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Background: Diabetic retinopathy (DR) is characterised by neurovascular degeneration as a result of chronic hyperglycaemia. Proliferative diabetic retinopathy (PDR) is the most serious complication of DR and can lead to total (central and peripheral) visual loss. PDR is characterised by the presence of abnormal new blood vessels, so-called "new vessels," at the optic disc (NVD) or elsewhere in the retina (NVE). PDR can progress to high-risk characteristics (HRC) PDR (HRC-PDR), which is defined by the presence of NVD more than one-fourth to one-third disc area in size plus vitreous haemorrhage or pre-retinal haemorrhage, or vitreous haemorrhage or pre-retinal haemorrhage obscuring more than one disc area. In severe cases, fibrovascular membranes grow over the retinal surface and tractional retinal detachment with sight loss can occur, despite treatment. Although most, if not all, individuals with diabetes will develop DR if they live long enough, only some progress to the sight-threatening PDR stage.  OBJECTIVES: To determine risk factors for the development of PDR and HRC-PDR in people with diabetes and DR., Search Methods: We searched the Cochrane Central Register of Controlled Trials (CENTRAL; which contains the Cochrane Eyes and Vision Trials Register; 2022, Issue 5), Ovid MEDLINE, and Ovid Embase. The date of the search was 27 May 2022. Additionally, the search was supplemented by screening reference lists of eligible articles. There were no restrictions to language or year of publication.  SELECTION CRITERIA: We included prospective or retrospective cohort studies and case-control longitudinal studies evaluating prognostic factors for the development and progression of PDR, in people who have not had previous treatment for DR. The target population consisted of adults (≥18 years of age) of any gender, sexual orientation, ethnicity, socioeconomic status, and geographical location, with non-proliferative diabetic retinopathy (NPDR) or PDR with less than HRC-PDR, diagnosed as per standard clinical practice. Two review authors independently screened titles and abstracts, and full-text articles, to determine eligibility; discrepancies were resolved through discussion. We considered prognostic factors measured at baseline and any other time points during the study and in any clinical setting. Outcomes were evaluated at three and eight years (± two years) or lifelong.  DATA COLLECTION AND ANALYSIS: Two review authors independently extracted data from included studies using a data extraction form that we developed and piloted prior to the data collection stage. We resolved any discrepancies through discussion. We used the Quality in Prognosis Studies (QUIPS) tool to assess risk of bias. We conducted meta-analyses in clinically relevant groups using a random-effects approach. We reported hazard ratios (HR), odds ratios (OR), and risk ratios (RR) separately for each available prognostic factor and outcome, stratified by different time points. Where possible, we meta-analysed adjusted prognostic factors. We evaluated the certainty of the evidence with an adapted version of the GRADE framework.   MAIN RESULTS: We screened 6391 records. From these, we identified 59 studies (87 articles) as eligible for inclusion. Thirty-five were prospective cohort studies, 22 were retrospective studies, 18 of which were cohort and six were based on data from electronic registers, and two were retrospective case-control studies. Twenty-three studies evaluated participants with type 1 diabetes (T1D), 19 with type 2 diabetes (T2D), and 17 included mixed populations (T1D and T2D). Studies on T1D included between 39 and 3250 participants at baseline, followed up for one to 45 years. Studies on T2D included between 100 and 71,817 participants at baseline, followed up for one to 20 years. The studies on mixed populations of T1D and T2D ranged from 76 to 32,553 participants at baseline, followed up for four to 25 years.  We found evidence indicating that higher glycated haemoglobin (haemoglobin A1c (HbA1c)) levels (adjusted OR ranged from 1.11 (95% confidence interval (CI) 0.93 to 1.32) to 2.10 (95% CI 1.64 to 2.69) and more advanced stages of retinopathy (adjusted OR ranged from 1.38 (95% CI 1.29 to 1.48) to 12.40 (95% CI 5.31 to 28.98) are independent risk factors for the development of PDR in people with T1D and T2D. We rated the evidence for these factors as of moderate certainty because of moderate to high risk of bias in the studies.  There was also some evidence suggesting several markers for renal disease (for example, nephropathy (adjusted OR ranged from 1.58 (95% CI not reported) to 2.68 (2.09 to 3.42), and creatinine (adjusted meta-analysis HR 1.61 (95% CI 0.77 to 3.36)), and, in people with T1D, age at diagnosis of diabetes (< 12 years of age) (standardised regression estimate 1.62, 95% CI 1.06 to 2.48), increased triglyceride levels (adjusted RR 1.55, 95% CI 1.06 to 1.95), and larger retinal venular diameters (RR 4.28, 95% CI 1.50 to 12.19) may increase the risk of progression to PDR. The certainty of evidence for these factors, however, was low to very low, due to risk of bias in the included studies, inconsistency (lack of studies preventing the grading of consistency or variable outcomes), and imprecision (wide CIs). There was no substantial and consistent evidence to support duration of diabetes, systolic or diastolic blood pressure, total cholesterol, low- (LDL) and high- (HDL) density lipoproteins, gender, ethnicity, body mass index (BMI), socioeconomic status, or tobacco and alcohol consumption as being associated with incidence of PDR. There was insufficient evidence to evaluate prognostic factors associated with progression of PDR to HRC-PDR.  AUTHORS' CONCLUSIONS: Increased HbA1c is likely to be associated with progression to PDR; therefore, maintaining adequate glucose control throughout life, irrespective of stage of DR severity, may help to prevent progression to PDR and risk of its sight-threatening complications. Renal impairment in people with T1D or T2D, as well as younger age at diagnosis of diabetes mellitus (DM), increased triglyceride levels, and increased retinal venular diameters in people with T1D may also be associated with increased risk of progression to PDR. Given that more advanced DR severity is associated with higher risk of progression to PDR, the earlier the disease is identified, and the above systemic risk factors are controlled, the greater the chance of reducing the risk of PDR and saving sight., (Copyright © 2023 The Authors. Cochrane Database of Systematic Reviews published by John Wiley & Sons, Ltd. on behalf of The Cochrane Collaboration.)

