The contribution of the English NHS Diabetic Eye Screening Programme to reductions in diabetes-related blindness, comparisons within Europe, and future challenges

SMART (artificial intelligence enabled) DROP (diabetic retinopathy outcomes and pathways): Study protocol for diabetic retinopathy management

INTRODUCTION

Delayed diagnosis of diabetic retinopathy (DR) remains a significant challenge, often leading to preventable blindness and visual impairment. Given that physicians are frequently the first point of contact for people with diabetes, there is a critical need for integrated screening programs within diabetes clinics to enhance DR management and reduce the risk of severe vision loss.

METHODS AND ANALYSIS

We will conduct a prospective cohort study comparing (i) the intervention cohort, screened at diabetes clinics and referred to eye clinics per the proposed pathway, and (ii) the standard-of-care (SOC) eye clinic cohort. The study will be conducted in Hyderabad, India, at LV Prasad Eye Institute and four IDEA (Institute of Diabetes, Endocrinology, and Adiposity) Clinics. The primary objective is to evaluate the effectiveness of a systematic diabetic retinopathy screening program in achieving earlier detection and reducing visual impairment among People With Diabetes (PWD) attending IDEA clinics compared to routine care at eye care settings. The screening program will be operationalized using AI-enabled tools and supported by trained non-medical technicians. We will perform visual acuity tests and non-mydriatic fundus photography using AI-assisted cameras. DR-positive patients will be referred for treatment and follow-up. We aim to achieve high accuracy (>90%) in appropriate referral of DR and high screening coverage (>80%) of eligible PWD. Success metrics include screening uptake, AI diagnostic accuracy, referral rates, cost-effectiveness, patient satisfaction, follow-up adherence, and long-term outcomes.

CONCLUSION

This study aims to enhance diabetic retinopathy screening and management through an AI-enabled approach at diabetes clinics, improving early detection and care pathways. The findings will contribute to evidence-based strategies for optimizing DR screening and management, with results disseminated through peer-reviewed publications to inform policy and practice.

TRIAL REGISTRATION

Trial registration number: CTRI/2024/03/064518 [Registered on: 20/03/2024] (https://ctri.nic.in/).

Effect of the COVID-19 pandemic on diabetic retinopathy and referral levels in the English National Health Service Diabetic Eye Screening Programme

AIMS

The aim was to determine the effect of the COVID-19 pandemic on diabetic retinopathy and referral rates in the English National Health Service (NHS) Diabetic Eye Screening Programme (DESP).

METHODS

Non-patient identifiable data are submitted centrally from the 57 regional centres in the NHS DESP on a quarterly basis and analysed using STATA, comparing 01/04/2019-31/03/2020 and 01/04/2021-31/03/2022. Patient characteristics were analysed from National Diabetes Audit (NDA) data.

RESULTS

There were 2,274,635 grades from the 57 centres in 2019-2020 and 2,199,623 grades in 2021-2022. The proportion of eyes with referable DR increased from 3.1% in 2019-2020 to 3.2% in the 2021-2022 NHS year (p < 0.01) with a small increase in the level of non-referable DR from 24.6% to 24.8% (p < 0.01). The median proportion of ungradable eyes in 2019-2020 was 2.6% (IQR: 2.3% to 3.3%) increasing to 3.1% (IQR: 2.5% to 3.7%) in 2021-2022. NDA data demonstrated that the proportions with type 1 diabetes receiving eye screening were higher in the latter year (8.3% vs. 7.3%).

CONCLUSION

The COVID-19 pandemic was associated with small increases in referable retinopathy rates from 3.1% to 3.2%, non-referable DR from 24·6% to 24.8% and an increase in the ungradable image rate from 2.6% to 3.1%, the latter increase possibly being caused by untreated cataract during the pandemic. Risk stratification of invitations in the recovery period was believed to have contributed to keeping the referable rates low and supports a similar approach in extension of the screening interval for low-risk groups.

Generating evidence to support the role of AI in diabetic eye screening: considerations from the UK National Screening Committee

Screening for diabetic retinopathy has been shown to reduce the risk of sight loss in people with diabetes, because of early detection and treatment of sight-threatening disease. There is long-standing interest in the possibility of automating parts of this process through artificial intelligence, commonly known as automated retinal imaging analysis software (ARIAS). A number of such products are now on the market. In the UK, Scotland has used a rules-based autograder since 2011, but the diabetic eye screening programmes in the rest of the UK rely solely on human graders. With more sophisticated machine learning-based ARIAS now available and greater challenges in terms of human grader capacity, in 2019 the UK's National Screening Committee (NSC) was asked to consider the modification of diabetic eye screening in England with ARIAS. Following up on a review of ARIAS research highlighting the strengths and limitations of existing evidence, the NSC here sets out their considerations for evaluating evidence to support the introduction of ARIAS into the diabetic eye screening programme.

Recognition of ophthalmology consultation and fundus examination among individuals with diabetes in Japan: A cross-sectional study using claims-questionnaire linked data

AIMS

This study aimed to assess the relationship between individuals' recognition of ophthalmology consultation recommendations, their knowledge of the recommended frequency of diabetic retinopathy screening, and the likelihood of undergoing fundus examinations.

