Biennial eye screening in patients with diabetes without retinopathy: 10-year experience

Predicting vision-threatening diabetic retinopathy in patients with type 2 diabetes mellitus: Systematic review, meta-analysis, and prospective validation study

Background

Delayed diagnosis and treatment of vision-threatening diabetic retinopathy (VTDR) is a common cause of visual impairment in individuals with type 2 diabetes mellitus (T2DM). Identification of VTDR predictors is the key to early prevention and intervention, but the predictors from previous studies are inconsistent. This study aims to conduct a systematic review and meta-analysis of the existing evidence for VTDR predictors, then to develop a risk prediction model after quantitatively summarising the predictors across studies, and finally to validate the model with two Chinese cohorts.

Methods

We systematically retrieved cohort studies that reported predictors of VTDR in T2DM patients from PubMed, Ovid, Embase, Scopus, Cochrane Library, Web of Science, and ProQuest from their inception to December 2023. We extracted predictors reported in two or more studies and combined their corresponding relative risk (RRs) using meta-analysis to obtain pooled RRs. We only selected predictors with statistically significant pooled RRs to develop the prediction model. We also prospectively collected two Chinese cohorts of T2DM patients as the validation set and assessed the discrimination and calibration performance of the prediction model by the time-dependent ROC curve and calibration curve.

Results

Twenty-one cohort studies involving 622 490 patients with T2DM and 57 107 patients with VTDR were included in the meta-analysis. Age of diabetes onset, duration of diabetes, glycosylated haemoglobin (HbA1c), estimated glomerular filtration rate (eGFR), hypertension, high albuminuria and diabetic treatment were used to construct the prediction model. We validated the model externally in a prospective multicentre cohort of 555 patients with a median follow-up of 52 months (interquartile range = 39-77). The area under the curve (AUC) of the prediction model was all above 0.8 for 3- to 10-year follow-up periods and different cut-off value of each year provided the optimal balance between sensitivity and specificity. The data points of the calibration curves for each year closely surround the corresponding dashed line.

Conclusions

The risk prediction model of VTDR has high discrimination and calibration performance based on validation cohorts. Given its demonstrated effectiveness, there is significant potential to expand the utilisation of this model within clinical settings to enhance the detection and management of individuals at high risk of VTDR.

Prediction of retinopathy progression using deep learning on retinal images within the Scottish screening programme

BACKGROUND/AIMS

National guidelines of many countries set screening intervals for diabetic retinopathy (DR) based on grading of the last screening retinal images. We explore the potential of deep learning (DL) on images to predict progression to referable DR beyond DR grading, and the potential impact on assigned screening intervals, within the Scottish screening programme.

METHODS

We consider 21 346 and 247 233 people with type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM), respectively, each contributing on average 4.8 and 4.4 screening intervals of which 1339 and 4675 intervals concluded with a referable screening episode. Information extracted from fundus images using DL was used to predict referable status at the end of interval and its predictive value in comparison to screening-assigned DR grade was assessed.

RESULTS

The DL predictor increased the area under the receiver operating characteristic curve in comparison to a predictor using current DR grades from 0.809 to 0.87 for T1DM and from 0.825 to 0.87 for T2DM. Expected sojourn time-the time from becoming referable to being rescreened-was found to be 3.4 (T1DM) and 2.7 (T2DM) weeks less for a DL-derived policy compared with the current recall policy.

CONCLUSIONS

We showed that, compared with using the current retinopathy grade, DL of fundus images significantly improves the prediction of incident referable retinopathy before the next screening episode. This can impact screening recall interval policy positively, for example, by reducing the expected time with referable disease for a fixed workload-which we show as an exemplar. Additionally, it could be used to optimise workload for a fixed sojourn time.

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.

Is diabetic retinopathy screening worthwhile among people first diagnosed with diabetes at older ages? A cohort study of Norfolk diabetic retinopathy screening programme

AIMS

England's Diabetic Eye Disease Screening Programme offers screening to every resident over age 12 with diabetes, starting as soon as possible after diagnosis and repeated annually. People first diagnosed with diabetes at older ages have shorter life expectancy and therefore may be less likely to benefit from screening and treatment. To inform decisions about whether diabetic eye screening policy should be stratified by age, we investigated the probability of receiving treatment according to age at first screening episode.

METHODS

This was a cohort study of participants in the Norfolk Diabetic Retinopathy Screening Programme from 2006 to 2017, with individuals' programme data linked to hospital treatment and death data recorded up to 2021. We estimated and compared the probability, annual incidence and screening costs of receiving retinal laser photocoagulation or intravitreal injection and of death, in age groups defined by age at first screening episode.

RESULTS

The probability of death increased with increasing age at diagnosis, while the probability of receiving either treatment decreased with increasing age. The estimated cost of screening per person who received either or both treatments was £18,608 among all participants, increasing with age up to £21,721 in those aged 70-79 and £26,214 in those aged 80-89.

CONCLUSIONS

Diabetic retinopathy screening is less effective and less cost-effective with increasing age at diagnosis of diabetes, because of the increasing probability of death before participants develop sight-threatening diabetic retinopathy and can benefit from treatment. Upper age limits on entry into screening programmes or risk stratification in older age groups may, therefore, be justifiable.