Introduction: Undiagnosed diabetes is a global health issue. Previous studies have estimated that about 24.1%-75.1% of all diabetes cases are undiagnosed, leading to more diabetic complications and inducing huge healthcare costs. Many current methods for diabetes diagnosis rely on metabolic indices and are subject to considerable variability. In contrast, a digital approach based on retinal image represents a stable marker of overall glycemic status., Research Design and Methods: Our study involves 2221 subjects for developing a classification model, with 945 subjects with diabetes and 1276 controls. The training data included 70% and the testing data 30% of the subjects. All subjects had their retinal images taken using a non-mydriatic fundus camera. Two separate data sets were used for external validation. The Hong Kong testing data contain 734 controls without diabetes and 660 subjects with diabetes, and the UK testing data have 1682 subjects with diabetes., Results: The 10-fold cross-validation using the support vector machine approach has a sensitivity of 92% and a specificity of 96.2%. The separate testing data from Hong Kong provided a sensitivity of 99.5% and a specificity of 91.1%. For the UK testing data, the sensitivity is 98.0%. The accuracy of the Caucasian retinal images is comparable with that of the Asian data. It implies that the digital method can be applied globally. Those with diabetes complications in both Hong Kong and UK data have a higher probability of risk of diabetes compared with diabetes subjects without complications., Conclusions: A digital machine learning-based method to estimate the risk of diabetes based on retinal images has been developed and validated using both Asian and Caucasian data. Retinal image analysis is a fast, convenient, and non-invasive technique for community health applications. In addition, it is an ideal solution for undiagnosed diabetes prescreening., Competing Interests: Competing interests: BZ and JL have a patent 'Method and device for retinal image analysis' licensed to Health View Bioanalytic, which received royalties through The Chinese University of Hong Kong. BZ and JL are founders and shareholders of Health View Bioanalytic, Bioanalytic Holdings, and Bioanalytic International Holdings. ML is the director of Bioanalytic Holdings and Bioanalytic International Holdings., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Medical image segmentation is a well-studied subject within the field of image processing. The goal of this research is to create an AI retinal screening grading system that is both accurate and fast. We introduce a new segmentation network which achieves state-of-the-art results on semantic segmentation of color fundus photographs. By applying the net-work to identify anatomical markers of diabetic retinopathy (DR) and diabetic macular edema (DME), we collect sufficient information to classify patients by grades R0 and R1 or above, M0 and M1., Methods: The AI grading system was trained on screening data to evaluate the presence of DR and DME. The core algorithm of the system is a deep learning network that segments relevant anatomical features in a retinal image. Patients were graded according to the standard NHS Diabetic Eye Screening Program feature-based grading protocol., Results: The algorithm performance was evaluated with a series of 6,981 patient retinal images from routine diabetic eye screenings. It correctly predicted 98.9% of retinopathy events and 95.5% of maculopathy events. Non-disease events prediction rate was 68.6% for retinopathy and 81.2% for maculopathy., Conclusion: This novel deep learning model was trained and tested on patient data from annual diabetic retinopathy screenings can classify with high accuracy the DR and DME status of a person with diabetes. The system can be easily reconfigured according to any grading protocol, without running a long AI training procedure. The incorporation of the AI grading system can increase the graders' productivity and improve the final outcome accuracy of the screening process.

