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Abstract To address challenges in screening for chronic kidney disease (CKD), we devised a deep learning-based CKD screening model named UWF-CKDS. It utilizes ultra-wide-field (UWF) fundus images to predict the presence of CKD. We validated the model with data from 23 tertiary hospitals across China. Retinal vessels and retinal microvascular parameters (RMPs) were extracted to enhance model interpretability, which revealed a significant correlation between renal function and RMPs. UWF-CKDS, utilizing UWF images, RMPs, and relevant medical history, can accurately determine CKD status. Importantly, UWF-CKDS exhibited superior performance compared to CTR-CKDS, a model developed using the central region (CTR) cropped from UWF images, underscoring the contribution of the peripheral retina in predicting renal function. The study presents UWF-CKDS as a highly implementable method for large-scale and accurate CKD screening at the population level.

Abstract Background Housing has been associated with dementia risk and disability, but associations of housing with differential patterns of neuropsychiatric symptoms (NPS) among dementia-free older adults remain to be explored. The present study sought to explore the contribution of housing status on NPS and subsyndromes associated with cognitive dysfunction in community-dwelling dementia-free elderly in Singapore. Methods A total of 839 dementia-free elderly from the Epidemiology of Dementia in Singapore (EDIS) study aged ≥ 60 were enrolled in the current study. All participants underwent clinical, cognitive, and neuropsychiatric inventory (NPI) assessments. The housing status was divided into three categories according to housing type. Cognitive function was measured by a comprehensive neuropsychological battery. The NPS were assessed using 12-term NPI and were grouped into four clinical subsyndromes: psychosis, hyperactivity, affective, and apathy. Associations of housing with composite and domain-specific Z-scores, as well as NPI scores, were assessed using generalized linear models (GLM). Binary logistic regression models analysed the association of housing with the presence of NPS and significant NPS (NPI total scores ≥ 4). Results Better housing status (5-room executive apartments, condominium, or private housing) was associated with better NPS (OR = 0.49, 95%CI = 0.24 to 0.98, P

Abstract The objective of this study is to define structure–function relationships of pathological lesions related to age-related macular degeneration (AMD) using microperimetry and multimodal retinal imaging. We conducted a cross-sectional study of 87 patients with AMD (30 eyes with early and intermediate AMD and 110 eyes with advanced AMD), compared to 33 normal controls (66 eyes) recruited from a single tertiary center. All participants had enface and cross-sectional optical coherence tomography (Heidelberg HRA-2), OCT angiography, color and infra-red (IR) fundus and microperimetry (MP) (Nidek MP-3) performed. Multimodal images were graded for specific AMD pathological lesions. A custom marking tool was used to demarcate lesion boundaries on corresponding enface IR images, and subsequently superimposed onto MP color fundus photographs with retinal sensitivity points (RSP). The resulting overlay was used to correlate pathological structural changes to zonal functional changes. Mean age of patients with early/intermediate AMD, advanced AMD and controls were 73(SD = 8.2), 70.8(SD = 8), and 65.4(SD = 7.7) years respectively. Mean retinal sensitivity (MRS) of both early/intermediate (23.1 dB; SD = 5.5) and advanced AMD (18.1 dB; SD = 7.8) eyes were significantly worse than controls (27.8 dB, SD = 4.3) (p

Abstract Background The Diabetic Retinopathy Extended Screening Study (DRESS) aims to develop and validate a new DR/diabetic macular edema (DME) risk stratification model in patients with Type 2 diabetes (DM) to identify low-risk groups who can be safely assigned to biennial or triennial screening intervals. We describe the study methodology, participants’ baseline characteristics, and preliminary DR progression rates at the first annual follow-up. Methods DRESS is a 3-year ongoing longitudinal study of patients with T2DM and no or mild non-proliferative DR (NPDR, non-referable) who underwent teleophthalmic screening under the Singapore integrated Diabetic Retinopathy Programme (SiDRP) at four SingHealth Polyclinics. Patients with referable DR/DME (> mild NPDR) or ungradable fundus images were excluded. Sociodemographic, lifestyle, medical and clinical information was obtained from medical records and interviewer-administered questionnaires at baseline. These data are extracted from medical records at 12, 24 and 36 months post-enrollment. Baseline descriptive characteristics stratified by DR severity at baseline and rates of progression to referable DR at 12-month follow-up were calculated. Results Of 5,840 eligible patients, 78.3% (n = 4,570, median [interquartile range [IQR] age 61.0 [55–67] years; 54.7% male; 68.0% Chinese) completed the baseline assessment. At baseline, 97.4% and 2.6% had none and mild NPDR (worse eye), respectively. Most participants had hypertension (79.2%) and dyslipidemia (92.8%); and almost half were obese (43.4%, BMI ≥ 27.5 kg/m2). Participants without DR (vs mild DR) reported shorter DM duration, and had lower haemoglobin A1c, triglycerides and urine albumin/creatinine ratio (all p

BackgroundChina exited strict Zero-COVID policy with a surge in Omicron variant infections in December 2022. Given China’s pandemic policy and population immunity, employing Baidu Index (BDI) to analyze the evolving disease landscape and estimate the nationwide pneumonia hospitalizations in the post Zero COVID period, validated by hospital data, holds informative potential for future outbreaks.MethodsRetrospective observational analyses were conducted at the conclusion of the Zero-COVID policy, integrating internet search data alongside offline records. Methodologies employed were multidimensional, encompassing lagged Spearman correlation analysis, growth rate assessments, independent sample T-tests, Granger causality examinations, and Bayesian structural time series (BSTS) models for comprehensive data scrutiny.ResultsVarious diseases exhibited a notable upsurge in the BDI after the policy change, consistent with the broader trajectory of the COVID-19 pandemic. Robust connections emerged between COVID-19 and diverse health conditions, predominantly impacting the respiratory, circulatory, ophthalmological, and neurological domains. Notably, 34 diseases displayed a relatively high correlation (r > 0.5) with COVID-19. Among these, 12 exhibited a growth rate exceeding 50% post-policy transition, with myocarditis escalating by 1,708% and pneumonia by 1,332%. In these 34 diseases, causal relationships have been confirmed for 23 of them, while 28 garnered validation from hospital-based evidence. Notably, 19 diseases obtained concurrent validation from both Granger causality and hospital-based data. Finally, the BSTS models approximated approximately 4,332,655 inpatients diagnosed with pneumonia nationwide during the 2 months subsequent to the policy relaxation.ConclusionThis investigation elucidated substantial associations between COVID-19 and respiratory, circulatory, ophthalmological, and neurological disorders. The outcomes from comprehensive multi-dimensional cross-over studies notably augmented the robustness of our comprehension of COVID-19’s disease spectrum, advocating for the prospective utility of internet-derived data. Our research highlights the potential of Internet behavior in predicting pandemic-related syndromes, emphasizing its importance for public health strategies, resource allocation, and preparedness for future outbreaks.

