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National and subnational estimates of the prevalence of diabetic retinopathy and vision-threatening diabetic retinopathy (VTDR) are needed to inform the stepwise implementation of systematic retinal screening for people with diabetes in India to decrease the rate of blindness. We aimed to assess these national and subnational estimates and to stratify the prevalence of diabetic retinopathy and VTDR on the basis of people with known versus undiagnosed diabetes, urban versus rural residence, and epidemiological transition level (ETL) and Socio-demographic Index (SDI) categories of states.We did a multicentre cross-sectional screening study for diabetic retinopathy using a complex cluster sampling design in people aged 40 years or older in ten Indian states and one union territory between Dec 20, 2018, and March 20, 2020. We did non-mydriatic retinal screening and assessed risk factor burden for people with diabetes. We estimated nationally weighted prevalence of diabetic retinopathy and VTDR for individuals with known and undiagnosed diabetes by urban versus rural residence, and by state categorisation by ETL and SDI. We also assessed adjusted risk factors.From 42 146 participants screened, 7910 (18·8%) were identified to have diabetes. Of these, 6133 (77·5%; 4350 with known diabetes and 1783 with undiagnosed diabetes) had gradable retinal images. 3411 (56%) participants were women and 2722 (44%) were men, and the median age was 56 years (IQR 49-65). The estimated national prevalence was 12·5% (95% CI 11·0-14·2) for diabetic retinopathy and 4·0% (3·4-4·8) for VTDR, with no significant differences between urban and rural residence for diabetic retinopathy. Compared with individuals with undiagnosed diabetes, we observed a higher prevalence of diabetic retinopathy (15·5% [13·4-17·8] vs 8·0% [6·3-10·1]) and VTDR (5·3% [4·5-6·3] vs 2·4% [1·6-3·6]) in individuals with known diabetes. The prevalence was significantly lower in low ETL-SDI states compared with high and middle ETL-SDI states for diabetic retinopathy (by 7·0%, 1·9-12·2, p=0·024) and VTDR (by 4·8%, 3·0-6·6, p0·0001). Hyperglycaemia was the strongest modifiable risk factor.We estimate that, in absolute numbers, approximately 3 million people aged 40 years or older have VTDR in India, with a higher prevalence in those with known diabetes residing in high and middle ETI-SDI states.UKRI Global Challenge Research Fund.

This paper discusses the importance of investigating DR using machine learning and a computational method to rank DR risk factors by importance using different machine learning models. The dataset was collected from four large population-based studies conducted in India between 2001 and 2010 on the prevalence of DR and its risk factors. We deployed different machine learning models on the dataset to rank the importance of the variables (risk factors). The study uses a t-test and Shapely additive explanations (SHAP) to rank the risk factors. Then, it uses five machine learning models (K-Nearest Neighbor, Decision Tree, Support Vector Machines, Logistic Regression, and Naive Bayes) to identify the unimportant risk factors based on the area under the curve criterion to predict DR. To determine the overall significance of risk variables, a weighted average of each classifier’s importance is used. The ranking of risk variables is provided to machine learning models. To construct a model for DR prediction, the combination of risk factors with the highest AUC is chosen. The results show that the risk factors glycosylated hemoglobin and systolic blood pressure were present in the top three risk factors for DR in all five machine learning models when the t-test was used for ranking. Furthermore, the risk factors, namely, systolic blood pressure and history of hypertension, were present in the top five risk factors for DR in all the machine learning models when SHAP was used for ranking. Finally, when an ensemble of the five machine learning models was employed, independently with both the t-test and SHAP, systolic blood pressure and diabetes mellitus duration were present in the top four risk factors for diabetic retinopathy. Decision Tree and K-Nearest Neighbor resulted in the highest AUCs of 0.79 (t-test) and 0.77 (SHAP). Moreover, K-Nearest Neighbor predicted DR with 82.6% (t-test) and 78.3% (SHAP) accuracy.

AIM: To evaluate the effectiveness of tele-ophthalmology (TO) versus face-to-face screening for diabetic retinopathy (DR) in diabetes care centers (DCC) across India. METHODS: This is an observational, multicenter, retrospective, cross-sectional study of DR screening in individuals with diabetes performed across 35 branches of a chain of DCC in 20 cities in India over 1 year. In 30 DCC, DR screening was performed by TO, where retinal images obtained using Fundus on Phone camera were uploaded through the telemedicine network for centralized DR grading by eight retina specialists. In five DCC, DR screening was performed by fundus examination (FE) by the same retina specialists. The rate of detection of sight-threatening DR (STDR) (defined as the presence of proliferative DR and/or diabetic macular edema) through the two modes was compared. RESULTS: A total of 58,612 individuals were screened for DR from January 1, 2018 to December 31, 2018: 25,316 by TO and 33,296 by FE. The mean age and mean duration of diabetes of the individuals with diabetes screened by TO was 55.8 ± 11.2 years and 9.5 ± 7.3 years; and in individuals screened by FE, it was 57.5 ± 11.6 years and 11.5 ± 8.0 years respectively. The mean glycated hemoglobin was 8.8% ± 2.1% and 8.5% ± 1.9% in the two groups, respectively. Any DR was detected in 31.7% (95% confidence interval [CI]: 31.0–32.3) by tele-screening and in 38.5% (95% CI: 37.9–39.0) by FE, whereas STDR was detected in 7.3% (95% CI: 7.0–7.7) by TO and in 10.5% (95% CI: 10.2–10.9) by FE. Overall, 11.4% individuals with diabetes in the TO group, including 4.1% with ungradable images, were advised referral to retina specialists for further management. CONCLUSION: Screening for DR at DCC using TO is feasible and effective for STDR detection in India and may be adopted throughout India.