Aims: Identifying and modulating risk factors is essential to prevent visual impairment due to diabetic retinopathy (DR). This study examines incident DR with metabolic and hormonal factors in newly-diagnosed, treatment naïve, individuals with Type2 Diabetes Mellitus (T2DM), over a 5 year period from diagnosis., Methods: 233 T2DM subjects underwent serial DR screening using digital photography and standardised Meal Tolerance Tests at diagnosis and after 1, 2 and 5 years. Subjects (179) with no DR throughout the 5-year study period were compared with those who developed DR (54)., Results: Of 233 subjects, 54(23.2%) developed DR by 5 years, background DR in 50(93%) and exudative maculopathy in 4(7%) individuals. Of these subjects, 12(22%) developed DR after 1 year, 15(28%) after 2 years and 27(50%) after 5 years. At baseline, those with DR at 5 years had higher HbA 1c (p = 0.017), higher fasting plasma glucose (PG) (p = 0.031) and postprandial PG (p = 0.009). They were associated with reduced basal β-cell secretory function (M 0 ) (p = 0.025), lower (p = 0.000) postprandial β-cell responsiveness (M 1 ) and β-cell function (HOMA-B) (p = 0.044)., Conclusions: There is an independent association between glycaemic control and β-cell dysfunction at the time of diagnosis of T2DM, with incident DR over a follow-up period of 5 years., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Objective: To determine the risk factors for having diabetic retinopathy (DR) in children and young people (CYP) with type 1 diabetes (T1DM) at first screening., Methods: Records from the Diabetes Eye Screening Wales (DESW) service for people in Wales, UK, with T1DM diagnosed under age 18 years were combined with other electronic health record (EHR) data in the Secure Anonymised Information Linkage (SAIL) Databank. Data close to the screening date were collected, and risk factors derived from multivariate, multinomial logistic regression modelling., Results: Data from 4172 persons, with median (lower quartile, upper quartile) age 16.3 (13.0, 22.3) years and duration of diabetes 6.6 (2.3, 12.3) years were analysed. 62.6% (n = 2613) had no DR, 26.7% (n = 1112) background DR, and 10.7% (n = 447) had referable DR (RDR). No RDR was observed under 19 years of age. Factors associated with an increased risk of DR were diabetes duration, elevated HbA 1c , and diastolic blood pressure. People diagnosed with T1DM at 12 years or older had an additional risk for each year they had diabetes compared to those diagnosed before age 12 controlling for the diabetes duration (odds ratios 1.23 and 1.34, respectively)., Conclusions: This study found that 37.4% of the study cohort had DR at first screening, the risk being greater the longer the duration of diabetes or higher the HbA 1c and diastolic blood pressure. In addition, people diagnosed at 12 years of age or over were more likely to have DR with each additional year with diabetes., (© 2020. The Author(s), under exclusive licence to Springer Nature Limited part of Springer Nature.)

Aims: To understand factors associated with repeat non-attendance at screening for diabetes-related retinopathy., Methods: Retrospective observational study using anonymised data from Diabetic Eye Screening Wales for people with a full history of screening invitations and attendances was linked with primary and secondary care records held in the Secure Anonymised Information Linkage Databank. Repeat non-attendance was defined as no record of attendance during any 36-month period despite three cycles of annual screening invitations. The associations between repeat non-attendance and potential risk factors were examined using multivariable logistic regression analysis, stratified according to type 1 and type 2 diabetes., Results: A total of 18% with type 1 diabetes (1146/6513) and 8% with type 2 diabetes (12,475/156,525) were repeat non-attenders. Participants attending their very first appointment were least likely to become repeat non-attenders [odds ratio (95% confidence interval)]: type 1 diabetes: 0.12 (0.09, 0.17) and type 2 diabetes: 0.08 (0.07, 0.09). For both types of diabetes, those of a younger age, living in areas of higher deprivation and subject to multiple house moves were at greater risk of becoming repeat non-attenders., Conclusion/interpretation: A more tailored approach is needed for the younger population, those living in areas of higher deprivation and/or undergoing multiple residential relocation and to ensure attendance at their initial appointment to minimise future repeat non-attendance., (© 2021 The Authors. Diabetic Medicine published by John Wiley & Sons Ltd on behalf of Diabetes UK.)

Objective: Examine the health and economic impact of extending screening intervals in people with Type 2 diabetes (T2DM) and Type 1 diabetes (T1DM) without diabetes-related retinopathy (DR)., Setting: Diabetic Eye Screening Wales (DESW)., Study Design: Retrospective observational study with cost-utility analysis (CUA) and Decremental Cost-Effectiveness Ratios (DCER) study., Intervention: Biennial screening versus usual care (annual screening)., Inputs: Anonymised data from DESW were linked to primary care data for people with two prior screening events with no DR. Transition probabilities for progression to DR were estimated based on a subset of 26,812 and 1232 people with T2DM and T1DM, respectively. DCER above £20,000 per QALY was considered cost-effective., Results: The base case analysis DCER results of £71,243 and £23,446 per QALY for T2DM and T1DM respectively at a 3.5% discount rate and £56,822 and £14,221 respectively when discounted at 1.5%. Diabetes management represented by the mean HbA 1c was 7.5% for those with T2DM and 8.7% for T1DM., Sensitivity Analysis: Extending screening to biennial based on HbA 1c , being the strongest predictor of progression of DR, at three levels of HbA 1c 6.5%, 8.0% and 9.5% lost one QALY saving the NHS £106,075; £58,653 and £31,626 respectively for T2DM and £94,696, £37,646 and £11,089 respectively for T1DM. In addition, extending screening to biennial based on the duration of diabetes > 6 years for T2DM per QALY lost, saving the NHS £54,106 and for 6-12 and > 12 years for T1DM saving £83,856, £23,446 and £13,340 respectively., Conclusions: Base case and sensitivity analyses indicate biennial screening to be cost-effective for T2DM irrespective of HbA 1c and duration of diabetes. However, the uncertainty around the DCER indicates that annual screening should be maintained for those with T1DM especially when the HbA 1c exceeds 80 mmol/mol (9.5%) and duration of diabetes is greater than 12 years.

