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Purpose: To evaluate the incidence and severity of retinopathy of prematurity (ROP) amongst surviving triplets. Methods: Records of preterm babies born to mothers with triplet pregnancies were retrieved from our Indian twin city ROP study database between 1 Jan 2000 and 31 Dec 2020 and analyzed. Results: 253 surviving triplet babies born to 108 mothers were evaluated. 48 out of 108 (44%) mothers received treatment for infertility. Data was available and analyzed for 242 babies (484 eyes). Mean gestational age was 31.76 ± 3.74 weeks (26- 38 weeks). The mean birth weight was 1.44 ± 0.37 kg (0.57–2.76 kg). At the first screening, incomplete vascularization was noted in 67% (131 babies;322 eyes) of which ROP was diagnosed in 14% (28 babies; 56 eyes). Among them, only 18 babies (53%) were the smallest birth weight babies in each of the triplet sets. Treatment with laser or bevacizumab was performed in 14 babies (5.8%), one eye of one baby additionally needed vitreoretinal surgical intervention. Good anatomical outcomes in terms of regression of ROP without sequelae were achieved in all babies. Conclusion: The present study reveals low incidence and favorable outcomes of ROP in triplet pregnancies in a large cohort of babies from a middle-income country. Our cohort did not show any difference in the treatment-requiring ROP among the larger or smaller birth weight babies of the same gestational age. In multiple pregnancies, gestational age remains a critical factor for ROP development; however, this does not necessitate modifying screening or treatment criteria in such triplet pregnancies.

Abstract Introduction Physicians need an accurate understanding of diabetic retinopathy (DR) severity to optimally manage patients. The aim of this prospective study is to correlate the severity of macular and peripheral retinal vascular abnormalities seen on widefield (WF) optical coherence tomography angiography (OCTA) with DR grading based on WF fundus photography. Methods The study included 150 eyes from 82 patients with treatment-naïve DR. All patients were imaged with WF fundus photography and swept-source WF OCTA. Quantitative and qualitative analyses of the foveal avascular zone (FAZ) size and shape, and measurement of capillary nonperfusion (CNP) areas, were performed from the OCTA images. The mixed-effects model was used to compare the DR grading from WF photography with the vascular changes seen on WF-OCTA, and Bonferroni correction was applied to the gradings. Results The mean [± standard deviation (SD)] age of patients was 55.5 (± 9.4) years. The WF-OCTA showed that an increasing size of the FAZ (from 0.442 (± 0.059) µm to 0.933 (± 0.086) µm) correlated with increasing severity of the DR (as determined with WF photography). The deep capillary plexus, FAZ size, and CNP areas in eyes with proliferative diabetic retinopathy (PDR) differed from those with mild nonproliferative diabetic retinopathy (NPDR) (p

Abstract The editorial outlines an integrated approach to managing diabetic ocular complications, combining advanced scientific research with practical public health strategies to improve the prevention, diagnosis, and treatment of diabetic retinopathy and macular edema globally.

Purpose: To evaluate the feasibility and outcome of a real-time retinopathy of prematurity (ROP) telescreening strategy using videoconferencing in a community setting in India. Method: In a prospective study, trained allied ophthalmic personnel obtained the fundus images in the presence of the parents and local childcare providers. Analysis of images and parental counseling were done in real time by an ROP specialist located at a tertiary center using videoconferencing software. A subset of babies was also examined using bedside indirect ophthalmoscopy by an ROP care-trained ophthalmologist. The data were analyzed using descriptive statistics, sensitivity, specificity, positive and negative predictive values, and correlation coefficient. Results: Over 9 months, we examined 576 babies (1152 eyes) in six rural districts of India. The parents accepted the model as they recognized that a remotely located specialist was evaluating all images in real time. The strategy saved the travel time for ROP specialists by 477 h (47.7 working days) and for parents (47,406 h or 1975.25 days), along with the associated travel cost. In a subgroup analysis (100 babies, 200 eyes), the technology had a high sensitivity (97.2%) and negative predictivity value (92.7%). It showed substantial agreement (k = 0.708) with the bedside indirect ophthalmoscopy by ROP specialists with respect to the detection of treatment warranting ROP. Also, the strategy helped train the participants. Conclusion: Real-time ROP telescreening using videoconferencing is sensitive enough to detect treatment warranting ROPs and saves skilled workforce and time. The real-time audiovisual connection allows optimal supervision of imaging, provides excellent training opportunities, and connects ophthalmologists directly with the parents.