A systematic review of diabetic retinopathy screening intervals

The current evidence on whether annual diabetic retinopathy (DR) screening intervals can be extended was reviewed. A systematic review protocol was followed (PROSPERO ID: CRD42022359590). Original longitudinal articles that specifically assessed DR screening intervals were in English and collected data after 2000 were included. Two reviewers independently conducted the search and reviewed the articles for quality and relevant information. The heterogeneity of the data meant that a meta-analysis was not appropriate. Twelve publications were included. Studies were of good quality and many used data from DR screening programs. Studies fit into three categories; those that assessed specific DR screening intervals, those that determined optimal DR screening intervals and those that developed/assessed DR screening risk equations. For those with type 2 diabetes, extending screening intervals to 3- to 4-yearly in those with no baseline DR appeared safe. DR risk equations considered clinical factors and allocated those at lower risk of DR progression screening intervals of up to five years. Those with baseline DR or type 1 diabetes appeared to have a higher risk of progression to STDR and needed more frequent screening. DR screening intervals can be extended to 3-5 yearly in certain circumstances. These include patients with type 2 diabetes and no current DR, and those who have optimal management of other risk factors such as glucose and blood pressure.

Diabetic retinopathy in China: Epidemiology, screening and treatment trends-A review

Diabetic retinopathy (DR) is the leading cause of vision impairment in the global working-age population. In China, with one-third of the world's diabetes population estimated at 141 million, the blindness prevalence due to DR has increased significantly. The country's geographic variations in socioeconomic status have led to prominent disparities in DR prevalence, screening and management. Reported risk factors for DR in China include the classic ones, such as long diabetes duration, hyperglycaemia, hypertension and rural habitats. There is no national-level DR screening programme in China, but significant pilot efforts are underway for screening innovations. Novel agents with longer durations, noninvasive delivery or multi-target are undergoing clinical trials in China. Although optimised medical insurance policies have enhanced accessibility for expensive therapies like anti-VEGF drugs, further efforts in DR prevention and management in China are required to establish nationwide cost-effective screening programmes, including telemedicine and AI-based solutions, and to improve insurance coverage for related out-of-pocket expenses.

Diabetic retinopathy and visual impairment in a Norwegian diabetic coast population with a high dietary intake of fish oils. An observational study

PURPOSE

To present retinal and visual findings in a Norwegian west coast diabetic population and to elucidate the effect of dietary intake of marine polyunsaturated fatty acids (PUFAs) on the development of diabetic retinopathy (DR).

METHODS

In an eye practice in an archipelago of 314 km², serving a population of about 40 000, we recorded the prevalence of visual impairment and DR in a referred diabetic population. 510 consecutive patients were included, 238 females and 272 males. 50 patients had type I and 460 had type II diabetes mellitus (DM). Self-reported medication, diet supplements, HbA1c and fish consumption were registered.

RESULTS

In the type I group, the median age was 44.5 and median DM duration 11.5 years [1-44]. 48% had photographic evidence of DR, 8 patients (16%) had proliferative retinopathy (PDR), and 6 patients (12%) had diabetic macular oedema (DME). All had best-corrected visual acuity (BCVA) of 0.5 (log MAR 0.3) or better in the best eye. In the type II group, the median DM duration was 8 years [1-53], and median age was 66. 98% had best eye BCVA at or better than 0.5 (log MAR 0.3) in the best eye.

CONCLUSION

None of the 510 patients had BCVA worse than 0.3 (log MAR 0.48) due to diabetic retinopathy. Compared to similar studies, we found a very low visual impairment rate. A possible protective effect of PUFA on the prevalence and progression of diabetic microangiopathy including retinopathy is discussed.

Two-field non-mydriatic fundus photography for diabetic retinopathy screening: a protocol for a systematic review and meta-analysis

INTRODUCTION

Diabetic retinopathy (DR) is one of the most prevalent microvascular complications of diabetes mellitus. Guidelines for DR screening in different countries vary greatly, including fundus photography, slit-lamp biomicroscopy, indirect ophthalmoscopy, Optical Coherence Tomography (OCT), OCT-A and Fundus Fluorescein Angiography (FFA). Two-field non-mydriatic fundus photography (NMFP) is an effective screening method due to its low cost and less time-consuming process. However, it is controversial due to the sensitivity and specificity of two-field NMFP. This review intends to evaluate the performance of the two-field NMFP in diagnosing DR and helps clinicians determine the most optimal screening method.

METHODS AND ANALYSIS

Two reviewers will independently search on the Medline, Embase, Cochrane databases, ProQuest, Opengrey, Chinese National Knowledge Infrastructure, Wanfang Data, VIP China Science and Technology Journal Database, Chinese BioMedical Literature Database, ISRCTN, ClinicalTrials.gov and the WHO ICTRP to identify relevant studies. There is no restriction posed on the language of the study. Included studies focus on the performance of two-field NMFP in detecting DR in diabetes patients. Analysis and evaluation of the studies will be examined by two reviewers independently using the Quality Assessment for Diagnostic Accuracy Studies-2 tool and later evaluated using the Population, Intervention, Comparison, Outcome, Study design criteria. A random-effect model will calculate the diagnostic indicators, including the sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic OR, area under the curve and 95% CIs. We will also develop a summary receiver operating characteristic curve. We anticipate analysing subgroups according to the factors, which may lead to heterogeneity, including DR levels of patients, the reference standards, camera models, the interpretation criteria. The data will be analysed by STATA software. This study was registered with PROSPERO.

ETHICS AND DISSEMINATION

This review will analyse the published data. Patients/the public were not involved in this research. The results of this study will be published in peer-reviewed journals.

PROSPERO REGISTRATION NUMBER

CRD42020203608.