Purpose: To review the evidence for imaging modalities in assessing the vascular component of diabetic retinal disease (DRD), to inform updates to the DRD staging system. Design: Standardized narrative review of the literature by an international expert workgroup, as part of the DRD Staging System Update Effort, a project of the Mary Tyler Moore Vision Initiative. Overall, there were 6 workgroups: Vascular Retina, Neural Retina, Systemic Health, Basic and Cellular Mechanisms, Visual Function, and Quality of Life. Participants: The Vascular Retina workgroup, including 16 participants from 4 countries. Methods: Literature review was conducted using standardized evidence grids for 5 modalities: standard color fundus photography (CFP), widefield color photography (WFCP), standard fluorescein angiography (FA), widefield FA (WFFA), and OCT angiography (OCTA). Summary levels of evidence were determined on a validated scale from I (highest) to V (lowest). Five virtual workshops were held for discussion and consensus. Main Outcome Measures: Level of evidence for each modality. Results: Levels of evidence for standard CFP, WFCP, standard FA, WFFA, and OCTA were I, II, I, I, and II respectively. Traditional vascular lesions on standard CFP should continue to be included in an updated staging system, but more studies are required before they can be used in posttreatment eyes. Widefield color photographs can be used for severity grading within the area covered by standard CFPs, although these gradings may not be directly interchangeable with each other. Evaluation of the peripheral retina on WFCP can be considered, but the method of grading needs to be clarified and validated. Standard FA and WFFA provide independent prognostic value, but the need for dye administration should be considered. OCT angiography has significant potential for inclusion in the DRD staging system, but various barriers need to be addressed first. Conclusions: This study provides evidence-based recommendations on the utility of various imaging modalities for assessment of the vascular component of DRD, which can inform future updates to the DRD staging system. Although new imaging modalities offer a wealth of information, there are still major gaps and unmet research needs that need to be addressed before this potential can be realized. Financial Disclosure(s): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

BackgroundDiabetic kidney disease (DKD) and diabetic retinopathy (DR) are major diabetic microvascular complications, contributing significantly to morbidity, disability, and mortality worldwide. The kidney and the eye, having similar microvascular structures and physiological and pathogenic features, may experience similar metabolic changes in diabetes. ObjectiveThis study aimed to use machine learning (ML) methods integrated with metabolic data to identify biomarkers associated with DKD and DR in a multiethnic Asian population with diabetes, as well as to improve the performance of DKD and DR detection models beyond traditional risk factors. MethodsWe used ML algorithms (logistic regression [LR] with Least Absolute Shrinkage and Selection Operator and gradient-boosting decision tree) to analyze 2772 adults with diabetes from the Singapore Epidemiology of Eye Diseases study, a population-based cross-sectional study conducted in Singapore (2004-2011). From 220 circulating metabolites and 19 risk factors, we selected the most important variables associated with DKD (defined as an estimated glomerular filtration rate

Abstract Neovascular age-related macular degeneration (nAMD), along with its clinical subtype known as polypoidal choroidal vasculopathy (PCV), are among the leading causes of vision loss in elderly Asians. In a genome-wide association study (GWAS) comprising 3,128 nAMD (1,555 PCV and 1,573 typical nAMD), and 5,493 controls of East Asian ancestry, we identify twelve loci, of which four are novel ( $$P \, < \, 1.19\times {10}^{-8}$$ P < 1.19 × 10 − 8 ). Substantial genetic sharing between PCV and typical nAMD is noted (r g = 0.666), whereas collagen extracellular matrix and fibrosis-related pathways are more pronounced for PCV. Whole-exome sequencing in 259 PCV patients revealed functional rare variants burden in collagen type I alpha 1 chain gene (COL1A1; $$P=1.05\times {10}^{-6}$$ P = 1.05 × 10 − 6 ) and potential enrichment of functional rare mutations at AMD-associated loci. At the GATA binding protein 5 (GATA5) locus, the most significant GWAS novel loci, the expressions of genes including laminin subunit alpha 5 (Lama5), mitochondrial ribosome associated GTPase 2 (Mtg2), and collagen type IX alpha 3 chain (Col9A3), are significantly induced during retinal angiogenesis and subretinal fibrosis in murine models. Furthermore, retinoic acid increased the expression of LAMA5 and MTG2 in vitro. Taken together, our data provide insights into the genetic basis of AMD pathogenesis in the Asian population.

Summary: We investigated the relationship of preconception maternal retinal vasculature and utero-fetoplacental circulation in ensuing pregnancy. Embedded in a hospital-based, prospective preconception cohort, 396 women with a singleton live birth were included for analysis. We assessed retinal vascular caliber during preconception phase and retrieved ultrasonogram results documenting utero-fetoplacental circulatory indices using Doppler ultrasonography and documented them at 18–21 weeks, 24–28 weeks, and 32–34 weeks where available. We performed a modified Poisson regression to estimate the relative risk of utero-fetoplacental abnormalities, adjusting for major confounders including pre-pregnancy and blood pressure. Per 10 μm increment in maternal preconception retinal venules was associated with over two-fold risks in developing notching (Relative risk [RR]: 2.84; 95% confidence interval [CI]: 1.79, 4.81) and ≥95th percentile umbilical artery pulsatility index (2.36; 1.72, 3.23) during mid-to-late pregnancy, respectively. Women with preconception retinal venular widening tended to demonstrate steeper resistance increments in both maternal uterine arteries and fetal umbilical arteries during mid-to-late pregnancy.

Purpose: To examine the 6-year incidence of visual impairment (VI) and identify risk factors associated with VI in a multiethnic Asian population. Design: Prospective, population-based, cohort study. Participants: Adults aged ≥ 40 years were recruited from the Singapore Epidemiology of Eye Diseases cohort study at baseline. Eligible subjects were re-examined after 6 years. Subjects included in the final analysis had a mean age of 56.1 ± 8.9 years, and 2801 (50.5%) were female. Methods: All participants underwent standardized examination and interviewer-administered questionnaire at baseline. Incidences were standardized to the Singapore Population Census 2010. A Poisson binomial regression model was used to evaluate the associations between baseline factors and incident presenting VI. Main Outcome Measures: Incident presenting VI was assessed at the 6-year follow-up visit. Visual impairment (presenting visual acuity < 20/40), low vision (presenting visual acuity < 20/40 but ≥ 20/200), and blindness (presenting visual acuity < 20/200) were defined based on United States definition. Results: A total of 5551 subjects (2188 Chinese, 1837 Indians, and 1526 Malays) were evaluated, of whom 514 developed incident presenting VI over 6 years. Malays had a higher incidence of low vision and blindness (13.0%; 0.6%) than Indians (7.0%; 0.1%) and Chinese (7.7%; 0.2%). Among Malay individuals with VI at baseline, 52.8% remained visually impaired after 6 years, which was considerably higher than Chinese (32.4%) and Indians (37.2%). Older age (per decade; relative risk [RR] = 1.59), a history of cardiovascular disease (RR = 1.38), current smoking (RR = 1.31), smaller housing type (1- to 2-room public flat; RR = 2.01), and no formal education (RR = 1.63) at baseline were associated with a higher risk of incident VI (all P ≤ 0.027). Older age (> 60 years) contributed the highest population attributable risk to incident VI (27.1%), followed by lower monthly income (Singapore dollar < $2000; 26.4%) and smaller housing type (24.7%). Overall, undercorrected refractive error (49.1%) and cataract (82.6%) were leading causes for low vision and blindness, respectively. This was consistently observed across the 3 ethnicities. Conclusions: In this multiethnic Asian population, Malays had a higher VI incidence compared to Indians and Chinese. Leading causes of VI are mostly treatable, suggesting that more efforts are needed to further mitigate preventable visual loss. Financial Disclosure(s): The authors have no proprietary or commercial interest in any materials discussed in this article.

