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Diabetic retinopathy (DR) is a leading cause of blindness in adults worldwide. Early detection and intervention can prevent blindness; however, many patients do not receive their recommended annual diabetic eye examinations, primarily owing to limited access. To evaluate the safety and accuracy of an artificial intelligence (AI) system (the EyeArt Automated DR Detection System, version 2.1.0) in detecting both more-than-mild diabetic retinopathy (mtmDR) and vision-threatening diabetic retinopathy (vtDR). A prospective multicenter cross-sectional diagnostic study was preregistered (NCT03112005) and conducted from April 17, 2017, to May 30, 2018. A total of 942 individuals aged 18 years or older who had diabetes gave consent to participate at 15 primary care and eye care facilities. Data analysis was performed from February 14 to July 10, 2019. Retinal imaging for the autonomous AI system and Early Treatment Diabetic Retinopathy Study (ETDRS) reference standard determination. Primary outcome measures included the sensitivity and specificity of the AI system in identifying participants' eyes with mtmDR and/or vtDR by 2-field undilated fundus photography vs a rigorous clinical reference standard comprising reading center grading of 4 wide-field dilated images using the ETDRS severity scale. Secondary outcome measures included the evaluation of imageability, dilated-if-needed analysis, enrichment correction analysis, worst-case imputation, and safety outcomes. Of 942 consenting individuals, 893 patients (1786 eyes) met the inclusion criteria and completed the study protocol. The population included 449 men (50.3%). Mean (SD) participant age was 53.9 (15.2) years (median, 56; range, 18-88 years), 655 were White (73.3%), and 206 had type 1 diabetes (23.1%). Sensitivity and specificity of the AI system were high in detecting mtmDR (sensitivity: 95.5%; 95% CI, 92.4%-98.5% and specificity: 85.0%; 95% CI, 82.6%-87.4%) and vtDR (sensitivity: 95.1%; 95% CI, 90.1%-100% and specificity: 89.0%; 95% CI, 87.0%-91.1%) without dilation. Imageability was high without dilation, with the AI system able to grade 87.4% (95% CI, 85.2%-89.6%) of the eyes with reading center grades. When eyes with ungradable results were dilated per the protocol, the imageability improved to 97.4% (95% CI, 96.4%-98.5%), with the sensitivity and specificity being similar. After correcting for enrichment, the mtmDR specificity increased to 87.8% (95% CI, 86.3%-89.5%) and the sensitivity remained similar; for vtDR, both sensitivity (97.0%; 95% CI, 91.2%-100%) and specificity (90.1%; 95% CI, 89.4%-91.5%) improved. This prospective multicenter cross-sectional diagnostic study noted safety and accuracy with use of the EyeArt Automated DR Detection System in detecting both mtmDR and, for the first time, vtDR, without physician assistance. These findings suggest that improved access to accurate, reliable diabetic eye examinations may increase adherence to recommended annual screenings and allow for accelerated referral of patients identified as having vtDR.