Validation of Automated Screening for Referable Diabetic Retinopathy With an Autonomous Diagnostic Artificial Intelligence System in a Spanish Population

PURPOSE

The purpose of this study is to compare the diagnostic performance of an autonomous artificial intelligence (AI) system for the diagnosis of referable diabetic retinopathy (RDR) to manual grading by Spanish ophthalmologists.

METHODS

Subjects with type 1 and 2 diabetes participated in a diabetic retinopathy (DR) screening program in 2011 to 2012 in Valencia (Spain), and two images per eye were collected according to their standard protocol. Mydriatic drops were used in all patients. Retinal images-one disc and one fovea centered-were obtained under the Medical Research Ethics Committee approval and de-identified. Exams were graded by the autonomous AI system (IDx-DR, Coralville, Iowa, United States), and manually by masked ophthalmologists using adjudication. The outputs of the AI system and manual adjudicated grading were compared using sensitivity and specificity for diagnosis of both RDR and vision-threatening diabetic retinopathy (VTDR).

RESULTS

A total of 2680 subjects were included in the study. According to manual grading, prevalence of RDR was 111/2680 (4.14%) and of VTDR was 69/2680 (2.57%). Against manual grading, the AI system had a 100% (95% confidence interval [CI]: 97%-100%) sensitivity and 81.82% (95% CI: 80%-83%) specificity for RDR, and a 100% (95% CI: 95%-100%) sensitivity and 94.64% (95% CI: 94%-95%) specificity for VTDR.

CONCLUSION

Compared to manual grading by ophthalmologists, the autonomous diagnostic AI system had high sensitivity (100%) and specificity (82%) for diagnosing RDR and macular edema in people with diabetes in a screening program. Because of its immediate, point of care diagnosis, autonomous diagnostic AI has the potential to increase the accessibility of RDR screening in primary care settings.

Testing the performance of risk prediction models to determine progression to referable diabetic retinopathy in an Irish type 2 diabetes cohort

Background /Aims

To evaluate the performance of existing prediction models to determine risk of progression to referable diabetic retinopathy (RDR) using data from a prospective Irish cohort of people with type 2 diabetes (T2D).

Methods

A cohort of 939 people with T2D followed prospectively was used to test the performance of risk prediction models developed in Gloucester, UK, and Iceland. Observed risk of progression to RDR in the Irish cohort was compared with that derived from each of the prediction models evaluated. Receiver operating characteristic curves assessed models’ performance.

Results

The cohort was followed for a total of 2929 person years during which 2906 screening episodes occurred. Among 939 individuals followed, there were 40 referrals (4%) for diabetic maculopathy, pre-proliferative DR and proliferative DR. The original Gloucester model, which includes results of two consecutive retinal screenings; a model incorporating, in addition, systemic biomarkers (HbA1c and serum cholesterol); and a model including results of one retinopathy screening, HbA1c, total cholesterol and duration of diabetes, had acceptable discriminatory power (area under the curve (AUC) of 0.69, 0.76 and 0.77, respectively). The Icelandic model, which combined retinopathy grading, duration and type of diabetes, HbA1c and systolic blood pressure, performed very similarly (AUC of 0.74).

Conclusion

In an Irish cohort of people with T2D, the prediction models tested had an acceptable performance identifying those at risk of progression to RDR. These risk models would be useful in establishing more personalised screening intervals for people with T2D.

Risk of Blindness Among Patients With Diabetes and Newly Diagnosed Diabetic Retinopathy

OBJECTIVE

To evaluate the association between initial diabetic retinopathy (DR) severity/risk of blindness in patients with newly diagnosed DR/good vision in the U.S.

RESEARCH DESIGN AND METHODS

This retrospective cohort study evaluated adult patients with good vision (20/40 or better) and newly diagnosed DR between 1 January 2013 and 31 December 2017 (index date) in the American Academy of Ophthalmology's Intelligent Research in Sight (IRIS) Registry. The primary exposure of interest was DR severity at index: mild nonproliferative DR (NPDR), moderate NPDR, severe NPDR, and proliferative DR (PDR). The main outcome measure was development of sustained blindness (SB), defined as study eyes with Snellen visual acuity readings of 20/200 or worse at two separate visits ≥3 months apart that did not improve beyond 20/100.

RESULTS

Among 53,535 eligible eyes (mean follow-up 662.5 days), 678 (1.3%) eyes developed SB. Eyes with PDR at index represented 10.5% (5,629 of 53,535) of the analysis population but made up 26.5% (180 of 678) of eyes that developed SB. Kaplan-Meier analysis revealed that eyes with moderate NPDR, severe NPDR, and PDR at index were 2.6, 3.6, and 4.0 times more likely, respectively, to develop SB after 2 years of DR diagnosis versus eyes with mild DR at index. In a Cox proportional hazards model adjusted for index characteristics/development of ocular conditions during follow-up, eyes with PDR had an increased risk of developing SB versus eyes with mild NPDR at index (hazard ratio 2.26 [95% CI 2.09-2.45]).

CONCLUSIONS

In this longitudinal ophthalmologic registry population involving eyes with good vision, more advanced DR at first diagnosis was a significant risk factor for developing SB.

Evaluation of a novel artificial intelligence-based screening system for diabetic retinopathy in community of China: a real-world study

PURPOSE

To evaluate the performance of an AI-based diabetic retinopathy (DR) grading model in real-world community clinical setting.

METHODS

Participants with diabetes on record in the chosen community were recruited by health care staffs in a primary clinic of Zhengzhou city, China. Retinal images were prospectively collected during December 2018 and April 2019 based on intent-to-screen principle. A pre-validated AI system based on deep learning algorithm was deployed to screen DR graded according to the International Clinical Diabetic Retinopathy scale. Kappa value of DR severity, the sensitivity, specificity of detecting referable DR (RDR) and any DR were generated based on the standard of the majority manual grading decision of a retina specialist panel.