MATERIALS AND METHODS

This cross-sectional secondary analysis linked claims and health checkup data to a questionnaire survey. Questionnaires were distributed to randomly sampled National Health Insurance beneficiaries in Tsukuba City, using data from claims and health checkups. Weighting was applied based on sample extraction and response rates. We calculated the proportions of fundus examinations and knowledge of screening frequency according to the recognition of ophthalmology consultation recommendations. The association between visits to medical facilities with diabetes specialists and diabetic retinopathy screening was also examined.

RESULTS

Among 290 participants, 47.6% recognized ophthalmology consultation recommendations. Those who recognized these recommendations had better knowledge of the screening frequency (93.4% vs. 49.6%) and were more likely to undergo fundus examinations (72.9% vs. 30.1%; adjusted risk ratio 2.36; 95% CI, 1.65-3.38). Participants who visited medical facilities with diabetes specialists were more likely to recognize recommendations, have knowledge of screening frequency, and undergo fundus examinations.

CONCLUSIONS

Recognition of ophthalmology consultation recommendations was associated with better knowledge of screening frequency and higher participation in fundus examinations. Increasing awareness through healthcare provider recommendations may improve diabetic retinopathy screening rates, highlighting the need for targeted interventions to promote eye care among individuals with diabetes.

Predicting the need for diabetic macular oedema treatment from photographic screening in the Singapore Integrated Diabetic Retinopathy Programme (SiDRP)

OBJECTIVE

To identify diabetic maculopathy features from photographic screening that are predictive of treatment on referral to a tertiary care centre.

METHODS

Retrospective review of participants who underwent screening by Singapore Integrated Diabetic Retinopathy Programme from 2015 to 2019. Participants underwent visual acuity (VA) test and non-stereoscopic retinal photographs. Maculopathy features include haemorrhages, microaneurysm and hard exudates (HE), stratified by inner and outer zone (1 and 1-2 disc diameter from fovea respectively) and VA of 6/12. Diabetic macular oedema (DMO) treatment was defined as intravitreal injection or macular photocoagulation up to 540 days from point of referral.

RESULTS

16,712 patients screened had referable eye disease. Out of 3518 maculopathy suspects, 281 (8.0%) received DMO treatment within 540 days. Those treated for DMO had shorter duration of diabetes (6.90 vs. 9.13 years, p < 0.001), higher total cholesterol (4.65 ± 1.20 vs. 4.36 ± 1.13 mmol/L, p = 0.001) and LDL cholesterol (2.59 ± 1.05 vs. 2.37 ± 0.93 mmol/L, p < 0.05) than those without treatment. High-risk features, including inner zone haemorrhages with VA ≤ 6/12 (HR 12.0, 95% CI: 5.5-25.9) and inner zone hard exudates (HR 7.4, 95% CI: 3.4-15.8), significantly increased the likelihood of requiring DMO treatment compared to low-risk features. Higher body mass index is protective of DMO treatment in mild non-proliferative diabetic retinopathy (HR 0.84, 95% CI: 0.73-0.97).

CONCLUSION

Haemorrhages, microaneurysms and HE within inner zone are important photographic features predictive of DMO treatment. VA is an important stratification for screening especially in patients with only visible haemorrhages.

Impact of teleretinal screening program on diabetic retinopathy screening compliance rates in community health centers: a quasi-experimental study

BACKGROUND

Diabetic retinopathy (DR) remains a leading cause of preventable blindness, with inadequate screening rates even in urban areas with high concentrations of medical professionals. While medical guidelines recommend annual diabetic retinopathy screening for patients with diabetes mellitus, adherence to these recommendations remains low. This study evaluates the impact of a novel teleretinal DR screening program on screening compliance across urban community health centers in Boston, Massachusetts.

METHODS

We conducted a quasi-experimental study comparing DR screening compliance between intervention and comparison community health centers before and after implementing a teleretinal screening program. Participants included patients diagnosed with diabetes mellitus with primary care providers at the studied sites. We defined compliance as completion of either teleretinal screening or a documented eye care professional examination within the previous 365 days. Monthly compliance rates were analyzed using two-way fixed effects regression and event study techniques.

RESULTS

The study included 10,247 patients with diabetes mellitus who received care at six participating sites, generating 222 monthly compliance rate estimates. Baseline compliance rates before implementation ranged from 25 to 40% across sites. The two-way fixed effects regression analysis revealed that the screening program significantly increased DR compliance rates by an average of 7.2% points (p < 0.001). Event study analysis showed positive effects across all sites, though the initial improvement tended to diminish over time.

CONCLUSIONS

Implementation of a community-based teleretinal DR screening program significantly improved compliance with annual screening guidelines in urban communities. These findings support the broader adoption of teleretinal screening as an effective strategy for preventing DR-related vision loss in vulnerable populations. Further research is needed to assess long-term clinical outcomes and optimize program sustainability.

Impact of COVID-19 and recovery of routine diabetic retinopathy digital screening across different regions in England: an analysis of publicly available data

OBJECTIVE

This study aims to examine the reduction and subsequent recovery of routine digital screening (RDS) uptake in England from 2018 to 2022, exploring national, regional and individual Diabetic Eye Screening Programme (DESP) levels. The COVID-19 lockdown in most areas of England was from 26 March 2020 to 23 June 2020 (first national lockdown), 5 November 2020 to 2 December 2020 (second national lockdown) and 6 January 2021 to 8 March 2021 (third national lockdown).