Objectives: To compare retinal thickness before and after treatment with the fluocinolone acetonide (FAc) 190 µg intravitreal implant in people with diabetic macular edema (DME) using data from the Iluvien Clinical Evidence study in the UK (ICE-UK)., Methods: For this retrospective cohort study, data on people attending any one of 13 participating ophthalmology departments and treated with FAc intravitreal implant between April 1, 2013 and April 15, 2015 were collected for 12 months prior to and at least 12 months after implantation. Cross-sectional and longitudinal patterns of central foveal thickness (CFT) were compared before and after FAc implant., Results: There were 208 people who contributed data from 233 individual eyes treated with the FAc implant. Mean age was 68.1 years and 62% were male. Median (interquartile range) CFT decreased from 462 µm (354-603 µm) at time of implant to 309 µm (222-433 µm) at 12 months post-implant (p < .001). Over the same period, a reduction of ≥10%, ≥25%, and ≥50% in CFT was observed in 113 (65%), 87 (50%), and 37 (21%) treated eyes, respectively. Eyes with a CFT of ≥400 µm at the time of implant were significantly more likely to achieve a reduction in CFT of ≥10%, ≥25%, and ≥50% at 12 months (all p < .001) compared with eyes with a CFT of <400 µm at implant. Both retinal thickness and changes in retinal thickness were loosely correlated with visual acuity., Conclusion: A marked reduction in retinal thickness was observed in people following FAc intravitreal implant for DME. The response was related to the degree of retinal thickness prior to treatment.

Objectives: To compare visual and anatomical outcomes between eyes treated with fluocinolone acetonide (FAc) 190 µg intravitreal implant for clinically significant chronic diabetic macular edema (DME) and fellow eyes not treated with FAc implant using data from the Iluvien Clinical Evidence study in the UK (ICE-UK) study., Methods: In this retrospective cohort study, data on people attending hospital eye services and treated with the FAc implant between April 1, 2013 and April 15, 2015 were collected. Changes in visual acuity (VA), central foveal thickness (CFT) and intraocular pressure (IOP) were compared between study eyes (intervention) and fellow eyes., Results: A total of 208 people were selected. Mean age was 68.1 years and 62% were male. Mean change in VA was -0.09 LogMAR units for study eyes and 0.04 LogMAR units for fellow eyes at 12 months post-implant (p < .001). Over the same period, ≥5 letter, ≥10 letter and ≥15 letter improvements in Early Treatment Diabetic Retinopathy Study (ETDRS) score were achieved by more FAc treated eyes than by fellow eyes (41% versus 23%, p < .001; 28% versus 11%, p < .001; and 18% versus 4%, p < .001 at 12 months, respectively). Differences in the mean change in CFT (-113 µm versus -13 µm, p < .001) and IOP (3.2 mmHg versus -0.2 mmHg, p < .001) were also observed between study and fellow eyes at 12 months., Conclusion: Visual acuity improved in study eyes over the 12 months following FAc implant and worsened in fellow eyes. Over the same period, study eyes showed a larger improvement in central foveal thickness. Intraocular pressure worsened in study eyes only. Change in visual acuity, central foveal thickness and intraocular pressure between FAc implant and the end of the 12-month follow-up period differed significantly between study and fellow eyes.

Objectives: To assess healthcare resource use and costs of treating people with clinically significant diabetic macular edema (DME) with fluocinolone acetonide (FAc) 190 µg intravitreal implant in routine clinical practice., Methods: The retrospective Iluvien Clinical Evidence (ICE-UK) study collected data on people prescribed the FAc implant in any one of 13 ophthalmology centers between April 1, 2013 and April 15, 2015. Data were collected for 12 months before and after implantation. Standard UK costs were attributed to healthcare resource use., Results: In total, 208 people contributing 233 FAc-treated eyes were selected. Mean age was 68.1 years and 62% were male. The mean (standard deviation, SD) number of anti-vascular endothelial growth factor (anti-VEGF) injections per FAc treated eye in the 12 months prior to implant was 2.8 (2.5), decreasing to 0.6 (1.4) for the same period after implant (p < .001). The corresponding figures for other steroid injections (dexamethasone and triamcinolone) were 0.14 (0.4) before and 0.08 (0.4) after implant (p = .016). There was no statistically significant difference in the number of laser therapies required in the 12 months before and after FAc implant (mean = 0.12 vs 0.11, respectively; p = .626). Overall, mean (SD) healthcare costs were £2,691 (£1,850) before and £1,239 (£1,203) after FAc implant (p < .001). The unit drug and administration cost per FAc implant was £5,680., Conclusions: Excluding the cost of the FAc implant, healthcare costs were significantly reduced in the 12 months post-implant. FAc implant has a duration of 3 years. This needs to be considered when interpreting the cost associated with the FAc implant.