Abstract Purpose To study the role of artificial intelligence (AI) in developing diabetic macular edema (DME) management recommendations by creating and comparing responses to clinicians in hypothetical AI-generated case scenarios. The study also examined whether its joint recommendations followed national DME management guidelines. Methods The AI hypothetically generated 50 ocular case scenarios from 25 patients using keywords like age, gender, type, duration and control of diabetes, visual acuity, lens status, retinopathy stage, coexisting ocular and systemic co-morbidities, and DME-related retinal imaging findings. For DME and ocular co-morbidity management, we calculated inter-rater agreements (kappa analysis) separately for clinician responses, AI-platforms, and the “majority clinician response” (the maximum number of identical clinician responses) and “majority AI-platform” (the maximum number of identical AI responses). Treatment recommendations for various situations were compared to the Indian national guidelines. Results For DME management, clinicians (ĸ=0.6), AI platforms (ĸ=0.58), and the ‘majority clinician response’ and ‘majority AI response’ (ĸ=0.69) had moderate to substantial inter-rate agreement. The study showed fair to substantial agreement for ocular co-morbidity management between clinicians (ĸ=0.8), AI platforms (ĸ=0.36), and the ‘majority clinician response’ and ‘majority AI response’ (ĸ=0.49). Many of the current study’s recommendations and national clinical guidelines agreed and disagreed. When treating center-involving DME with very good visual acuity, lattice degeneration, renal disease, anaemia, and a recent history of cardiovascular disease, there were clear disagreements. Conclusion For the first time, this study recommends DME management using large language model-based generative AI. The study’s findings could guide in revising the global DME management guidelines.

PURPOSE: To evaluate the factors influencing the refractive outcomes following silicone oil tamponade (SOT) and silicone oil removal (SOR) in different lens statuses post-vitreoretinal surgery. DESIGN: Retrospective analysis of three different lens statuses. MATERIALS AND METHODS: This was a descriptive study that included 150 eyes of 147 patients who had undergone pars plana vitrectomy with SOT and SOR between January 2017 and June 2021. Demographic profile, spherical equivalent refraction (SER), and its association with clinical features were evaluated with SOT and post-SOR. RESULTS: The mean (±standard deviation [SD]) age was 47 ± 17.8 years, including all three groups. SER was represented in diopters (D). The mean ± SD refraction with SOT in phakic, pseudophakic, and aphakic was 4.28 ± 2.59 D, 2.94 ± 2.58 D, and 3.98 ± 4.82 D. The mean SER post-SOR in phakic, pseudophakic, and aphakic was −2.72 ± 2.03 D, −1.12 ± 1.41 D, and 8.22 ± 3.70 D. The diagnosis of rhegmatogenous retinal detachment (RRD) among 96 eyes (64%) is the common indicator to perform vitreoretinal (VR) surgery. A minority of subjects were managed with retinal lasers before VR surgery (14%). The macula was attached in 100 eyes (67.6%), the belt buckle was done in 37 eyes (24.7%), and the silicone oil viscosity with 1000 centistoke was chosen in 129 eyes (86%). CONCLUSION: SOT was used as a tamponade in VR surgeries irrespective of lens status. The significant predictor for post-SOR refraction in phakic and aphakic is post-SOT refraction. In pseudophakic, gender and diagnosis of RRD are the predictors of SOR refraction.

Abstract Purpose To study the role of artificial intelligence (AI) to identify key risk factors for diabetic retinopathy (DR) screening and develop recommendations based on clinician and large language model (LLM) based AI platform opinions for newly detected diabetes mellitus (DM) cases. Methods Five clinicians and three AI applications were given 20 AI-generated hypothetical case scenarios to assess DR screening timing. We calculated inter-rater agreements between clinicians, AI-platforms, and the “majority clinician response” (defined as the maximum number of identical responses provided by the clinicians) and “majority AI-platform” (defined as the maximum number of identical responses among the 3 distinct AI). Scoring was used to identify risk factors of different severity. Three, two, and one points were given to risk factors requiring screening immediately, within a year, and within five years, respectively. After calculating a cumulative screening score, categories were assigned. Results Clinicians, AI platforms, and the “majority clinician response” and “majority AI response” had fair inter-rater reliability (k value: 0.21–0.40). Uncontrolled DM and systemic co-morbidities required immediate screening, while family history of DM and a co-existing pregnancy required screening within a year. The absence of these risk factors required screening within 5 years of DM diagnosis. Screening scores in this study were between 0 and 10. Cases with screening scores of 0–2 needed screening within 5 years, 3–5 within 1 year, and 6–12 immediately. Conclusion Based on the findings of this study, AI could play a critical role in DR screening of newly diagnosed DM patients by developing a novel DR screening score. Future studies would be required to validate the DR screening score before it could be used as a reference in real-life clinical situations. Clinical trial registration Not applicable.