Young children's vision screening, as part of a preventative health care service, produces great value for developing regions. Besides yielding a high return on investment from forestalling surgeries using a low-cost intervention at a young age, it improves school performance and thus boosts future labor force quality. Leveraging low-skilled health care workers with smartphones and automated diagnosis to offer such programs can be a scalable model in resource-limited areas. This study aimed to develop and evaluate an effective, efficient, and comprehensive vision screening solution for school children in resource-limited areas. First, such an exam would need to cover the major risk factors of amblyopia and myopia, 2 major sources of vision impairment effectively preventable at a young age. Second, the solution must be integrated with digital patient record-keeping for long-term monitoring and popular statistical analysis. Last, it should utilize low-skilled technicians and only low-cost tools that are available in a typical school in developing regions, without compromising quality or efficiency. A workflow for the screening program was designed and a smartphone app was developed to implement it. In the standardized screening procedure, a young child went through the smartphone-based photoscreening in a dark room. The child held a smartphone in front of their forehead, displaying pre-entered personal information as a quick response code that duplexed as a reference of scale. In one 10-second procedure, the child's personal information and interpupillary distance, relative visual axis alignment, and refractive error ranges were measured and analyzed automatically using image processing and artificial intelligence algorithms. The child's risk for strabismus, myopia, and anisometropia was then derived and consultation given. A preliminary evaluation of the solution was conducted alongside yearly physical exams in Luoyang, Henan, People's Republic of China. It covered 20 students with suspected strabismus and 80 randomly selected students, aged evenly between 8 and 10. Each examinee took about 1 minute, and a streamlined workflow allowed 3 exams to run in parallel. The 1-shot and 2-shot measurement success rates were 87% and 100%, respectively. The sensitivity and specificity of strabismus detection were 0.80 and 0.98, respectively. The sensitivity and specificity of myopia detection were 0.83 and 1.00, respectively. The sensitivity and specificity of anisometropia detection were 0.80 and 1.00, respectively. The proposed vision screening program is effective, efficient, and scalable. Compared with previously published studies on utilizing a smartphone for an automated Hirschberg test and photorefraction screening, this comprehensive solution is optimized for practicality and robustness, and is thus better ready-to-deploy. Our evaluation validated the achievement of the program's design specifications.

The Influence of Age, Duration of Diabetes, Cataract, and Pupil Size on Image Quality in Digital Photographic Retinal Screening Peter Henry Scanlon , MRCP 1 , Chris Foy , MSC 2 , Raman Malhotra , FRCO, PHTH 3 and Stephen J. Aldington , DMS 4 1 Department of Ophthalmology, Cheltenham General Hospital, Cheltenham, U.K. 2 R&D Support Unit, Gloucester Hospitals National Health Service Trust, Gloucester, U.K. 3 Oxford Eye Hospital, Oxford, U.K. 4 Retinopathy Grading Centre, Imperial College, London, U.K. Address correspondence and reprint requests to Dr. Peter Scanlon, Gloucestershire Eye Unit, Cheltenham General Hospital, Sandford Road, Cheltenham, GL53 7AN, U.K. E-mail: peter.scanlon{at}glos.nhs.uk Abstract OBJECTIVE —To evaluate the effect of age, duration of diabetes, cataract, and pupil size on the image quality in digital photographic screening. RESEARCH DESIGN AND METHODS —Randomized groups of 3,650 patients had one-field, nonmydriatic, 45° digital retinal imaging photography before mydriatic two-field photography. A total of 1,549 patients were then examined by an experienced ophthalmologist. Outcome measures were ungradable image rates, age, duration of diabetes, detection of referable diabetic retinopathy, presence of early or obvious central cataract, pupil diameter, and iris color. RESULTS —The ungradable image rate for nonmydriatic photography was 19.7% (95% CI 18.4–21.0) and for mydriatic photography was 3.7% (3.1–4.3). The odds of having one eye ungradable increased by 2.6% (1.6–3.7) for each extra year since diagnosis for nonmydriatic, by 4.1% (2.7–5.7) for mydriatic photography irrespective of age, by 5.8% (5.0–6.7) for nonmydriatic, and by 8.4% (6.5–10.4) for mydriatic photography for every extra year of age, irrespective of years since diagnosis. Obvious central cataract was present in 57% of ungradable mydriatic photographs, early cataract in 21%, no cataract in 9%, and 13% had other pathologies. The pupil diameter in the ungradable eyes showed a significant trend ( P < 0.001) in the three groups (obvious cataract 4.434, early cataract 3.379, and no cataract 2.750). CONCLUSIONS —The strongest predictor of ungradable image rates, both for nonmydriatic and mydriatic digital photography, is the age of the person with diabetes. The most common cause of ungradable images was obvious central cataract. Footnotes A table elsewhere in this issue shows conventional and Système International (SI) units and conversion factors for many substances. Accepted June 23, 2005. Received February 9, 2005. DIABETES CARE