DESIGN

Retrospective data analysis.

SETTING

DESPs of England.

PARTICIPANTS

Individuals with diabetes who were invited to take part in the DESP programmes.

METHODS

Publicly available data from Public Health England (2018-2019) and National Health Service England (2019-2022) were examined to identify the rate of uptake (proportion of those who attended the DESPs to those who were invited) of RDS at national and regional levels and by each DESP in England.

PRIMARY OUTCOME MEASURES

Rate of uptake of RDS.

RESULTS

The national uptake of RDS decreased from 82% (2019-2020) to 68% (2020-2021) and then increased to 78% (2021-2022). At the regional level, the sharpest drop was in the Midlands which decreased from 79% (2019-2020) to 53% (2020-2021), increasing to 73% (2021-2022) but did not reach pre-COVID-19 levels. At individual DESP levels across England, the greatest drop in attendance (2020-2021) was recorded in Derbyshire (79% to 45%), Barnsley and Rotherham (78% to 45%) and Arden, Herefordshire and Worcestershire (78% to 46%). Although these DESPs showed an increase in 2021-2022 of 33%, 21% and 31%, they did not reach prepandemic (2018-2019) rates of 81%, 85% and 82%, respectively. Data suggest that West Sussex, East Sussex and East and North Hertfordshire DESPs maintained relatively higher uptake rates (86%-89%) in 2020-2021.

CONCLUSION

COVID-19 had an impact on England's diabetic eye screening attendance, with notable variations across regions and DESPs. Different regions and DESPs showed variable post-COVID-19 recovery. More importantly, what was not evident is the increased uptake that should have occurred after the COVID-19 lockdown to compensate for the low uptake during the lockdown. In some areas, addressing some of the barriers that affect retinal screening uptake may improve future attendance.

Sheffield One-Stop Service: A potential model to improve the screening uptake of diabetic peripheral neuropathy and other microvascular complications of diabetes

The world is experiencing an enormous rise in the prevalence of diabetes, which is associated with massive healthcare costs that threaten to overwhelm many healthcare systems. Most of the diabetes expenditure is attributed to the management of chronic diabetes complications, including diabetic peripheral neuropathy (DPN)/diabetic foot complications, chronic kidney disease, sight-threatening retinopathy and cardiovascular diseases. Of these complications, the most overlooked is DPN. Most consultations around the world do not even involve taking off shoes and socks to carry out a foot examination, and even when carried out, the peripheral neurological examination using the 10-g monofilament diagnoses DPN when it is already at an advanced stage. Thus, all too often diabetes complications are diagnosed late, resulting in devastating outcomes, particularly in low- to middle-income countries. There is, therefore, an urgent need to instigate new strategies to improve microvascular screening uptake using a holistic protocol for annual diabetes health checks outside the busy diabetes clinic. One such approach, the Sheffield One-Stop Microvascular Screening Service, which involves modern point of care devices to diagnose DPN, has been shown to be feasible and effective, resulting in high uptake and early management of diabetes complications. This article outlines the advantages of this One-Stop Microvascular Screening Service and a plan to trial an adapted version of this service to a resource-limited country, the Philippines. If successful, this model has the potential for implementation in other countries around the world.

Integrated image-based deep learning and language models for primary diabetes care

Primary diabetes care and diabetic retinopathy (DR) screening persist as major public health challenges due to a shortage of trained primary care physicians (PCPs), particularly in low-resource settings. Here, to bridge the gaps, we developed an integrated image-language system (DeepDR-LLM), combining a large language model (LLM module) and image-based deep learning (DeepDR-Transformer), to provide individualized diabetes management recommendations to PCPs. In a retrospective evaluation, the LLM module demonstrated comparable performance to PCPs and endocrinology residents when tested in English and outperformed PCPs and had comparable performance to endocrinology residents in Chinese. For identifying referable DR, the average PCP's accuracy was 81.0% unassisted and 92.3% assisted by DeepDR-Transformer. Furthermore, we performed a single-center real-world prospective study, deploying DeepDR-LLM. We compared diabetes management adherence of patients under the unassisted PCP arm (n = 397) with those under the PCP+DeepDR-LLM arm (n = 372). Patients with newly diagnosed diabetes in the PCP+DeepDR-LLM arm showed better self-management behaviors throughout follow-up (P < 0.05). For patients with referral DR, those in the PCP+DeepDR-LLM arm were more likely to adhere to DR referrals (P < 0.01). Additionally, DeepDR-LLM deployment improved the quality and empathy level of management recommendations. Given its multifaceted performance, DeepDR-LLM holds promise as a digital solution for enhancing primary diabetes care and DR screening.

Inhibition of BMP4 alleviates diabetic retinal vascular dysfunction via the VEGF and smad1/5 signalling

Objective:The aim of our study was to determine the molecular mechanism of BMP4 (bone morphogenetic protein 4) in DR (diabetic retinopathy).Methods: Human retinal endothelial cell (HRECs) induced by high glucose to simulate one of the pathogenesis in the diabetic retinopathy (DR) model. RT-qPCR and western blot were used to detect the mRNA and protein levels of BMP4 in the STZ/HG group. Flow cytometry and TUNEL staining were performed to detect the apoptosis. Angiogenesis was evaluated by tube formation assay. Transwell assay and wound healing assay were used to detect cell migration ability. H&E staining was used to evaluate the pathological changes.Results: BMP4 was significantly upregulated in the STZ/HG group. Sh-BMP4 significantly inhibited the migration and angiogenesis of RVECs induced by HG. In addition, both in vivo and in vitro experiments confirmed that sh-BMP4 could significantly promote RVECs apoptosis in the HG/STZ group. Western blot results showed that sh-BMP4 could down-regulate the expressions of p-smad1, p-smad5 and VEGF.Conclusions: Inhibition of BMP4 could alleviate the damage of diabetic retinopathy by regulating the p-smad1/5/VEGF signaling axis, inhibiting angiogenesis and promoting apoptosis.