Purpose: For OCT retinal thickness measurements to be used as a prodromal age-related macular degeneration (AMD) risk marker, the 3-dimensional (3D) topographic variation of the relationship between genetic susceptibility to AMD and retinal thickness needs to be assessed. We aimed to evaluate individual retinal layer thickness changes and topography at the macula that are associated with AMD genetic susceptibility. Design: Genetic association study. Participants: A total of 1579 healthy participants (782 Chinese, 353 Malays, and 444 Indians) from the multiethnic Singapore Epidemiology of Eye Diseases study were included. Methods: Spectral-domain OCT and automatic segmentation of individual retinal layers were performed to produce 10 retinal layer thickness measurements at each ETDRS subfield, producing 3D topographic information. Age-related macular degeneration genetic susceptibility was represented via single nucleotide polymorphisms (SNPs) and aggregated via whole genome (overall) and pathway-specific age-related macular degeneration polygenic risk score (PRSAMD). Main Outcome Measures: Associations of individual SNPs, overall PRSAMD, and pathway-specific PRSAMD with retinal thickness were analyzed by individual retinal layer and ETDRS subfield. Results: CFH rs10922109, ARMS2-HTRA1 rs3750846, and LIPC rs2043085 were the top AMD susceptibility SNPs associated with retinal thickness of individual layers (P

Summary: In low- and middle-income countries (LMICs), the fields of medicine and public health grapple with numerous challenges that continue to hinder patients' access to healthcare services. ChatGPT, a publicly accessible chatbot, has emerged as a potential tool in aiding public health efforts in LMICs. This viewpoint details the potential benefits of employing ChatGPT in LMICs to improve medicine and public health encompassing a broad spectrum of domains ranging from health literacy, screening, triaging, remote healthcare support, mental health support, multilingual capabilities, healthcare communication and documentation, medical training and education, and support for healthcare professionals. Additionally, we also share potential concerns and limitations associated with the use of ChatGPT and provide a balanced discussion on the opportunities and challenges of using ChatGPT in LMICs.

Introduction: Educational attainment, widely used in epidemiologic studies as a surrogate for socioeconomic status, is a predictor of cardiovascular health outcomes.Methods: A two-stage genome-wide meta-analysis of low-density lipoprotein cholesterol (LDL), high-density lipoprotein cholesterol (HDL), and triglyceride (TG) levels was performed while accounting for gene-educational attainment interactions in up to 226,315 individuals from five population groups. We considered two educational attainment variables: “Some College” (yes/no, for any education beyond high school) and “Graduated College” (yes/no, for completing a 4-year college degree). Genome-wide significant (p < 5 × 10−8) and suggestive (p < 1 × 10−6) variants were identified in Stage 1 (in up to 108,784 individuals) through genome-wide analysis, and those variants were followed up in Stage 2 studies (in up to 117,531 individuals).Results: In combined analysis of Stages 1 and 2, we identified 18 novel lipid loci (nine for LDL, seven for HDL, and two for TG) by two degree-of-freedom (2 DF) joint tests of main and interaction effects. Four loci showed significant interaction with educational attainment. Two loci were significant only in cross-population analyses. Several loci include genes with known or suggested roles in adipose (FOXP1, MBOAT4, SKP2, STIM1, STX4), brain (BRI3, FILIP1, FOXP1, LINC00290, LMTK2, MBOAT4, MYO6, SENP6, SRGAP3, STIM1, TMEM167A, TMEM30A), and liver (BRI3, FOXP1) biology, highlighting the potential importance of brain-adipose-liver communication in the regulation of lipid metabolism. An investigation of the potential druggability of genes in identified loci resulted in five gene targets shown to interact with drugs approved by the Food and Drug Administration, including genes with roles in adipose and brain tissue.Discussion: Genome-wide interaction analysis of educational attainment identified novel lipid loci not previously detected by analyses limited to main genetic effects.

Background Genome-wide association studies for glycemic traits have identified hundreds of loci associated with these biomarkers of glucose homeostasis. Despite this success, the challenge remains to link variant associations to genes, and underlying biological pathways. Methods To identify coding variant associations which may pinpoint effector genes at both novel and previously established genome-wide association loci, we performed meta-analyses of exome-array studies for four glycemic traits: glycated hemoglobin (HbA1c, up to 144,060 participants), fasting glucose (FG, up to 129,665 participants), fasting insulin (FI, up to 104,140) and 2hr glucose post-oral glucose challenge (2hGlu, up to 57,878). In addition, we performed network and pathway analyses. Results Single-variant and gene-based association analyses identified coding variant associations at more than 60 genes, which when combined with other datasets may be useful to nominate effector genes. Network and pathway analyses identified pathways related to insulin secretion, zinc transport and fatty acid metabolism. HbA1c associations were strongly enriched in pathways related to blood cell biology. Conclusions Our results provided novel glycemic trait associations and highlighted pathways implicated in glycemic regulation. Exome-array summary statistic results are being made available to the scientific community to enable further discoveries.

Background Case-finding is a recommended approach for dementia early detection in the community.Aims To investigate the discriminant validity and cost-effectiveness of a stepwise dementia case-finding approach in a Singaporean older adult community.Methods The two-phase study was conducted in the community from 2009 to 2015 in Singapore. A total of 3780 participants (age ≥60 years) completed phase I (a brief cognitive screening); 918 completed phase II and were included in the final analysis. In phase I, all participants were administered the Abbreviated Mental Test (AMT) and the Progressive Forgetfulness Question (PFQ). Those who screened positive on either test were invited to phase II, whereby the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA) and a formal neuropsychological battery were administered, followed by the research diagnosis of no cognitive impairment, cognitive impairment no dementia (CIND)-Mild (≤2 impaired cognitive domains), CIND-Moderate (>2 impaired domains) or dementia. Receiver operating characteristic curve analyses were conducted for the different cognitive instruments. All discriminant indices were calculated, including sensitivity, specificity, positive and negative predictive values (NPV) and accuracy. Cost-effectiveness analysis was conducted by estimating the amount of screening time needed and the number of older adults requiring re-evaluation in two case-finding scenarios, ie, with or without preselection by the PFQ.Results The stepwise case-finding approach (preselection by the PFQ, then MMSE or MoCA or AMT) showed an excellent NPV (>99%) and accuracy (>86%) for excluding dementia-free cases. Without preselection by the PFQ, screening time for the three cognitive tools were 317.5, 317.5 and 254 hours, with 159, 302 and 175 screen-positive older adults involved in further evaluation. By adopting the stepwise case-finding approach, total screening time were 156.5, 156.5 and 126.2 hours, which decreased by 50.7%, 50.7% and 50.3% as compared with those without preselection. Furthermore, after preselection, only 98, 167 and 145 screen-positive older adults required further evaluation, corresponding to a reduction of 38.4%, 44.7% and 17.1% in the numbers compared with those without preselection.Conclusions A stepwise approach for dementia case-finding should be implemented in the community to minimise the time and resources needed for large-scale early detection of dementia.

BackgroundThe growing global burden of visual impairment necessitates better population eye screening for early detection of eye diseases. However, accessibility to testing is often limited and centralized at in-hospital settings. Furthermore, many eye screening programs were disrupted by the COVID-19 pandemic, presenting an urgent need for out-of-hospital solutions. ObjectiveThis study investigates the performance of a novel remote perimetry application designed in a virtual reality metaverse environment to enable functional testing in community-based and primary care settings. MethodsThis was a prospective observational study investigating the performance of a novel remote perimetry solution in comparison with the gold standard Humphrey visual field (HVF) perimeter. Subjects received a comprehensive ophthalmologic assessment, HVF perimetry, and remote perimetry testing. The primary outcome measure was the agreement in the classification of overall perimetry result normality by the HVF (Swedish interactive threshold algorithm–fast) and testing with the novel algorithm. Secondary outcome measures included concordance of individual testing points and perimetry topographic maps. ResultsWe recruited 10 subjects with an average age of 59.6 (range 28-81) years. Of these, 7 (70%) were male and 3 (30%) were female. The agreement in the classification of overall perimetry results was high (9/10, 90%). The pointwise concordance in the automated classification of individual test points was 83.3% (8.2%; range 75%-100%). In addition, there was good perimetry topographic concordance with the HVF in all subjects. ConclusionsRemote perimetry in a metaverse environment had good concordance with gold standard perimetry using the HVF and could potentially avail functional eye screening in out-of-hospital settings.

