Integration of smartphone technology and artificial intelligence for advanced ophthalmic care: A systematic review.

Background: The convergence of smartphone technology and artificial intelligence (AI) has revolutionized the landscape of ophthalmic care, offering unprecedented opportunities for diagnosis, monitoring, and management of ocular conditions. Nevertheless, there is a lack of systematic studies on discussing the integration of smartphone and AI in this field. Main text: This review includes 52 studies, and explores the integration of smartphones and AI in ophthalmology, delineating its collective impact on screening methodologies, disease detection, telemedicine initiatives, and patient management. The collective findings from the curated studies indicate promising performance of the smartphone-based AI screening for various ocular diseases which encompass major retinal diseases, glaucoma, cataract, visual impairment in children and ocular surface diseases. Moreover, the utilization of smartphone-based imaging modalities, coupled with AI algorithms, is able to provide timely, efficient and cost-effective screening for ocular pathologies. This modality can also facilitate patient self-monitoring, remote patient monitoring and enhancing accessibility to eye care services, particularly in underserved regions. Challenges involving data privacy, algorithm validation, regulatory frameworks and issues of trust are still need to be addressed. Furthermore, evaluation on real-world implementation is imperative as well, and real-world prospective studies are currently lacking. Conclusions: Smartphone ocular imaging merged with AI enables earlier, precise diagnoses, personalized treatments, and enhanced service accessibility in eye care. Collaboration is crucial to navigate ethical and data security challenges while responsibly leveraging these innovations, promising a potential revolution in care access and global eye health equity.

A systematic review of economic evaluation of artificial intelligence-based screening for eye diseases: From possibility to reality.

Artificial Intelligence (AI) has become a focus of research in the rapidly evolving field of ophthalmology. Nevertheless, there is a lack of systematic studies on the health economics of AI in this field. We examine studies from the PubMed, Google Scholar, and Web of Science databases that employed quantitative analysis, retrieved up to July 2023. Most of the studies indicate that AI leads to cost savings and improved efficiency in ophthalmology. On the other hand, some studies suggest that using AI in healthcare may raise costs for patients, especially when taking into account factors such as labor costs, infrastructure, and patient adherence. Future research should cover a wider range of ophthalmic diseases beyond common eye conditions. Moreover, conducting extensive health economic research, designed to collect data relevant to its own context, is imperative.

Three-Year Outcomes of the Paul Glaucoma Implant for Treatment of Glaucoma.

PRCIS: In our case series, the 3-year failure for Paul Glaucoma Implant (PGI) implantation was 14.6%. At 3 years postoperatively, there was a significant reduction in mean intraocular pressure (IOP) and the number of glaucoma medications used. OBJECTIVE: To determine the 3-year efficacy and safety of the PGI, a novel glaucoma tube shunt in patients with glaucoma. METHODS: Retrospective review of all patients who had undergone PGI implantation in a single tertiary institution in Singapore between May 1, 2017 and January 1, 2022. Data were extracted from electronic health records (Computerized Patient Support System 2 and Epic). The primary outcome measure was failure, defined as IOP >18 mm Hg or <6 mm Hg on 2 consecutive visits after 3 months, reoperation for IOP-related indication, explantation of implant, or loss of light perception vision. Complete success was defined as the absence of failure without medications at 36 months, and qualified success similarly, but with medications. Postoperative mean IOP, mean number of IOP-lowering medications used, and visual acuity were also assessed. RESULTS: Forty-eight eyes in 48 patients were identified. Thirty-one patients (64.6%) had primary open angle and angle closure glaucoma, and 18 (37.5%) had previous existing tube implants or trabeculectomy. At 3 years postoperatively, 7 cases (14.6%) fulfilled the criteria for failure and 36 (75%) met the criteria for complete success. The mean IOP at 36 months was 14.9 ± 4.11 mm Hg, from the mean preoperative IOP of 20.6 ± 6.13 mm Hg ( P < 0.001). The mean number of IOP-lowering medications used was reduced from 3.13 ± 0.959 preoperatively to 0.167 ± 0.476 at 36 months ( P < 0.001). The most common postoperative complication was hypotony (n = 17, 35.4%), of which the majority were self-limiting, followed by hyphema (n = 5, 10.4%) and tube exposure (n = 4, 8.3%). CONCLUSION: The PGI demonstrated sustained IOP reduction and a reduction of medication burden at 3 years postoperatively.