Predicting 1, 2 and 3 year emergent referable diabetic retinopathy and maculopathy using deep learning

BACKGROUND

Predicting diabetic retinopathy (DR) progression could enable individualised screening with prompt referral for high-risk individuals for sight-saving treatment, whilst reducing screening burden for low-risk individuals. We developed and validated deep learning systems (DLS) that predict 1, 2 and 3 year emergent referable DR and maculopathy using risk factor characteristics (tabular DLS), colour fundal photographs (image DLS) or both (multimodal DLS).

METHODS

From 162,339 development-set eyes from south-east London (UK) diabetic eye screening programme (DESP), 110,837 had eligible longitudinal data, with the remaining 51,502 used for pretraining. Internal and external (Birmingham DESP, UK) test datasets included 27,996, and 6928 eyes respectively.

RESULTS

Internal multimodal DLS emergent referable DR, maculopathy or either area-under-the receiver operating characteristic (AUROC) were 0.95 (95% CI: 0.92-0.98), 0.84 (0.82-0.86), 0.85 (0.83-0.87) for 1 year, 0.92 (0.87-0.96), 0.84 (0.82-0.87), 0.85 (0.82-0.87) for 2 years, and 0.85 (0.80-0.90), 0.79 (0.76-0.82), 0.79 (0.76-0.82) for 3 years. External multimodal DLS emergent referable DR, maculopathy or either AUROC were 0.93 (0.88-0.97), 0.85 (0.80-0.89), 0.85 (0.76-0.85) for 1 year, 0.93 (0.89-0.97), 0.79 (0.74-0.84), 0.80 (0.76-0.85) for 2 years, and 0.91 (0.84-0.98), 0.79 (0.74-0.83), 0.79 (0.74-0.84) for 3 years.

CONCLUSIONS

Multimodal and image DLS performance is significantly better than tabular DLS at all intervals. DLS accurately predict 1, 2 and 3 year emergent referable DR and referable maculopathy using colour fundal photographs, with additional risk factor characteristics conferring improvements in prognostic performance. Proposed DLS are a step towards individualised risk-based screening, whereby AI-assistance allows high-risk individuals to be closely monitored while reducing screening burden for low-risk individuals.

Global estimates on the number of people blind or visually impaired by diabetic retinopathy: a meta-analysis from 2000 to 2020

OBJECTIVES

To estimate global and regional trends from 2000 to 2020 of the number of persons visually impaired by diabetic retinopathy and their proportion of the total number of vision-impaired individuals.

METHODS

Data from population-based studies on eye diseases between 1980 to 2018 were compiled. Meta-regression models were performed to estimate the prevalence of blindness (presenting visual acuity <3/60) and moderate or severe vision impairment (MSVI; <6/18 to ≥3/60) attributed to DR. The estimates, with 95% uncertainty intervals [UIs], were stratified by age, sex, year, and region.

RESULTS

In 2020, 1.07 million (95% UI: 0.76, 1.51) people were blind due to DR, with nearly 3.28 million (95% UI: 2.41, 4.34) experiencing MSVI. The GBD super-regions with the highest percentage of all DR-related blindness and MSVI were Latin America and the Caribbean (6.95% [95% UI: 5.08, 9.51]) and North Africa and the Middle East (2.12% [95% UI: 1.55, 2.79]), respectively. Between 2000 and 2020, changes in DR-related blindness and MSVI were greater among females than males, predominantly in the super-regions of South Asia (blindness) and Southeast Asia, East Asia, and Oceania (MSVI).

CONCLUSIONS

Given the rapid global rise in diabetes and increased life expectancy, DR is anticipated to persist as a significant public health challenge. The findings emphasise the need for gender-specific interventions and region-specific DR healthcare policies to mitigate disparities and prevent avoidable blindness. This study contributes to the expanding body of literature on the burden of DR, highlighting the need for increased global attention and investment in this research area.

An eye on equity: faricimab-driven health equity improvements in diabetic macular oedema using a distributional cost-effectiveness analysis from a UK societal perspective

BACKGROUND/OBJECTIVES

Diabetic macular oedema (DMO) is a leading cause of blindness in developed countries, with significant disease burden associated with socio-economic deprivation. Distributional cost-effectiveness analysis (DCEA) allows evaluation of health equity impacts of interventions, estimation of how health outcomes and costs are distributed in the population, and assessments of potential trade-offs between health maximisation and equity. We conducted an aggregate DCEA to determine the equity impact of faricimab.

METHODS

Data on health outcomes and costs were derived from a cost-effectiveness model of faricimab compared with ranibizumab, aflibercept and off-label bevacizumab using a societal perspective in the base case and a healthcare payer perspective in scenario analysis. Health gains and health opportunity costs were distributed across socio-economic subgroups. Health and equity impacts, measured using the Atkinson inequality index, were assessed visually on an equity-efficiency impact plane and combined into a measure of societal welfare.