Objective: The aim of the Iluvien Clinical Evidence study in the UK (ICE-UK) was to assess the real-world effectiveness of fluocinolone acetonide (FAc) 190 µg intravitreal implant for the treatment of clinically significant chronic diabetic macular edema (DME) in routine clinical practice., Methods: This retrospective study collected data from patient medical records in 13 ophthalmology centers for people with DME prescribed FAc intravitreal implant between April 1, 2013 and April 15, 2015. Visual acuity (VA) and intraocular pressure (IOP) measurements were collected for 12 months prior to and after implant., Results: Two hundred and eight people, contributing 233 eyes, treated with FAc implant were included. Mean age was 68.1 years and 62% were male. In the 12 months prior to FAc implant, VA declined. Median (interquartile range, IQR) VA was 0.66 (0.48-1.00) LogMAR units (equivalent to 52.0 ETDRS letters) at implant, improving to 0.60 (0.38-0.90) LogMAR units (55.0 letters) at 12 months post-implant (p < 0.001). In total, 44%, 30%, and 18% of people achieved an improvement in ETDRS score of ≥5, ≥10, and ≥15 letters, respectively, over the same period. A small but significant (p < .001) increase in median IOP was observed (median = 15.0, IQR = 13.0-18.0 mmHg at implant to 18.0, 15.0-21.0 mmHg at 12 months). In the 12 months following implant, additional IOP-lowering therapy was prescribed in 15% of subjects previously not requiring such therapy., Conclusion: Following FAc implant, an overall significant improvement in VA was observed over a period of 12 months, accompanied by a significant but small increase in IOP.

Objective: The aim of this study was to analyse the changes in new certifications for both sight impairment (SI) and severe sight impairment (SSI, blindness) in Wales due to diabetic retinopathy (DR)/maculopathy between 2007 and 2015., Research Design and Methods: This is a retrospective analysis of annual data of new certifications for visual impairment and blindness (Certificate of Vision Impairment) for England and Wales derived from the national database provided by the Certifications Office, Moorfields Eye Hospital, over a period of 8 years from 2007., Results: In Wales there were 339 less new certifications for both SI and severe SSI from any cause combined from 2007-2008 to 2014-2015. The number SI and SSI combined specifically due to DR was reduced by 22 in people with known diabetes. This was a reduction in new certifications over the observation period from 82.4 to 46.9 per 100 000 (-43.1%) with a fall in SSI from 31.3 to 15.8 per 100 000 (-49.4%), respectively. During this observation period however, there was a parallel increase in 52 229 (39.8%) persons with diabetes in Wales., Conclusions: While acknowledging the limitations of the certification process and the increasing numbers of persons with diabetes, the incidence of SI and SSI per 100 000 population of persons with diabetes in Wales has almost halved over an 8-year period up to 2015. This may reflect the earlier diagnosis of DR and sight-threatening DR since the introduction of screening and/or improved diabetes management with timely onward referral and newer treatments., Competing Interests: Competing interests: None declared., (© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.)

Purpose: The association of hyperglycemia and diabetic retinopathy (DR) in established type 2 diabetes mellitus (T2DM) subjects is well accepted. However, the association between β-cell responsiveness and insulin sensitivity leading to fasting and postprandial hyperglycemia with DR in newly diagnosed treatment-naïve T2DM subjects remain unreported., Methods: A total of 544 newly diagnosed treatment-naïve T2DM subjects were screened for DR (digital photography) and underwent a standardized meal tolerance test. Serial plasma glucose and insulin levels were measured, and fasting (M0) and postprandial β-cell responsiveness calculated Calculating Pancreatic Response Program along with homeostasis model assessment-β cell function (HOMA-B) and HOMA-Insulin Sensitivity. A subgroup of 201 subjects also underwent a frequently sampled IV glucose tolerance test and the acute insulin response to glucose, insulin sensitivity, and glucose effectiveness (SG) estimated (MINMOD model)., Results: A total of 16.5% (90) subjects had DR at diagnosis. Subjects with DR had significantly reduced M0, HOMA-B and SG leading to higher fasting and postprandial (2 hour) glucose and significantly lower fasting and postprandial (2 hour) insulin. Factors independently associated with DR in multivariate logistic regression analysis were M0, HOMA-B, and SG with fasting and postprandial (2 hour) glucose and insulin. There was no statistical difference in glycated hemoglobin, systolic blood pressure, acute insulin response to glucose, and insulin sensitivity between those with or without DR., Principal Conclusions: In this cohort of newly diagnosed T2DM subjects, DR is associated with reduced β-cell responsiveness, resulting from β-cell failure rather than insulin resistance, leading to fasting and postprandial hyperglycemia and hypoinsulinemia.

Aims: Determine the prevalence and severity of diabetic retinopathy (DR) and risk factors in a large community based screening programme, in order to accurately estimate the future burden of this specific and debilitating complication of diabetes., Methods: A cross-sectional analysis of 91,393 persons with diabetes, 5003 type 1 diabetes and 86,390 type 2 diabetes, at their first screening by the community based National Diabetic Retinopathy Screening Service for Wales from 2005 to 2009. Image capture used 2×45° digital images per eye following mydriasis, classified by qualified retinal graders with final grading based on the worst eye., Results: The prevalence of any DR and sight-threatening DR in those with type 1 diabetes was 56.0% and 11.2%, respectively, and in type 2 diabetes was 30.3% and 2.9%, respectively. The presence of DR, non-sight-threatening and sight-threatening, was strongly associated with increasing duration of diabetes for either type 1 or type 2 diabetes and also associated with insulin therapy in those with type 2 diabetes., Conclusions: Prevalence of DR within the largest reported community-based, quality assured, DR screening programme, was higher in persons with type 1 diabetes; however, the major burden is represented by type 2 diabetes which is 94% of the screened population., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.)