Uncorrected refractive error is the leading cause of vision impairment in children globally, and studies have demonstrated that spectacle correction addresses the large majority of childhood vision impairment. Furthermore, trial evidence illustrates the beneficial impact of spectacles on learning, with effect sizes exceeding that of other school health interventions. While it is established that good vision is important for learning and optimising childhood development and quality of life, many countries lack healthcare systems that provide vision screening or universal access to eyecare for all citizens. This review examined school vision screening across several regions/countries, focusing on conditions that should be targeted and the corresponding interventions. The range of international models, the status of global refractive service coverage and measures needed for improvement are discussed. Vision screening protocols need to effectively detect vision impairment, seamlessly connect with intervention services to deliver spectacles and signpost for future access to eyecare. Conditions which may not be treatable with spectacles alone, including amblyopia, strabismus and other ocular diseases, also warrant signposting for treatment. The vision community must unite to urge governments to invest in building service capacity; allocating the necessary resources and effectively developing public health systems to support vision screening and access to eyecare. Schools play a crucial role in enabling population-based vision screening and need to be supported with eyecare interventions and resources. This will ensure optimised approaches to correct avoidable vision loss and provide children with the educational and health outcomes they deserve.

BackgroundTo investigate the feasibility of using the Stopping Elderly Accidents, Deaths and Injuries (STEADI) Falls Risk Tool Kit during community-based eye health screenings to assess falls risk of participants enrolled in the Manhattan Vision Screening and Follow-Up Study (NYC-SIGHT).MethodsCross-sectional analysis of data from a 5-year prospective, cluster-randomised clinical trial conducted in affordable housing developments in New York City in adults age 40 years and older. Prescreening questions determined whether participants were at risk of falling. STEADI tests classified participants at low, moderate or high risk of falling. Multivariate logistic regression determined odds of falls risk of all enrolled participants.Results708 participants completed the eye health screening; 351 (49.6%) performed STEADI tests; mean age: 71.0 years (SD±11.3); 72.1% female; 53.6% Black, non-Hispanic, 37.6% Hispanic/Latino. Level of falls risk: 32 (9.1%) low, 188 (53.6%) moderate and 131 (37.3%) high. Individuals age >80 (OR 5.921, 95% CI (2.383 to 14.708), p=0.000), had blurry vision (OR 1.978, 95% CI (1.186 to 3.300), p=0.009), high blood pressure (OR 2.131, 95% CI (1.252 to 3.628), p=0.005), arthritis (OR 2.29876, 95% CI (1.362 to 3.875), p=0.002) or foot problems (OR 5.239, 95% CI (2.947 to 9.314), p=0.000) had significantly higher odds of falling, emergency department visits or hospitalisation due to falling.ConclusionThis study detected a significant amount of falls risk in an underserved population. The STEADI Falls Risk screening questions were easy for eye care providers to ask, were highly predictive of falls risk and may be adequate for referral to occupational health and/or physical therapy.

Background and Objectives: Visual impairment and reduced stereovision significantly impact the quality of life and increase fall risk in older adults. While standard clinical assessment of visual functions is essential in this population, its use is often limited by the need for specialized equipment and trained personnel. Tablet-based screening tools offer a practical alternative but require clinical validation. This study aimed to assess the agreement, reliability, and diagnostic performance of a tablet-based screening application (index methods) compared to established clinical reference methods for assessing visual acuity (VA) and stereovision (SV) in adults over 60 years. Materials and Methods: This prospective, non-blinded, cross-sectional, feasibility study included two cohorts: a test–retest group of 24 older adults assessed twice within 7 days, and a clinical cross-sectional group of 135 participants recruited from primary care practices. VA was measured using tablet-based Landolt C test and compared with an ETDRS-style chart, while stereovision was assessed using tablet-based static and dynamic random dot stereograms and compared with the TNO stereotest. Agreement and reliability were evaluated using Bland–Altman analysis, intraclass correlation coefficients (ICC), and receiver operating characteristic (ROC) curves. Results: The index VA method demonstrated good test–retest reliability (ICC = 0.79) with no significant difference between repeated measurements. In the clinical cross-sectional group, visual acuity measurements showed a small mean bias (0.022 logMAR) between the index and reference methods, which remained within clinically acceptable limits, particularly in the intermediate acuity range. For stereovision, the index SV tests showed high test–retest agreement. Using a TNO cutoff of 480 arcsec, the index SV method demonstrated good diagnostic accuracy (AUC 0.87 for static and 0.85 for dynamic stimuli) with high sensitivity for detecting impaired stereovision. Conclusions: The tablet-based index method provided reliable and clinically comparable results for VA and SV assessments in older adults, supporting its potential use as a screening tool in primary care and community-based settings.