Six-Year Incidence and Risk Factors for Primary Open-Angle Glaucoma and Ocular Hypertension: The Singapore Epidemiology of Eye Diseases Study.

OBJECTIVE: To determine the incidence and risk factors for primary open-angle glaucoma (POAG) and ocular hypertension (OHT) in a multiethnic Asian population. DESIGN: Population-based cohort study. PARTICIPANTS: The Singapore Epidemiology of Eye Diseases study included 10 033 participants in the baseline examination between 2004 and 2011. Of those, 6762 (response rate = 78.8%) participated in the 6-year follow-up visit between 2011 and 2017. METHODS: Standardized examination and investigations were performed, including slit lamp biomicroscopy, intraocular pressure (IOP) measurement, pachymetry, gonioscopy, optic disc examination and static automated perimetry. Glaucoma was defined according to a combination of clinical evaluation, ocular imaging (fundus photo, visual field, and OCT) and criteria given by International Society of Geographical and Epidemiological Ophthalmology. OHT was defined on the basis of elevated IOP over the upper limit of normal; i.e., 20.4 mmHg, 21.5 mmHg, and 22.6 mmHg for the Chinese, Indian, and Malay cohort respectively, without glaucomatous optic disc change. MAIN OUTCOME MEASURES: Incidence of POAG, OHT, and OHT progression. RESULTS: The overall 6-year age-adjusted incidences of POAG and OHT were 1.31% (95% confidence interval [CI], 1.04-1.62) and 0.47% (95% CI, 0.30-0.70). The rate of progression of baseline OHT to POAG at 6 years was 5.32%. Primary open-angle glaucoma incidence was similar (1.37%) in Chinese and Indians and lower (0.80%) in Malays. Malays had higher incidence (0.79%) of OHT than Indians (0.38%) and Chinese (0.37%). Baseline parameters associated with higher risk of POAG were older age (per decade: odds ratio [OR], 1.90; 95% CI, 1.54-2.35; P < 0.001), higher baseline IOP (per mmHg: OR, 1.20; 95% CI, 1.12-1.29; P < 0.001) and longer axial length (per mm: OR, 1.22; 95% CI, 1.07-1.40, P = 0.004). CONCLUSION: Six-year incidence of POAG was 1.31% in a multiethnic Asian population. Older age, higher IOP, and longer axial length were associated with higher risk of POAG. These findings can help in future projections and guide public healthcare policy decisions for screening at-risk individuals. FINANCIAL DISCLOSURE(S): The authors have no proprietary or commercial interest in any materials discussed in this article.

How can we better evaluate paediatric progression of myopia and associated risk factors? Lessons from the COVID-19 pandemic: A systematic review.

PURPOSE: During the COVID-19 pandemic, home-based and remote learning-particularly using electronic devices-was rapidly pushed out. Increased near-work, screen time exposure and lack of outdoor time are risk factors that contribute to childhood myopia, but it is difficult to adopt recommendations from prior publications as a consistent limitation in the literature is the heterogeneity of research methodology. This review seeks to systematically evaluate how observational studies published during the pandemic have quantified and measured risk factors and myopia in school-going children and adolescents. METHODS: Three scientific databases (PubMed, CINAHL, Scopus) were systematically searched from March 2020 to April 2022. Findings from relevant studies were descriptively summarised in relation to the PICOS-based objective of the review. RESULTS: The final sample of 13 studies included research from six countries and comprised 1 411 908 children and adolescents. The majority of studies (N = 10; 76.9%) used spherical equivalent refraction (SER) of -0.5 dioptres or lower as a common definition of myopia. Most studies (77.8%) measuring screen time exposure found it higher during COVID-19 compared to pre-COVID, but only one study used objective measurement of screen time. The average critical appraisal score of the sample was only 66.1%, with a considerable number of studies failing to identify and adjust for potential confounders. CONCLUSION: Future studies should consider emergent objective and validated measures of risk factors, account for potential a priori confounders and covariates and ensure more representativeness in the sociodemographic makeup of their samples.

