Development and Evaluation of a Retrieval-Augmented Large Language Model Framework for Ophthalmology.

Importance: Although augmenting large language models (LLMs) with knowledge bases may improve medical domain-specific performance, practical methods are needed for local implementation of LLMs that address privacy concerns and enhance accessibility for health care professionals. Objective: To develop an accurate, cost-effective local implementation of an LLM to mitigate privacy concerns and support their practical deployment in health care settings. Design, Setting, and Participants: ChatZOC (Sun Yat-Sen University Zhongshan Ophthalmology Center), a retrieval-augmented LLM framework, was developed by enhancing a baseline LLM with a comprehensive ophthalmic dataset and evaluation framework (CODE), which includes over 30 000 pieces of ophthalmic knowledge. This LLM was benchmarked against 10 representative LLMs, including GPT-4 and GPT-3.5 Turbo (OpenAI), across 300 clinical questions in ophthalmology. The evaluation, involving a panel of medical experts and biomedical researchers, focused on accuracy, utility, and safety. A double-masked approach was used to try to minimize bias assessment across all models. The study used a comprehensive knowledge base derived from ophthalmic clinical practice, without directly involving clinical patients. Exposures: LLM response to clinical questions. Main Outcomes and Measures: Accuracy, utility, and safety of LLMs in responding to clinical questions. Results: The baseline model achieved a human ranking score of 0.48. The retrieval-augmented LLM had a score of 0.60, a difference of 0.12 (95% CI, 0.02-0.22; P = .02) from baseline and not different from GPT-4 with a score of 0.61 (difference = 0.01; 95% CI, -0.11 to 0.13; P = .89). For scientific consensus, the retrieval-augmented LLM was 84.0% compared with the baseline model of 46.5% (difference = 37.5%; 95% CI, 29.0%-46.0%; P < .001) and not different from GPT-4 with a value of 79.2% (difference = 4.8%; 95% CI, -0.3% to 10.0%; P = .06). Conclusions and Relevance: Results of this quality improvement study suggest that the integration of high-quality knowledge bases improved the LLM's performance in medical domains. This study highlights the transformative potential of augmented LLMs in clinical practice by providing reliable, safe, and practical clinical information. Further research is needed to explore the broader application of such frameworks in the real world.

Shaping school for childhood myopia: the association between floor area ratio of school environment and myopia in China.

AIM: To investigate the association of floor area ratio (FAR), an indicator of built environments, and myopia onset. METHODS: This prospective cohort study recruited 136 753 children aged 6-10 years from 108 schools in Shenzhen, China at baseline (2016-2017). Refractive power was measured with non-cycloplegic autorefraction over a 2-year follow-up period. FAR was objectively evaluated using geographical information system technology. Mixed-effects logistic regression models were constructed to examine the association of FAR with a 2-year cumulative incidence of myopia among individuals without baseline myopia; multiple linear regression model, with a 2-year cumulative incidence rate of myopia at each school. RESULTS: Of 101 624 non-myopic children (56.3% boys; mean (SE) age, 7.657±1.182 years) included in the study, 26 391 (26.0%) of them developed myopia after 2 years. In the individual-level analysis adjusting for demographic, socioeconomic and greenness factors, an IQR in FAR was associated with a decreased risk of 2-year myopia incidence (OR 0.898, 95% CI 0.866 to 0.932, p<0.001). Similar findings were observed in the analysis additionally adjusted for genetic and behavioural factors (OR 0.821, 95% CI 0.766 to 0.880, p<0.001). In the school-level, an IQR increase in FAR was found to be associated with a 2.0% reduction in the 2-year incidence rate of myopia (95% CI 1.3% to 2.6%, p<0.001). CONCLUSIONS: Exposure to higher FAR was associated with a decreased myopia incidence, providing insights into myopia prevention through school built environments in China.

Digital ray: enhancing cataractous fundus images using style transfer generative adversarial networks to improve retinopathy detection.