To examine the inter-observer agreement between two retina specialists in grading diabetic retinopathy (DR) severity in ultra-wide-field fundus photographs.Two hundred and seventy patients with diabetes, who visited the vitreoretinal specialty at a tertiary eye care hospital, with or without DR underwent comprehensive ophthalmic examination, dilated retinal exam and Optos ultra-wide-field (UWF) retinal photography. Optos images were graded for DR severity based on the International Clinical Diabetic Retinopathy Disease Severity Scale by two retina specialists with same number of years of experience, masked to the clinical details of the participants.The two graders showed agreement in 229/270 images (84.8%) and disagreement in 41/270 images (15.2%). The unweighted kappa for agreement between graders was k = 0.715, SE = 0.037 and the weighted kappa was k = 0.838, SE = 0.022. No DR was identified in 170/270 (62.9%) patients, mild NPDR in 15/270 (5.6%) patients, moderate NPDR in 35/270 (12.9%) patients, severe NPDR in 4/270 (1.48%) patient and PDR in 5/270 (1.85%) patients by both graders. Disagreement was neither related to the learning curve of graders nor with the patient's age (p = 0.574), gender (p = 0.169), duration of diabetes (0.660) or the lens being phakic or pseudophakic (p = 0.171) on logistic regression.The impact of disagreement noted between observers in grading DR on UWF fundus photographs should be considered when utilizing UWF system in clinical studies.

Objective To examine the relationship of visual function as assessed by visual acuity, contrast sensitivity, and multifocal electroretinography (mfERG) to macular structural and microvascular measures on optical coherence tomography (OCT) and angiography (OCTA) in individuals with diabetes. Methods This is a prospective observational study conducted at a tertiary eye care centre in India. Right eyes of 121 adults with type 2 diabetes with no diabetic retinopathy (DR), mild or moderate nonproliferative DR (NPDR) were examined. Severe NPDR, proliferative DR and diabetic macular oedema were excluded. Participants underwent assessment of glycated haemoglobin (HbA1C), blood pressure, best corrected visual acuity (LogMAR), contrast sensitivity (CS), mfERG, ultrawide field fundus photography, OCT and OCTA. Correlations were assessed by Spearman's rank correlation (rho). Results Of the total of 121 eyes, 89 had No DR, 32 had mild to moderate NPDR. In the No DR group, the LogMAR acuity was significantly and negatively correlated to central subfoveal thickness (CST) (rho = -0.420), macular vessel density (rho = -0.270) and perfusion (rho = -0.270). (ii) Contrast sensitivity correlated to foveal avascular zone circularity (rho = 0.297); (iii) mfERG P1 response densities were better with higher macular perfusion index (rho = 0.240). In the NPDR group, the LogMAR acuity also showed a significant negative correlation to CST (rho = -0.379). Other correlations were not significant. Conclusion Retinal and visual functional changes are evident in diabetic patients with No DR and are correlated to subclinical retinal structural changes detectable using multimodal imaging.

Introduction: To report the 10-year rate of vitrectomies and the associated factors in people with proliferative diabetic retinopathy (PDR) from a multicentric cohort of people with diabetes mellitus. Methods: Ten centres in India with established vitreoretinal (VR) services for over 10 years were invited to provide long-term data on PDR. People with Type 1 or 2 diabetes with a clinical diagnosis of active PDR in 1 or both eyes were included. Baseline data collected included age, sex, duration of diabetes, source of referral and best-corrected visual acuity, and diabetic retinopathy status in both eyes. Available follow-up data included the numbers of panretinal photocoagulation (PRP) sessions, cataract surgery, treatment of diabetic macular oedema, use of anti-vascular endothelial growth factor (VEGF) therapy, vitrectomy with or without retinal surgeries over 10 years. Results: Over 10 years, 89% needed supplemental PRP after initial complete PRP. One-third required retinal surgery, 16% needed intravitreal injection. Men (74.5%) had significant higher risk for vitreous (VR) surgery. Of the group with low-risk PDR, 56.8% did not require VR surgery, p < 0.001. Of the patients who underwent cataract surgery and had intravitreal anti-VEGF injections, 78.5 and 28.2% needed subsequent vitreous (VR) surgery, p = 0.006 and