RESULTS

Of the 193 eligible participants, 173 (89.6%) were readable with at least one eye image. Mean [SD] age was 69.3 (9.0) years old. Total of 321 eyes (83.2%) were graded both by AI and the specialist panel. The κ value in eye image grading was 0.715. The sensitivity, specificity and area under curve for detection of RDR were 84.6% (95% CI: 54.6- 98.1%), 98.0% (95% CI: 94.3-99.6%) and 0.913 (95% CI: 0.797-1.000), respectively. For detection of any DR, the upper indicators were 90.0% (95% CI: 68.3-98.8), 96.6% (95% CI: 92.1-98.9) and 0.933 (95% CI: 0.933-1.000), respectively.

CONCLUSION

The AI system showed relatively good consistency with ophthalmologist diagnosis in DR grading, high specificity and acceptable sensitivity for identifying RDR and any DR.

TRANSLATIONAL RELEVANCE

It is feasible to apply AI-based DR screening in community.

PRECIS

Deployed in community real-world clinic setting, AI-based DR screening system showed high specificity and acceptable sensitivity in identifying RDR and any DR. Good DR diagnostic consistency was found between AI and manual grading. These prospective evidences were essential for regulatory approval.

Safety and cost-effectiveness of individualised screening for diabetic retinopathy: the ISDR open-label, equivalence RCT

AIMS/HYPOTHESIS

Using variable diabetic retinopathy screening intervals, informed by personal risk levels, offers improved engagement of people with diabetes and reallocation of resources to high-risk groups, while addressing the increasing prevalence of diabetes. However, safety data on extending screening intervals are minimal. The aim of this study was to evaluate the safety and cost-effectiveness of individualised, variable-interval, risk-based population screening compared with usual care, with wide-ranging input from individuals with diabetes.

METHODS

This was a two-arm, parallel-assignment, equivalence RCT (minimum 2 year follow-up) in individuals with diabetes aged 12 years or older registered with a single English screening programme. Participants were randomly allocated 1:1 at baseline to individualised screening at 6, 12 or 24 months for those at high, medium and low risk, respectively, as determined at each screening episode by a risk-calculation engine using local demographic, screening and clinical data, or to annual screening (control group). Screening staff and investigators were observer-masked to allocation and interval. Data were collected within the screening programme. The primary outcome was attendance (safety). A secondary safety outcome was the development of sight-threatening diabetic retinopathy. Cost-effectiveness was evaluated within a 2 year time horizon from National Health Service and societal perspectives.

RESULTS

A total of 4534 participants were randomised. After withdrawals, there were 2097 participants in the individualised screening arm and 2224 in the control arm. Attendance rates at first follow-up were equivalent between the two arms (individualised screening 83.6%; control arm 84.7%; difference -1.0 [95% CI -3.2, 1.2]), while sight-threatening diabetic retinopathy detection rates were non-inferior in the individualised screening arm (individualised screening 1.4%, control arm 1.7%; difference -0.3 [95% CI -1.1, 0.5]). Sensitivity analyses confirmed these findings. No important adverse events were observed. Mean differences in complete case quality-adjusted life-years (EuroQol Five-Dimension Questionnaire, Health Utilities Index Mark 3) did not significantly differ from zero; multiple imputation supported the dominance of individualised screening. Incremental cost savings per person with individualised screening were £17.34 (95% CI 17.02, 17.67) from the National Health Service perspective and £23.11 (95% CI 22.73, 23.53) from the societal perspective, representing a 21% reduction in overall programme costs. Overall, 43.2% fewer screening appointments were required in the individualised arm.

CONCLUSIONS/INTERPRETATION

Stakeholders involved in diabetes care can be reassured by this study, which is the largest ophthalmic RCT in diabetic retinopathy screening to date, that extended and individualised, variable-interval, risk-based screening is feasible and can be safely and cost-effectively introduced in established systematic programmes. Because of the 2 year time horizon of the trial and the long time frame of the disease, robust monitoring of attendance and retinopathy rates should be included in any future implementation.

TRIAL REGISTRATION

ISRCTN 87561257 FUNDING: The study was funded by the UK National Institute for Health Research. Graphical abstract.

Digital Ophthalmology in the UK - Diabetic Retinopathy Screening and Virtual Glaucoma Clinics in the National Health Service

The customary doctor and patient interactions are currently undergoing significant changes through technological advances in imaging and data processing and the need for reducing person-to person contacts during the COVID-19 crisis. There is a trend away from face-to-face examinations to virtual assessments and decision making. Ophthalmology is particularly amenable to such changes, as a high proportion of clinical decisions are based on routine tests and imaging results, which can be assessed remotely. The uptake of digital ophthalmology varies significantly between countries. Due to financial constraints within the National Health Service, specialized ophthalmology units in the UK have been early adopters of digital technology. For more than a decade, patients have been managed remotely in the diabetic retinopathy screening service and virtual glaucoma clinics. We describe the day-to-day running of such services and the doctor and patient experiences with digital ophthalmology in daily practice.

Use in clinical practice of an automated screening method of diabetic retinopathy that can be derived using a diagnostic artificial intelligence system

BACKGROUND AND OBJECTIVE

To compare the diagnostic performance of an autonomous diagnostic artificial intelligence (AI) system for the diagnosis of derivable diabetic retinopathy (RDR) with manual classification.