Purpose The relationship between refractive error at age 1 and the risk of developing amblyopia or accommodative esotropia, and the protection offered by early glasses, is unknown. These are determined in the Early Glasses Study, a prospective, population-based, longitudinal, randomized controlled study. We report baseline findings. Methods Healthy children aged 12–18 months were recruited at Children’s Healthcare Centres (CHCs) and received an entry orthoptic examination followed by cycloplegic retinoscopy. Children with amblyopia, strabismus, ophthalmic disease or very high refractive error were excluded. Those exceeding the AAPOS 2003 Criteria (> + 3.5D spherical equivalent (SE), > 1.5D astigmatism, > 1.5D anisometropia) were randomized into wearing glasses or not, and are followed-up by research orthoptists. Other children are followed-up by regular vision screening at CHCs and visual acuity is measured in all children at age 4. Results Parents of 865 children were called, 123 were excluded. Of 742 children enrolled, 601 underwent the entry orthoptic examination at age 14.5 ± 1.7 months. Mean SE was + 1.73 ± 1.18D, astigmatism -0.70 ± 0.44D, anisometropia 0.21D (IQR: 0–0.25). Of 62 (10.3%) children exceeding the Criteria, 52 were randomized into wearing glasses or not. Of 539 other children, 522 are followed up at CHCs. In total, 31 were excluded: 2 had strabismus and amblyopia, 7 strabismus, 2 amblyopia suspect, 1 strabismus suspect, 1 squinting during sinusitis, 4 excessive refractive error, 9 myopia, 2 ptosis, 1 oculomotor apraxia, 1 Duane syndrome, 1 congenital nystagmus. Conclusion Prevalence of strabismus (10/601) was as expected, but prevalence of amblyopia (2/601) was low, suggesting that common amblyopia develops later than generally thought. Key messages What is known High refractive errors cause amblyopia, but no study has determined the exact relationship between the kind and size of refractive error at age 1 and the risk to develop amblyopia, and assessed the protective effect of glasses in a controlled, population-based, longitudinal study. What is new At baseline, 601 children received a full orthoptic examination followed by retinoscopy in cycloplegia at the age of 14.5 ± 1.7 months; 10.3% had high refractive error exceeding spherical equivalent > + 3.5D, > 1.5D astigmatism, > 1D oblique astigmatism or > 1.5D anisometropia. The prevalence of amblyopia was lower (0.3%) than expected, suggesting that most amblyopia develops after the first year of life. The prevalence of anisometropia, associated with amblyopia in older children, was low (0.8%).

Objectives Considering the escalating incidence of strabismus and its consequential jeopardy to binocular vision, there is an imperative demand for expeditious and precise screening methods. This study was to develop an artificial intelligence (AI) platform in the form of an applet that facilitates the screening and management of strabismus on any mobile device. Methods The Visual Transformer (VIT_16_224) was developed using primary gaze photos from two datasets covering different ages. The AI model was evaluated by 5-fold cross-validation set and tested on an independent test set. The diagnostic performance of the AI model was assessed by calculating the Accuracy, Precision, Specificity, Sensitivity, F1-Score and Area Under the Curve (AUC). Results A total of 6194 photos with corneal light-reflection (with 2938 Exotropia, 1415 Esotropia, 739 Vertical Deviation and 1562 Orthotropy) were included. In the internal validation set, the AI model achieved an Accuracy of 0.980, Precision of 0.941, Specificity of 0.979, Sensitivity of 0.958, F1-Score of 0.951 and AUC of 0.994. In the independent test set, the AI model achieved an Accuracy of 0.967, Precision of 0.980, Specificity of 0.970, Sensitivity of 0.960, F1-Score of 0.975 and AUC of 0.993. Conclusions Our study presents an advanced AI model for strabismus screening which integrates electronic archives for comprehensive patient histories. Additionally, it includes a patient-physician interaction module for streamlined communication. This innovative platform offers a complete solution for strabismus care, from screening to long-term follow-up, advancing ophthalmology through AI technology for improved patient outcomes and eye care quality.