To study the clinical characteristics and incidence of microvascular complications among childhood and adolescent onset type 1 (T1DM) and type 2 diabetes (T2DM) seen at a tertiary care diabetes center in India.From our electronic medical records, we retrieved clinical and biochemical details of 4555 individuals with childhood and adolescent onset diabetes (diagnosed below the age of 20 years) seen between 1992 and 2017. T1DM was diagnosed if there was history of ketoacidosis or fasting C-peptide0.3 PMol/mL and stimulated C-peptide0.6 PMol/mL or if insulin treatment was required from the time of diagnosis. T2DM was diagnosed based on absence of ketosis, or fasting C-peptide ≥0.6 PMol/mL and stimulated1.0 PMoL/mL, or response to oral hypoglycemic agents for more than 2 years. We calculated the incidence rates of retinopathy (presence of at least one definite microaneurysm by retinal photography), nephropathy (urinary albumin excretion ≥30 μg/mg of creatinine) and neuropathy (vibration perception threshold ≥20 V) per 1000 person-years of follow up.Among the 4555 individuals with childhood and adolescent-onset diabetes, 71.4% had T1DM, 19.5% T2DM and 9.1% other forms of diabetes. Age at first visit and duration of diabetes were significantly higher in T2DM when compared to T1DM. The age adjusted incidence of retinopathy was 52.9/1000 person years (Confidence Intervals [CI]: 42.9-62.8) in T1DM and 49.8/1000 person years (CI 30.8-68.8) in T2DM; nephropathy, 6.2 (CI 3.3-9.0) and 13.8 (CI 5.6-22.0); and neuropathy, 8.8(CI 3.6-14.0) and 24.0 (CI 9.8-38.2) in T1DM and T2DM, respectively.The incidence of microvascular complications is high among childhood and adolescent-onset T1DM and T2DM and these calls for more aggressive control of diabetes.

Purpose: To assess the proportion of people with type 2 diabetes mellitus (T2DM) with diabetic retinopathy (DR) and sight-threatening DR (STDR) and associated risk factors in select eye-care facilities across India. Methods: In this observational study, data of people with T2DM presenting for the first time at the retina clinic of eye-care facilities across India was recorded. Data collected in 2016 over 6 months included information on systemic, clinical, and ocular parameters. International Clinical Diabetic Retinopathy (ICDR) classification scale was used to grade DR. STDR was defined as presence of severe nonproliferative (NPDR), proliferative diabetic retinopathy (PDR), and/or diabetic macular edema (DME). Results: The analysis included 11,182 people with T2DM from 14 eye-care facilities (mean age 58.2 ± 10.6 years; mean duration of diabetes 9.1 ± 7.6 years; 59.2% male). The age-standardized proportion of DR was 32.3% (95%Confidence Interval, CI: 31.4-33.2) and STDR was 19.1% (95%CI: 18.4-19.8). DME was diagnosed in 9.1% (95%CI: 8.5-9.6) and 10.7% (95%CI: 10.1-11.3) people had PDR. Statistically significant factors associated with increased risk of DR (by multivariate logistic regression analysis) were: male gender (Odds ratio[OR] 1.57, 95%CI: 1.16-2.15); poor glycemic control–glycated hemoglobin (HbA1c >10%)(OR 2.39, 95% CI: 1.1-5.22); requirement of insulin (OR 2.55, 95%CI: 1.8-3.6);history of hypertension (OR 1.42, 95%CI: 1.06-1.88) and duration of diabetes >15 years (OR 5.25, 95%CI: 3.01-9.15). Conclusion: Diabetic retinopathy was prevalent in 1/3rd and sight-threatening DR in 1/5th of people with T2DM presenting at eye-care facilities in this pan-India facility-based study. The duration of diabetes was the strongest predictor for retinopathy.

Artificial intelligence (AI) in healthcare is the use of computer-algorithms in analyzing complex medical data to detect associations and provide diagnostic support outputs. AI and deep learning (DL) find obvious applications in fields like ophthalmology wherein huge amount of image-based data need to be analyzed; however, the outcomes related to image recognition are reasonably well-defined. AI and DL have found important roles in ophthalmology in early screening and detection of conditions such as diabetic retinopathy (DR), age-related macular degeneration (ARMD), retinopathy of prematurity (ROP), glaucoma, and other ocular disorders, being successful inroads as far as early screening and diagnosis are concerned and appear promising with advantages of high-screening accuracy, consistency, and scalability. AI algorithms need equally skilled manpower, trained optometrists/ophthalmologists (annotators) to provide accurate ground truth for training the images. The basis of diagnoses made by AI algorithms is mechanical, and some amount of human intervention is necessary for further interpretations. This review was conducted after tracing the history of AI in ophthalmology across multiple research databases and aims to summarise the journey of AI in ophthalmology so far, making a close observation of most of the crucial studies conducted. This article further aims to highlight the potential impact of AI in ophthalmology, the pitfalls, and how to optimally use it to the maximum benefits of the ophthalmologists, the healthcare systems and the patients, alike.