RESULTS

At an opportunity cost threshold of £20,000/quality-adjusted life year (QALY), faricimab displayed an increase in net health benefits against all comparators and was found to improve equity. The equity impact increased the greater the concerns for reducing health inequalities over maximising population health. Using a healthcare payer perspective, faricimab was equity improving in most scenarios.

CONCLUSIONS

Long-acting therapies with fewer injections, such as faricimab, may reduce costs, improve health outcomes and increase health equity. Extended economic evaluation frameworks capturing additional value elements, such as DCEA, enable a more comprehensive valuation of interventions, which is of relevance to decision-makers, healthcare professionals and patients.

Development and validation of a simple and practical model for early detection of diabetic macular edema in patients with type 2 diabetes mellitus using easily accessible systemic variables

OBJECTIVE

Diabetic macular edema (DME) is the leading cause of visual impairment in patients with diabetes mellitus (DM). The goal of early detection has not yet achieved due to a lack of fast and convenient methods. Therefore, we aim to develop and validate a prediction model to identify DME in patients with type 2 diabetes mellitus (T2DM) using easily accessible systemic variables, which can be applied to an ophthalmologist-independent scenario.

METHODS

In this four-center, observational study, a total of 1994 T2DM patients who underwent routine diabetic retinopathy screening were enrolled, and their information on ophthalmic and systemic conditions was collected. Forward stepwise multivariable logistic regression was performed to identify risk factors of DME. Machine learning and MLR (multivariable logistic regression) were both used to establish prediction models. The prediction models were trained with 1300 patients and prospectively validated with 104 patients from Guangdong Provincial People's Hospital (GDPH). A total of 175 patients from Zhujiang Hospital (ZJH), 115 patients from the First Affiliated Hospital of Kunming Medical University (FAHKMU), and 100 patients from People's Hospital of JiangMen (PHJM) were used as external validation sets. Area under the receiver operating characteristic curve (AUC), accuracy (ACC), sensitivity, and specificity were used to evaluate the performance in DME prediction.

RESULTS

The risk of DME was significantly associated with duration of DM, diastolic blood pressure, hematocrit, glycosylated hemoglobin, and urine albumin-to-creatinine ratio stage. The MLR model using these five risk factors was selected as the final prediction model due to its better performance than the machine learning models using all variables. The AUC, ACC, sensitivity, and specificity were 0.80, 0.69, 0.80, and 0.67 in the internal validation, and 0.82, 0.54, 1.00, and 0.48 in prospective validation, respectively. In external validation, the AUC, ACC, sensitivity and specificity were 0.84, 0.68, 0.90 and 0.60 in ZJH, 0.89, 0.77, 1.00 and 0.72 in FAHKMU, and 0.80, 0.67, 0.75, and 0.65 in PHJM, respectively.

CONCLUSION

The MLR model is a simple, rapid, and reliable tool for early detection of DME in individuals with T2DM without the needs of specialized ophthalmologic examinations.

Extending the diabetic retinopathy screening intervals in Singapore: methodology and preliminary findings of a cohort study

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 < 0.05). To date, we have extracted 41.8% (n = 1909) of the 12-month follow-up data. Of these, 99.7% (n = 1,904) did not progress to referable DR. Those who progressed to referable DR status (0.3%) had no DR at baseline.

CONCLUSIONS

In our prospective study of patients with T2DM and non-referable DR attending polyclinics, we found extremely low annual DR progression rates. These preliminary results suggest that extending screening intervals beyond 12 months may be viable and safe for most participants, although our 3-year follow up data are needed to substantiate this claim and develop the risk stratification model to identify low-risk patients with T2DM who can be assigned biennial or triennial screening intervals.

Earlier diagnosis of peripheral neuropathy in primary care: A call to action

Peripheral neuropathy (PN) often remains undiagnosed (~80%). Earlier diagnosis of PN may reduce morbidity and enable earlier risk factor reduction to limit disease progression. Diabetic peripheral neuropathy (DPN) is the most common PN and the 10 g monofilament is endorsed as an inexpensive and easily performed test for DPN. However, it only detects patients with advanced neuropathy at high risk of foot ulceration. There are many validated questionnaires to diagnose PN, but they can be time-consuming and have complex scoring systems. Primary care physicians (PCPs) have busy clinics and lack access to a readily available screening method to diagnose PN. They would prefer a short, simple, and accurate tool to screen for PN. Involving the patient in the screening process would not only reduce the time a physician requires to make a diagnosis but would also empower the patient. Following an expert meeting of diabetologists and neurologists from the Middle East, South East Asia and Latin America, a consensus was formulated to help improve the diagnosis of PN in primary care using a simple tool for patients to screen themselves for PN followed by a consultation with the physician to confirm the diagnosis.

Five-year outcomes of digital diabetic eye screening in individuals aged 80 and 85 years

OBJECTIVE

To assess the incidence of referable diabetic retinopathy (DR) in patients aged 80 and 85 years to determine whether screening interval can be extended safely in this age group.

METHODS

Patients who were aged 80 and 85 years when they attended digital screening during April 2014-March 2015 were included. Screening results at baseline and over the next four years were analysed.

