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Artificial intelligence (AI) and digital innovation are transforming healthcare. Technologies such as machine learning in image analysis, natural language processing in medical chatbots and electronic medical record extraction have the potential to improve screening, diagnostics and prognostication, leading to precision medicine and preventive health. However, it is crucial to ensure that AI research is conducted with scientific rigour to facilitate clinical implementation. Therefore, reporting guidelines have been developed to standardise and streamline the development and validation of AI technologies in health. This commentary proposes a structured approach to utilise these reporting guidelines for the translation of promising AI techniques from research and development into clinical translation, and eventual widespread implementation from bench to bedside. Keywords: Artificial intelligence, clinical translation, digital innovation, guidelines

The application of artificial intelligence (AI) in medicine and ophthalmology has experienced exponential breakthroughs in recent years in diagnosis, prognosis, and aiding clinical decision-making. The use of digital data has also heralded the need for privacy-preserving technology to protect patient confidentiality and to guard against threats such as adversarial attacks. Hence, this review aims to outline novel AI-based systems for ophthalmology use, privacy-preserving measures, potential challenges, and future directions of each.Several key AI algorithms used to improve disease detection and outcomes include: Data-driven, imagedriven, natural language processing (NLP)-driven, genomics-driven, and multimodality algorithms. However, deep learning systems are susceptible to adversarial attacks, and use of data for training models is associated with privacy concerns. Several data protection methods address these concerns in the form of blockchain technology, federated learning, and generative adversarial networks.AI-applications have vast potential to meet many eyecare needs, consequently reducing burden on scarce healthcare resources. A pertinent challenge would be to maintain data privacy and confidentiality while supporting AI endeavors, where data protection methods would need to rapidly evolve with AI technology needs. Ultimately, for AI to succeed in medicine and ophthalmology, a balance would need to be found between innovation and privacy.

Age-related cataracts are the leading cause of visual impairment among older adults. Many significant cases remain undiagnosed or neglected in communities, due to limited availability or accessibility to cataract screening. In the present study, we report the development and validation of a retinal photograph-based, deep-learning algorithm for automated detection of visually significant cataracts, using more than 25,000 images from population-based studies. In the internal test set, the area under the receiver operating characteristic curve (AUROC) was 96.6%. External testing performed across three studies showed AUROCs of 91.6–96.5%. In a separate test set of 186 eyes, we further compared the algorithm’s performance with 4 ophthalmologists’ evaluations. The algorithm performed comparably, if not being slightly more superior (sensitivity of 93.3% versus 51.7–96.6% by ophthalmologists and specificity of 99.0% versus 90.7–97.9% by ophthalmologists). Our findings show the potential of a retinal photograph-based screening tool for visually significant cataracts among older adults, providing more appropriate referrals to tertiary eye centers.

Topic To provide updated estimates on the global prevalence and number of people with diabetic retinopathy (DR) through 2045. Clinical Relevance The International Diabetes Federation (IDF) estimated the global population with diabetes mellitus (DM) to be 463 million in 2019 and 700 million in 2045. Diabetic retinopathy remains a common complication of DM and a leading cause of preventable blindness in the adult working population. Methods We conducted a systematic review using PubMed, Medline, Web of Science, and Scopus for population-based studies published up to March 2020. Random effect meta-analysis with logit transformation was performed to estimate global and regional prevalence of DR, vision-threatening DR (VTDR), and clinically significant macular edema (CSME). Projections of DR, VTDR, and CSME burden were based on population data from the IDF Atlas 2019. Results We included 59 population-based studies. Among individuals with diabetes, global prevalence was 22.27% (95% confidence interval [CI], 19.73%–25.03%) for DR, 6.17% (95% CI, 5.43%–6.98%) for VTDR, and 4.07% (95% CI, 3.42%–4.82%) for CSME. In 2020, the number of adults worldwide with DR, VTDR, and CSME was estimated to be 103.12 million, 28.54 million, and 18.83 million, respectively; by 2045, the numbers are projected to increase to 160.50 million, 44.82 million, and 28.61 million, respectively. Diabetic retinopathy prevalence was highest in Africa (35.90%) and North American and the Caribbean (33.30%) and was lowest in South and Central America (13.37%). In meta-regression models adjusting for habitation type, response rate, study year, and DR diagnostic method, Hispanics (odds ratio [OR], 2.92; 95% CI, 1.22–6.98) and Middle Easterners (OR, 2.44; 95% CI, 1.51–3.94) with diabetes were more likely to have DR compared with Asians. Discussion The global DR burden is expected to remain high through 2045, disproportionately affecting countries in the Middle East and North Africa and the Western Pacific. These updated estimates may guide DR screening, treatment, and public health care strategies.