BACKGROUND/AIMS: The aim of this study was to develop and evaluate digital ray, based on preoperative and postoperative image pairs using style transfer generative adversarial networks (GANs), to enhance cataractous fundus images for improved retinopathy detection. METHODS: For eligible cataract patients, preoperative and postoperative colour fundus photographs (CFP) and ultra-wide field (UWF) images were captured. Then, both the original CycleGAN and a modified CycleGAN (C2ycleGAN) framework were adopted for image generation and quantitatively compared using Frechet Inception Distance (FID) and Kernel Inception Distance (KID). Additionally, CFP and UWF images from another cataract cohort were used to test model performances. Different panels of ophthalmologists evaluated the quality, authenticity and diagnostic efficacy of the generated images. RESULTS: A total of 959 CFP and 1009 UWF image pairs were included in model development. FID and KID indicated that images generated by C2ycleGAN presented significantly improved quality. Based on ophthalmologists' average ratings, the percentages of inadequate-quality images decreased from 32% to 18.8% for CFP, and from 18.7% to 14.7% for UWF. Only 24.8% and 13.8% of generated CFP and UWF images could be recognised as synthetic. The accuracy of retinopathy detection significantly increased from 78% to 91% for CFP and from 91% to 93% for UWF. For retinopathy subtype diagnosis, the accuracies also increased from 87%-94% to 91%-100% for CFP and from 87%-95% to 93%-97% for UWF. CONCLUSION: Digital ray could generate realistic postoperative CFP and UWF images with enhanced quality and accuracy for overall detection and subtype diagnosis of retinopathies, especially for CFP.\ TRIAL REGISTRATION NUMBER: This study was registered with ClinicalTrials.gov (NCT05491798).

Protocol for performing deep learning-based fundus fluorescein angiography image analysis with classification and segmentation tasks.

Fundus fluorescein angiography (FFA) examinations are widely used in the evaluation of fundus disease conditions to facilitate further treatment suggestions. Here, we present a protocol for performing deep learning-based FFA image analytics with classification and segmentation tasks. We describe steps for data preparation, model implementation, statistical analysis, and heatmap visualization. The protocol is applicable in Python using customized data and can achieve the whole process from diagnosis to treatment suggestion of ischemic retinal diseases. For complete details on the use and execution of this protocol, please refer to Zhao et al.1.

Postoperative myopic shift and visual acuity rehabilitation in patients with bilateral congenital cataracts.

Background: This study aimed to explore the postoperative myopic shift and its relationship to visual acuity rehabilitation in patients with bilateral congenital cataracts (CCs). Methods: Bilateral CC patients who underwent cataract extraction and primary intraocular lens implantations before 6 years old were included and divided into five groups according to surgical ages (<2, 2-3, 3-4, 4-5, and 5-6 years). The postoperative myopic shift rates, spherical equivalents (SEs), and the best corrected visual acuity (BCVA) were measured and analyzed. Results: A total of 1,137 refractive measurements from 234 patients were included, with a mean follow-up period of 34 months. The postoperative mean SEs at each follow-up in the five groups were linearly fitted with a mean R2 = 0.93 ± 0.03, which showed a downtrend of SE with age (linear regression). Among patients with a follow-up of 4 years, the mean postoperative myopic shift rate was 0.84, 0.81, 0.68, 0.24, and 0.28 diopters per year (D/y) in the five age groups (from young to old), respectively. The BCVA of those with a surgical age of <2 years at the 4-year visit was 0.26 (LogMAR), and the mean postoperative myopic shift rate was 0.84 D/y. For patients with a surgical age of 2-6 years, a poorer BCVA at the 4-year visit was found in those with higher postoperative myopic shift rates (r = 0.974, p = 0.026, Pearson's correlation test). Conclusion: Performing cataract surgery for patients before 2 years old and decreasing the postoperative myopic shift rates for those with a surgical age of 2-6 years may benefit visual acuity rehabilitation.

Cost-effectiveness and cost-utility of a digital technology-driven hierarchical healthcare screening pattern in China.

Utilization of digital technologies for cataract screening in primary care is a potential solution for addressing the dilemma between the growing aging population and unequally distributed resources. Here, we propose a digital technology-driven hierarchical screening (DH screening) pattern implemented in China to promote the equity and accessibility of healthcare. It consists of home-based mobile artificial intelligence (AI) screening, community-based AI diagnosis, and referral to hospitals. We utilize decision-analytic Markov models to evaluate the cost-effectiveness and cost-utility of different cataract screening strategies (no screening, telescreening, AI screening and DH screening). A simulated cohort of 100,000 individuals from age 50 is built through a total of 30 1-year Markov cycles. The primary outcomes are incremental cost-effectiveness ratio and incremental cost-utility ratio. The results show that DH screening dominates no screening, telescreening and AI screening in urban and rural China. Annual DH screening emerges as the most economically effective strategy with 341 (338 to 344) and 1326 (1312 to 1340) years of blindness avoided compared with telescreening, and 37 (35 to 39) and 140 (131 to 148) years compared with AI screening in urban and rural settings, respectively. The findings remain robust across all sensitivity analyses conducted. Here, we report that DH screening is cost-effective in urban and rural China, and the annual screening proves to be the most cost-effective option, providing an economic rationale for policymakers promoting public eye health in low- and middle-income countries.