RESULTS

1880 patients aged 80 and 1105 patients aged 85 were included. Patients referred to hospital eye service (HES) for DR ranged from 0.7% to 1.4% in the 80-year-old cohort over 5 years. In this cohort a total of 76 (4%) were referred to HES for DR, of which 11 (0.6%) received treatment. Over the course of the follow up (FU), 403 (21%) died. In the 85-year-old cohort, referral to HES for DR each year ranged from 0.1% to 1.3%. In this cohort a total of 27 (2.4%) were referred to HES for DR, of which 4 (0.4%) received treatment. Over the course of follow-up 541(49%) died. All treated cases were for maculopathy in both cohorts and there were no cases of proliferative diabetic retinopathy requiring treatment.

CONCLUSION

This study showed that the risk of progression of retinopathy is quite low in this age group and only a small proportion of patients developed referable retinopathy requiring treatment. This suggests relooking at the need for screening and ideal screening intervals in patients aged 80 years and over with no referable DR as they can be potentially classed as a group with low risk of sight loss.

Save our Sight (SOS): a collective call-to-action for enhanced retinal care across health systems in high income countries

With a growing aging population, the prevalence of age-related eye disease and associated eye care is expected to increase. The anticipated growth in demand, coupled with recent medical advances that have transformed eye care for people living with retinal diseases, particularly neovascular age-related macular degeneration (nAMD) and diabetic eye disease, has presented an opportunity for health systems to proactively manage the expected burden of these diseases. To do so, we must take collective action to address existing and anticipated capacity limitations by designing and implementing sustainable strategies that enable health systems to provide an optimal standard of care. Sufficient capacity will enable us to streamline and personalize the patient experience, reduce treatment burden, enable more equitable access to care and ensure optimal health outcomes. Through a multi-modal approach that gathered unbiased perspectives from clinical experts and patient advocates from eight high-income countries, substantiated perspectives with evidence from the published literature and validated findings with the broader eye care community, we have exposed capacity challenges that are motivating the community to take action and advocate for change. Herein, we propose a collective call-to-action for the future management of retinal diseases and potential strategies to achieve better health outcomes for individuals at-risk of, or living with, retinal disease.

Ethnic disparities in progression rates for sight-threatening diabetic retinopathy in diabetic eye screening: a population-based retrospective cohort study

INTRODUCTION

The English Diabetic Eye Screening Programme (DESP) offers people living with diabetes (PLD) annual eye screening. We examined incidence and determinants of sight-threatening diabetic retinopathy (STDR) in a sociodemographically diverse multi-ethnic population.

RESEARCH DESIGN AND METHODS

North East London DESP cohort data (January 2012 to December 2021) with 137 591 PLD with no retinopathy, or non-STDR at baseline in one/both eyes, were used to calculate STDR incidence rates by sociodemographic factors, diabetes type, and duration. HR from Cox models examined associations with STDR.

RESULTS

There were 16 388 incident STDR cases over a median of 5.4 years (IQR 2.8-8.2; STDR rate 2.214, 95% CI 2.214 to 2.215 per 100 person-years). People with no retinopathy at baseline had a lower risk of sight-threatening diabetic retinopathy (STDR) compared with those with non-STDR in one eye (HR 3.03, 95% CI 2.91 to 3.15, p<0.001) and both eyes (HR 7.88, 95% CI 7.59 to 8.18, p<0.001). Black and South Asian individuals had higher STDR hazards than white individuals (HR 1.57, 95% CI 1.50 to 1.64 and HR 1.36, 95% CI 1.31 to 1.42, respectively). Additionally, every 5-year increase in age at inclusion was associated with an 8% reduction in STDR hazards (p<0.001).

CONCLUSIONS

Ethnic disparities exist in a health system limited by capacity rather than patient economic circumstances. Diabetic retinopathy at first screen is a strong determinant of STDR development. By using basic demographic characteristics, screening programmes or clinical practices can stratify risk for sight-threatening diabetic retinopathy development.

Uncertainty-inspired open set learning for retinal anomaly identification

Failure to recognize samples from the classes unseen during training is a major limitation of artificial intelligence in the real-world implementation for recognition and classification of retinal anomalies. We establish an uncertainty-inspired open set (UIOS) model, which is trained with fundus images of 9 retinal conditions. Besides assessing the probability of each category, UIOS also calculates an uncertainty score to express its confidence. Our UIOS model with thresholding strategy achieves an F1 score of 99.55%, 97.01% and 91.91% for the internal testing set, external target categories (TC)-JSIEC dataset and TC-unseen testing set, respectively, compared to the F1 score of 92.20%, 80.69% and 64.74% by the standard AI model. Furthermore, UIOS correctly predicts high uncertainty scores, which would prompt the need for a manual check in the datasets of non-target categories retinal diseases, low-quality fundus images, and non-fundus images. UIOS provides a robust method for real-world screening of retinal anomalies.

Competing risks analysis for neutrophil to lymphocyte ratio as a predictor of diabetic retinopathy incidence in the Scottish population

BACKGROUND

Diabetic retinopathy (DR) is a major sight-threatening microvascular complication in individuals with diabetes. Systemic inflammation combined with oxidative stress is thought to capture most of the complexities involved in the pathology of diabetic retinopathy. A high level of neutrophil-lymphocyte ratio (NLR) is an indicator of abnormal immune system activity. Current estimates of the association of NLR with diabetes and its complications are almost entirely derived from cross-sectional studies, suggesting that the nature of the reported association may be more diagnostic than prognostic. Therefore, in the present study, we examined the utility of NLR as a biomarker to predict the incidence of DR in the Scottish population.