MATERIALS AND METHODS

Patients with type 1 and type 2 diabetes participated in a diabetic retinopathy (DR) screening program between 2011-2012. 2 images of each eye were collected. Unidentifiable retinal images were obtained, one centered on the disc and one on the fovea. The exams were classified with the autonomous AI system and manually by anonymous ophthalmologists. The results of the AI system and manual classification were compared in terms of sensitivity and specificity for the diagnosis of both (RDR) and diabetic retinopathy with decreased vision (VTDR).

RESULTS

10,257 retinal inages of 5,630 eyes of 2,680 subjects were included. According to the manual classification, the prevalence of RDR was 4.14% and that of VTDR 2.57%. The AI system recorded 100% (95% CI: 97-100%) sensitivity and 81.82% (95% CI: 80 -83%) specificity for RDR, and 100% (95% CI: 95-100%) of sensitivity and 94.64% (95% CI: 94-95%) of specificity for VTDR.

CONCLUSIONS

Compared to the manual classification, the autonomous diagnostic AI system registered a high sensitivity (100%) and specificity (82%) in the diagnosis of RDR and macular edema in people with diabetes. Due to its immediate diagnosis, the autonomous diagnostic AI system can increase the accessibility of RDR screening in primary care settings.

Visual contrast sensitivity could be an early marker of diabetic retinopathy

The present study aimed to explore the early predictive marker of diabetic retinopathy (DR) and to elucidate the associated demographic, metabolic, and ocular factors. We enrolled 43 type 2 diabetic subjects with mild non-proliferative retinopathy (MNPDR), 30 diabetic subjects with no retinopathy (DNR), and 35 healthy controls (HC). The study groups showed no significant alteration in central macular thickness (CMT) and visual acuity (VA). The contrast sensitivity (CS) score was found to be significantly lower among DNR and MNPDR subjects compared to HCs (p < 0.0001). Between MNPDR and DNR subjects, the CS score was significantly lower in the former (p = 0.0036). CS score discriminated DNR subjects from HC, with 74% accuracy for the optimal threshold 0.71. The associated area under the ROC curve (AUC) is 0.82 (p < 0.0001) while the discrimination rule has 66% sensitivity and 80% specificity. The CS score also discriminated MNPDR subjects from DNR with 64% accuracy for the optimal threshold 0.53. The associated AUC is 0.65 (p < 0.023) and the rule has 86% sensitivity and 33% specificity. According to best subset regression analysis, not only glycaemic parameters but also lipid parameters [low-density lipoprotein cholesterol (LDL-C) (p = 0.045) and triglycerides (TG) (p = 0.0005)] were found to be significant predictors of CS. CMT (p = 0.058) was another marginally significant predictor of CS. CS may be used as an early predictive marker for DR. So, not only hyperglycemia, but also hyperlipidemia seems to significantly affect retinal CS function in diabetes.

Andalusian program for early detection of diabetic retinopathy: implementation and 15-year follow-up of a population-based screening program in Andalusia, Southern Spain

INTRODUCTION

Diabetic retinopathy (DR) is a preventable cause of vision loss and blindness worldwide. We aim at analyzing the impact of a population-based screening program of DR using retinal photography with remote reading in terms of population coverage, diagnosis of asymptomatic DR and impact on visual disability, in the region of Andalusia, Spain, in the period 2005-2019.

RESEARCH DESIGN AND METHODS

Descriptive study. Sociodemographic and clinical features included in the Andalusian program for early detection of diabetic retinopathy (APDR) were analyzed. Population coverage, annual incidence of DR, and DR severity gradation were analyzed. Estimated data on prevalence and incidence of legal blindness due to DR were included.

RESULTS

407 762 patients with at least one successful DR examination during the study period were included. Most of the performed retinographies (784 584, 84.3%) were 'non-pathological.' Asymptomatic DR was detected in 52 748 (5.9%) retinographies, most of them (94.2%) being classified as 'mild to moderate non-proliferative DR.' DR was detected in 44 815 patients, while sight-threatening DR (STDR) in 6256 patients; cumulative incidence of DR was 11.0% and STDR was 1.5%, as DR and STDR was detected in 44 815 and 6256 patients, respectively. Annual incidence risk per patient recruitment year progressively decreased from 22.0% by January 2005 to 3.2% by June 2019.

CONCLUSIONS

Implementation of a long-term population-based screening program for early detection of DR is technically feasible and clinically viable. Thus, after 15 years of existence, the program has enabled the screening of the vast majority of the target population allowing the optimization of healthcare resources and the identification of asymptomatic DR.

Cost-effectiveness of biennial screening for diabetes related retinopathy in people with type 1 and type 2 diabetes compared to annual screening

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.

Personalising screening of sight-threatening diabetic retinopathy - qualitative evidence to inform effective implementation

BACKGROUND

Internationally, systematic screening for sight-threatening diabetic retinopathy (STDR) usually includes annual recall. Researchers and policy-makers support extending screening intervals, citing evidence from observational studies with low incidence rates. However, there is little research around the acceptability to people with diabetes (PWD) and health care professionals (HCP) about changing eye screening intervals.

METHODS

We conducted a qualitative study to explore issues surrounding acceptability and the barriers and enablers for changing from annual screening, using in-depth, semistructured interviews analysed using the constant comparative method. PWD were recruited from general practices and HCP from eye screening networks and related specialties in North West England using purposive sampling. Interviews were conducted prior to the commencement of and during a randomised controlled trial (RCT) comparing fixed annual with variable (6, 12 or 24 month) interval risk-based screening.

