Delay in diabetic retinopathy screening increases the rate of detection of referable diabetic retinopathy

Aims - To assess whether there is a relationship between delay in retinopathy screening after diagnosis of Type 2 diabetes and level of retinopathy detected. Methods - Patients were referred from 88 primary care practices to an English National Health Service diabetic eye screening programme. Data for screened patients were extracted from the primary care databases using semi-automated data collection algorithms supplemented by validation processes. The programme uses two-field mydriatic digital photographs graded by a quality assured team. Results - Data were available for 8183 screened patients with diabetes newly diagnosed in 2005, 2006 or 2007. Only 163 with Type 1 diabetes were identified and were insufficient for analysis. Data were available for 8020 with newly diagnosed Type 2 diabetes. Of these, 3569 were screened within 6 months, 2361 between 6 and 11 months, 1058 between 12 and 17 months, 366 between 18 and 23 months, 428 between 24 and 35 months, and 238 at 3 years or more after diagnosis. There were 5416 (67.5%) graded with no retinopathy, 1629 (20.3%) with background retinopathy in one eye, 753 (9.4%) with background retinopathy in both eyes and 222 (2.8%) had referable diabetic retinopathy. There was a significant trend (P = 0.0004) relating time from diagnosis to screening detecting worsening retinopathy. Of those screened within 6 months of diagnosis, 2.3% had referable retinopathy and, 3 years or more after diagnosis, 4.2% had referable retinopathy. Conclusions - The rate of detection of referable diabetic retinopathy is elevated in those who were not screened promptly after diagnosis of Type 2 diabetes

Prospective evaluation of an artificial intelligence-enabled algorithm for automated diabetic retinopathy screening of 30 000 patients.

BACKGROUND/AIMS: Human grading of digital images from diabetic retinopathy (DR) screening programmes represents a significant challenge, due to the increasing prevalence of diabetes. We evaluate the performance of an automated artificial intelligence (AI) algorithm to triage retinal images from the English Diabetic Eye Screening Programme (DESP) into test-positive/technical failure versus test-negative, using human grading following a standard national protocol as the reference standard. METHODS: Retinal images from 30 405 consecutive screening episodes from three English DESPs were manually graded following a standard national protocol and by an automated process with machine learning enabled software, EyeArt v2.1. Screening performance (sensitivity, specificity) and diagnostic accuracy (95% CIs) were determined using human grades as the reference standard. RESULTS: Sensitivity (95% CIs) of EyeArt was 95.7% (94.8% to 96.5%) for referable retinopathy (human graded ungradable, referable maculopathy, moderate-to-severe non-proliferative or proliferative). This comprises sensitivities of 98.3% (97.3% to 98.9%) for mild-to-moderate non-proliferative retinopathy with referable maculopathy, 100% (98.7%,100%) for moderate-to-severe non-proliferative retinopathy and 100% (97.9%,100%) for proliferative disease. EyeArt agreed with the human grade of no retinopathy (specificity) in 68% (67% to 69%), with a specificity of 54.0% (53.4% to 54.5%) when combined with non-referable retinopathy. CONCLUSION: The algorithm demonstrated safe levels of sensitivity for high-risk retinopathy in a real-world screening service, with specificity that could halve the workload for human graders. AI machine learning and deep learning algorithms such as this can provide clinically equivalent, rapid detection of retinopathy, particularly in settings where a trained workforce is unavailable or where large-scale and rapid results are needed

A Simple Risk Stratification for Time to Development of Sight-Threatening Diabetic Retinopathy

OBJECTIVE: The American Diabetes Association and the English NHS Diabetic Eye Screening Program recommend annual screening for diabetic retinopathy (DR) with referral to ophthalmology clinics of patients with sight-threatening DR (STDR). Using only longitudinal data from retinal photographs in the population-based NHS Diabetic Eye Screening Program in Gloucestershire, we developed a simple means to estimate risk of STDR. RESEARCH DESIGN AND METHODS: From 2005, 14,554 patients with no DR or mild nonproliferative DR only at two consecutive annual digital photographic screenings were categorized by the presence of DR in neither, one, or both eyes at each screening and were followed for a further median 2.8 years. RESULTS: Of 7,246 with no DR at either screening, 120 progressed to STDR, equivalent to an annual rate of 0.7%. Of 1,778 with no DR in either eye at first screening and in one eye at second screening, 80 progressed to STDR, equivalent to an annual rate of 1.9% and to a hazard ratio (HR) of 2.9 (95% CI 2.2-3.8) compared with those with no DR. Of 1,159 with background DR in both eyes at both screenings, 299 progressed to STDR equivalent to an annual rate of 11% and an HR of 18.2 (14.7-22.5) compared with individuals with no DR. CONCLUSIONS: Combining the results from 2 consecutive years of photographic screening enables estimation of the risk of future development of STDR. In countries with systematic screening programs, these results could inform decisions about screening frequency

