-making. This review discusses the evolving role of LLMs in ophthalmology, focusing on their current applications and future potential in enhancing ophthalmic care. Recent findings LLMs in ophthalmology have demonstrated potential in improving patient communication and aiding preliminary diagnostics because of their ability to process complex language and generate human-like domain-specific interactions. However, some studies have shown potential for harm and there have been no prospective real-world studies evaluating the safety and efficacy of LLMs in practice. Summary While current applications are largely theoretical and require rigorous safety testing before implementation, LLMs exhibit promise in augmenting patient care quality and efficiency. Challenges such as data privacy and user acceptance must be overcome before LLMs can be fully integrated into clinical practice.

A 12-year-old female individual receives a diagnosis of SARS-CoV-2 and reports bilateral blurry vision, large blue paracentral scotomata, and a migraine without a scintillating scotoma. What would you do next?