Background: This study aims to assess systemic risk factors in diabetes mellitus (DM) patients and predict diabetic retinopathy (DR) using a Random Forest (RF) classification model. Methods: We included DM patients presenting to the retina clinic for first-time DR screening. Data on age, gender, diabetes type, treatment history, DM control status, family history, pregnancy history, and systemic comorbidities were collected. DR and sight-threatening DR (STDR) were diagnosed via a dilated fundus examination. The dataset was split 80:20 into training and testing sets. The RF model was trained to detect DR and STDR separately, and its performance was evaluated using misclassification rates, sensitivity, and specificity. Results: Data from 1416 DM patients were analyzed. The RF model was trained on 1132 (80%) patients. The misclassification rates were 0% for DR and ~20% for STDR in the training set. External testing on 284 (20%) patients showed 100% accuracy, sensitivity, and specificity for DR detection. For STDR, the model achieved 76% (95% CI-70.7%–80.7%) accuracy, 53% (95% CI-39.2%–66.6%) sensitivity, and 80% (95% CI-74.6%–84.7%) specificity. Conclusions: The RF model effectively predicts DR in DM patients using systemic risk factors, potentially reducing unnecessary referrals for DR screening. However, further validation with diverse datasets is necessary to establish its reliability for clinical use.

Purpose: To report a big data analysis of risk and protective factors in patients with AMD, as well as report on the age-adjusted prevalence in a geriatric Indian cohort in a hospital setting. Methods: This retrospective, observational study of all patients older than 60 years of age. Multiple logistic regression was performed for the binary outcome and the presence of AMD. Variables analyzed include age, gender, socioeconomic status, occupation, urban-rural-metropolitan distribution, self-reported history of diabetes mellitus (DM), hypertension (HTN), or coronary artery disease (CAD), ocular comorbidities, history of cataract surgery, and presenting VA. Odds ratios (OR) and 99% confidence intervals were calculated. Results: Of the 608,171 patients over the age of 60 years who attended our clinics, 1.68% of subjects had a diagnosis of AMD (N = 10,217). Less than half (4,621 of 10,217 with AMD) of them were diagnosed to have dry AMD. Cataract, glaucoma, and diabetic retinopathy were associated with lower risk of AMD. Cataract surgery was associated with the higher risk of AMD (OR = 1.20; 99% CI 1.13-1.29). Smoking was not associated with AMD. Conclusion: Big data analysis from a hospital setting shows that the prevalence of AMD above the age of 60 years is low. More patients with wet AMD present for treatment compared to dry AMD. Smoking was not associated with AMD in the Indian population. Cataract surgery was associated with higher prevalence of AMD.

Objectives This study provides an estimate of the annual cost of blindness and moderate to severe visual impairment (MSVI) among people with diabetes aged 40 years and above in India in the year 2019.Design A cost of illness study.Setting India.Participants People with diabetes aged 40 years and above in India in the year 2019.Primary and secondary outcome measures Estimates are provided for the total costs of screening for most common vision-threatening eye conditions, treatment of these conditions, economic activity lost by these people and their family carers whose ability to work is affected, and loss of quality of life experienced by people with diabetes and blindness or MSVI.Results It is estimated that for people with diabetes aged 40 years or above, annual screening followed by eye examination where required would cost around 42.3 billion Indian rupees (INR) (4230 crores) per year; treating sight problems around 2.87 billion INR (287 crores) per year if 20% of those needing treatment receive it; and lost economic activity around 472 billion INR (47 200 crores). Moreover, 2.86 million (0.286 crores) quality-adjusted life years (QALYs) are lost annually due to blindness and MSVI. The estimate of lost production is highly sensitive to the proportion of people with MSVI able to work and how their output compares with that of a person with no visual impairment.Conclusions This is the first study to estimate the cost of blindness and MSVI for people aged 40 years and over with diabetes in India. The annual cost to the Indian economy is substantial. This cost will be expected to fall if a successful screening and treatment plan is introduced in India. Further work is suggested using more robust data, when available, to estimate the loss of productivity and loss of QALYs, as this would be worthwhile.