Digital health technologies have been in use for many years in a wide spectrum of healthcare scenarios. This narrative review outlines the current use and the future strategies and significance of digital health technologies in modern healthcare applications. It covers the current state of the scientific field (delineating major strengths, limitations, and applications) and envisions the future impact of relevant emerging key technologies. Furthermore, we attempt to provide recommendations for innovative approaches that would accelerate and benefit the research, translation and utilization of digital health technologies.

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

Abstract Background Currently in the United Kingdom, cardiovascular disease (CVD) risk assessment is based on the QRISK3 score, in which 10% 10-year CVD risk indicates clinical intervention. However, this benchmark has limited efficacy in clinical practice and the need for a more simple, non-invasive risk stratification tool is necessary. Retinal photography is becoming increasingly acceptable as a non-invasive imaging tool for CVD. Previously, we developed a novel CVD risk stratification system based on retinal photographs predicting future CVD risk. This study aims to further validate our biomarker, Reti-CVD, (1) to detect risk group of ≥ 10% in 10-year CVD risk and (2) enhance risk assessment in individuals with QRISK3 of 7.5–10% (termed as borderline-QRISK3 group) using the UK Biobank. Methods Reti-CVD scores were calculated and stratified into three risk groups based on optimized cut-off values from the UK Biobank. We used Cox proportional-hazards models to evaluate the ability of Reti-CVD to predict CVD events in the general population. C-statistics was used to assess the prognostic value of adding Reti-CVD to QRISK3 in borderline-QRISK3 group and three vulnerable subgroups. Results Among 48,260 participants with no history of CVD, 6.3% had CVD events during the 11-year follow-up. Reti-CVD was associated with an increased risk of CVD (adjusted hazard ratio [HR] 1.41; 95% confidence interval [CI], 1.30–1.52) with a 13.1% (95% CI, 11.7–14.6%) 10-year CVD risk in Reti-CVD-high-risk group. The 10-year CVD risk of the borderline-QRISK3 group was greater than 10% in Reti-CVD-high-risk group (11.5% in non-statin cohort [n = 45,473], 11.5% in stage 1 hypertension cohort [n = 11,966], and 14.2% in middle-aged cohort [n = 38,941]). C statistics increased by 0.014 (0.010–0.017) in non-statin cohort, 0.013 (0.007–0.019) in stage 1 hypertension cohort, and 0.023 (0.018–0.029) in middle-aged cohort for CVD event prediction after adding Reti-CVD to QRISK3. Conclusions Reti-CVD has the potential to identify individuals with ≥ 10% 10-year CVD risk who are likely to benefit from earlier preventative CVD interventions. For borderline-QRISK3 individuals with 10-year CVD risk between 7.5 and 10%, Reti-CVD could be used as a risk enhancer tool to help improve discernment accuracy, especially in adult groups that may be pre-disposed to CVD.

Abstract Our study aims to identify children at risk of developing high myopia for timely assessment and intervention, preventing myopia progression and complications in adulthood through the development of a deep learning system (DLS). Using a school-based cohort in Singapore comprising of 998 children (aged 6–12 years old), we train and perform primary validation of the DLS using 7456 baseline fundus images of 1878 eyes; with external validation using an independent test dataset of 821 baseline fundus images of 189 eyes together with clinical data (age, gender, race, parental myopia, and baseline spherical equivalent (SE)). We derive three distinct algorithms – image, clinical and mix (image + clinical) models to predict high myopia development (SE ≤ −6.00 diopter) during teenage years (5 years later, age 11–17). Model performance is evaluated using area under the receiver operating curve (AUC). Our image models (Primary dataset AUC 0.93–0.95; Test dataset 0.91–0.93), clinical models (Primary dataset AUC 0.90–0.97; Test dataset 0.93–0.94) and mixed (image + clinical) models (Primary dataset AUC 0.97; Test dataset 0.97–0.98) achieve clinically acceptable performance. The addition of 1 year SE progression variable has minimal impact on the DLS performance (clinical model AUC 0.98 versus 0.97 in primary dataset, 0.97 versus 0.94 in test dataset; mixed model AUC 0.99 versus 0.97 in primary dataset, 0.95 versus 0.98 in test dataset). Thus, our DLS allows prediction of the development of high myopia by teenage years amongst school-going children. This has potential utility as a clinical-decision support tool to identify “at-risk” children for early intervention.

Clinically significant genetic variation in Asian populations is under-characterized. Here, the authors show the diversity in prevalence and spectrum of human disease and pharmacogenetic variants in a multi-ethnic Asian population.

IntroductionAge-related macular degeneration (AMD) is one of the leading causes of vision impairment globally and early detection is crucial to prevent vision loss. However, the screening of AMD is resource dependent and demands experienced healthcare providers. Recently, deep learning (DL) systems have shown the potential for effective detection of various eye diseases from retinal fundus images, but the development of such robust systems requires a large amount of datasets, which could be limited by prevalence of the disease and privacy of patient. As in the case of AMD, the advanced phenotype is often scarce for conducting DL analysis, which may be tackled via generating synthetic images using Generative Adversarial Networks (GANs). This study aims to develop GAN-synthesized fundus photos with AMD lesions, and to assess the realness of these images with an objective scale.MethodsTo build our GAN models, a total of 125,012 fundus photos were used from a real-world non-AMD phenotypical dataset. StyleGAN2 and human-in-the-loop (HITL) method were then applied to synthesize fundus images with AMD features. To objectively assess the quality of the synthesized images, we proposed a novel realness scale based on the frequency of the broken vessels observed in the fundus photos. Four residents conducted two rounds of gradings on 300 images to distinguish real from synthetic images, based on their subjective impression and the objective scale respectively.Results and discussionThe introduction of HITL training increased the percentage of synthetic images with AMD lesions, despite the limited number of AMD images in the initial training dataset. Qualitatively, the synthesized images have been proven to be robust in that our residents had limited ability to distinguish real from synthetic ones, as evidenced by an overall accuracy of 0.66 (95% CI: 0.61–0.66) and Cohen’s kappa of 0.320. For the non-referable AMD classes (no or early AMD), the accuracy was only 0.51. With the objective scale, the overall accuracy improved to 0.72. In conclusion, GAN models built with HITL training are capable of producing realistic-looking fundus images that could fool human experts, while our objective realness scale based on broken vessels can help identifying the synthetic fundus photos.

Summary: Genomic researchers increasingly utilize commercial cloud service providers (CSPs) to manage data and analytics needs. CSPs allow researchers to grow Information Technology (IT) infrastructure on demand to overcome bottlenecks when combining large datasets. However, without adequate security controls, the risk of unauthorized access may be higher for data stored on the cloud. Additionally, regulators are mandating data access patterns and specific security protocols for the storage and use of genomic data. While CSP provides tools for security and regulatory compliance, building the necessary controls required for cloud solutions is not trivial. Research Assets Provisioning and Tracking Online Repository (RAPTOR) by the Genome Institute of Singapore is a cloud-native genomics data repository and analytics platform that implements a “five-safes” framework to provide security and governance controls to data contributors and users, leveraging CSP for sharing and analysis of genomic datasets without the risk of security breaches or running afoul of regulations.