Early Diagnosis of Syndromic Congenital Cataracts in a Large Cohort of Congenital Cataracts.

PURPOSE: To explore the factors related to the diagnosis yield of syndromic congenital cataracts and describe the phenotype-genotype correlation in congenital cataract patients. DESIGN: Prospective cohort study. METHODS: Setting: the participants from underwent clinical examinations between 2021 and 2022. Facial and anterior eye segment photographs, pre- and postoperative ocular parameters, and medical and family histories were recorded. Bioinformatics analysis was performed using whole-exome sequencing data. Statistical and correlation analyses were performed using the basic characteristics, deep phenotype, and genotype data. PARTICIPANTS: 115 patients with unrelated congenital cataract. INTERVENTIONS: performing clinical examinations, whole-exome sequencing, and bioinformatics analysis for all participants. MAIN OUTCOMES AND MEASURES: factors related to the genetic diagnosis yield of syndromic congenital cataracts. RESULTS: Bilaterally asymmetrical cataracts were identified to be associated with syndromic congenital cataracts. The overall genetic diagnostic yield in the cohort was 72.2%. In total, 34.8% of the probands were early diagnosed with various syndromes with the help of genetic information. A phenotype-genotype correlation was detected for some genes and deep phenotypes. CONCLUSIONS: We highlight the importance of screening syndromic diseases in the patients with asymmetrical congenital cataracts. Application of whole-exome sequencing helps provide early diagnosis and treatment for the patients with syndromic congenital cataracts. This study also achieved a high genetic diagnostic yield, expanded the genotypic spectrum, and found phenotype-genotype correlations. A comprehensive analysis of cataract symmetricity, family history, and deep phenotypes makes the genotype prediction of some congenital cataract patients possible.

Green Space Morphology and School Myopia in China.

Importance: China has experienced both rapid urbanization and major increases in myopia prevalence. Previous studies suggest that green space exposure reduces the risk of myopia, but the association between myopia risk and specific geometry and distribution characteristics of green space has yet to be explored. These must be understood to craft effective interventions to reduce myopia. Objective: To evaluate the associations between myopia and specific green space morphology using novel quantitative data from high-resolution satellite imaging. Design, Setting, and Participants: This prospective cohort study included students grades 1 to 4 (aged 6 to 9 years) in Shenzhen, China. Baseline data were collected in 2016-2017, and students were followed up in 2018-2019. Data were analyzed from September 2020 to January 2022. Exposures: Eight landscape metrics were calculated using land cover data from high-resolution Gaofen-2 satellite images to measure area, aggregation, and shape of green space. Main Outcome and Measures: The 2-year cumulative change in myopia prevalence at each school and incidence of myopia at the student level after 2 years were calculated as main outcomes. The associations between landscape metrics and school myopia were assessed, controlling for geographical, demographic, and socioeconomic factors. Principal component analyses were performed to further assess the joint effect of landscape metrics at the school and individual level. Results: A total of 138 735 students were assessed at baseline. Higher proportion, aggregation, and better connectivity of green space were correlated with slower increases in myopia prevalence. In the principal component regression, a 1-unit increase in the myopia-related green space morphology index (the first principal component) was negatively associated with a 1.7% (95% CI, -2.7 to -0.6) decrease in myopia prevalence change at the school level (P = .002). At the individual level, a 1-unit increase in myopia-related green space morphology index was associated with a 9.8% (95% CI, 4.1 to 15.1) reduction in the risk of incident myopia (P < .001), and the association remained after further adjustment for outdoor time, screen time, reading time, and parental myopia (adjusted odds ratio, 0.88; 95% CI, 0.80 to 0.97; P = .009). Conclusions and Relevance: Structure of green space was associated with a decreased relative risk of myopia, which may provide guidance for construction and renovation of schools. Since risk estimates only indicate correlations rather than causation, further interventional studies are needed to assess the effect on school myopia of urban planning and environmental designs, especially size and aggregation metrics of green space, on school myopia.