To determine the 6-year incidence of primary glaucoma and its risk factors in an Indian population in Singapore.Cohort population-based study.Indian adults between 40 and 80 years of age living in Singapore. A total of 3400 participants underwent the baseline examination between 2007 and 2009. Of them, 2200 (response rate, 75.5% of those eligible) participated in the 6-year follow-up visit between 2013 and 2015.Standardized examination and investigations were performed, including indentation gonioscopy, intraocular pressure (IOP) measurement, optic disc examination, and static automated perimetry. Glaucoma was defined according to the International Society Geographical and Epidemiological Ophthalmology criteria.Incidences of primary open-angle glaucoma (POAG) and primary angle-closure glaucoma (PACG).The age-standardized incidences of primary glaucoma, POAG, and PACG were 1.68% (95% confidence interval [CI], 1.21%-2.32%), 1.37% (95% CI, 0.94%-1.96%), and 0.32% (95% CI, 0.15%-0.66%), respectively. For eyes with ocular hypertension (n = 45) at baseline, the incidence of POAG was 4.83% (95% CI, 1.24%-17.21%) and for eyes with primary angle closure (n = 14) or suspected primary angle closure (n = 101), the incidence of PACG developing was 1.82% (95% CI, 0.37%-9.68%). Baseline factors associated significantly with risk of primary glaucoma developing included older age (per decade; odds ratio [OR], 1.84; 95% CI, 1.44-2.36; P0.001), larger vertical cup-to-disc ratio (per 0.1 unit; OR, 2.78; 95% CI, 2.12-3.64; P0.001), and higher IOP (per millimeter of mercury; OR, 1.25; 95% CI, 1.13-1.38; P0.001). However, 71 of 85 eyes (84.5%) diagnosed with incident glaucoma had IOP of less than 21 mmHg at the time of examination.Our study showed that the overall age-standardized incidence of primary glaucoma was 1.68% in an Indian population in Singapore. In our population, the incidence of POAG was only half and the incidence of PACG was similar to the incidence reported by the Chennai Eye Disease Study.

The outbreak of the coronavirus disease 2019 has further increased the urgent need for digital transformation within the health care settings, with the use of artificial intelligence/deep learning, internet of things, telecommunication network/virtual platform, and blockchain. The recent advent of metaverse, an interconnected online universe, with the synergistic combination of augmented, virtual, and mixed reality described several years ago, presents a new era of immersive and real-time experiences to enhance human-to-human social interaction and connection. In health care and ophthalmology, the creation of virtual environment with three-dimensional (3D) space and avatar, could be particularly useful in patient-fronting platforms (eg, telemedicine platforms), operational uses (eg, meeting organization), digital education (eg, simulated medical and surgical education), diagnostics, and therapeutics. On the other hand, the implementation and adoption of these emerging virtual health care technologies will require multipronged approaches to ensure interoperability with real-world virtual clinical settings, user-friendliness of the technologies and clinical efficiencies while complying to the clinical, health economics, regulatory, and cybersecurity standards. To serve the urgent need, it is important for the eye community to continue to innovate, invent, adapt, and harness the unique abilities of virtual health care technology to provide better eye care worldwide.