Aims: To assess the incidence and progression of diabetic retinopathy (DR) 12 months post bariatric surgery in persons with morbid obesity and type 2 diabetes., Methods: A retrospective pilot analysis of electronic hospital records between 1998 and 2012., Results: 40 of 148 subjects had pre- and post-surgery DR screening. Of those without DR pre-surgery 1.5% (n = 26) progressed to minimum background DR (BDR) post surgery. Those with minimum BDR (n = 9) pre-surgery revealed no progression, with 55.6% (n = 5) showing evidence of regression. One person with moderately severe BDR and two with pre-proliferative DR (PPDR) prior to surgery experienced progression. Two persons with PPDR prior to surgery remained under the hospital eye services and were therefore not eligible to be re-assessed by the screening service., Conclusions: There was a low incidence of new DR and progression of DR in those either without evidence of retinopathy or with minimal BDR prior to surgery with some subjects showing evidence of regression. There was however a risk of progression of DR in those with moderate BDR or worse, and should therefore be monitored closely post-surgery., (© 2014.)

Objective: To describe the prevalence and associated risk factors for diabetic retinopathy (DR) within a multiethnic population at presentation to a diabetes clinic in South Africa., Research Design and Methods: Retinal photography was conducted using a nonmydriatic digital camera without mydriasis and graded by one of three senior graders. Logistic regression analyses were used to assess the association between any DR, referable DR, and clinical risk factors., Results: A total of 1,537 persons with type 1 and 3,978 with type 2 diabetes were included. Prevalence of any DR in type 1 diabetes was 35.2% (background DR 26% and referable DR 9.2%) and in type 2 diabetes was 20.5% (14.1 and 6.4%, respectively). In type 1 diabetes, there was an increased risk of any DR in Asian Indians, whereas the risk of referable DR was increased for indigenous Africans compared with Caucasians. In type 2 diabetes, the risk was increased for all non-Caucasians compared with Caucasians. Longer duration of diabetes and elevated HbA(1c) were independently associated with any and referable DR in both type 1 and type 2 diabetes, with the addition of hypertension and smoking in type 1 diabetes when adjusted for age at diagnosis of diabetes, sex, and ethnicity., Conclusions: The prevalence of DR in this population from South Africa was similar to that reported globally; however, ethnic differences were observed. Increasing duration of diabetes and poor glycemic control were the strongest risk factors associated with any and referable DR in both type 1 and type 2 diabetes.

The prevalence of diabetes in developing countries is on the increase and along with it the need to provide structured care to avoid the feared long term complications among them loss of vision and blindness due to diabetic retinopathy (DR). The biggest hurdle facing most developing countries is the lack of resources and trained manpower to both screen and treat the large number of people with DR. Countries also face the additional problem of unequal distribution of resources between the urban and rural areas. To overcome these challenges models of mobile diabetic retinopathy screening and treatment aided by the use of telemedicine have been introduced and demonstrated to be popular and effective. The aim of this review article is to describe different mobile diabetic retinopathy screening and treatment models developed in India, which can be readily replicated in developing countries presented with similar difficulties., (Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.)

Background: This study evaluated the operating characteristics of a reading software (Retinalyze System, Retinalyze A/S, Hørsholm, Denmark) for automated prescreening of digital fundus images for diabetic retinopathy., Methods: Digital fundus images of patients with diabetes were retrospectively selected from the Bro Taf diabetic retinopathy screening program in Wales, UK in the period of 2002-2004, which has been superseded by the Diabetic Retinopathy Screening Service for Wales. A gold standard reference was defined by classifying each patient as having or not having diabetic retinopathy based on overall visual grading of the digitized images using the Bro Taf reading protocol. Automated grading was applied using automated red or bright lesion detection at varying detection sensitivities and adjusting for image quality. Operating characteristics included sensitivity, specificity, positive predictive values, and negative predictive values (PPV and NPV, respectively)., Results: Automated analysis of four hundred fundus photographs of 192 eyes from 96 patients with diabetes was performed. The automated red lesion detection had a sensitivity of 82%, specificity of 75%, PPV of 41%, and NPV of 95%. Combined automated red and bright lesion detection yielded a sensitivity of 88%, specificity of 52%, PPV of 28%, and NPV of 95%. Performance of the combined red and bright lesion detection at elevated thresholds in images of good quality demonstrated a sensitivity of 93%, specificity of 78%, PPV of 46%, and NPV of 98%., Conclusions: Prescreening for diabetic retinopathy by automated detection of single fundus lesions seem to be achieved with minimal false negativity and can help to decrease the burden of manual diabetic retinopathy screening.