Serum Heat Shock Protein 27 and Diabetes Complications in the EURODIAB Prospective Complications Study : A Novel Circulating Marker for Diabetic Neuropathy

OBJECTIVE—Heat shock protein 27 (HSP27) is a member of the small heat shock protein family of proteins. HSP27 expression is enhanced in target tissues of diabetic microvascular complications, and changes in circulating serum HSP27 levels (sHSP27) have been reported in patients with macrovascular disease. We investigated whether sHSP27 levels were associated with micro- and macrovascular complications in type 1 diabetic patients

Clinical efficacy and safety of a light mask for prevention of dark adaptation in treating and preventing progression of early diabetic macular oedema at 24 months (CLEOPATRA): a multicentre, phase 3, randomised controlled trial

Background: We aimed to assess 24-month outcomes of wearing an organic light-emitting sleep mask as an intervention to treat and prevent progression of non-central diabetic macular oedema. Methods: CLEOPATRA was a phase 3, single-blind, parallel-group, randomised controlled trial undertaken at 15 ophthalmic centres in the UK. Adults with non-centre-involving diabetic macular oedema were randomly assigned (1:1) to wearing either a light mask during sleep (Noctura 400 Sleep Mask, PolyPhotonix Medical, Sedgefield, UK) or a sham (non-light) mask, for 24 months. Randomisation was by minimisation generated by a central web-based computer system. Outcome assessors were masked technicians and optometrists. The primary outcome was the change in maximum retinal thickness on optical coherence tomography (OCT) at 24 months, analysed using a linear mixed-effects model incorporating 4-monthly measurements and baseline adjustment. Analysis was done using the intention-to-treat principle in all randomised patients with OCT data. Safety was assessed in all patients. This trial is registered with Controlled-Trials.com, number ISRCTN85596558. Findings: Between April 10, 2014, and June 15, 2015, 308 patients were randomly assigned to wearing the light mask (n=155) or a sham mask (n=153). 277 patients (144 assigned the light mask and 133 the sham mask) contributed to the mixed-effects model over time, including 246 patients with OCT data at 24 months. The change in maximum retinal thickness at 24 months did not differ between treatment groups (mean change −9·2 μm [SE 2·5] for the light mask vs −12·9 μm [SE 2·9] for the sham mask; adjusted mean difference −0·65 μm, 95% CI −6·90 to 5·59; p=0·84). Median compliance with wearing the light mask at 24 months was 19·5% (IQR 1·9–51·6). No serious adverse events were related to either mask. The most frequent adverse events related to the assigned treatment were discomfort on the eyes (14 with the light mask vs seven with the sham mask), painful, sticky, or watery eyes (14 vs six), and sleep disturbance (seven vs one). Interpretation: The light mask as used in this study did not confer long-term therapeutic benefit on non-centre-involving diabetic macular oedema and the study does not support its use for this indication. Funding: The Efficacy and Mechanism Evaluation Programme, a Medical Research Council and National Institute for Health Research partnership

Effects of Topically Administered Neuroprotective Drugs in Early Stages of Diabetic Retinopathy:Results of the EUROCONDOR Clinical Trial

The primary objective of this study was to assess whether the topical administration of two neuroprotective drugs (brimonidine and somatostatin) could prevent or arrest retinal neurodysfunction in patients with type 2 diabetes. For this purpose, adults aged between 45 and 75 years with a diabetes duration ≥5 years and an Early Treatment of Diabetic Retinopathy Study (ETDRS) level of ≤35 were randomly assigned to one of three arms: placebo, somatostatin, or brimonidine. The primary outcome was the change in implicit time (IT) assessed by multifocal electroretinography between baseline and at the end of follow-up (96 weeks). There were 449 eligible patients allocated to brimonidine (n = 152), somatostatin (n = 145), or placebo (n = 152). When the primary end point was evaluated in the whole population, we did not find any neuroprotective effect of brimonidine or somatostatin. However, in the subset of patients (34.7%) with preexisting retinal neurodysfunction, IT worsened in the placebo group (P < 0.001) but remained unchanged in the brimonidine and somatostatin groups. In conclusion, the topical administration of the selected neuroprotective agents appears useful in preventing the worsening of preexisting retinal neurodysfunction. This finding points to screening retinal neurodysfunction as a critical issue to identify a subset of patients in whom neuroprotective treatment might be of benefit