Although the impact of vision-related quality of life (VRQoL) is assessed optimally using binocular visual acuity (VA), uniocular VA remains the preferred measurement method in clinic-based and epidemiologic studies. We compared the impact of distance presenting binocular VA and uniocular VA in the better-seeing (better-eye VA) and worse-seeing (worse-eye VA) eye on VRQoL.The Singapore Chinese Eye Study 2 (2015-2017), a population-based, cross-sectional study.One thousand eight hundred twenty-two individuals (mean age, 66.2 years [standard deviation, 8.9 years]; 51.1% women) were included.Presenting uniocular VA and binocular VA were assessed using a logarithm of the minimum angle of resolution number chart at a distance of 4 m under standard lighting by trained and certified study optometrists. Multiple linear regression models were constructed to determine the independent associations between binocular VA, better-eye VA, and worse-eye VA and the outcome (VRQoL), adjusted for potential confounders, including age, gender, socioeconomic status, and presence of comorbidities. In addition, a cluster sandwich estimator was used to determine if any differences in β estimates between the associations were statistically significant.Vision-related quality of life was measured using Rasch-transformed scores from the emotional, mobility, and reading domains of the Impact of Visual Impairment (IVI) questionnaire.Although every 2-line increase (worsening) in binocular VA and uniocular VA was associated independently with decrements in emotional, mobility, and reading IVI scores (P0.05 for all), the reductions in all VRQoL domains were substantially lower (P0.1) when using either the better-eye VA (compared with binocular VA β-estimates, -27.8%, -19.4%, and -24.2% difference in emotional, mobility, and reading IVI scores, respectively) or worse-eye VA (compared with binocular VA β estimates, -38.9%, -58.1%, and -57.5% reduction in emotional, mobility, and reading IVI scores, respectively) to quantify vision loss.Uniocular VA seems to underestimate the impact of vision loss on VRQoL indices compared with binocular VA. Our data suggest that researchers, clinicians, and policy planners should consider using binocular instead of uniocular measures of VA in patient-reported outcome evaluation of vision loss because it may better reflect its impact on VRQoL.

PurposeSevere dry eye is widely prevalent yet difficult to treat. This study aims to evaluate for improvement in epithelial status and the risk factors for lack of improvement in a cohort of patients in Singapore with severe dry eye.MethodsWe retrospectively identified 1712 patients with severe dry eye (≥grade 3 Delphi) in at least one eye, referred to a tertiary centre dry eye clinic from 2006 to 2017. We included patients with central corneal staining grade of ≥2 at referral and minimum follow-up duration of 6 months (n=407). An epithelial staining grade of ResultsThe mean follow-up duration was 4.0±2.4 years, with 88.0% (358/407) of patients achieving significant improvement. Various treatment modalities including topical corticosteroids (32.4%), cyclosporine (52.8%) and punctal plugs (24.1%) were used. Risk factors for non-improvement of staining grade include autoimmune disease (OR 3.2, 95% CI: 1.7 to 6.1), rheumatoid arthritis (RA) (OR 3.4 (1.8 to 6.6)), graft-versus-host disease (GVHD) (OR 3.4 (1.0 to 11.7)), reduced baseline Schirmer’s test (OR 2.1 (1.2 to 3.9)) and reduced tear break up time (OR 2.0 (1.0 to 3.8)). On multivariate analyses, RA and GVHD were still significant risk factors. Gender, age and meibum viscosity were not significantly associated with epithelial staining grade improvement.ConclusionsOverall, a high rate of corneal epithelial improvement was achieved. Nevertheless, there is an unmet need for more effective measures to reduce epitheliopathy in severe dry eye, especially in patients with systemic immune-mediated disease.

To describe the normative quantitative parameters of the macular retinal vasculature, as well as their systemic and ocular associations using OCT angiography (OCTA).Population-based, cross-sectional study.Adults aged50 years were recruited from the third examination of the population-based Singapore Malay Eye Study.All participants underwent a standardized comprehensive examination and spectral-domain OCTA (Optovue) of the macula. OCT angiography scans that revealed pre-existing retinal disease, revealed macular pathology, and had poor quality were excluded.The normative quantitative vessel densities of the superficial layer, deep layer, and foveal avascular zone (FAZ) were evaluated. Ocular and systemic associations with macular retinal vasculature parameters were also evaluated in a multivariable analysis using linear regression models with generalized estimating equation models.We included 1184 scans (1184 eyes) of 749 participants. The mean macular superficial vessel density (SVD) and deep vessel density (DVD) were 45.1 ± 4.2% (95% confidence interval [CI], 37.8%-51.4%) and 44.4 ± 5.2% (95% CI, 36.9%-53.2%), respectively. The mean SVD and DVD were highest in the superior quadrant (48.7 ± 5.9%) and nasal quadrant (52.7 ± 4.6%), respectively. The mean FAZ area and perimeter were 0.32 ± 0.11 mmThis study provided normative macular vasculature parameters in an adult Asian population, which may serve as reference values for quantitative interpretation of OCTA data in normal and disease states.