Purpose: Our aim was to determine if pulsatile ocular blood flow (POBF) measurements could distinguish between type 2 diabetes mellitus (DM) subjects with and without diabetic retinopathy (DR)., Methods: Ninety-eight DM subjects were recruited. POBF was measured using an Ocular Blood Flow tonometer and retinopathy was assessed using retinal digital photography. The duration of diabetes, blood pressure, glycosylated haemoglobin and plasma glucose level were also recorded., Results: Seventy-two subjects had no DR and 26 subjects exhibited mild to moderate non-proliferative DR. POBF was higher in those subjects with non-proliferative DR but did not reach significance. Those subjects receiving insulin treatment had a significantly longer duration of DM, higher HbA1c and plasma glucose levels and greater incidence of non-proliferative DR compared to subjects receiving oral hypoglycaemic agents, who in turn demonstrated higher levels of these parameters than those who were controlled by diet alone (ANOVA p < 0.05 in all cases). POBF was found to increase with level of management but not significantly so., Conclusions: A single measurement of POBF does not distinguish between subjects with and without mild/moderate non-proliferative DR.

In this paper we present mechanisms for imaging and spectral data discovery, as applied to the early detection of pathologic mechanisms underlying diabetic retinopathy in research and clinical trial scenarios. We discuss the Alchemist framework, built using a generic peer-to-peer architecture, supporting distributed database queries and complex search algorithms based on workflow. The Alchemist is a domain-independent search mechanism that can be applied to search and data discovery scenarios in many areas. We illustrate Alchemist's ability to perform complex searches composed as a collection of peer-to-peer overlays, Grid-based services and workflows, e.g. applied to image and spectral data discovery, as applied to the early detection and prevention of retinal disease and investigational drug discovery. The Alchemist framework is built on top of decentralised technologies and uses industry standards such as Web services and SOAP for messaging.

Purpose: To compare a fundus image-analysis algorithm for automated detection of hemorrhages and microaneurysms with visual detection of retinopathy in patients with diabetes., Methods: Four hundred fundus photographs (35-mm color transparencies) were obtained in 200 eyes of 100 patients with diabetes who were randomly selected from the Welsh Community Diabetic Retinopathy Study. A gold standard reference was defined by classifying each patient as having or not having diabetic retinopathy based on overall visual grading of the digitized transparencies. A single-lesion visual grading was made independently, comprising meticulous outlining of all single lesions in all photographs and used to develop the automated red lesion detection system. A comparison of visual and automated single-lesion detection in replicating the overall visual grading was then performed., Results: Automated red lesion detection demonstrated a specificity of 71.4% and a resulting sensitivity of 96.7% in detecting diabetic retinopathy when applied at a tentative threshold setting for use in diabetic retinopathy screening. The accuracy of 79% could be raised to 85% by adjustment of a single user-supplied parameter determining the balance between the screening priorities, for which a considerable range of options was demonstrated by the receiver-operating characteristic (area under the curve 90.3%). The agreement of automated lesion detection with overall visual grading (0.659) was comparable to the mean agreement of six ophthalmologists (0.648)., Conclusions: Detection of diabetic retinopathy by automated detection of single fundus lesions can be achieved with a performance comparable to that of experienced ophthalmologists. The results warrant further investigation of automated fundus image analysis as a tool for diabetic retinopathy screening.

Background: Stroke is the second leading cause of death worldwide, causing a considerable disease burden. Ischemic stroke is more frequent, but haemorrhagic stroke is responsible for more deaths. The clinical management and treatment are different, and it is advantageous to classify their risk as early as possible for disease prevention. Furthermore, retinal characteristics have been associated with stroke and can be used for stroke risk estimation. This study investigated machine learning approaches to retinal images for risk estimation and classification of ischemic and haemorrhagic stroke. Study design: A case-control study was conducted in the Shenzhen Traditional Chinese Medicine Hospital. According to the computerized tomography scan (CT) or magnetic resonance imaging (MRI) results, stroke patients were classified as either ischemic or hemorrhage stroke. In addition, a control group was formed using non-stroke patients fromthe hospital and healthy individuals from the community. Baseline demographic and medical information was collected from participants' hospital medical records. Retinal images of both eyes of each participant were taken within 2 weeks of admission. Classification models using a machine-learning approach were developed. A 10-fold cross-validation method was used to validate the results. Results: 711 patients were included, with 145 ischemic stroke patients, 86 haemorrhagic stroke patients, and 480 controls. Based on 10-fold cross-validation, the ischemic stroke risk estimation has a sensitivity and a specificity of 91.0% and 94.8%, respectively. The area under the ROC curve for ischemic stroke is 0.929 (95% CI 0.900 to 0.958). The haemorrhagic stroke risk estimation has a sensitivity and a specificity of 93.0% and 97.1%, respectively. The area under the ROC curve is 0.951 (95% CI 0.918 to 0.983). Conclusion: A fast and fully automaticmethod can be used for stroke subtype risk assessment and classification based on fundus photographs alone. [ABSTRACT FROM AUTHOR]