To evaluate the effect of metabolic surgery on microvascular changes associated with diabetic retinopathy (DR) and diabetic kidney disease (DKD) in obese Asian Indians with type 2 diabetes (T2DM), one year after metabolic surgery.This is a follow up study in 21 obese Asian Indians with T2DM who underwent metabolic surgery (MS). Diabetic microvascular complications were assessed before and one-year post surgery using urinary albumin, protein creatinine ratio, eGFR, retinal colour photography and Optical coherence tomography (OCT).Microalbuminuria (54±26 vs 28±16 vs 21±6 µg/mg, plt;0.001) and protein creatinine ratio (0.4±0.1 vs 0.2±0.03 vs 0.1±0.02, plt;0.05) reduced significantly 6 months and one year after Metabolic surgery (MS) respectively compared to baseline values. Estimated Glomerular Filtration (eGFR) rate and creatinine was stable and there was no decline in renal function one year after MS. DR was present in eight individuals at baseline. After metabolic surgery, 12 % of individuals achieved regression of DR and 12% individuals showed a one step regression from severe to moderate non proliferative DR while 12 % individuals progressed from moderate to severe non proliferative DR. Of the 14 (53.8%) individuals who had micro or macroalbuminuria at baseline, 43% individuals reverted back to normoalbuminuria. There was also a reduction in the usage of anti- hypertensive medications after MS.In obese Asian Indians with T2DM, metabolic surgery reduced urinary microalbuminuria and protein creatinine ratios at one-year post MS. MS resulted in stable D. Retionpathy status one-year post surgery. MS may help to improve in stabilisation of the microvascular complications in obese patients with T2DM.

Background: Delayed diagnosis and treatment of sight threatening diabetic retinopathy (STDR) is a common cause of visual impairment in people with Type 2 diabetes. Therefore, systematic regular retinal screening is recommended, but global coverage of such services is challenging. We aimed to develop and validate predictive models for STDR to identify 'at-risk' population for retinal screening. Methods: Models were developed using datasets obtained from general practices in inner London, United Kingdom (UK) on adults with type 2 Diabetes during the period 2007-2017. Three models were developed using Cox regression and model performance was assessed using C statistic, calibration slope and observed to expected ratio measures. Models were externally validated in cohorts from Wales, UK and India. Findings: A total of 40,334 people were included in the model development phase of which 1427 (3·54%) people developed STDR. Age, gender, diabetes duration, antidiabetic medication history, glycated haemoglobin (HbA1c), and history of retinopathy were included as predictors in the Model 1, Model 2 excluded retinopathy status, and Model 3 further excluded HbA1c. All three models attained strong discrimination performance in the model development dataset with C statistics ranging from 0·778 to 0·832, and in the external validation datasets (C statistic 0·685 - 0·823) with calibration slopes closer to 1 following re-calibration of the baseline survival. Interpretation: We have developed new risk prediction equations to identify those at risk of STDR in people with type 2 diabetes in any resource-setting so that they can be screened and treated early. Future testing, and piloting is required before implementation. Funding: This study was funded by the GCRF UKRI (MR/P207881/1) and supported by the NIHR Biomedical Research Centre at Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology.

Purpose: To examine (i) the retinal structure and function using optical coherence tomography angiography (OCTA) and multifocal electroretinography (mfERG), respectively, in eyes with and without nonproliferative diabetic retinopathy (NPDR), (ii) and their interrelationship between retinal structure (OCTA) and function (mfERG) in the two groups independently. Methods: This was a prospective observational study. One hundred twenty-one eligible participants with type 2 diabetes with No DR (n = 89), or with mild or moderate NPDR (n = 32) underwent ophthalmic examination, ultrawide field-view fundus photography, OCTA, and mfERG. Group differences were assessed using a Mann–Whitney U test. Correlations were assessed using Spearman's rho. Results: There were no significant differences in OCTA measures between the two groups. The mfERG P1 implicit times (rings 1–6) were significantly delayed and P1 response densities in rings 5 and 6 were significantly lower in participants with NPDR compared to those with No DR. In those with No DR, P1 implicit times in almost all rings were delayed in relation to lower vessel density and perfusion (maximum variance noted was 13%). In individuals with NPDR, the P1 response density in rings 2 and 3 showed a positive nonsignificant correlation with macular perfusion. Conclusion: In those with diabetes with No DR, retinal neuronal function is influenced by lower macular vessel density and perfusion. The retinal neuronal function is abnormal in individuals with NPDR compared to those with No DR and is not correlated with OCT angiometric measures, suggesting the likelihood of a different retinal structural correlate.