Assessment of angle closure disease in the age of artificial intelligence: A review.

Primary angle closure glaucoma is a visually debilitating disease that is under-detected worldwide. Many of the challenges in managing primary angle closure disease (PACD) are related to the lack of convenient and precise tools for clinic-based disease assessment and monitoring. Artificial intelligence (AI)- assisted tools to detect and assess PACD have proliferated in recent years with encouraging results. Machine learning (ML) algorithms that utilize clinical data have been developed to categorize angle closure eyes by disease mechanism. Other ML algorithms that utilize image data have demonstrated good performance in detecting angle closure. Nonetheless, deep learning (DL) algorithms trained directly on image data generally outperformed traditional ML algorithms in detecting PACD, were able to accurately differentiate between angle status (open, narrow, closed), and automated the measurement of quantitative parameters. However, more work is required to expand the capabilities of these AI algorithms and for deployment into real-world practice settings. This includes the need for real-world evaluation, establishing the use case for different algorithms, and evaluating the feasibility of deployment while considering other clinical, economic, social, and policy-related factors.

Minimally Invasive Glaucoma Surgery: Latest Developments and Future Challenges.

The development of minimally invasive glaucoma surgeries (MIGSs) was intended to provide safe and modestly efficacious modalities for early intervention of mild-to-moderate glaucoma, with minimal trauma and rapid recovery. They were mainly ab interno procedures that reduce intraocular pressure by facilitating the aqueous outflow by bypassing the trabecular meshwork resistance, reinforcing the uveoscleral flow via the supraciliary space, and reducing aqueous production by the ciliary body. While the cumulating evidence helps shape the role of the available MIGS, the exponential new development and advancement in this field has expanded the territory of MIGS. Apart from developing subconjunctival MIGS filtration devices (Xen gel stent and PRESERFLO MicroShunt), there is a tendency to revisit the "traditional" MIGS for alternative use and to modify the procedures with consideration of the fundamental aqueous outflow physiology. Combined MIGS has also been suggested, based on the theory that their different mechanisms may provide additive or synergistic effects. The advancement of laser procedures is also promising and could supplement unmet needs along the glaucoma treatment algorithm. This review examines the broad array of MIGS, updates the recent findings, discusses their potential alternative applications, and explores future challenges.

Teleophthalmology and retina: a review of current tools, pathways and services.

Telemedicine, the use of telecommunication and information technology to deliver healthcare remotely, has evolved beyond recognition since its inception in the 1970s. Advances in telecommunication infrastructure, the advent of the Internet, exponential growth in computing power and associated computer-aided diagnosis, and medical imaging developments have created an environment where telemedicine is more accessible and capable than ever before, particularly in the field of ophthalmology. Ever-increasing global demand for ophthalmic services due to population growth and ageing together with insufficient supply of ophthalmologists requires new models of healthcare provision integrating telemedicine to meet present day challenges, with the recent COVID-19 pandemic providing the catalyst for the widespread adoption and acceptance of teleophthalmology. In this review we discuss the history, present and future application of telemedicine within the field of ophthalmology, and specifically retinal disease. We consider the strengths and limitations of teleophthalmology, its role in screening, community and hospital management of retinal disease, patient and clinician attitudes, and barriers to its adoption.

Popular large language model chatbots' accuracy, comprehensiveness, and self-awareness in answering ocular symptom queries.