It is proposed to use Deep Convolution Neural Network (DCNN) which is a good classifier of natural images to learn speech spectrum images of sustained phonation to detect Parkinson’s Disease (PD) as an alternative to the existing feature-based machine learning method. It is shown that the proposed method yields very high accuracy without the need for separate feature computation stage. The speech spectrum representations proposed are Short Time Fourier Transform (STFT) spectrum of size Nx256 and Line Spectral Frequency (LSF) spectrum of size Nx16. LSF reflects the speech production mechanism and it is a novel idea to use LSF spectrum in DCNN to detect PD speech. The spectrum images look like random patterns and the performance is improved when using an additional deeper hidden layer of tampering pattern in the last stage of a fully connected layer. Using a standard PD-sustained phonation dataset the training accuracies achieved are 98.50% and 92.50% for STFT and LSF method, respectively. The validation accuracies achieved are 84.38% for STFT and 100% for LSF. The STFT method results in a sensitivity of 97.05%, a specificity of 88.63%, a precision of 86.84%, an F1-score of 91.66, a false positive rate (FPR) of 11.36%, and a false alarm rate of 12.82%. The LSF method results in a sensitivity 97.05%, a specificity of 95.45%, a precision of 94.28%, an F1-score of 95.65, an FPR of 4.50%, and a false alarm rate of 5.71%. The LSF based method performs better and the performance comparison with the state-of-the-art methods brings out the merits of the LSF spectrum image-based DCNN learning in PD detection using sustained phonation. [ABSTRACT FROM AUTHOR]

Purpose: To describe the clinical features and treatment outcomes in spontaneous uveal effusion syndrome (UES). Methods: A 10-year retrospective chart review of UES patients from a tertiary eye center was carried out. Optical coherence tomography (OCT), fundus fluorescein angiography, and ultrasound biomicroscopy (UBM) scans were performed. UES was managed based on presenting best-corrected visual acuity (BCVA), symptoms, and fundus findings. Patients with secondary causes of uveal effusion were excluded. Results: Twenty-five eyes of 16 patients were included. Of the 16 patients, 14 (88%) were male and 9 (56%) had bilateral disease. Fifteen of 25 affected eyes had nanophthalmos (axial length (AL) 20.5 mm. The presenting mean distance BCVA was 0.74 ± 0.64 logMAR (mean Snellen: 20/100). Eleven eyes had exudative retinal detachment, and 4 also had exudative choroidal detachment (CD). Choroidal thickness (CT) was increased in 11 eyes on B-scan ultrasonography, and the mean CT was 1.74 ± 0.38 mm. Sub-retinal fluid (SRF) and retinal folds were the most common OCT findings. UBM findings included shallow angles, peripheral CD, and supra-ciliary effusion. A combination of local and systemic corticosteroids was used to successfully treat 12 eyes, 6 needed surgery, and 7 were observed. Partial sclerectomy with anterior chamber maintainer-assisted SRF drainage was the favored surgery. The median period of follow-up was 6.5 months (0.1–76 months), and the mean distance BCVA at the last follow-up was 0.58 ± 0.42 logMAR (mean Snellen: 20/80). Conclusion: UES can be suitably managed both medically and surgically based on clinical presentation.

Purpose: To assess the feasibility of measuring patients' visual acuity (VA) in their homes by their caregivers. Methods: Patients consulting in a tertiary eye care institute were prospectively enrolled with informed consent. All underwent standard COMPlog distance VA testing. Patients and caregivers were oriented to test distance VA using the Peek Acuity app. The app was installed on the caregiver's or patient's smartphone. The patient's VA was measured by the caregiver in the clinic (baseline value) under supervision. After 1 week, the caregivers recorded the patient's VA with the Peek Acuity app at their home and reported the value in a telephone consultation. A questionnaire to assess the ease of using the app was administered at both the baseline visit and 1 week later. Results: A total of 100 patients (age group: 13 to 76 years) and 100 caregivers (age group: 17 to 65 years) participated. VA measurements with the Peek Acuity app were comparable with COMPlog (P > 0.1) both during the baseline and after 1-week measurement, regardless of the underlying ocular condition or educational level of the caregivers/patients. Most caregivers (95%) felt the app was easy to use. Conclusion: Though the Peek Acuity app was originally developed for health care workers to be used in field visits, we found that with proper orientation, the layperson can also use it. Such orientation can enable caregivers to effectively measure VA at home. Such a tool would enhance teleophthalmology consultations and can minimize the need for short follow-up visits.