To determine the incidence and risk factors of primary angle-closure disease (PACD) over 6 years in a multi-ethnic Asian population.Population-based, longitudinal study.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.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.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.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.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.

BackgroundTo develop computer-aided detection (CADe) of ORL abnormalities in the retinal pigmented epithelium, interdigitation zone and ellipsoid zone via optical coherence tomography (OCT).MethodsIn this retrospective study, healthy participants with normal ORL, and patients with abnormality of ORL including choroidal neovascularisation (CNV) or retinitis pigmentosa (RP) were included. First, an automatic segmentation deep learning (DL) algorithm, CADe, was developed for the three outer retinal layers using 120 handcraft masks of ORL. This automatic segmentation algorithm generated 4000 segmentations, which included 2000 images with normal ORL and 2000 (1000 CNV and 1000 RP) images with focal or wide defects in ORL. Second, based on the automatically generated segmentation images, a binary classifier (normal vs abnormal) was developed. Results were evaluated by area under the receiver operating characteristic curve (AUC).ResultsThe DL algorithm achieved an AUC of 0.984 (95% CI 0.976 to 0.993) for individual image evaluation in the internal test set of 797 images. In addition, performance analysis of a publicly available external test set (n=968) had an AUC of 0.957 (95% CI 0.944 to 0.970) and a second clinical external test set (n=1124) had an AUC of 0.978 (95% CI 0.970 to 0.986). Moreover, the CADe highlighted well normal parts of ORL and omitted highlights in abnormal ORLs of CNV and RP.ConclusionThe CADe can use OCT images to segment ORL and differentiate between normal ORL and abnormal ORL. The CADe classifier also performs visualisation and may aid future physician diagnosis and clinical applications.

Background/aimsTo evaluate the performances of deep learning (DL) algorithms for detection of presence and extent pterygium, based on colour anterior segment photographs (ASPs) taken from slit-lamp and hand-held cameras.MethodsReferable pterygium was defined as having extension towards the cornea from the limbus of >2.50 mm or base width at the limbus of >5.00 mm. 2503 images from the Singapore Epidemiology of Eye Diseases (SEED) study were used as the development set. Algorithms were validated on an internal set from the SEED cohort (629 images (55.3% pterygium, 8.4% referable pterygium)), and tested on two external clinic-based sets (set 1 with 2610 images (2.8% pterygium, 0.7% referable pterygium, from slit-lamp ASP); and set 2 with 3701 images, 2.5% pterygium, 0.9% referable pterygium, from hand-held ASP).ResultsThe algorithm’s area under the receiver operating characteristic curve (AUROC) for detection of any pterygium was 99.5%(sensitivity=98.6%; specificity=99.0%) in internal test set, 99.1% (sensitivity=95.9%, specificity=98.5%) in external test set 1 and 99.7% (sensitivity=100.0%; specificity=88.3%) in external test set 2. For referable pterygium, the algorithm’s AUROC was 98.5% (sensitivity=94.0%; specificity=95.3%) in internal test set, 99.7% (sensitivity=87.2%; specificity=99.4%) in external set 1 and 99.0% (sensitivity=94.3%; specificity=98.0%) in external set 2.ConclusionDL algorithms based on ASPs can detect presence of and referable-level pterygium with optimal sensitivity and specificity. These algorithms, particularly if used with a handheld camera, may potentially be used as a simple screening tool for detection of referable pterygium. Further validation in community setting is warranted.Synopsis/precisDL algorithms based on ASPs can detect presence of and referable-level pterygium optimally, and may be used as a simple screening tool for the detection of referable pterygium in community screenings.