METHODS

The incidence of DR was defined as the time to the first diagnosis of R1 or above grade in the Scottish retinopathy grading scheme from type 2 diabetes diagnosis. The effect of NLR and its interactions were explored using a competing risks survival model adjusting for other risk factors and accounting for deaths. The Fine and Gray subdistribution hazard model (FGR) was used to predict the effect of NLR on the incidence of DR.

RESULTS

We analysed data from 23,531 individuals with complete covariate information. At 10 years, 8416 (35.8%) had developed DR and 2989 (12.7%) were lost to competing events (death) without developing DR and 12,126 individuals did not have DR. The median (interquartile range) level of NLR was 2.04 (1.5 to 2.7). The optimal NLR cut-off value to predict retinopathy incidence was 3.04. After accounting for competing risks at 10 years, the cumulative incidence of DR and deaths without DR were 50.7% and 21.9%, respectively. NLR was associated with incident DR in both Cause-specific hazard (CSH = 1.63; 95% CI: 1.28-2.07) and FGR models the subdistribution hazard (sHR = 2.24; 95% CI: 1.70-2.94). Both age and HbA1c were found to modulate the association between NLR and the risk of DR.

CONCLUSIONS

The current study suggests that NLR has a promising potential to predict DR incidence in the Scottish population, especially in individuals less than 65 years and in those with well-controlled glycaemic status.

Single retinal image for diabetic retinopathy screening: performance of a handheld device with embedded artificial intelligence

BACKGROUND

Diabetic retinopathy (DR) is a leading cause of blindness. Our objective was to evaluate the performance of an artificial intelligence (AI) system integrated into a handheld smartphone-based retinal camera for DR screening using a single retinal image per eye.

METHODS

Images were obtained from individuals with diabetes during a mass screening program for DR in Blumenau, Southern Brazil, conducted by trained operators. Automatic analysis was conducted using an AI system (EyerMaps™, Phelcom Technologies LLC, Boston, USA) with one macula-centered, 45-degree field of view retinal image per eye. The results were compared to the assessment by a retinal specialist, considered as the ground truth, using two images per eye. Patients with ungradable images were excluded from the analysis.

RESULTS

A total of 686 individuals (average age 59.2 ± 13.3 years, 56.7% women, diabetes duration 12.1 ± 9.4 years) were included in the analysis. The rates of insulin use, daily glycemic monitoring, and systemic hypertension treatment were 68.4%, 70.2%, and 70.2%, respectively. Although 97.3% of patients were aware of the risk of blindness associated with diabetes, more than half of them underwent their first retinal examination during the event. The majority (82.5%) relied exclusively on the public health system. Approximately 43.4% of individuals were either illiterate or had not completed elementary school. DR classification based on the ground truth was as follows: absent or nonproliferative mild DR 86.9%, more than mild (mtm) DR 13.1%. The AI system achieved sensitivity, specificity, positive predictive value, and negative predictive value percentages (95% CI) for mtmDR as follows: 93.6% (87.8-97.2), 71.7% (67.8-75.4), 42.7% (39.3-46.2), and 98.0% (96.2-98.9), respectively. The area under the ROC curve was 86.4%.

CONCLUSION

The portable retinal camera combined with AI demonstrated high sensitivity for DR screening using only one image per eye, offering a simpler protocol compared to the traditional approach of two images per eye. Simplifying the DR screening process could enhance adherence rates and overall program coverage.

Cross-sectional study investigating the prevalence and causes of vision impairment in Northwest Portugal using capture-recapture

OBJECTIVES

The aim of this study was to estimate the prevalence and causes of vision impairment (VI) in Portugal.

SETTING

Information about people with VI was obtained from primary care centres, blind association (ACAPO) and from hospitals (the PCVIP study) in the Northwest of Portugal during a period spanning years 2014-2015. Causes of VI were obtained from hospitals.

PARTICIPANTS

Administrative and medical records of people with visual acuity in the better seeing eye of 0.5 decimal (0.30logMAR) or worse and/or visual field less than 20° were investigated. Capture-recapture with log-linear models was applied to estimate the number of individuals missing from lists of cases obtained from available sources.

PRIMARY AND SECONDARY OUTCOME MEASURES

Log-linear models were used to estimate the crude prevalence and the category specific prevalence of VI.

RESULTS

Crude prevalence of VI was 1.97% (95% CI 1.56% to 2.54%), and standardised prevalence was 1% (95% CI 0.78% to 1.27%). The age-specific prevalence was 3.27% (95% CI 2.36% to 4.90%), older than 64 years, 0.64% (95% CI 0.49% to 0.88%), aged 25-64 years, and 0.07% (95% CI 0.045% to 0.13%), aged less than 25 years. The female-to-male ratio was 1.3, that is, higher prevalence among females. The five leading causes of VI were diabetic retinopathy, cataract, age-related macular degeneration, glaucoma and disorders of the globe.