Telerehabilitation is a viable option to provide continuum of rehabilitation intervention in situations like the ongoing pandemic. Presently, there is no policy guidelines to the minimum standard of telerehabilitation. This paper describes procedures for telerehabilitation for people with blindness and low vision from the evidence-based practices from a premier eye institute in South India. The suggested guidelines can help develop and replicate similar models of telerehabilitation to reach people in need in difficult situations like COVID 19 pandemic.

Background Maternal age is an essential determinant of obstetric and neonatal outcomes. This study aims to evaluate the impact of maternal age on these outcomes in primiparous women in Bihar. Material and methods: A retrospective community-based study was conducted on 50 primiparous women between November 2021 and July 2023 in Murho PHC, Madhepura, Bihar. Data were collected from medical records and included maternal age, obstetric outcomes (e.g., mode of delivery, gestational age at delivery, complications), and neonatal outcomes (e.g., birth weight, Apgar scores, neonatal complications). The participants were categorized into two groups: younger mothers (≤25 years) and older mothers (>25 years). Statistical analyses were performed to compare outcomes between these groups. Results: The study included 30 younger mothers and 20 older mothers. The average gestational age at delivery was 39 weeks in younger mothers and 38 weeks in older mothers. The rate of cesarean deliveries was higher in older mothers (40%) compared to younger mothers (20%). Preterm birth rates were 10% in younger mothers and 15% in older mothers. Neonatal complications, such as low birth weight and low Apgar scores, were more prevalent in infants born to older mothers. The average birth weight was 3.2 kg for younger mothers and 2.9 kg for older mothers. Conclusion: Maternal age significantly impacts obstetric and neonatal outcomes in primiparous women. Older mothers are more likely to experience adverse outcomes, including higher rates of cesarean delivery and neonatal complications. These findings underscore the importance of targeted prenatal care for older primiparous women to mitigate potential risks. [ABSTRACT FROM AUTHOR]

Abstract Gut bacterial microbiome dysbiosis in type 2 Diabetes Mellitus (T2DM) has been reported, but such an association with Diabetic Retinopathy (DR) is not known. We explored possible link between gut bacterial microbiome dysbiosis and DR. Using fecal samples of healthy controls (HC) and people with T2DM with/without DR, gut bacterial communities were analysed using 16S rRNA gene sequencing and data analysed using QIIME and R software. Dysbiosis in the gut microbiomes, at phyla and genera level, was observed in people with T2DM and DR compared to HC. People with DR exhibited greater discrimination from HC. Microbiomes of people with T2DM and DR were also significantly different. Both DM and DR microbiomes showed a decrease in anti-inflammatory, probiotic and other bacteria that could be pathogenic, compared to HC, and the observed change was more pronounced in people with DR. This is the first report demonstrating dysbiosis in the gut microbiome (alteration in the diversity and abundance at the phyla and genera level) in people with DR compared to HC. Such studies would help in developing novel and targeted therapies to improve treatment of DR.

Purpose: The objective of this study was to identify and validate smartphone-based visual acuity (VA) apps that can be used in a teleophthalmology portal. Methods: The study was conducted in three phases: A survey to investigate if the SmartOptometry App was easy to download, understand and test (phase I), an in-clinic comparison of VA measured in a random testing order with four tools namely COMPlog, Reduced Snellen near vision, Peek Acuity (Distance VA) and SmartOptometry (Near VA) (phase II) and a repeatability study on these 4 tools by measuring VA again (phase III). The study recruited the employees of our institute and adhered to the strict COVID-19 protocols of testing. Results: Phase I Survey (n = 40) showed 90% of participants used android phones, 60% reported that instructions were clear, and all users were able to self-assess their near VA with SmartOptometry App. Phase II (n = 68) revealed that Peek Acuity was comparable to COMPlog VA (P = 0.31), however SmartOptometry was statistically significantly different (within 2 log MAR lines) from Reduced Snellen near vision test, particularly for young (n = 44, P = 0.004) and emmetropic (n = 16, P = 0.04) participants. All the 4 tests were found to be repeatable in phase III (n = 10) with a coefficient of repeatability ≤0.14. Conclusion: Smartphone-based apps were easy to download and can be used for checking patient's distance and near visual acuity. An effect of age and refractive error should be considered when interpreting the results. Further studies with real-time patients are required to identify potential benefits and challenges to solve.