We evaluated the 6-year incidence and risk factors of pterygium in a multi-ethnic Asian population. Participants who attended the baseline visit of the Singapore Epidemiology of Eye Diseases Study (year 2004–2011) and returned six years later, were included in this study. Pterygium was diagnosed based on anterior segment photographs. Incident pterygium was defined as presence of pterygium at 6-year follow-up in either eye, among individuals without pterygium at baseline. Multivariable logistic regression models were used to determine factors associated with incident pterygium, adjusting for baseline age, gender, ethnicity, body mass index, occupation type, educational level, income status, smoking, alcohol consumption, presence of hypertension, diabetes and hyperlipidemia. The overall age-adjusted 6-year incidence of pterygium was 1.2% (95% confidence interval [CI] 1.0–1.6%); with Chinese (1.9%; 95% CI 1.4%-2.5%) having the highest incidence rate followed by Malays (1.4%; 95% CI 0.9%-2.1%) and Indians (0.3%; 95% CI 0.3–0.7%). In multivariable analysis, Chinese (compared with Indians; odds ratio [OR] = 4.21; 95% CI 2.12–9.35) and Malays (OR 3.22; 95% CI 1.52–7.45), male (OR 2.13; 95% CI 1.26–3.63), outdoor occupation (OR 2.33; 95% CI 1.16–4.38), and smoking (OR 0.41; 95% CI 0.16–0.87) were significantly associated with incident pterygium. Findings from this multi-ethnic Asian population provide useful information in identifying at-risk individuals for pterygium.

To provide updated estimates on the global prevalence and number of people with diabetic retinopathy (DR) through 2045.The International Diabetes Federation (IDF) estimated the global population with diabetes mellitus (DM) to be 463 million in 2019 and 700 million in 2045. Diabetic retinopathy remains a common complication of DM and a leading cause of preventable blindness in the adult working population.We conducted a systematic review using PubMed, Medline, Web of Science, and Scopus for population-based studies published up to March 2020. Random effect meta-analysis with logit transformation was performed to estimate global and regional prevalence of DR, vision-threatening DR (VTDR), and clinically significant macular edema (CSME). Projections of DR, VTDR, and CSME burden were based on population data from the IDF Atlas 2019.We included 59 population-based studies. Among individuals with diabetes, global prevalence was 22.27% (95% confidence interval [CI], 19.73%-25.03%) for DR, 6.17% (95% CI, 5.43%-6.98%) for VTDR, and 4.07% (95% CI, 3.42%-4.82%) for CSME. In 2020, the number of adults worldwide with DR, VTDR, and CSME was estimated to be 103.12 million, 28.54 million, and 18.83 million, respectively; by 2045, the numbers are projected to increase to 160.50 million, 44.82 million, and 28.61 million, respectively. Diabetic retinopathy prevalence was highest in Africa (35.90%) and North American and the Caribbean (33.30%) and was lowest in South and Central America (13.37%). In meta-regression models adjusting for habitation type, response rate, study year, and DR diagnostic method, Hispanics (odds ratio [OR], 2.92; 95% CI, 1.22-6.98) and Middle Easterners (OR, 2.44; 95% CI, 1.51-3.94) with diabetes were more likely to have DR compared with Asians.The global DR burden is expected to remain high through 2045, disproportionately affecting countries in the Middle East and North Africa and the Western Pacific. These updated estimates may guide DR screening, treatment, and public health care strategies.