Objectives: To compare retinal thickness before and after treatment with the fluocinolone acetonide (FAc) 190 µg intravitreal implant in people with diabetic macular edema (DME) using data from the Iluvien Clinical Evidence study in the UK (ICE-UK). Methods: For this retrospective cohort study, data on people attending any one of 13 participating ophthalmology departments and treated with FAc intravitreal implant between April 1, 2013 and April 15, 2015 were collected for 12 months prior to and at least 12 months after implantation. Cross-sectional and longitudinal patterns of central foveal thickness (CFT) were compared before and after FAc implant. Results: There were 208 people who contributed data from 233 individual eyes treated with the FAc implant. Mean age was 68.1 years and 62% were male. Median (interquartile range) CFT decreased from 462 µm (354–603 µm) at time of implant to 309 µm (222–433 µm) at 12 months post-implant (p < .001). Over the same period, a reduction of ≥10%, ≥25%, and ≥50% in CFT was observed in 113 (65%), 87 (50%), and 37 (21%) treated eyes, respectively. Eyes with a CFT of ≥400 µm at the time of implant were significantly more likely to achieve a reduction in CFT of ≥10%, ≥25%, and ≥50% at 12 months (all p < .001) compared with eyes with a CFT of <400 µm at implant. Both retinal thickness and changes in retinal thickness were loosely correlated with visual acuity. Conclusion: A marked reduction in retinal thickness was observed in people following FAc intravitreal implant for DME. The response was related to the degree of retinal thickness prior to treatment. [ABSTRACT FROM AUTHOR]

Objectives: To compare visual and anatomical outcomes between eyes treated with fluocinolone acetonide (FAc) 190 µg intravitreal implant for clinically significant chronic diabetic macular edema (DME) and fellow eyes not treated with FAc implant using data from the Iluvien Clinical Evidence study in the UK (ICE-UK) study. Methods: In this retrospective cohort study, data on people attending hospital eye services and treated with the FAc implant between April 1, 2013 and April 15, 2015 were collected. Changes in visual acuity (VA), central foveal thickness (CFT) and intraocular pressure (IOP) were compared between study eyes (intervention) and fellow eyes. Results: A total of 208 people were selected. Mean age was 68.1 years and 62% were male. Mean change in VA was −0.09 LogMAR units for study eyes and 0.04 LogMAR units for fellow eyes at 12 months post-implant (p < .001). Over the same period, ≥5 letter, ≥10 letter and ≥15 letter improvements in Early Treatment Diabetic Retinopathy Study (ETDRS) score were achieved by more FAc treated eyes than by fellow eyes (41% versus 23%, p < .001; 28% versus 11%, p < .001; and 18% versus 4%, p < .001 at 12 months, respectively). Differences in the mean change in CFT (−113 µm versus −13 µm, p < .001) and IOP (3.2 mmHg versus −0.2 mmHg, p < .001) were also observed between study and fellow eyes at 12 months. Conclusion: Visual acuity improved in study eyes over the 12 months following FAc implant and worsened in fellow eyes. Over the same period, study eyes showed a larger improvement in central foveal thickness. Intraocular pressure worsened in study eyes only. Change in visual acuity, central foveal thickness and intraocular pressure between FAc implant and the end of the 12-month follow-up period differed significantly between study and fellow eyes. [ABSTRACT FROM AUTHOR]

The article discusses right screening time for diabetic retinopathy (DR) begin for children with type 1 diabetes. Topics discussed include visual impairment and blindness as a complication associated with diabetes, the American Academy of ophthalmology recommending for annual screening for all people with diabetes for more than five years and International Society for Pediatric and Adolescent Diabetes recommending screening for DR with two years of diabetes and from the age of 11 onwards.

In this paper we present mechanisms for imaging and spectral data discovery, as applied to the early detection of pathologic mechanisms underlying diabetic retinopathy in research and clinical trial scenarios. We discuss the Alchemist framework, built using a generic peer-to-peer architecture, supporting distributed database queries and complex search algorithms based on workflow. The Alchemist is a domain-independent search mechanism that can be applied to search and data discovery scenarios in many areas. We illustrate Alchemist's ability to perform complex searches composed as a collection of peer-to-peer overlays, Grid-based services and workflows, e.g. applied to image and spectral data discovery, as applied to the early detection and prevention of retinal disease and investigational drug discovery. The Alchemist framework is built on top of decentralised technologies and uses industry standards such as Web services and SOAP for messaging. [ABSTRACT FROM AUTHOR]

A defect in the blue sensitive mechanism has been reported in certain ocular and systemic diseases. For example, tritanopic colour vision defects and changes to the S-cone electroretinogram (ERG) have been demonstrated in glaucoma and diabetes mellitus. Electrophysiological methods of eliciting the S-cone ERG, however, often result in considerable L- and M-cone intrusion. We report the findings of a study employing the silent substitution S-cone ERG technique, which is thought to represent an almost pure S-cone signal, and the L'Anthony desaturated D15 colour vision test in subjects with Type 1 or 2 diabetes mellitus with no or minimal background retinopathy. The results of this study show a significantly increased S-cone ERG b-wave implicit time and significantly worse colour vision in those with background retinopathy compared with those with no diabetic retinopathy. This suggests that S-cone pathway dysfunction may be responsible for the deterioration in colour vision found in diabetes mellitus. [ABSTRACT FROM AUTHOR]

Reports developments on public health in Great Britain. Accuracy of non-mydriatic photography in detecting preproliferative and proliferative diabetic retinopathy; Inadequacy of government allocation for the training of future social workers; Significance of the biopsy cut procedure for ultrasound guided biopsy.