Purpose: To present clinical profile and risk factors of sight-threatening diabetic retinopathy (STDR) among people with age of onset of diabetes (AOD) 25 group. There was a higher prevalence of PDR with high-risk characteristics in AOD

The increased burden of diabetes in India has resulted in an increase in the complications of diabetes including sight-threatening diabetic retinopathy (DR). Visual impairment and blindness due to DR can be prevented by early detection and management of sight-threatening DR. Life-long evaluation by repetitive retinal screening of people with diabetes is an essential strategy as DR has an asymptomatic presentation. Fundus examination by trained ophthalmologists and fundus photography are established modes of screening. Various modes of opportunistic screening have been followed in India. Hospital-based screening (diabetes care/eye care) and community-based screening are the common modes. Tele-ophthalmology programs based on retinal imaging, remote interpretation, and grading of DR by trained graders/ophthalmologists have facilitated greater coverage of DR screening and enabled timely referral of those with sight-threatening DR. DR screening programs use nonmydriatic or mydriatic fundus cameras for retinal photography. Hand-held/smartphone-based fundus cameras that are portable, less expensive, and easy to use in remote places are gaining popularity. Good retinal image quality and accurate diagnosis play an important role in reducing unnecessary referrals. Recent advances like nonmydriatic ultrawide field fundus photography can be used for DR screening, though likely to be more expensive. The advent of artificial intelligence and deep learning has raised the possibility of automated detection of DR. Efforts to increase the awareness regarding DR is essential to ensure compliance to regular follow-up. Cost-effective sustainable models will ensure systematic nation-wide DR screening in the country.

Purpose: There is an exponential rise in the prevalence of diabetes mellitus (DM) in India. Ideally all people with DM should be periodically screening for diabetic retinopathy (DR) but is not practical with current infrastructure. An alternate strategy is to identify high-risk individuals with vision-threatening diabetic retinopathy (VTDR) for priority screening and treatment. Methods: We reanalyzed four population-based studies, conducted in South India between 2001 and 2010, and reclassified individuals above 40 years into known and newly diagnosed diabetes. Multiple regression analysis was done to identify risk factors in people with known and new DM. Results: The prevalence of DR in 44,599 subjects aged ≥40 years was 14.8% (18.4 and 4.7% in known and new DM, respectively), and the prevalence of VTDR was 5.1%. Higher risk factors of VTDR were older age >50 years, diabetes duration >5 years, and systolic blood pressure >140 mm Hg. Targeted screening of people with diabetes using high-risk criteria obtained from this study was able to detect 93.5% of all individuals with VTDR. Conclusion: In a limited resource country like India, a high-risk group-based targeted screening of individuals with DM could be prioritized while continuing the current opportunistic screening till India adopts universal screening of all people with DM.

The ORNATE India project is an interdisciplinary, multifaceted United Kingdom (UK)-India collaborative study aimed to build research capacity and capability in India and the UK to tackle the burden of diabetes-related visual impairment. For 51 months (October 2017-December 2021), this project built collaboration between six institutions in the UK and seven in India, including the Government of Kerala. Diabetic retinopathy (DR) screening models were evaluated in the public system in Kerala. An epidemiological study of diabetes and its complications was conducted through 20 centers across India covering 10 states and one union territory. The statistical analysis is not yet complete. In the UK, risk models for diabetes and its complications and artificial intelligence-aided tools are being developed. These were complemented by joint studies on various aspects of diabetes between collaborators in the UK and India. This interdisciplinary team enabled increased capability in several workstreams, resulting in an increased number of publications, development of cost-effective risk models, algorithms for risk-based screening, and policy for state-wide implementation of sustainable DR screening and treatment programs in primary care in Kerala. The increase in research capacity included multiple disciplines from field workers, administrators, project managers, project leads, screeners, graders, optometrists, nurses, general practitioners, and research associates in various disciplines. Cross-fertilization of these disciplines enabled the development of several collaborations external to this project. This collaborative project has made a significant impact on research capacity development in both India and the UK.

Purpose To examine (1) the retinal structure by optical coherence tomography (OCT) and function by means of multifocal electroretinography (mfERG) in eyes with and without nonproliferative diabetic retinopathy (NPDR) (2) for correspondence between local retinal function and OCT zones with retinal lesions. Methods One hundred and thirty-two eligible participants (30 with nonproliferative DR (NPDR) and 102 with diabetes with no DR) underwent comprehensive ophthalmic examination, optical coherence tomography for retinal thickness measures, mfERG, and ultra-wide field fundus photography. OCT Early Treatment Diabetic Retinopathy Study (ETDRS) grid was overlaid on to mfERG plots. Results Those with NPDR had significantly thicker full retinal measures in the nine (ETDRS) zones compared to no DR. mfERG P1 latencies in rings 1-6 were significantly delayed, while the response densities in rings 4-6 were lower in the NPDR group. Significant negative correlation was noted between OCT thickness and mfERG P1 response densities in many ETDRS zones. Significant positive correlation was noted between P1 latencies and OCT thickness in a few zones. The combination of cystic spaces, microaneurysms, and hard exudates were present in all zones and were associated with a decrease in P1 response densities compared to no lesions. Reduced P1 response densities were associated with a sporadic delay in the mfERG latencies and vice versa. The number of lesions did not show correspondence to the mfERG measures. Conclusions In eyes with NPDR, retinal function is differentially correlated with the DR lesions on OCT and can be assessed using multimodal imaging modalities.