Marie Loh, Weihua Zhang et al. use a genome-wide association study meta-analysis to examine variants associated with Type 2 diabetes (T2D) in South Asian and European ancestry cohorts. Their results provide further insights into the genetic mechanisms underlying T2D across ancestral populations.

Abstract Background Diagnostic performance of optical coherence tomography (OCT) to detect Alzheimer’s disease (AD) and mild cognitive impairment (MCI) remains limited. We assessed whether compensating the circumpapillary retinal nerve fiber layer (cpRNFL) thickness for multiple demographic and anatomical factors as well as the combination of macular layers improves the detection of MCI and AD. Methods This cross-sectional study of 62 AD (n = 92 eyes), 108 MCI (n = 158 eyes), and 55 cognitively normal control (n = 86 eyes) participants. Macular ganglion cell complex (mGCC) thickness was extracted. Circumpapillary retinal nerve fiber layer (cpRNFL) measurement was compensated for several ocular factors. Thickness measurements and their corresponding areas under the receiver operating characteristic curves (AUCs) were compared between the groups. The main outcome measure was OCT thickness measurements. Results Participants with MCI/AD showed significantly thinner measured and compensated cpRNFL, mGCC, and altered retinal vessel density (p

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.

PurposeThe COVID-19 pandemic has drastically disrupted global healthcare systems. With the higher demand for healthcare and misinformation related to COVID-19, there is a need to explore alternative models to improve communication. Artificial Intelligence (AI) and Natural Language Processing (NLP) have emerged as promising solutions to improve healthcare delivery. Chatbots could fill a pivotal role in the dissemination and easy accessibility of accurate information in a pandemic. In this study, we developed a multi-lingual NLP-based AI chatbot, DR-COVID, which responds accurately to open-ended, COVID-19 related questions. This was used to facilitate pandemic education and healthcare delivery.MethodsFirst, we developed DR-COVID with an ensemble NLP model on the Telegram platform (https://t.me/drcovid_nlp_chatbot). Second, we evaluated various performance metrics. Third, we evaluated multi-lingual text-to-text translation to Chinese, Malay, Tamil, Filipino, Thai, Japanese, French, Spanish, and Portuguese. We utilized 2,728 training questions and 821 test questions in English. Primary outcome measurements were (A) overall and top 3 accuracies; (B) Area Under the Curve (AUC), precision, recall, and F1 score. Overall accuracy referred to a correct response for the top answer, whereas top 3 accuracy referred to an appropriate response for any one answer amongst the top 3 answers. AUC and its relevant matrices were obtained from the Receiver Operation Characteristics (ROC) curve. Secondary outcomes were (A) multi-lingual accuracy; (B) comparison to enterprise-grade chatbot systems. The sharing of training and testing datasets on an open-source platform will also contribute to existing data.ResultsOur NLP model, utilizing the ensemble architecture, achieved overall and top 3 accuracies of 0.838 [95% confidence interval (CI): 0.826–0.851] and 0.922 [95% CI: 0.913–0.932] respectively. For overall and top 3 results, AUC scores of 0.917 [95% CI: 0.911–0.925] and 0.960 [95% CI: 0.955–0.964] were achieved respectively. We achieved multi-linguicism with nine non-English languages, with Portuguese performing the best overall at 0.900. Lastly, DR-COVID generated answers more accurately and quickly than other chatbots, within 1.12–2.15 s across three devices tested.ConclusionDR-COVID is a clinically effective NLP-based conversational AI chatbot, and a promising solution for healthcare delivery in the pandemic era.

Diabetic retinopathy (DR) is the major ocular complication of diabetes mellitus, and is a problem with significant global health impact. Major advances in diagnostics, technology and treatment have already revolutionized how we manage DR in the early part of the 21st century. For example, the accessibility of imaging with optical coherence tomography, and the development of anti-vascular endothelial growth factor (VEGF) treatment are just some of the landmark developments that have shaped the DR landscape over the last few decades. Yet, there are still more exciting advances being made. Looking forward to 2030, many of these ongoing developments are likely to further transform the field. First, epidemiologic projections show that the global burden of DR is not only increasing, but also shifting from high-income countries towards middle- and low-income areas. Second, better understanding of disease pathophysiology is placing greater emphasis on retinal neural dysfunction and non-vascular aspects of diabetic retinal disease. Third, a wealth of information is becoming available from newer imaging modalities such as widefield imaging systems and optical coherence tomography angiography. Fourth, artificial intelligence for screening, diagnosis and prognostication of DR will become increasingly accessible and important. Fifth, new pharmacologic agents targeting other non-VEGF-driven pathways, and novel therapeutic strategies such as gene therapy are being developed for DR. Finally, the classification system for diabetic retinal disease will need to be continually updated to keep pace with new developments. In this article, we discuss these major trends in DR that we expect to see in 2030 and beyond.

Diabetic retinopathy (DR) is a leading cause of visual impairment and blindness worldwide. Since DR was first recognized as an important complication of diabetes, there have been many attempts to accurately classify the severity and stages of disease. These historical classification systems evolved as understanding of disease pathophysiology improved, methods of imaging and assessing DR changed, and effective treatments were developed. Current DR classification systems are effective, and have been the basis of major research trials and clinical management guidelines for decades. However, with further new developments such as recognition of diabetic retinal neurodegeneration, new imaging platforms such as optical coherence tomography and ultra wide-field retinal imaging, artificial intelligence and new treatments, our current classification systems have significant limitations that need to be addressed. In this paper, we provide a historical review of different classification systems for DR, and discuss the limitations of our current classification systems in the context of new developments. We also review the implications of new developments in the field, to see how they might feature in a future, updated classification.

Objective: Lipid dysregulation and complement system (CS) activation are 2 important pathophysiology pathways for age-related macular degeneration (AMD). We hypothesized that the relationship between lipids and AMD may also differ according to CS genotype profile. Thus, the objective was to investigate the relationships between lipid-related metabolites and AMD according to CS genotypes. Design: Population-based cross-sectional study. Participants: A total of 6947 participants from Singapore Epidemiology of Eye Diseases study with complete relevant data were included. Methods: We investigated a total of 32 blood lipid–related metabolites from nuclear magnetic resonance metabolomics data including lipoproteins and their subclasses, cholesterols, glycerides, and phospholipids, as well as 4 CS single nucleotide polymorphisms (SNPs): rs10922109 (complement factor H), rs10033900 (complement factor I), rs116503776 (C2-CFB-SKIV2L), and rs2230199 (C3). We first investigated the associations between AMD and the 32 lipid-related metabolites using multivariable logistic regression models. Then, to investigate whether the effect of lipid-related metabolites on AMD differ according to the CS SNPs, we tested the possible interactions between the CS SNPs and the lipid-related metabolites. Main Outcome Measures: Age-related macular degeneration was defined using the Wisconsin grading system. Results: Among the 6947 participants, the prevalence of AMD was 6.1%, and the mean age was 58.3 years. First, higher levels of cholesterol in high-density lipoprotein (HDL) and medium and large HDL particles were associated with an increased risk of AMD, and higher levels of serum total triglycerides (TG) and several very-low–density lipoprotein subclass particles were associated with a decreased risk of AMD. Second, these lipids had significant interaction effects on AMD with 2 CS SNPs: rs2230199 and rs116503776 (after correction for multiple testing). For rs2230199, in individuals without risk allele, higher total cholesterol in HDL2 was associated with an increased AMD risk (odds ratio [OR] per standard deviation increase, 1.20; 95% confidence interval (CI), 1.06–1.37; P = 0.005), whereas, in individuals with at least 1 risk allele, higher levels of these particles were associated with a decreased AMD risk (OR, 0.69; 95% CI, 0.45–1.05; P = 0.079). Conversely, for rs116503776, in individuals without risk allele, higher serum total TG were associated with a decreased AMD risk (OR, 0.84; 95% CI, 0.74–0.95; P = 0.005), whereas, in individuals with 2 risk alleles, higher levels of these particles were associated with an increased risk of AMD (OR, 2.3, 95% CI, 0.99–5.39, P = 0.054). Conclusions: Lipid-related metabolites exhibit opposite directions of effects on AMD according to CS genotypes. This indicates that lipid metabolism and CS may have synergistic interplay in the AMD pathogenesis.