RESULTS

Thirty PWD and 21 HCP participants were interviewed prior to and 30 PWD during the parallel RCT. The data suggests that a move to variable screening intervals was generally acceptable in principle, though highlighted significant concerns and challenges to successful implementation. The current annual interval was recognised as unsustainable against a backdrop of increasing diabetes prevalence. There were important caveats attached to acceptability and a need for clear safeguards around: the safety and reliability of calculating screening intervals, capturing all PWD, referral into screening of PWD with diabetic changes regardless of planned interval. For PWD the 6-month interval was perceived positively as medical reassurance, and the 12-month seen as usual treatment. Concerns were expressed by many HCP and PWD that a 2-year interval was too lengthy and was risky for detecting STDR. There were also concerns about a negative effect upon PWD care and increasing non-attendance rates. Amongst PWD, there was considerable conflation and misunderstanding about different eye-related appointments within the health care system.

CONCLUSIONS

Implementing variable-interval screening into clinical practice is generally acceptable to PWD and HCP with important caveats, and misconceptions must be addressed. Clear safeguards against increasing non-attendance, loss of diabetes control and alternative referral pathways are required. For risk calculation systems to be safe, reliable monitoring and clear communication is required.

IDF Diabetes Atlas: A review of studies utilising retinal photography on the global prevalence of diabetes related retinopathy between 2015 and 2018

AIMS

The purpose of this study is to assess the prevalence of diabetic retinopathy (DR) world-wide from articles published since 2015 where the assessment of the presence and severity of DR was based on retinal images.

METHODS

A total of 4 databases were searched for the MESH terms diabetic retinopathy and prevalence. Of 112 publications 32 studies were included and individual data pooled for analysis. The presence of any DR or diabetic macular edema (DME) was recorded and severity as mild, moderate or severe non-proliferative DR (NPDR), proliferative DR (PDR) and DME and/or clinically significant macular edema (CSME). The level of severity of DR reported refer to persons with diabetes and not individual eyes.

RESULTS

The global prevalence of DR and DME, for the period 2015 to 2019 were 27.0% for any DR comprising of 25.2%, NPDR, 1.4% PDR and 4.6% DME. The lowest prevalence was in Europe at 20.6% and South East Asia at 12.5% and highest in Africa at 33.8%, Middle East and North Africa 33.8%, and the Western Pacific region at 36.2%.

CONCLUSIONS

This study illustrated difficulties in deriving a meaningful global prevalence rate for DR and DME due to the lack of uniformity in defining the study populations, methodological differences, retinal image capture and grading criteria. Therefore, international consensus is required using a minimal data set for future studies.

Incidence of sight-threatening diabetic retinopathy in people with Type 2 diabetes mellitus and numbers needed to screen: a systematic review

AIM

To investigate the incidence of sight-threatening diabetic retinopathy in Type 2 diabetes mellitus.

BACKGROUND

In most countries, yearly or biennial screening intervals for diabetic retinopathy in people with Type 2 diabetes are recommended. Fewer screening sessions reduce the effort required of people with Type 2 diabetes and reduce healthcare costs.

METHODS

We conducted a search of PubMed, Embase, Web of Science and the COCHRANE Library for studies published betweeen 1 January 2000 and 1 January 2017. Eligible studies were those that included general populations of >100 people with Type 2 diabetes mellitus. Additional study population criteria were absence of moderate diabetic retinopathy or more severe diabetic retinopathy at last screening session and at least two gradable retinal screening sessions. Outcomes of interest in the included studies were moderate and severe non-proliferative diabetic retinopathy (R2), proliferative diabetic retinopathy (R3) or maculopathy (M1), collectively known as sight-threatening or referable diabetic retinopathy.

RESULTS

A total of 17 studies were included. In people with Type 2 diabetes without or with only mild diabetic retinopathy at baseline, the average incidence rates of sight-threatening diabetic retinopathy were ~1 per 100 person-years and ~8 per 100 person-years, respectively. The average numbers needed to screen to detect one case of sight-threatening diabetic retinopathy were 175 and 19 in people without and with mild retinopathy at last screening, respectively.

CONCLUSION

In people with Type 2 diabetes without retinopathy at last screening, the incidence of severe sight-threatening retinopathy at the subsequent screening session was low. In people with mild retinopathy, progression to sight-threatening diabetic retinopathy was nearly 10-fold higher. This review supports lengthening of the screening interval of patients with Type 2 diabetes without retinopathy at last screening session.

Use of personalised risk-based screening schedules to optimise workload and sojourn time in screening programmes for diabetic retinopathy: A retrospective cohort study

BACKGROUND

National guidelines in most countries set screening intervals for diabetic retinopathy (DR) that are insufficiently informed by contemporary incidence rates. This has unspecified implications for interval disease risks (IDs) of referable DR, disparities in ID between groups or individuals, time spent in referable state before screening (sojourn time), and workload. We explored the effect of various screening schedules on these outcomes and developed an open-access interactive policy tool informed by contemporary DR incidence rates.