PurposeTo correlate Optical coherence tomography (OCT) based morphological patterns of diabetic macular edema (DME), prognostic biomarkers and grade of diabetic retinopathy (DR) in patients with various stages of chronic kidney disease (CKD) secondary to diabetes. DesignMulticentric retrospective cross-sectional study conducted at seven centres across India.MethodsData from medical records of patients with DME and CKD was entered in a common excel sheet across all seven centers. Staging of CKD was based on estimated glomerular filtration rate (eGFR). ResultsThe most common morphological pattern of DME was cystoid pattern (42%) followed by the mixed pattern (31%). The proportion of different morphological patterns did not significantly vary across various CKD stages (p=0.836). Presence of external limiting membrane-ellipsoid zone (ELM-EZ) defects (pConclusionsCystoid morphological pattern followed by mixed type was the most common pattern of DME on OCT found in patients suffering from stage 3 to 5 of CKD. However, the morphological patterns of DME did not significantly vary across various CKD stages. ELM-EZ defects may be considered as an important OCT biomarker for advanced stage of CKD.

Telemedicine is a promising strategy that utilizes telecommunication to provide health care in remote areas, facilitating beneficial interaction between the health care provider and people in rural areas and making affordable and accessible medical care available to remote, inaccessible areas of the world. This article provides an overview of some of the ways telemedicine is improving diabetes care outcomes at the community level. Telemedicine can play a number of roles in moving quality diabetes care forward. It is currently being used to create awareness among urban and rural population about the risk factors and prevention of diabetes; to facilitate patient monitoring; for remote diabetic retinopathy screening; and in diabetes prevention at the primary, secondary, and tertiary level. We also highlight the use of automated artificial intelligence software combined with telemedicine to conduct efficient real-time screening of complications such as diabetic retinopathy in remote areas where such facilities are currently unavailable.

IntroductionThe COVID-19 pandemic resulted in a national lockdown in India from midnight on 25 March 2020, with conditional relaxation by phases and zones from 20 April. We evaluated the impact of the lockdown in terms of healthcare provisions, physical health, mental health and social well-being within a multicentre cross-sectional study in India.MethodsThe SMART India study is an ongoing house-to-house survey conducted across 20 regions including 11 states and 1 union territory in India to study diabetes and its complications in the community. During the lockdown, we developed an online questionnaire and delivered it in English and seven popular Indian languages (Hindi, Tamil, Marathi, Telegu, Kannada, Bengali, Malayalam) to random samples of SMART-India participants in two rounds from 5 May 2020 to 24 May 2020. We used multivariable logistic regression to evaluate the overall impact on health and healthcare provision in phases 3 and 4 of lockdown in red and non-red zones and their interactions.ResultsA total of 2003 participants completed this multicentre survey. The bivariate relationships between the outcomes and lockdown showed significant negative associations. In the multivariable analyses, the interactions between the red zones and lockdown showed that all five dimensions of healthcare provision were negatively affected (non-affordability: OR 1.917 (95% CI 1.126 to 3.264), non-accessibility: OR 2.458 (95% CI 1.549 to 3.902), inadequacy: OR 3.015 (95% CI 1.616 to 5.625), inappropriateness: OR 2.225 (95% CI 1.200 to 4.126) and discontinuity of care: OR 6.756 (95% CI 3.79 to 12.042)) and associated depression and social loneliness.ConclusionThe impact of COVID-19 pandemic and lockdown on health and healthcare was negative. The exaggeration of income inequality during lockdown can be expected to extend the negative impacts beyond the lockdown.

Non-communicable diseases (NCDs) are a global health and developmental crisis. They cause premature mortality, aggravate poverty, and threaten global economies [2]. Four NCDs, cardiovascular diseases (CVDs), diabetes mellitus (DM), cancer, and chronic respiratory diseases, are the major causes of morbidity and mortality in the South-East Asia Region (SEAR), accounting for 55% of all deaths each year (~7.9 million) [3, 4]. In 2011, the World Health Organization (WHO) estimated a 21% increase in deaths due to NCDs over the next decade [5]. Furthermore, NCDs claim lives at a younger age in South-East Asia than in other WHO regions [6].