IntroductionAlzheimer's disease (AD) and age-related eye diseases pose an increasing burden as the world's population ages. However, there is limited understanding on the association of AD/cognitive impairment, no dementia (CIND) with age-related eye diseases.MethodsIn this cross-sectional, memory clinic-based study of multiethnic Asians aged 50 and above, participants were diagnosed as AD (n = 216), cognitive impairment, no dementia (CIND) (n = 252), and no cognitive impairment (NCI) (n = 124) according to internationally accepted criteria. Retinal photographs were graded for the presence of age-related macular degeneration (AMD) and diabetic retinopathy (DR) using standard grading systems. Multivariable-adjusted logistic regression models were used to determine the associations between neurological diagnosis and odds of having eye diseases.ResultsOver half of the adults had at least one eye disease, with AMD being the most common (60.1%; n = 356), followed by DR (8.4%; n = 50). After controlling for age, sex, race, educational level, and marital status, persons with AD were more likely to have moderate DR or worse (OR = 2.95, 95% CI = 1.15–7.60) compared with NCI. In the fully adjusted model, the neurological diagnosis was not associated with AMD (OR = 0.75, 95% CI = 0.45–1.24).ConclusionPatients with AD have an increased odds of having moderate DR or worse, which suggests that these vulnerable individuals may benefit from specific social support and screening for eye diseases.

Purpose: To investigate serum cholesterol efflux capacity (the ability of the serum to accept cholesterol) and factors that regulate it using nuclear magnetic resonance-quantified measures of lipoprotein particle composition and size and apolipoproteins metrics in patients with age-related macular degeneration (AMD). Design: Case-control study. Participants: Four hundred two serum samples from 80 patients with early AMD (eAMD), and 212 patients with neovascular AMD (nAMD), including 80 with typical nAMD (tAMD) and 132 with polypoidal choroidal vasculopathy (PCV), and 110 age- and gender matched control participants. Methods: Serum from participants showed cholesterol efflux capacity measured using in vitro cell assays and lipoprotein subfractions measured using nuclear magnetic resonance (Nightingale, Ltd). Associations between cholesterol efflux capacity (measured in percentage) and lipid subfractions were investigated in the patients and control participants. Main Outcome Measures: Cholesterol efflux capacity and lipid subfractions in control, eAMD, and nAMD. Associations between HDL subfractions and cholesterol efflux capacity. Results: Cholesterol efflux capacity was higher in patients with eAMD (68.0 ± 11.3% [mean ± standard deviation]) and nAMD (75.9 ± 27.7%) than in the control participants (56.9 ± 16.7%) after adjusting for age, gender, and use of lipid-lowering drug (P < 0.0001). Nuclear magnetic resonance lipidomics demonstrated that the mean diameter of HDL was larger both in eAMD (9.96 ± 0.27 mm [mean ± standard deviation]) and PCV (9.97 ± 0.23 mm) compared with that of the control participants (9.84 ± 0.24 mm; P = 0.0001 for both). Among the 28 HDL subfractions, most of the small, medium, and large HDLs, but none of the 7 extra large HDLs fractions, were associated moderately with cholesterol efflux capacity in eAMD and PCV (R = 0.149–0.277). Conclusions: Serum cholesterol efflux capacity was increased in eAMD and PCV, but not tAMD, possibly reflecting differential underlying pathophysiologic features of lipid dysregulation in tAMD and PCV. Further studies should be directed toward investigating the diverse biological activities of HDL in AMD, including macular pigment transport, regulation of inflammation, and local cholesterol transport system.

Abstract This study aimed to determine COVID-19-related awareness, knowledge, impact and preparedness among elderly Asians; and to evaluate their acceptance towards digital health services amidst the pandemic. 523 participants (177 Malays, 171 Indians, 175 Chinese) were recruited and underwent standardised phone interview during Singapore’s lockdown period (07 April till 01 June 2020). Multivariable logistic regression models were performed to evaluate the associations between demographic, socio-economic, lifestyle, and systemic factors, with COVID-19 awareness, knowledge, preparedness, well-being and digital health service acceptance. The average perception score on the seriousness of COVID-19 was 7.6 ± 2.4 (out of 10). 75.5% of participants were aware that COVID-19 carriers can be asymptomatic. Nearly all (≥ 90%) were aware of major prevention methods for COVID-19 (i.e. wearing of mask, social distancing). 66.2% felt prepared for the pandemic, and 86.8% felt confident with government’s handling and measures. 78.4% felt their daily routine was impacted. 98.1% reported no prior experience in using digital health services, but 52.2% felt these services would be helpful to reduce non-essential contact. 77.8% were uncomfortable with artificial intelligence software interpreting their medical results. In multivariable analyses, Chinese participants felt less prepared, and more likely felt impacted by COVID-19. Older and lower income participants were less likely to use digital health services. In conclusion, we observed a high level of awareness and knowledge on COVID-19. However, acceptance towards digital health service was low. These findings are valuable for examining the effectiveness of COVID-19 communication in Singapore, and the remaining gaps in digital health adoption among elderly.

Abstract The natural history and clinical significance of pachydrusen is unclear. This study aims to compare the longitudinal changes of eyes with pachydrusen and soft drusen and progression to exudative macular neovascularisation (MNV). Patients with a diagnosis of MNV in one eye only and the fellow eye was selected as the study eye. Study eyes were required to have pachydrusen or soft drusen on fundus photographs and follow up of at least 2 years or until exudative MNV occurred. Systematic grading was performed at baseline and change in drusen area and onset of exudative MNV recorded over the period of follow up. A total of 75 eyes from 75 patients (29 with pachydrusen and 46 with soft drusen) were included. There was no difference in the rate of progression to exudative MNV in the soft and pachydrusen groups (13.3% versus 24.1%, p = 0.38). Pachydrusen, as compared to soft drusen, was associated with polypoidal choroidal vasculopathy subtype (85.7% versus 16.7%, p

Abstract The objective was to examine prospectively the association between retinal microvascular signs and development of diabetic kidney disease (DKD) in Asian and White populations. We analysed two population-based cohorts, composing of 1,221 Asians (SEED) and 703 White (WESDR) adults with diabetes. Retinal microvascular signs at baseline included vascular caliber (arteriolar—CRAE, and venular—CRVE) and diabetic retinopathy (DR). Incident cases of DKD were identified after ~ 6-year. Incident cases were defined based on eGFR in SEED and proteinuria or history of renal dialysis in WESDR. The incidence of DKD were 11.8% in SEED and 14.0% in WESDR. Wider CRAE in SEED (OR = 1.58 [1.02, 2.45]) and wider CRVE (OR = 1.69 [1.02, 2.80)) in WESDR were associated with increased risk of DKD. Presence of DR was associated with an increased risk of DKD in both cohorts (SEED: OR = 1.91 [1.21, 3.01] in SEED, WESDR: OR = 1.99 [1.18, 3.35]). Adding DR and retinal vascular calibers in the model beyond traditional risk factors led to an improvement of predictive performance of DKD risk between 1.1 and 2.4%; and improved classification (NRI 3 between 9%). Microvascular changes in the retina are longitudinally associated with risk of DKD.