BackgroundThe ability of deep learning (DL) algorithms to identify eyes with neovascular age-related macular degeneration (nAMD) from optical coherence tomography (OCT) scans has been previously established. We herewith evaluate the ability of a DL model, showing excellent performance on a Korean data set, to generalse onto an American data set despite ethnic differences. In addition, expert graders were surveyed to verify if the DL model was appropriately identifying lesions indicative of nAMD on the OCT scans.MethodsModel development data set—12 247 OCT scans from South Korea; external validation data set—91 509 OCT scans from Washington, USA. In both data sets, normal eyes or eyes with nAMD were included. After internal testing, the algorithm was sent to the University of Washington, USA, for external validation. Area under the receiver operating characteristic curve (AUC) and precision–recall curve (AUPRC) were calculated. For model explanation, saliency maps were generated using Guided GradCAM.ResultsOn external validation, AUC and AUPRC remained high at 0.952 (95% CI 0.942 to 0.962) and 0.891 (95% CI 0.875 to 0.908) at the individual level. Saliency maps showed that in normal OCT scans, the fovea was the main area of interest; in nAMD OCT scans, the appropriate pathological features were areas of model interest. Survey of 10 retina specialists confirmed this.ConclusionOur DL algorithm exhibited high performance for nAMD identification in a Korean population, and generalised well to an ethnically distinct, American population. The model correctly focused on the differences within the macular area to extract features associated with nAMD.

AimsTo evaluate the normative profiles for neuroretinal rim area (RA) in a multiethnic Asian population.MethodsSubjects were recruited from the Singapore Epidemiology of Eye Diseases (2009–2015) study and underwent standardised examinations. RA measurements were performed using Cirrus high-definition optical coherence tomography (Carl Zeiss Meditec). Multivariable linear regression with generalised estimating equation model was used to evaluate the associations between demographic, systemic and ocular factors with RA.ResultsA total of 9394 eyes from 5116 subjects (1724 Chinese, 1463 Malay, 1929 Indian) were included in the final analysis. The mean (±SD) of RA was 1.28 (±0.23) mm2 for Chinese, 1.33 (±0.26) mm2 for Malays, and 1.23 (±0.23) mm2 for Indians. The 5th percentile value for RA was 0.94 mm2 for Chinese, 0.96 mm2 for Malay, and 0.89 mm2 for Indian. In multivariable analysis, following adjustment for age, gender, body mass index, diabetes mellitus, hyperlipidaemia, history of cataract surgery, axial length, intraocular pressure (IOP) and disc area, Indian eyes have smaller RA when compared with Malays (β=−0.074; 95% CI −0.090 to −0.058; pConclusionIn this multiethnic population-based study, we observed significantly smaller RA in Indian eyes, compared with Chinese and Malays. This indicates the need of a more refined ethnic-specific RA normative databases among Asians.

To evaluate the association between different classes of antihypertensive medication with retinal nerve fiber layer (RNFL) and ganglion cell-inner plexiform layer (GC-IPL) thickness in a nonglaucomatous multiethnic Asian population.Population-based, cross-sectional study.A total of 9144 eyes for RNFL analysis (2668 Malays, 3554 Indians, and 2922 Chinese) and 8549 eyes for GC-IPL analysis (2460 Malays, 3230 Indians, and 2859 Chinese) aged 44 to 86 years.Participants underwent standardized systemic and ocular examinations and interviewer-administered questionnaires for collection of data on medication and other variables. Intraocular pressure (IOP) readings were obtained by Goldmann applanation tonometry before pupil dilation for fundoscopy and OCT imaging. Blood pressure (BP) was measured with an automatic BP monitor. Mean arterial pressure (MAP) was defined as diastolic BP plus 1/3 (systolic BP - diastolic BP). Regression models were used to investigate the association of antihypertensive medication with OCT measurements of RNFL and GC-IPL.Average and sectoral RNFL and GC-IPL thickness.After adjusting for age, gender, ethnicity, MAP, IOP, body mass index (BMI), and presence of diabetes, we found that participants taking any type of antihypertensive medication (β = -0.83; 95% confidence interval [CI], -1.46 to -0.02; P = 0.01), specifically angiotensin-converting enzyme inhibitors (ACEIs) (β = -1.66; 95% CI, -2.57 to -0.75; P0.001) or diuretics (β = -1.38; 95% CI, -2.59 to -0.17; P0.05), had thinner average RNFL in comparison with participants who were not receiving antihypertensive treatment. Use of a greater number of antihypertensive medications was significantly associated with thinner average RNFL (P for trend = 0.001). This association was most evident in the inferior RNFL quadrant in participants using ACEIs (β = -2.44; 95% CI, -3.99 to -0.89; P = 0.002) or diuretics (β = -2.76; 95% CI, -4.76 to -0.76; P = 0.007). A similar trend was noted in our analysis of macular GC-IPL thickness.Use of 2 or more antihypertensive medications, ACEI, and diuretics were associated with a loss of structural markers of retinal ganglion cell health in a multiethnic Asian population.