CONCLUSIONS

The prevalence of VI in Portugal was within the expected range and in line with other European countries. A significant number of cases of VI might be due to preventable cases and, therefore, a reduction of the prevalence of VI in Portugal seems possible. Women and old people were more likely to have VI and, therefore, these groups require extra attention. Future studies are necessary to characterise temporal changes in prevalence of VI in Portugal.

Changes in the Epidemiology of Diabetic Retinopathy in Spain: A Systematic Review and Meta-Analysis

Background. The aim of the present study was to determine the prevalence and incidence of diabetic retinopathy (DR) and its changes in the last 20 years in type 2 diabetes mellitus (T2DM) patients in Spain. Methods. A systematic review with a meta-analysis was carried out on the studies published between 2001–2020 on the prevalence and incidence of DR and sight-threatening diabetic retinopathy (STDR) in Spain. The articles included were selected from four databases and publications of the Spanish Ministry of Health and Regional Health Care System (RHCS). The meta-analysis to determine heterogeneity and bias between studies was carried out with the MetaXL 4.0. Results. Since 2001, we have observed an increase in the detection of patients with DM, and at the same time, screening programs for RD have been launched; thus, we can deduce that the increase in the detection of patients with DM, many of them in the initial phases, far exceeds the increased detection of patients with DR. The prevalence of DR was higher between 2001 and 2008 with values of 28.85%. These values decreased over the following period between 2009 and 2020 with a mean of 15.28%. Similarly the STDR prevalence decrease from 3.67% to 1.92% after 2008. The analysis of the longitudinal studies determined that the annual DR incidence was 3.83%, and the STDR annual incidence was 0.41%. Conclusion. In Spain, for T2DM, the current prevalence of DR is 15.28% and 1.92% forSTDR. The annual incidence of DR is 3.83% and is 0.41% for STDR.

Improving the screening of risk factors in diabetic retinopathy

INTRODUCTION

In 2002, Diabetic Retinopathy was reported as the leading cause of blindness in the working age group. The introduction of systematic screening programs in the UK has reduced visual loss and blindness due to diabetic retinopathy, but it does still occur with catastrophic consequences for the individual.

AREAS COVERED

The author conducted an ongoing search for articles relating to diabetic retinopathy since 2000 utilizing Zetoc Alert with keywords and contents page lists from relevant journals. This review covers the risk factors for loss of vision due to diabetic retinopathy and discusses ways in which the awareness of these risk factors can be used to further reduce visual loss. Some risk factors such as glycemic and B/P control are well known from landmark trials. This review has included these factors but concentrated more on the evidence behind those risk factors that are not so clearly defined or so well known.

EXPERT OPINION

The major risk factors are well known, but one continues to find that people with diabetes lose vision in situations in which a better awareness of the risks by both the individual with diabetes and the health workers involved may have prevented the visual loss.

Identification of the Relationship between Hub Genes and Immune Cell Infiltration in Vascular Endothelial Cells of Proliferative Diabetic Retinopathy Using Bioinformatics Methods

Background

Diabetic retinopathy (DR) is a serious ophthalmopathy that causes blindness, especially in the proliferative stage. However, the pathogenesis of its effect on endothelial cells, especially its relationship with immune cell infiltration, remains unclear.

Methods

The dataset GSE94019 was downloaded from the Gene Expression Omnibus (GEO) database to obtain DEGs. Through aggregate analyses such as Gene Ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway enrichment analysis, a protein-protein interaction (PPI) network was constructed to analyze the potential function of DEGs. Weighted gene coexpression network analysis (WGCNA) and Cytoscape software including molecular complex detection (MCODE) and cytoHubba plug-ins were used to comprehensively analyze and determine the hub genes. ImmuCellAI analysis was performed to further study the relationship between samples, hub genes, and 24 types of immune cell infiltration. Finally, gene-set enrichment analysis (GSEA) was employed to identify the enrichment of immune cell infiltration and endothelial cell phenotype modifications in GO biological processes (BP) based on the expression level of hub genes.

Results

2393 DEGs were identified, of which 800 genes were downregulated, and 1593 genes were upregulated. The results of functional enrichment revealed that 1398 BP terms were significantly enriched in DEGs. Three hub genes, EEF1A1, RPL11, and RPS27A, which were identified by conjoint analysis using WGCNA and Cytoscape software, were positively correlated with the number of CD4 naive T cells and negatively correlated with the numbers of B cells. The number of CD4 naive T cells, T helper 2 (Th2) cells, and effector memory T (Tem) cells were significantly higher while CD8 naive T cells and B cells significantly were lower in the diabetic group than in the nondiabetic group.

Conclusions

We unearthed the DEGs and Hub genes of endothelial cells related to the pathogenesis of PDR: EEF1A1, RPL11, and RPS27A, which are highly related to each other and participate in the specific biological process of inflammation-related immune cell infiltration and endothelial cell development, chemotaxis, and proliferation, thus providing new perspectives into the diagnosis of and potential “killing two birds with one stone” targeted therapy for PDR.

Bridging the valley of death between research and implementing a systematic diabetic retinopathy screening program in low- and medium-income countries

Translating research findings to routine clinical practice is fraught with obstacles. The gap between the end of a research project and the implementation of its results is often termed the “valley of death.” In this perspective, we highlight the barriers and potential solutions in translating research on diabetic retinopathy care pathways to implementation in the clinic. This gap analysis applies to all countries around the world, though it predominantly applies to low- and middle-income countries.