In light of growing interest in using emerging large language models (LLMs) for self-diagnosis, we systematically assessed the performance of ChatGPT-3.5, ChatGPT-4.0, and Google Bard in delivering proficient responses to 37 common inquiries regarding ocular symptoms. Responses were masked, randomly shuffled, and then graded by three consultant-level ophthalmologists for accuracy (poor, borderline, good) and comprehensiveness. Additionally, we evaluated the self-awareness capabilities (ability to self-check and self-correct) of the LLM-Chatbots. 89.2% of ChatGPT-4.0 responses were 'good'-rated, outperforming ChatGPT-3.5 (59.5%) and Google Bard (40.5%) significantly (all p < 0.001). All three LLM-Chatbots showed optimal mean comprehensiveness scores as well (ranging from 4.6 to 4.7 out of 5). However, they exhibited subpar to moderate self-awareness capabilities. Our study underscores the potential of ChatGPT-4.0 in delivering accurate and comprehensive responses to ocular symptom inquiries. Future rigorous validation of their performance is crucial to ensure their reliability and appropriateness for actual clinical use.

Correction: From 2 dimensions to 3rd dimension: Quantitative prediction of anterior chamber depth from anterior segment photographs via deep-learning.

[This corrects the article DOI: 10.1371/journal.pdig.0000193.].

Axial length elongation profiles from 3 to 6 years in an Asian paediatric population: the Growing Up in Singapore Towards Healthy Outcomes birth cohort study (GUSTO).

AIMS: To determine axial length (AL) elongation profiles in children aged 3-6 years in an Asian population. METHODS: Eligible subjects were recruited from the Growing Up in Singapore Towards Healthy Outcomes birth cohort. AL measurement was performed using IOLMaster (Carl Zeiss Meditec, Jena, Germany) at 3 and 6 years. Anthropometric measurements at birth, cycloplegic refraction at 3 and 6 years, questionnaires on the children's behavioural habits at 2 years and parental spherical equivalent refraction were performed. Multivariable linear regression model with generalised estimating equation was performed to determine factors associated with AL elongation. RESULTS: 273 eyes of 194 children were included. The mean AL increased from 21.72±0.59 mm at 3 years to 22.52±0.66 mm at 6 years (p<0.001). Myopic eyes at 6 years had greater AL elongation (1.02±0.34 mm) compared with emmetropic eyes (0.85±0.25 mm, p=0.008) and hyperopic eyes (0.74±0.16 mm, p<0.001). The 95th percentile limit of AL elongation was 1.59 mm in myopes, 1.34 mm in emmetropes and 1.00 mm in hyperopes. Greater birth weight (per 100 g, ß=0.010, p=0.02) was significantly associated with greater AL elongation from 3 to 6 years, while parental and other behavioural factors assessed at 2 years were not (all p≥0.08). CONCLUSION: In this preschool cohort, AL elongates at an average length of 0.80 mm from 3 to 6 years, with myopes demonstrating the greatest elongation. The differences in 95th percentile limits for AL elongation between myopes, emmetropes and hyperopes can be valuable information in identifying myopia development in preschool children.

Benchmarking large language models' performances for myopia care: a comparative analysis of ChatGPT-3.5, ChatGPT-4.0, and Google Bard.

BACKGROUND: Large language models (LLMs) are garnering wide interest due to their human-like and contextually relevant responses. However, LLMs' accuracy across specific medical domains has yet been thoroughly evaluated. Myopia is a frequent topic which patients and parents commonly seek information online. Our study evaluated the performance of three LLMs namely ChatGPT-3.5, ChatGPT-4.0, and Google Bard, in delivering accurate responses to common myopia-related queries. METHODS: We curated thirty-one commonly asked myopia care-related questions, which were categorised into six domains-pathogenesis, risk factors, clinical presentation, diagnosis, treatment and prevention, and prognosis. Each question was posed to the LLMs, and their responses were independently graded by three consultant-level paediatric ophthalmologists on a three-point accuracy scale (poor, borderline, good). A majority consensus approach was used to determine the final rating for each response. 'Good' rated responses were further evaluated for comprehensiveness on a five-point scale. Conversely, 'poor' rated responses were further prompted for self-correction and then re-evaluated for accuracy. FINDINGS: ChatGPT-4.0 demonstrated superior accuracy, with 80.6% of responses rated as 'good', compared to 61.3% in ChatGPT-3.5 and 54.8% in Google Bard (Pearson's chi-squared test, all p ≤ 0.009). All three LLM-Chatbots showed high mean comprehensiveness scores (Google Bard: 4.35; ChatGPT-4.0: 4.23; ChatGPT-3.5: 4.11, out of a maximum score of 5). All LLM-Chatbots also demonstrated substantial self-correction capabilities: 66.7% (2 in 3) of ChatGPT-4.0's, 40% (2 in 5) of ChatGPT-3.5's, and 60% (3 in 5) of Google Bard's responses improved after self-correction. The LLM-Chatbots performed consistently across domains, except for 'treatment and prevention'. However, ChatGPT-4.0 still performed superiorly in this domain, receiving 70% 'good' ratings, compared to 40% in ChatGPT-3.5 and 45% in Google Bard (Pearson's chi-squared test, all p ≤ 0.001). INTERPRETATION: Our findings underscore the potential of LLMs, particularly ChatGPT-4.0, for delivering accurate and comprehensive responses to myopia-related queries. Continuous strategies and evaluations to improve LLMs' accuracy remain crucial. FUNDING: Dr Yih-Chung Tham was supported by the National Medical Research Council of Singapore (NMRC/MOH/HCSAINV21nov-0001).