Neovascular glaucoma (NVG) is a sight-threatening secondary glaucoma characterized by appearance of new vessels over the iris and proliferation of fibrovascular tissue in the anterior chamber angle. Retinal ischemia is the common driving factor and common causes are central retinal vein occlusion, proliferative diabetic retinopathy, and ocular ischemic syndrome. The current rise in the prevalence of NVG is partly related to increase in people with diabetes. A high index of suspicion and a thorough anterior segment evaluation to identify the early new vessels on the iris surface or angle are essential for early diagnosis of NVG. With newer imaging modalities such as the optical coherence tomography angiography and newer treatment options such as the anti-vascular endothelial growth factor, it is possible to detect retinal ischemia early, tailor appropriate treatment, monitor disease progression, and treatment response. The management strategies are aimed at reducing the posterior segment ischemia, reduce the neovascular drive, and control the elevated intraocular pressure. This review summarizes the causes, pathogenesis, and differential diagnoses of NVG, and the management guidelines. We also propose a treatment algorithm of neovascular glaucoma.

Purpose: The present study's objectives are 1) to describe a novel model of Diabetic Retinopathy Capacity Building (DRCB) for optometrists in the detection of diabetes-related retinal pathology in India and 2) to assess the outcomes of this model by comparing the ability of optometrists to detect these diseases using retinal photographs, vis-à-vis, a specialist ophthalmologist. Methods: The DRCB model for optometrists conducted between August 2016 and August 2018 included training, certification in the screening, and referral guidelines for Diabetic Retinopathy (DR) and hospital-and community-based service delivery. Training included a 7-month long fellowship in DR and mentored participation as cofacilitators in 1-day orientation workshops on DR screening guidelines across India. The sensitivity and specificity of study optometrists in screening for DR by fundus photography were compared to a retina specialist before certification. Results: A total of eight optometrists successfully completed their DR fellowship in the project duration of 24 months. The sensitivity and specificity of detection of any DR were 95 and 79%, any Diabetic macular edema (DME) was 80 and 86%. The sensitivity and specificity of detection of sight threatening DR were 88 and 90% and DME was 72% and 92% respectively. Seven workshops were cofacilitated by study optometrists training 870 optometrists in DR screening guidelines across India. Conclusion: The present DRCB model results advocate for an optometry coordinated DR screening in India. Lessons learnt from this model can be useful in designing community-based task sharing initiatives for optometrists in DR screening.

Purpose: The aim of this study was to report visual and anatomical outcomes following treatment for diabetic macular edema (DME) in clinical practice in India. Methods: Retrospective chart review of patients with DME who were initiated on treatment and followed up for at least 1 year at 9 tertiary eye care centers during 2016–2017 was performed. Data on demographics, systemic illnesses, visual acuity and anatomical characteristics of DME, treatment history were collated and analyzed for change in visual acuity level and central macular thickness at 1 year. Results: A total 1853 patients were diagnosed with treatable DME during study period, 1315 patients were treated and 556 patients (1019 eyes) followed up at one year. Although patients achieved significantly better anatomical outcome (central macular thickness of