Diabetic retinopathy (DR) is an emerging preventable cause of blindness in India. All India Ophthalmology Society (AIOS) and Vitreo-Retinal Society of India (VRSI) have initiated several measures to improve of DR screening in India. This article is a consensus statement of the AIOS DR task force and VRSI on practical guidelines of DR screening in India. Although there are regional variations in the prevalence of diabetes in India at present, all the States in India should screen their population for diabetes and its complications. The purpose of DR screening is to identify people with sight-threatening DR (STDR) so that they are treated promptly to prevent blindness. This statement provides strategies for the identification of people with diabetes for DR screening, recommends screening intervals in people with diabetes with and without DR, and describes screening models that are feasible in India. The logistics of DR screening emphasizes the need for dynamic referral pathways with feedback mechanisms. It provides the clinical standards required for DR screening and treatment of STDR and addresses the governance and quality assurance (QA) standards for DR screening in Indian settings. Other aspects incorporate education and training, recommendations on Information technology (IT) infrastructure, potential use of artificial intelligence for grading, data capture, and requirements for maintenance of a DR registry. Finally, the recommendations include public awareness and the need to work with diabetologists to control the risk factors so as to have a long-term impact on prevention of diabetes blindness in India.

To assess the prevalence of diabetic retinopathy (DR) and associated risk factors in Asian Indians with prediabetes.In a cross-sectional study conducted at two tertiary care diabetes centres in Chennai, India, clinical and biochemical assessment and nonmydriatic ultra-wide field fundus photography was performed in individuals with prediabetes (impaired fasting glucose [IFG] and/or impaired glucose tolerance [IGT]) based on oral glucose tolerance test (OGTT) and/or glycated hemoglobin (HbA1c) between 5.7% and 6.4% in 2019. The retinal photographs were graded by certified ophthalmologists. Systemic risk factors associated with DR in prediabetes were assessed.The mean age of the 192 individuals with prediabetes was 48 ± 13 years (55.2% were males). DR was present in 12 (6.3%) individuals of which nine (4.7%) had mild non-proliferative DR (NPDR) and three (1.6%) had moderate NPDR. None had severe sight-threatening DR. The Poisson multiple regression analysis showed that after adjusting for other systemic covariates, HbA1c values ≥ 6% (6-6.4%) was associated with 2 times higher relative risk of DR (Risk ratio 1.95 (95% CI 1.07-3.545, p = 0.028) in comparison to HbA1c 6%).DR was present in about 6% of the Asian Indians with prediabetes. Higher HbA1c values among individuals with prediabetes was associated with twice the relative risk for DR. Robust control of HbA1c should be encouraged even before the diagnosis of diabetes is established.

The global burden of diabetes has resulted in an increase in the prevalence of diabetic retinopathy (DR), a microvascular complication of diabetes. Lifelong repetitive screening for DR is essential for early detection and timely management to prevent visual impairment due to the silent sight-threatening disorder. Colour fundus photography (CFP) is helpful for documentation of the retinopathy as well as for counselling the patient. CFP has established roles in DR screening, detection, progression and monitoring of treatment response. DR screening programmes use validated mydriatic or non-mydriatic fundus cameras for retinal imaging and trained image graders identify referable DR. Smartphone-based fundus cameras and handheld fundus cameras that are cost-effective, portable and easy to handle in remote places are gaining popularity in recent years. The images captured with these low-cost devices can be immediately sent to trained ophthalmologists for grading of DR. Recent increase in numbers of telemedicine programmes based on imaging with digital fundus cameras and remote interpretation has facilitated larger population coverage of DR screening and timely referral of those with sight-threatening DR to ophthalmologists. Good-quality retinal imaging and accurate diagnosis are essential to reduce inappropriate referrals. Advances in digital imaging such as ultra-wide field imaging and multi-modal imaging have opened new avenues for assessing DR. Fundus cameras with integrated artificial intelligence (AI)-based automated algorithms can also provide instant DR diagnosis and reduce the burden of healthcare systems. We review the different types of fundus cameras currently used in DR screening and management around the world.摘要: 在全球, 糖尿病的患病率日益增长导致了微血管并发症—糖尿病视网膜病变(DR)的患病率增加。为了早期发现和及时治疗, 对DR患者的终身反复筛查至关重要, 以防因这种隐匿的视力威胁造成视力损害。彩色眼底照相(CFP)有助于记录视网膜病变以及有利于患者进行咨询。CFP已在DR的筛查、检测、进展和监测治疗反应等方面发挥了重要作用。DR筛查项目使用经过验证的散瞳或非散瞳眼底相机进行视网膜成像并且由训练有素的图像分级员识别DR。智能手机近年来在偏远地区越来越受欢迎, 基于手机的眼底相机和手持式眼底相机具有成本效益低、便携和易于操作的特点。使用这些低成本设备捕获的图像可以立即发送给训练有素的眼科医生, 以便对DR进行分级。最近, 基于数字眼底相机成像和远程解读的远程医疗计划数量增加, 有助于扩大DR筛查的人群覆盖面, 并及时将患有视力损伤的DR患者转诊给眼科医生。高质量的视网膜成像和精准的诊断对于减少不当的转诊至关重要。数字成像的进步, 如超宽范围成像和多模式成像, 为评估DR开辟了新的途径。带有集成人工智能(AI)自动化算法的眼底相机还可以提供即时的DR诊断, 并减轻医疗系统的负担。我们对目前世界各地用于DR筛查和管理的不同类型的眼底相机进行了综述。.