We aimed to estimate the supply of ophthalmologists in relation to the global and regional burden of vision-threatening diabetic retinopathy (VTDR). Diabetes mellitus (DM) population data from seven world regions were obtained from the International Diabetes Federation Atlas 2017. A systematic review was performed to include population-, community-based studies that reported country-specific VTDR prevalence. Random effect meta-analysis was then performed to estimate global and regional VTDR prevalence. VTDR prevalence estimates coupled with DM population data were then used to estimate the number of VTDR cases. Global and regional number of ophthalmologists were derived from the International Council of Ophthalmology Report 2015. Fifty studies (17 from Western Pacific [WP], nine North America and Caribbean [NAC], nine Middle East and North Africa [MENA], five Europe, eight South East Asia [SEA], one South and Central America [SACA] and one from Africa) were included. Global VTDR prevalence was 7.26% (95% CI, 6.18-8.32%). Regional VTDR prevalence was 14.35% in Africa, 11.21% in MENA, 10.00% in NAC, 6.32% in Europe, 6.22% in WP, 5.83% in SACA and 2.97% in SEA. Globally, there were 7.16 ophthalmologists per 1000 VTDR patients. Europe had the highest ophthalmologist per 1000 VTDR patient ratio at 18.03 followed by SACA (17.41), while NAC, MENA and Africa had the lowest at 4.90, 4.81 and 0.91 respectively. Across regions, the ophthalmologist densities ranged from 0.91 to 18.03 per 1000 VTDR patients, with NAC, MENA and Africa having less than 5 ophthalmologists per 1000 patients. These findings will aid global and regional policy planning and healthcare resource allocation for VTDR management.摘要: 我们旨在评估眼科医生的资源与威胁视力的糖尿病视网膜病变 (vision-threatening diabetic retinopathy VTDR) 给全球和局部地区带来的影响。全球7个地区的糖尿病 (Diabetes mellitus DM) 人口数据来自于2017年 国际糖尿病地图 (IDF地图) 。该系统综述纳入了以人群及社区为基础开展的研究, 报告了特定国家VTDR的发病率。随后也进行了随机效应荟萃分析以进一步评估全球和局部地区VTDR的发病率。结合VTDR发病率与DM人口数据可用于评估VTDR总例数。全球和局部地区眼科医生的人数来源于2015年国际眼科学会报告。 本文纳入了50个研究 (17个来自西太平洋, 9个来自北美和加勒比, 9个来自中东和北非, 5个来自欧洲, 8个来自东南亚, 1个来自南美和中美洲, 1个来自非洲) 。全球VTDR的患病率为7.26% (95% CI, 6.18–8.32%)。非洲局部地区VTDR的患病率为14.35%, 中东和北非地区为11.21%, 北美和加勒比地区为10.00%, 欧洲地区为6.32%, 西太平洋地区为6.22%, 南美和中美洲地区为5.83%, 东南亚地区为2.97% 。全球每1000名VTDR患者中对应7.16名眼科医生。欧洲每1000名VTDR患者中眼科医生的比例最高, 为18.03, 其次是南美和中美洲, 为17.41, 而北美和加勒比、中东和北非及非洲的比例最低, 分别为4.90、4.81和0.91。 在不同地区, 每1000名VTDR患者中, 眼科医生的密度从0.91到18.03不等, 而北美和加勒比、中东和北非以及非洲每1000名患者中只有不到5名的眼科医生。这些发现将有助于全球和地区政策的制定以及针对VTDR管理的医疗资源的分配。.