Purpose: Intraocular infection in patients with COVID-19 could be different in the presence of treatment with systemic corticosteroid and immunosuppressive agents. We describe the epidemiology and microbiological profile of intraocular infection in COVID-19 patients after their release from the hospital. Methods: We analyzed the clinical and microbiological data of laboratory-confirmed COVID-19 patients from April 2020 to January 2021 presenting with features of endogenous endophthalmitis within 12 weeks of their discharge from the hospital in two neighboring states in South India. The data included demography, systemic comorbidities, COVID-19 treatment details, time interval to visual symptoms, the microbiology of systemic and ocular findings, ophthalmic management, and outcomes. Results: The mean age of 24 patients (33 eyes) was 53.6 ± 13.5 (range: 5–72) years; 17 (70.83%) patients were male. Twenty-two (91.6%) patients had systemic comorbidities, and the median period of hospitalization for COVID-19 treatment was 14.5 ± 0.7 (range: 7–63) days. Infection was bilateral in nine patients. COVID-19 treatment included broad-spectrum systemic antibiotics (all), antiviral drugs (22, 91.66% of patients), systemic corticosteroid (21, 87.5% of patients), supplemental oxygen (18, 75% of patients), low molecular weight heparin (17, 70.8% of patients), admission in intensive care units (16, 66.6% of patients), and interleukin-6 inhibitor (tocilizumab) (14, 58.3% of patients). Five (20.8%) patients died of COVID-19-related complications during treatment for endophthalmitis; one eye progressed to pan ophthalmitis and orbital cellulitis; eight eyes regained vision >20/400. Fourteen of 19 (73.7%) vitreous biopsies were microbiologically positive (culture, PCR, and microscopy), and the majority (11 patients, 78.5%) were fungi. Conclusion: Intraocular infection in COVID-19 patients is predominantly caused by fungi. We suggest a routine eye examination be included as a standard of care of COVID-19.

Summary: Background: We undertook a Grand Challenges in Global Eye Health prioritisation exercise to identify the key issues that must be addressed to improve eye health in the context of an ageing population, to eliminate persistent inequities in health-care access, and to mitigate widespread resource limitations. Methods: Drawing on methods used in previous Grand Challenges studies, we used a multi-step recruitment strategy to assemble a diverse panel of individuals from a range of disciplines relevant to global eye health from all regions globally to participate in a three-round, online, Delphi-like, prioritisation process to nominate and rank challenges in global eye health. Through this process, we developed both global and regional priority lists. Findings: Between Sept 1 and Dec 12, 2019, 470 individuals complete round 1 of the process, of whom 336 completed all three rounds (round 2 between Feb 26 and March 18, 2020, and round 3 between April 2 and April 25, 2020) 156 (46%) of 336 were women, 180 (54%) were men. The proportion of participants who worked in each region ranged from 104 (31%) in sub-Saharan Africa to 21 (6%) in central Europe, eastern Europe, and in central Asia. Of 85 unique challenges identified after round 1, 16 challenges were prioritised at the global level; six focused on detection and treatment of conditions (cataract, refractive error, glaucoma, diabetic retinopathy, services for children and screening for early detection), two focused on addressing shortages in human resource capacity, five on other health service and policy factors (including strengthening policies, integration, health information systems, and budget allocation), and three on improving access to care and promoting equity. Interpretation: This list of Grand Challenges serves as a starting point for immediate action by funders to guide investment in research and innovation in eye health. It challenges researchers, clinicians, and policy makers to build collaborations to address specific challenges. Funding: The Queen Elizabeth Diamond Jubilee Trust, Moorfields Eye Charity, National Institute for Health Research Moorfields Biomedical Research Centre, Wellcome Trust, Sightsavers, The Fred Hollows Foundation, The Seva Foundation, British Council for the Prevention of Blindness, and Christian Blind Mission. Translations: For the French, Spanish, Chinese, Portuguese, Arabic and Persian translations of the abstract see Supplementary Materials section.

Objective. To describe the clinical indications and the impact of implementation of specific teleophthalmology referral guidelines in a large rural village vision centre network in India. Methods. This cross-sectional vision centre-based study included 1,016,284 patients presenting between January 2017 and March 2020. Patients who were referred for a teleophthalmology opinion were included as cases. The data were collected using the eyeSmart EMR app on a smart tablet. A training intervention was done to reinforce the implementation of targeted teleophthalmology referral guidelines. Results. Overall, 63,703 (6.3%) patients were referred for a teleophthalmology opinion and were included for analysis. The median age was 41 (IQR: 26-59) years, and adults (88.4%) were commonly referred for a consult. The two most common age groups were between 31-40 years (17.4%) and 21-30 years (16.3%), and the majority of patients were male (59.1%). The most common clinical indication was cornea and anterior segment disorders (71.05%). The most common queries for teleophthalmology referral before versus after the reinforcement of implementation of guidelines were red eye (33.4% vs. 45.6%) followed by cataract (21.2% vs. 8.1%). There was an increase in the red eye (