Proposal of a new slit-lamp shield for ophthalmic examination and assessment of its effectiveness using computational simulations / Avaliação da eficácia e proposta de um novo protetor de lâmpada de fenda durante exame oftálmico por meio de simulações computacionais

ABSTRACT Purpose: This study aimed to use computational models for simulating the movement of respiratory droplets when assessing the efficacy of standard slit-lamp shield versus a new shield designed for increased clinician comfort as well as adequate protection. Methods: Simulations were performed using the commercial software Star-CCM+. Respiratory droplets were assumed to be 100% water in volume fraction with particle diameter distribution represented by a geometric mean of 74.4 (±1.5 standard deviation) μm over a 4-min duration. The total mass of respiratory droplets expelled from patients' mouths and droplet accumulation on the manikin were measured under the following three conditions: with no slit-lamp shield, using the standard slit-lamp shield, and using our new proposed shield. Results: The total accumulated water droplet mass (kilogram) and percentage of expelled mass accumulated on the shield under the three aforementioned conditions were as follows: 5.84e-10 kg (28% of the total weight of particle emitted that settled on the manikin), 9.14e-13 kg (0.045%), and 3.19e-13 (0.015%), respectively. The standard shield could shield off 99.83% of the particles that would otherwise be deposited on the manikin, which is comparable to 99.95% for the proposed design. Conclusion: Slit-lamp shields are effective infection control tools against respiratory droplets. The proposed shield showed comparable effectiveness compared with conventional slit-lamp shields, but with potentially enhanced ergonomics for ophthalmologists during slit-lamp examinations.

RESUMO Introdução: Os oftalmologistas têm alto risco de contrair a doença do Coronavírus-19 devido à proximidade com os pacientes durante os exames com lâmpada de fenda. Usamos um modelo de computação para avaliar a eficácia das proteções para lâmpadas de fenda e propusemos uma nova proteção ergonomicamente projetada. Métodos: As simulações foram realizadas no software comercial Star-CCM +. Os aerossóis de gotículas foram considerados 100% de água em fração de volume com distribuição de diâmetro de partícula representada por uma média geométrica de 74,4 ± 1,5 (desvio padrão) μm ao longo de uma duração de quatro minutos. A massa total de gotículas de água acumulada no manequim e a massa expelida pela boca do paciente foram medidas em três condições diferentes: 1) Sem protetor de lâmpada de fenda, 2) com protetor padrão, 3) Com o novo protetor proposto. Resultados: A massa total acumulada das gotas de água (kg) e a porcentagem da massa expelida acumulada no escudo para cada uma das respectivas condições foram; 1) 5,84e-10 kg (28% do peso total da partícula emitida que assentou no manequim), 2) 9,14e-13 kg (0,045%), 3,19e-13 (0,015%). O escudo padrão foi capaz de proteger 99,83% das partículas que, de outra forma, teriam se depositado no manequim, o que é semelhante a 99,95% para o projeto proposto. Conclusão: Protetores com lâmpada de fenda são ferramentas eficazes de controle de infecção contra gotículas respiratórias. O protetor proposto mostrou eficácia comparável em comparação com os protetores de lâmpada de fenda convencionais, mas potencialmente oferece uma melhor ergonomia para oftalmologistas durante o exame de lâmpada de fenda.