Abstract The coronavirus disease 2019 (COVID-19) pandemic has overwhelmed healthcare services, faced with the twin challenges in acutely meeting the medical needs of patients with COVID-19 while continuing essential services for non-COVID-19 illnesses. The need to re-invent, re-organize and transform healthcare and co-ordinate clinical services at a population level is urgent as countries that controlled initial outbreaks start to experience resurgences. A wide range of digital health solutions have been proposed, although the extent of successful real-world applications of these technologies is unclear. This study aims to review applications of artificial intelligence (AI), telehealth, and other relevant digital health solutions for public health responses in the healthcare operating environment amidst the COVID-19 pandemic. A systematic scoping review was performed to identify potentially relevant reports. Key findings include a large body of evidence for various clinical and operational applications of telehealth (40.1%, n = 99/247). Although a large quantity of reports investigated applications of artificial intelligence (AI) (44.9%, n = 111/247) and big data analytics (36.0%, n = 89/247), weaknesses in study design limit generalizability and translation, highlighting the need for more pragmatic real-world investigations. There were also few descriptions of applications for the internet of things (IoT) (2.0%, n = 5/247), digital platforms for communication (DC) (10.9%, 27/247), digital solutions for data management (DM) (1.6%, n = 4/247), and digital structural screening (DS) (8.9%, n = 22/247); representing gaps and opportunities for digital public health. Finally, the performance of digital health technology for operational applications related to population surveillance and points of entry have not been adequately evaluated.

Abstract We examined the choriocapillaris microvasculature using a non-invasive swept-source optical coherence tomography angiography (SS-OCTA) in 41 healthy controls and 71 hypertensive patients and determined possible correlations with BP and renal parameters. BP levels, serum creatinine and urine microalbumin/creatinine ratio (MCR) specimens were collected. The estimated glomerular filtration rate (eGFR) was calculated based on CKD-EPI Creatinine Equation. The main outcome was choriocapillaris flow deficits (CFD) metrics (density, size and numbers). The CFD occupied a larger area and were fewer in number in the hypertensive patients with poor BP control (407 ± 10 µm2; 3260 ± 61) compared to the hypertensives with good BP control (369 ± 5 µm2; 3551 ± 41) and healthy controls (365 ± 11 µm2; 3581 ± 84). Higher systolic BP (β = 9.90, 95% CI, 2.86–16.93), lower eGFR (β = − 0.85; 95% CI, − 1.58 to − 0.13) and higher urine MCR (β = 1.53, 95% CI, 0.32–2.78) were associated with larger areas of CFD. Similar significant associations with systolic BP, eGFR and urine MCR were found with number of CFD. These findings highlight the potential role of choriocapillaris imaging using SS-OCTA as an indicator of systemic microvascular abnormalities secondary to hypertensive disease.

Abstract 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.

Abstracts Background The retina and brain share many neuronal and vasculature characteristics. We investigated the retinal microvasculature in Alzheimer’s disease (AD) and mild cognitive impairment (MCI) using optical coherence tomography angiography (OCTA). Methods In this cross-sectional study, 24 AD participants, 37 MCI participants, and 29 controls were diagnosed according to internationally accepted criteria. OCTA images of the superficial and deep capillary plexus (SCP, DCP) of the retinal microvasculature were obtained using a commercial OCTA system (Zeiss Cirrus HD-5000 with AngioPlex, Carl Zeiss Meditec, Dublin, CA). The main outcome measures were vessel density (VD) and fractal dimension (FD) in the SCP and DCP within a 2.5-mm ring around the fovea which were compared between groups. Perfusion density of large vessels and foveal avascular zone (FAZ) area were additional outcome parameters. Results Age, gender, and race did not differ among groups. However, there was a significant difference in diabetes status (P = 0.039) and systolic blood pressure (P = 0.008) among the groups. After adjusting for confounders, AD participants showed significantly decreased VD in SCP and DCP (P = 0.006 and P = 0.015, respectively) and decreased FD in SCP (P = 0.006), compared to controls. MCI participants showed significantly decreased VD and FD only in SCP (P = 0.006 and P 0.05) compared with controls. There was no difference in the OCTA variables between AD and MCI (P > 0.05). Perfusion density of large vessels and FAZ area did not differ significantly between groups (P > 0.05). Conclusions and relevance Eyes of patients with AD have significantly reduced macular VD in both plexuses whereas MCI participants only showed reduction in the superficial plexus. Changes in the retinal microvasculature and capillary network may offer a valuable insight on the brain in AD.

Here, the authors report a multi-ethnic genome wide association meta-analysis of 12 studies from the International Cataract Genetics Consortium. They find six new loci associated with age-related nuclear cataract, in addition to replicating the association at CRYAA, and suggest a strong genetic link between age-related nuclear and congenital cataracts.

Background This study examined the associations between quantitative optical coherence tomography angiography (OCTA) parameters and myocardial abnormalities as documented on cardiovascular magnetic resonance imaging in patients with systemic hypertension. Methods and Results We conducted a cross‐sectional study of 118 adults with hypertension (197 eyes). Patients underwent cardiovascular magnetic resonance imaging and OCTA (PLEX Elite 9000, Carl Zeiss Meditec). Associations between OCTA parameters (superficial and deep retinal capillary density) and adverse cardiac remodeling (left ventricular mass, remodeling index, interstitial fibrosis, global longitudinal strain, and presence of left ventricular hypertrophy) were studied using multivariable linear regression analysis with generalized estimating equations. Of the 118 patients with hypertension enrolled (65% men; median [interquartile range] age, 59 [13] years), 29% had left ventricular hypertrophy. After adjusting for age, sex, systolic blood pressure, diabetes, and signal strength of OCTA scans, patients with lower superficial capillary density had significantly higher left ventricular mass (β=−0.150; 95% CI, −0.290 to −0.010), higher interstitial volume (β=−0.270; 95% CI, −0.535 to −0.0015), and worse global longitudinal strain (β=−0.109; 95% CI, −0.187 to −0.032). Lower superficial capillary density was found in patients with hypertension with replacement fibrosis versus no replacement fibrosis (16.53±0.64 mm‐1 versus 16.96±0.64 mm‐1; P=0.003). Conclusions We showed significant correlations between retinal capillary density and adverse cardiac remodeling markers in patients with hypertension, supporting the notion that the OCTA could provide a non‐invasive index of microcirculation alteration for vascular risk stratification in people with hypertension.