Aims To determine the association between albuminuria and primary open-angle glaucoma (POAG). Methods Participants of the Singapore Chinese Eye study were recruited and underwent standardised ocular and systemic examinations. Albuminuria was determined using urinary albumin-to-creatinine ratio (UACR, mg/g) based on random spot urinary albumin and creatinine measurements. POAG was defined using the International Society of Geographic and Epidemiological Ophthalmology classification. Multivariable logistic regression with generalised estimating equation model was used to evaluate the association between albuminuria and POAG, while accounting for correlation between eyes. Results A total of 3009 Chinese adults (5963 eyes), aged 40–80 years, were included in this study, of which, 52 subjects (75 eyes) had POAG. Higher UACR (per 50 mg/g increase) was independently associated with POAG (OR=1.04, 95% CI 1.01 to 1.07, p=0.003) following adjustment for age, gender, intraocular pressure, diabetes mellitus, hyperlipidaemia, hypertension, anti-hypertensive medication, history of cardiovascular disease, current smoking status, alcohol intake, body mass index and estimated glomerular filtration rate. Further stratification revealed that individuals with macroalbuminuria were 8.00 times likely to have POAG (95% CI 2.97 to 21.54, p Conclusion In this population-based study of Chinese adults, albuminuria was independently associated with POAG. Our findings provide further understanding on the pathogenesis of POAG and may potentially help to better identify individuals at risk of POAG.

Background/AimTo investigate normative patterns and factors associated with presbyopia progression in a multiethnic Asian population.MethodsMalay, Indian and Chinese participants aged 40–80 years who had baseline and 6-year follow-up examinations with subjective refraction data were recruited from the Singapore Epidemiology of Eye Diseases Study. Presbyopia progression was defined as an increase in near addition power of ≥+0.50 dioptre (D) from baseline to follow-up visit. Modified Poisson regression analyses were used to determine baseline factors associated with presbyopia progression.ResultsFrom the eligible 3974 eyes, 2608 eyes were included for final analysis after excluding eyes with a history of cataract surgery (929 eyes) and best-corrected distance visual acuity worse than 20/40 (342 eyes). Overall the mean near addition power change over 6 years was +0.25 D; Malays showed greater change (+0.37 D) compared with Indians (+0.23 D) and Chinese (+0.16 D). After adjusting for baseline age, gender, body mass index, hypertension, cataract, refractive error and daily hours of reading and writing, Malays were more likely to have presbyopia progression compared with Chinese (RR (relative risk)=1.67; 95% CI 1.43 to 1.95; pConclusionIn this Asian population, the near addition power change over 6 years was lower than the current near addition prescription guidelines (+0.25 D vs +0.60 D). Our findings may help update near addition prescription guidelines that can be more tailored to Asians.

BackgroundWe examined the associations between the 6-year incidence of age-related macular degeneration (AMD) and vision-related quality of life (VRQoL), and the contribution of presenting visual acuity (VA), in an Asian population.MethodsFundus images from the Singapore Chinese Eye Study, a population-based cohort study (baseline: 2009–2011; follow-up: 2015–2017), were graded using a modified Wisconsin age-related maculopathy grading system. Incident AMD was defined as no baseline AMD in both eyes and early/late AMD in the worse eye at follow-up. Presenting VA was assessed using the logarithm of the minimum angle of resolution chart at 4 m under standard lighting conditions with habitual correction. Multiple linear regression models determined the associations between AMD incidence with changes in the Rasch-transformed scores of the Reading, Mobility and Emotional VRQoL domains of the 32-item Impact of Visual Impairment (IVI-32) questionnaire, adjusted for traditional confounders. The contribution of presenting VA to changes in VRQoL was also estimated.ResultsOf the 2251 participants without AMD at baseline (mean age (SD): 57.7 (9) years, 51.4% women), 101 (4.5%) and 11 (0.5%) developed incident early and late AMD at follow-up, respectively. Incident late AMD was associated with significant 30.3%, 32.5% and 30.9% decrements in Reading, Mobility and Emotional IVI scores, respectively. The contribution of presenting VA ranged between 1.62% and 4.35% of the observed decrements. No significant associations were noted with incident early AMD.ConclusionIncident late AMD had a substantial impact on all aspects of VRQoL, with presenting VA contributing only minimally to this longitudinal relationship.