Variability in Grading Diabetic Retinopathy Using Retinal Photography and Its Comparison with an Automated Deep Learning Diabetic Retinopathy Screening Software.

BACKGROUND: Diabetic retinopathy (DR) screening using colour retinal photographs is cost-effective and time-efficient. In real-world clinical settings, DR severity is frequently graded by individuals of different expertise levels. We aim to determine the agreement in DR severity grading between human graders of varying expertise and an automated deep learning DR screening software (ADLS). METHODS: Using the International Clinical DR Disease Severity Scale, two hundred macula-centred fundus photographs were graded by retinal specialists, ophthalmology residents, family medicine physicians, medical students, and the ADLS. Based on referral urgency, referral grading was divided into no referral, non-urgent referral, and urgent referral to an ophthalmologist. Inter-observer and intra-group variations were analysed using Gwet's agreement coefficient, and the performance of ADLS was evaluated using sensitivity and specificity. RESULTS: The agreement coefficient for inter-observer and intra-group variability ranged from fair to very good, and moderate to good, respectively. The ADLS showed a high area under curve of 0.879, 0.714, and 0.836 for non-referable DR, non-urgent referable DR, and urgent referable DR, respectively, with varying sensitivity and specificity values. CONCLUSION: Inter-observer and intra-group agreements among human graders vary widely, but ADLS is a reliable and reasonably sensitive tool for mass screening to detect referable DR and urgent referable DR.

From 2 dimensions to 3rd dimension: Quantitative prediction of anterior chamber depth from anterior segment photographs via deep-learning.

Anterior chamber depth (ACD) is a major risk factor of angle closure disease, and has been used in angle closure screening in various populations. However, ACD is measured from ocular biometer or anterior segment optical coherence tomography (AS-OCT), which are costly and may not be readily available in primary care and community settings. Thus, this proof-of-concept study aims to predict ACD from low-cost anterior segment photographs (ASPs) using deep-learning (DL). We included 2,311 pairs of ASPs and ACD measurements for algorithm development and validation, and 380 pairs for algorithm testing. We captured ASPs with a digital camera mounted on a slit-lamp biomicroscope. Anterior chamber depth was measured with ocular biometer (IOLMaster700 or Lenstar LS9000) in data used for algorithm development and validation, and with AS-OCT (Visante) in data used for testing. The DL algorithm was modified from the ResNet-50 architecture, and assessed using mean absolute error (MAE), coefficient-of-determination (R2), Bland-Altman plot and intraclass correlation coefficients (ICC). In validation, our algorithm predicted ACD with a MAE (standard deviation) of 0.18 (0.14) mm; R2 = 0.63. The MAE of predicted ACD was 0.18 (0.14) mm in eyes with open angles and 0.19 (0.14) mm in eyes with angle closure. The ICC between actual and predicted ACD measurements was 0.81 (95% CI 0.77, 0.84). In testing, our algorithm predicted ACD with a MAE of 0.23 (0.18) mm; R2 = 0.37. Saliency maps highlighted the pupil and its margin as the main structures used in ACD prediction. This study demonstrates the possibility of predicting ACD from ASPs via DL. This algorithm mimics an ocular biometer in making its prediction, and provides a foundation to predict other quantitative measurements that are relevant to angle closure screening.

Proposal of a new slit-lamp shield for ophthalmic examination and assessment of its effectiveness using computational simulations.