METHODS AND FINDINGS

Scottish Diabetic Retinopathy Screening Programme data from 1 January 2007 to 31 December 2016 were linked to diabetes registry data. This yielded 128,606 screening examinations in people with type 1 diabetes (T1D) and 1,384,360 examinations in people with type 2 diabetes (T2D). Among those with T1D, 47% of those without and 44% of those with referable DR were female, mean diabetes duration was 21 and 23 years, respectively, and mean age was 26 and 24 years, respectively. Among those with T2D, 44% of those without and 42% of those with referable DR were female, mean diabetes duration was 9 and 14 years, respectively, and mean age was 58 and 52 years, respectively. Individual probability of developing referable DR was estimated using a generalised linear model and was used to calculate the intervals needed to achieve various IDs across prior grade strata, or at the individual level, and the resultant workload and sojourn time. The current policy in Scotland-screening people with no or mild disease annually and moderate disease every 6 months-yielded large differences in ID by prior grade (13.2%, 3.6%, and 0.6% annually for moderate, mild, and no prior DR strata, respectively, in T1D) and diabetes type (2.4% in T1D and 0.6% in T2D overall). Maintaining these overall risks but equalising risk across prior grade strata would require extremely short intervals in those with moderate DR (1-2 months) and very long intervals in those with no prior DR (35-47 months), with little change in workload or average sojourn time. Changing to intervals of 12, 9, and 3 months in T1D and to 24, 9, and 3 months in T2D for no, mild, and moderate DR strata, respectively, would substantially reduce disparity in ID across strata and between diabetes types whilst reducing workload by 26% and increasing sojourn time by 2.3 months. Including clinical risk factor data gave a small but significant increment in prediction of referable DR beyond grade (increase in C-statistic of 0.013 in T1D and 0.016 in T2D, both p < 0.001). However, using this model to derive personalised intervals did not have substantial workload or sojourn time benefits over stratum-specific intervals. The main limitation is that the results are pertinent only to countries that share broadly similar rates of retinal disease and risk factor distributions to Scotland.

CONCLUSIONS

Changing current policies could reduce disparities in ID and achieve substantial reductions in workload within the range of IDs likely to be deemed acceptable. Our tool should facilitate more rational policy setting for screening.

Validation of a model for the prediction of retinopathy in persons with type 1 diabetes

BACKGROUND/AIM

To validate a previously developed model for prediction of diabetic retinopathy (DR) for personalised retinopathy screening in persons with type 1 diabetes.

METHODS

Retrospective medical data of persons with type 1 diabetes treated in an academic hospital setting were used for analysis. Sight-threatening retinopathy (STR) was defined as the presence of severe non-proliferative DR, proliferative DR or macular oedema. The presence and grade of retinopathy, onset of diabetes, systolic blood pressure, and levels of haemoglobin A_1c were used to calculate an individual risk estimate and personalised screening interval. In persons with STR, the occurrence was compared with the calculated date of screening. The model's predictive performance was measured using calibration and discrimination techniques.

RESULTS

Of the 268 persons included in our study, 24 (9.0%) developed STR during a mean follow-up of 4.6 years. All incidences of STR occurred after the calculated screening date. By applying the model, the mean calculated screening interval was 30.5 months, which is a reduction in screening frequency of 61% compared with annual screening and 21% compared with biennial screening. The discriminatory ability was good (Harrell's C-statistic=0.82, 95% CI 0.74 to 0.90), and calibration showed an overestimation of risk in persons who were assigned to a higher risk for STR.

CONCLUSION

This validation study suggests that a screening programme based on the previously developed prediction model is safe and efficient. The use of a personalised screening frequency could improve cost-effectiveness of diabetic eye care.

Personalized risk-based screening for diabetic retinopathy: A multivariate approach versus the use of stratification rules

AIMS

To evaluate our proposed multivariate approach to identify patients who will develop sight-threatening diabetic retinopathy (STDR) within a 1-year screen interval, and explore the impact of simple stratification rules on prediction.

MATERIALS AND METHODS

A 7-year dataset (2009-2016) from people with diabetes (PWD) was analysed using a novel multivariate longitudinal discriminant approach. Level of diabetic retinopathy, assessed from routine digital screening photographs of both eyes, was jointly modelled using clinical data collected over time. Simple stratification rules based on retinopathy level were also applied and compared with the multivariate discriminant approach.

RESULTS

Data from 13 103 PWD (49 520 screening episodes) were analysed. The multivariate approach accurately predicted whether patients developed STDR or not within 1 year from the time of prediction in 84.0% of patients (95% confidence interval [CI] 80.4-89.7), compared with 56.7% (95% CI 55.5-58.0) and 79.7% (95% CI 78.8-80.6) achieved by the two stratification rules. While the stratification rules detected up to 95.2% (95% CI 92.2-97.6) of the STDR cases (sensitivity) only 55.6% (95% CI 54.5-56.7) of patients who did not develop STDR were correctly identified (specificity), compared with 85.4% (95% CI 80.4-89.7%) and 84.0% (95% CI 80.7-87.6%), respectively, achieved by the multivariate risk model.

CONCLUSIONS

Accurate prediction of progression to STDR in PWD can be achieved using a multivariate risk model whilst also maintaining desirable specificity. While simple stratification rules can achieve good levels of sensitivity, the present study indicates that their lower specificity (high false-positive rate) would therefore necessitate a greater frequency of eye examinations.

An Automated Grading System for Detection of Vision-Threatening Referable Diabetic Retinopathy on the Basis of Color Fundus Photographs

OBJECTIVE

The goal of this study was to describe the development and validation of an artificial intelligence-based, deep learning algorithm (DLA) for the detection of referable diabetic retinopathy (DR).

RESEARCH DESIGN AND METHODS

A DLA using a convolutional neural network was developed for automated detection of vision-threatening referable DR (preproliferative DR or worse, diabetic macular edema, or both). The DLA was tested by using a set of 106,244 nonstereoscopic retinal images. A panel of ophthalmologists graded DR severity in retinal photographs included in the development and internal validation data sets (n = 71,043); a reference standard grading was assigned once three graders achieved consistent grading outcomes. For external validation, we tested our DLA using 35,201 images of 14,520 eyes (904 eyes with any DR; 401 eyes with vision-threatening referable DR) from population-based cohorts of Malays, Caucasian Australians, and Indigenous Australians.