To provide the real-world outcomes of people with proliferative diabetic retinopathy (PDR) in India and highlight opportunities for improvement of their disease status and to evaluate their visual acuity (VA) status. A multicenter retrospective study in which ten centers in India with established vitreoretinal services for over 10 years were invited to provide long-term data on PDR. This study population were of Indian nationality. Patients with a diagnosis of type 1 or 2 diabetes with a clinical diagnosis of active PDR in any or both eyes, who had long term follow-up for up to 10 years were included. Baseline data collected included age, sex, duration of diabetes, source of referral and best-corrected visual acuity, diabetic retinopathy status in both eyes. Available follow-up data on VA were collected at 6 months post baseline, 5 years and 10 years within a ± 3 months window. Evaluating the presenting VA of people with PDR, short-term outcomes at 6 months and the incidence of visual impairment (VI) at 5 and 10 years are the main outcome of the study. Data was available for 516, 424 and 455 patients at baseline, 5 years and 10 years respectively. Gender and duration of diabetes did not have statistically significant effect on VI outcomes. Eyes receiving treatment early in the disease course (i.e. baseline VA ≥ 6/12) had significantly better VA outcomes at 10 years versus eyes treated at a later stage (i.e. baseline VA p = p = p > 0.05). The age standardized incidence for VI was 11.10% (95% CI 8.1, 14.2) and for blindness was found to be 7.7% (95% CI 5.2, 10.3). Our results suggest that despite robust recent clinical trial results showing that pan retinal photocoagulation is an excellent treatment for PDR, people with diabetes in India need to be made aware of annual screening and treatment of their eyes to avoid vision impairment and blindness.

IntroductionPrevious epidemiological studies have reported on the prevalence of diabetic kidney disease (DKD) and diabetic retinopathy (DR) from India. The aim of this study is to evaluate the effect of DKD on the development of new-onset DR and sight-threatening diabetic retinopathy (STDR) in Asian Indians with type 2 diabetes (T2D).Research design and methodsThe study was done on anonymized electronic medical record data of people with T2D who had undergone screening for DR and renal work-up as part of routine follow-up at a tertiary care diabetes center in Chennai, South India. The baseline data retrieved included clinical and biochemical parameters including renal profiles (serum creatinine, estimated glomerular filtration rate (eGFR) and albuminuria). Grading of DR was performed using the modified Early Treatment Diabetic Retinopathy Study grading system. STDR was defined as the presence of proliferative diabetic retinopathy (PDR) and/or diabetic macular edema. DKD was defined by the presence of albuminuria (≥30 µg/mg) and/or reduction in eGFR (2). Cox regression analysis was used to evaluate the hazard ratio (HR) for DR and STDR.ResultsData of 19 909 individuals with T2D (mean age 59.6±10.2 years, mean duration of diabetes 11.1±12.1 years, 66.1% male) were analyzed. At baseline, DR was present in 7818 individuals (39.3%), of whom 2249 (11.3%) had STDR. During the mean follow-up period of 3.9±1.9 years, 2140 (17.7%) developed new-onset DR and 980 individuals with non-proliferative DR (NPDR) at baseline progressed to STDR. Higher serum creatinine (HR 1.5, 95% CI 1.3 to 1.7; p2 (HR 4.9, 95% CI 2.9 to 8.2; p300 µg/mg (HR 3.0, 95% CI 2.4 to 3.8; pConclusionsDKD at baseline is a risk factor for progression to STDR. Physicians should promptly refer their patients with DKD to ophthalmologists for timely detection and management of STDR.

In India, more than 72 million people have diabetes. Diabetic retinopathy (DR), a vision-threatening complication of people with diabetes, is an important cause of avoidable blindness. The delay in the detection of DR is due to lack of awareness and shortage of ophthalmologists trained in the management of DR. With this background, in 2015, we initiated a capacity-building program “Certificate Course in Evidence Based Management of Diabetic Retinopathy (CCDR)” with an objective to build the skills and core competencies of the physicians across India in the management of diabetes and DR. The program has completed four cycles and 578 physicians have been trained. The course elicited an excellent response, which reflects the much-felt need for skill improvement in DR diagnosis and management for physicians in India. This model demonstrates an innovative modality to address DR-related avoidable blindness in a resource-restraint country like India.