PURPOSE: This study aimed to use computational models for simulating the movement of respiratory droplets when assessing the efficacy of standard slit-lamp shield versus a new shield designed for increased clinician comfort as well as adequate protection. METHODS: Simulations were performed using the commercial software Star-CCM+. Respiratory droplets were assumed to be 100% water in volume fraction with particle diameter distribution represented by a geometric mean of 74.4 (±1.5 standard deviation) µm over a 4-min duration. The total mass of respiratory droplets expelled from patients' mouths and droplet accumulation on the manikin were measured under the following three conditions: with no slit-lamp shield, using the standard slit-lamp shield, and using our new proposed shield. RESULTS: The total accumulated water droplet mass (kilogram) and percentage of expelled mass accumulated on the shield under the three aforementioned conditions were as follows: 5.84e-10 kg (28% of the total weight of particle emitted that settled on the manikin), 9.14e-13 kg (0.045%), and 3.19e-13 (0.015%), respectively. The standard shield could shield off 99.83% of the particles that would otherwise be deposited on the manikin, which is comparable to 99.95% for the proposed design. Conclusion: Slit-lamp shields are effective infection control tools against respiratory droplets. The proposed shield showed comparable effectiveness compared with conventional slit-lamp shields, but with potentially enhanced ergonomics for ophthalmologists during slit-lamp examinations.

Mendelian Randomization Implicates Bidirectional Association between Myopia and Primary Open-Angle Glaucoma or Intraocular Pressure.

PURPOSE: Observational studies suggest that myopic eyes carry a greater risk of primary open-angle glaucoma (POAG); however, the evidence for this association is inconsistent. This may be the result of confounding factors that arise from myopia that complicate clinical tests for glaucoma. This study used Mendelian randomization (MR) analysis to determine genetic causal associations among myopia, glaucoma, and glaucoma-related traits that overcome the effects of external confounders. DESIGN: Bidirectional genetic associations between myopia and refractive spherical equivalent (RSE), POAG, and POAG endophenotypes were investigated. PARTICIPANTS: Data from the largest publicly available genetic banks (n = 216,257-542,934) were analyzed. METHODS: Multiple MR models and multivariate genomic structural modeling to identify significant mediators for the relationship between myopia and POAG. MAIN OUTCOME MEASURES: Genetic causal associations between myopia and POAG and POAG endophenotypes. RESULTS: We found consistent bidirectional genetic associations between myopia and POAG and between myopia and intraocular pressure (IOP) using multiple MR models at Bonferroni-corrected levels of significance. Intraocular pressure showed the most significant mediation effect on RSE and POAG (Sobel test, 0.13; 95% confidence interval, 0.09-0.17; P = 1.37 × 10-8). CONCLUSIONS: A strong bidirectional genetic causal link exists between myopia and POAG that is mediated mainly by IOP. Our findings suggest that IOP-lowering treatment for glaucoma may be beneficial in myopic eyes, despite the challenges of establishing a clear clinical diagnosis. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found after the references.

Use of anterior segment imaging and direct cyclopexy repair of cyclodialysis cleft.

We aim to describe different imaging modalities to localize cyclodialysis clefts and direct cyclopexy repair of cyclodialysis clefts. We reviewed the record of a patient with traumatic cyclodialysis cleft who underwent direct cyclopexy retrospectively. Preoperative and postoperative visual acuity and intraocular pressure (IOP) were recorded. Gonioscopy, ultrasound biomicroscopy (UBM) and 360° swept-source anterior segment optical coherence tomography (SS-ASOCT) were used to localize the cyclodialysis cleft. We concluded that UBM is the current gold standard imaging modality in localization of cyclodialysis clefts, and that SS-ASOCT is potentially useful as alternative imaging modality. Direct cyclopexy is an effective treatment for large cyclodialysis cleft with good IOP control and visual outcomes.

Efficacy of smartphone-based retinal photography by undergraduate students in screening and early diagnosing diabetic retinopathy.