Background To evaluate the stability and predictive ability of uncorrected visual acuity (UCVA), non-cycloplegic refraction (NCR), and axial length (AL) as indicators in non-cycloplegic school vision screening for myopia. Methods This retrospective cohort study is based on the Shanghai Child and Adolescent Large-scale Eye Study (SCALE). Participants included students who failed school screenings and were referred for follow-up cycloplegic refractions at eye hospitals within three months. We evaluated the differences in UCVA, spherical equivalent (SE), and AL between school screenings and hospital re-evaluations. Furthermore, we assessed the validity of using UCVA in combination with NCR as predictive metrics for myopia referral. Results Among the 8,492 children, 4,357 (51.3%) were boys, with a mean age of 8.26 years (SD = 2.77). AL was identified as a reliable myopia screening indicator across all age groups (ICC = 0.981; 95% CI: 0.978–0.984), outperforming UCVA (ICC = 0.791) and SE (ICC = 0.806). The estimated prevalence of myopia using UCVA and NCR was 76.10%, significantly higher than 58.37% observed with cycloplegic testing. Sensitivity was 96.93% and specificity was 53.13% (Youden index = 0.5). In preschoolers, myopia rates decreased from 50.17% before to 19.82% after cycloplegia, while school-aged children exhibited better consistency. Decision curve analysis showed that the full model incorporating AL did not significantly benefit school-aged children, but may offer greater net benefits for preschoolers. Conclusions AL should be integrated into screening programs for preschoolers. For school-aged children, the combination of UCVA and NCR suffices for myopia prediction, potentially eliminating the need for cycloplegia.

Background The assessment of impaired vision is included in falls prevention guidance for older adults, but implementation is variable. We conducted a scoping review to better understand current practice and inform future implementation research around vision assessments for older adults attending acute hospitals following a fall. We explored the extent and types of evidence, key concepts, methods, emerging topics and identified evidence gaps. Methods JBI methodology was followed. MEDLINE, AMED, EMBASE, PsychInfo, CINAHL and WebofScience were systematically searched for literature on the assessment of vision in older adults attending acute hospitals following a fall. Sources eligible for inclusion had a mean/median population age of 65 years or over, included patients presenting to an acute hospital setting following a fall and described vision assessments in these patients. Grey literature, conference abstracts and sources without a full text were excluded. Title, abstract and full-text screening were completed by two independent reviewers. Data extraction and charting of the data were performed by the primary author. Data analysis comprised descriptive statistics of study characteristics and content analysis of vision assessment methods used. Results We included 27 studies from 13 countries, between 1806 and 2024. Studies reported various vision assessment methods. Questions frequently asked in vision assessments included: presence of visual symptoms ( n  = 9), date of last eye test ( n  = 9) and previous ocular history ( n  = 5). The most common visual function assessed was distance visual acuity ( n  = 12). Six studies used standardised screening tools, including: the Stopping Elderly Accidents, Deaths & Injuries (STEADI) 12-question falls risk screening tool, a modified Kombinert Alvorlig Sansesvikt (Combined Serious Sensory Impairment) (KAS-Screen), procedures of the InterRAI-AC, the St Thomas’s Risk Assessment Tool In Falling elderly inpatients (STRATIFY), the Physiological Profile Assessment (PPA) and the Look Out! Bedside vision check. The most common post-screening interventions were: advising an eye test with an optometrist ( n  = 8), advising an ophthalmology referral ( n  = 7) and patient education ( n  = 6). Conclusions The literature on vision screening in this population was sparse and there was heterogeneity in current practices, highlighting the need for standardised screening protocols. More research is needed to evaluate vision screening services in this population and to explore implementation barriers.