Abstract Background Systematically review the evidence describing the impact of anti–vascular endothelial growth factor (anti-VEGF) therapy on neovascular age-related macular degeneration (nAMD) patient outcomes and healthcare resource utilization. Methods A systematic literature review was completed using Medline and EMBASE for publications prior to July 2018, and proceedings from major ophthalmology conferences (January 2016 to July 2018). The search strategy combined terms for nAMD with terms for anti-VEGF and study design. The review focused on publications describing the impact of anti-VEGF on blindness, visual impairment, vision-related quality of life (VRQoL), mortality, and costs. The search targeted data collected in epidemiological or observational studies to reflect real-world outcomes but also considered modeling-based approaches. Results The use of anti-VEGF in clinical practice was associated with significant reduction in the incidence of blindness by nAMD. Population-based analyses reported reduction in incidence among the general population of 47% (9.1 cases/100,000 in 2006 to 4.8 cases/100,000 in 2011). Among patients aged ≥50 years, a reduction of 50% was observed (52.2 cases/100,000 in 2000 to 25.7 cases/100,000 in 2010). In some cases, the odds of decreased vision (defined as decline from normal to moderate, moderate to severe, or severe to blindness) fell by 41% following introduction of anti-VEGF. Patients’ VRQoL improved with treatment, with patients reporting a positive impact shortly after treatment was initiated. Change on National Eye Institute 25-Item Visual Function Questionnaire score from baseline to month 12 ranged from 0.7 to 4.4. Although nAMD patients report signs of depression and anxiety, the evidence suggests that there is no association between the use of anti-VEGF and the prevalence or diagnosis of depression. The introduction of anti-VEGF led to increased overall treatment costs due to replacement of existing less frequently administered treatments (e.g. photodynamic therapy) and increased number of patients treated (prior to anti-VEGF, only ~ 20% of patients were eligible for treatment). Conclusions The introduction of anti-VEGF agents has been associated with a positive impact on patient-relevant outcomes, including a significant reduction in incidence of blindness and visual impairment by nAMD. Anti-VEGF agents replaced less-effective treatments, improving patient outcomes and broadening the patient population eligible for treatment.

Abstract Deep learning (DL) has been shown to be effective in developing diabetic retinopathy (DR) algorithms, possibly tackling financial and manpower challenges hindering implementation of DR screening. However, our systematic review of the literature reveals few studies studied the impact of different factors on these DL algorithms, that are important for clinical deployment in real-world settings. Using 455,491 retinal images, we evaluated two technical and three image-related factors in detection of referable DR. For technical factors, the performances of four DL models (VGGNet, ResNet, DenseNet, Ensemble) and two computational frameworks (Caffe, TensorFlow) were evaluated while for image-related factors, we evaluated image compression levels (reducing image size, 350, 300, 250, 200, 150 KB), number of fields (7-field, 2-field, 1-field) and media clarity (pseudophakic vs phakic). In detection of referable DR, four DL models showed comparable diagnostic performance (AUC 0.936-0.944). To develop the VGGNet model, two computational frameworks had similar AUC (0.936). The DL performance dropped when image size decreased below 250 KB (AUC 0.936, 0.900, p

Purpose: To assess the effect of axial length (AL) on the prevalence of pathologic myopia (PM) and associated myopic features in a Singaporean hospital-based cohort of patient with high myopia (HM).Methods: In total, 923 HM eyes from 495 individuals were recruited from the Myopic and Pathologic Eyes in Singapore (MyoPES) cohort and underwent ocular biometry, fundus photography, fundus autofluorescence, and swept-source optical coherence tomography (SS-OCT). Images were analyzed for the presence of myopic macular degeneration (MMD), myopic choroidal neovascularization (mCNV), myopic traction maculopathy (MTM), peripapillary atrophy (PPA), myopic tilted disc, posterior staphyloma (PS), dome-shaped macula (DSM), vitremacular adhesions (VMA), and the epiretinal membrane (ERM). Eyes were stratified into quartiles based on ALs to determine cut-off values to perform comparisons between shorter-length and longer-length groups. A χ2-test was done to determine the difference in the prevalence of pathologies between groups.Results: Overall, mean AL was 29.2 ± 2.2 mm (range 25.0–36.7 mm). Myopic macular degeneration, PPA, myopic tilted disc, and ERM have AL threshold of ≥27.5 mm, whereas MTM has an AL threshold of ≥29.0 mm. We found that there was a significantly higher prevalence of MMD (88.2 vs. 49.4%; p < 0.001), PPA (98.1 vs. 80.1%; p < 0.001), myopic tilted disc (72.7 vs. 50.2%; p < 0.001), and ERM (81.4 vs. 17.3%; p = 0.003) in eyes with AL ≥ 27.5 mm vs. eyes without AL

Purpose(1) To investigate the relative importance of convenience (consultation frequency and injection frequency) against treatment outcomes (visual and anatomical outcomes) and out-of-pocket medical costs via a discrete choice experiment (DCE), and (2) to investigate how patient characteristics affect patient treatment preferences.MethodsEligibility criteria were: (1) receiving a neovascular age-related macular degeneration (nAMD) diagnosis; (2) receiving anti-VEGF treatment; (3) being ≥21 years old, and (4) being able to speak and understand English/Mandarin. Patients were presented with eight choice tasks and asked to choose between their current treatment and two hypothetical treatments that varied by six attributes: number of clinic visits in a year, number of injections in a year, vision quality, control of swelling in retina, drug labelling and out-of-pocket cost.ResultsThis analysis involved 180 patients. Based on latent class logistic regressions, vision quality was the most important attribute (34%) followed by cost (24%). The frequency of total clinic visits (15%) was the third most-important attribute, closely followed by labelling (12%) and control of retina swelling (11%). Injection frequency was the least important attribute (4%).ConclusionsVision quality was the most important attribute followed by the out-of-pocket costs. Given the same outcomes, patients preferred treatment regimens which require fewer total clinic visits. In comparison, injection frequency alone did not influence patient preferences. With increasing treatment options for nAMD, understanding patients' preferences can help clinicians in selecting agents and treatment regimen most preferred for each patient, which may lead to improved long-term adherence and outcomes.

Abstract Background To explore the prevalence and determinants of unawareness of diabetes, hypertension and hypercholesterolemia and its association with poor disease control in a multi-ethnic Asian population without cardiovascular disease (CVD). Methods We included 6904 Chinese, Malay and Indian individuals (mean age [SD] 58.2 [10.2] years; 52.6% female) with diabetes, hypertension and/or hypercholesterolemia from the cross-sectional population-based Singapore Epidemiology of Eye Diseases study (2004–2011). Diabetes was defined as random blood glucose ≥ 11.1 mmol/L or HbA1c > 6.5% or self-reported use of diabetes medication; hypertension as systolic blood pressure ≥ 140 mmHg or diastolic blood pressure ≥ 90 mmHg or self-reported use of anti-hypertensive treatment; and hypercholesterolemia as total cholesterol ≥ 6.2 mmol/L or self-reported use of lipid-lowering medications. Unawareness was based on participants’ answers to the questions: “Did your medical practitioner ever tell you that you have diabetes/hypertension/high cholesterol?” The determinants of unawareness, and its association with poor disease control, were assessed using multivariable binary logistic regression models adjusted for known potential confounders. Results Of the 2380 (34.5%), 5386 (78.0%) and 3607 (52.2%) with diabetes, hypertension and hypercholesterolemia, respectively, unawareness rates were 30.7%, 43.1% and 40.9%, respectively. Having a higher BMI, particularly if obese, and Malay ethnicity were associated with greater unawareness of diabetes; Malay and Indian ethnicities and current smoking with greater unawareness of hypertension; and education ≤6 years, current smoking, and blue collar jobs or unemployment with greater unawareness of hypercholesterolemia (all P < 0.05). Lack of awareness of each condition was independently associated with poorer disease control in the case of hypertension and hypercholesterolemia, while the converse was true for diabetes (all P < 0.05). Conclusions Unawareness of diabetes, hypertension, or hypercholesterolemia is high in Singapore, with risk factors varying across all three diseases, although Malay ethnicity is a consistent one. Unawareness was also associated with poor management for hypertension and hypercholesterolemia. Public health education and screening programs should target at-risk individuals, especially Malays, to reduce the likelihood of incident CVD.