BACKGROUND: To evaluate the efficacy of retinal photography obtained by undergraduate students using a smartphone-based device in screening and early diagnosing diabetic retinopathy (DR). METHODS: We carried out an open prospective study with ninety-nine diabetic patients (194 eyes), who were submitted to an ophthalmological examination in which undergraduate students registered images of the fundus using a smartphone-based device. At the same occasion, an experienced nurse captured fundus photographs from the same patients using a gold standard tabletop camera system (Canon CR-2 Digital Non-Mydriatic Retinal Camera), with a 45º field of view. Two distinct masked specialists evaluated both forms of imaging according to the presence or absence of sings of DR and its markers of severity. We later compared those reports to assess agreement between the two technologies. RESULTS: Concerning the presence or absence of DR, we found an agreement rate of 84.07% between reports obtained from images of the smartphone-based device and from the regular (tabletop) fundus camera; Kappa: 0.67; Sensitivity: 71.0% (Confidence Interval [CI]: 65.05-78.16%); Specificity: 94.06% (CI: 90.63-97.49%); Accuracy: 84.07%; Positive Predictive Value (PPV): 90.62%; Negative Predictive Value (NPV): 80.51%. As for the classification between proliferative diabetic retinopathy and non-proliferative diabetic retinopathy, we found an agreement of 90.00% between the reports; Kappa: 0.78; Sensitivity: 86.96%; (CI: 79.07-94.85%); Specificity: 91.49% (CI: 84.95-98.03%); Accuracy: 90.00%; PPV: 83.33%; NPV: 93.48%. Regarding the degree of classification of DR, we found an agreement rate of 69.23% between the reports; Kappa: 0.52. As relating to the presence or absence of hard macular exudates, we found an agreement of 84.07% between the reports; Kappa: 0.67; Sensitivity: 71.60% (CI: 65.05-78.16%); Specificity: 94.06% (CI: 90.63-97.49%); Accuracy: 84.07%; PPV: 90.62%; NPV: 80.51%. CONCLUSION: The smartphone-based device showed promising accuracy in the detection of DR (84.07%), making it a potential tool in the screening and early diagnosis of DR.

Six-Year Incidence and Risk Factors for Primary Angle-Closure Disease: The Singapore Epidemiology of Eye Diseases Study.

PURPOSE: To determine the incidence and risk factors of primary angle-closure disease (PACD) over 6 years in a multi-ethnic Asian population. DESIGN: Population-based, longitudinal study. PARTICIPANTS: The Singapore Epidemiology of Eye Diseases study is a population-based cohort study conducted among adults aged 40 years or more. The baseline examination was conducted between 2004 and 2010, and the 6-year follow-up visit was conducted between 2011 and 2017. Of 6762 participants who attended the follow-up examination, 5298 at risk for primary angle-closure glaucoma (PACG) and 5060 at risk for PACD were included for analyses. METHODS: Standardized examinations including slit-lamp biomicroscopy, indentation gonioscopy, intraocular pressure (IOP) measurement, and static automated perimetry were performed. In this study, PACD includes primary angle-closure suspect (PACS), primary angle-closure (PAC), and PACG. MAIN OUTCOME MEASURES: The 6-year PACD incidence was evaluated among an at-risk population excluding adults with baseline glaucoma, PACS, PAC, pseudophakia at baseline or follow-up, or laser peripheral iridotomy or iridectomy at baseline visit. Logistic regression analysis adjusting for age, gender, and ethnicity was performed to evaluate associations between PACD development and demographic or ocular characteristics. Forward selection based on the Quasi-likelihood Information Criterion was used in multivariable analysis to reduce potential multicollinearity. RESULTS: The 6-year age-adjusted PACD incidence was 3.50% (95% confidence interval [CI], 2.94-4.16). In multivariable analysis, increasing age per decade (odds ratio [OR], 1.35; 95% CI, 1.15-1.59), higher IOP (OR, 1.04; 95% CI, 1.00-1.08), and shallower anterior chamber depth (OR, 1.11; 95% CI, 1.08-1.14) at baseline were associated with higher odds of PACD, whereas late posterior subcapsular cataract (PSC) (OR, 0.60; 95% CI, 0.48-0.76) was associated with lower odds of PACD. The 6-year age-adjusted incidences of PACG, PAC, and PACS were 0.29% (95% CI, 0.14-0.55), 0.46% (95% CI, 0.29-0.75), and 2.54% (95% CI, 2.07-3.12), respectively. CONCLUSIONS: Our study showed that the 6-year incidence of PACD was 3.50%. Increasing age, higher IOP, and shallower anterior chamber were associated with a higher risk of incident PACD, whereas late PSC was associated with a lower odds of PACD. These findings can aid in future projections and formulation of health care policies for screening of at-risk individuals for timely intervention.