RESULTS

Among the 71,043 retinal images in the training and validation data sets, 12,329 showed vision-threatening referable DR. In the internal validation data set, the area under the curve (AUC), sensitivity, and specificity of the DLA for vision-threatening referable DR were 0.989, 97.0%, and 91.4%, respectively. Testing against the independent, multiethnic data set achieved an AUC, sensitivity, and specificity of 0.955, 92.5%, and 98.5%, respectively. Among false-positive cases, 85.6% were due to a misclassification of mild or moderate DR. Undetected intraretinal microvascular abnormalities accounted for 77.3% of all false-negative cases.

CONCLUSIONS

This artificial intelligence-based DLA can be used with high accuracy in the detection of vision-threatening referable DR in retinal images. This technology offers potential to increase the efficiency and accessibility of DR screening programs.

Evidence-based Danish guidelines for screening of diabetic retinopathy

PURPOSE

Diabetic retinopathy (DR) is among the leading causes of visual loss in the working-age population. It is generally accepted that screening of DR is cost-effective and can detect DR before it becomes sight-threatening to allow timely treatment.

METHODS

A group of retinal specialists was formed by the Danish Ophthalmological Society with the aim to formulate contemporary evidence-based guidelines for screening of DR in order to implement these in the Danish screening system.

RESULTS

We hereby present evidence for DR-screening regarding (1) classification of DR, (2) examination techniques, (3) screening intervals and (4) automated screening. It is our recommendation that the International Clinical Retinopathy Disease Severity Scale should be used to classify DR. As a minimum, mydriatic two-field disc- and macular-centred images are required. In the case of suspected clinically significant diabetic macular oedema, supplementary optical coherence tomography can increase the diagnostic accuracy. There is solid evidence to support a flexible, individualized screening regimen. In particular, it is possible to prolong screening intervals to 24-48 months for patients with no or mild nonproliferative diabetic retinopathy (NPDR), but it is also possible to use extended intervals of 12-24 months for patients with moderate NPDR given that these are well-regulated regarding glycaemic control (HbA1c ≤ 53 mmol/mol) and blood pressure (≤130/80 mmHg). Automated screening of DR is encouraging but is not ready for implementation at present.

CONCLUSION

Danish evidenced-based guidelines for screening of DR support high-quality imaging and allow flexible, individualized screening intervals with a potential for extension to patients with low risk of DR progression.

Validation of automated screening for referable diabetic retinopathy with the IDx-DR device in the Hoorn Diabetes Care System

Purpose

To increase the efficiency of retinal image grading, algorithms for automated grading have been developed, such as the IDx‐DR 2.0 device. We aimed to determine the ability of this device, incorporated in clinical work flow, to detect retinopathy in persons with type 2 diabetes.

Methods

Retinal images of persons treated by the Hoorn Diabetes Care System (DCS) were graded by the IDx‐DR device and independently by three retinal specialists using the International Clinical Diabetic Retinopathy severity scale (ICDR) and EURODIAB criteria. Agreement between specialists was calculated. Results of the IDx‐DR device and experts were compared using sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV), distinguishing between referable diabetic retinopathy (RDR) and vision‐threatening retinopathy (VTDR). Area under the receiver operating characteristic curve (AUC) was calculated.

Results

Of the included 1415 persons, 898 (63.5%) had images of sufficient quality according to the experts and the IDx‐DR device. Referable diabetic retinopathy (RDR) was diagnosed in 22 persons (2.4%) using EURODIAB and 73 persons (8.1%) using ICDR classification. Specific intergrader agreement ranged from 40% to 61%. Sensitivity, specificity, PPV and NPV of IDx‐DR to detect RDR were 91% (95% CI: 0.69–0.98), 84% (95% CI: 0.81–0.86), 12% (95% CI: 0.08–0.18) and 100% (95% CI: 0.99–1.00; EURODIAB) and 68% (95% CI: 0.56–0.79), 86% (95% CI: 0.84–0.88), 30% (95% CI: 0.24–0.38) and 97% (95% CI: 0.95–0.98; ICDR). The AUC was 0.94 (95% CI: 0.88–1.00; EURODIAB) and 0.87 (95% CI: 0.83–0.92; ICDR). For detection of VTDR, sensitivity was lower and specificity was higher compared to RDR. AUC's were comparable.

Conclusion

Automated grading using the IDx‐DR device for RDR detection is a valid method and can be used in primary care, decreasing the demand on ophthalmologists.

Implementation of medical retina virtual clinics in a tertiary eye care referral centre

BACKGROUND

The increasing incidence of medical retinal diseases has created capacity issues across UK. In this study, we describe the implementation and outcomes of virtual medical retina clinics (VMRCs) at Moorfields Eye Hospital, South Division, London. It represents a promising solution to ensure that patients are seen and treated in a timely fashion METHODS: First attendances in the VMRC (September 2016-May 2017) were included. It was open to non-urgent external referrals and to existing patients in a face-to-face clinic (F2FC). All patients received visual acuity testing, dilated fundus photography and optical coherence tomography scans. Grading was performed by consultants, fellows and allied healthcare professionals. Outcomes of these virtual consultations and reasons for F2FC referrals were assessed.

RESULTS

A total number of 1729 patients were included (1543 were internal and 186 external referrals). The majority were diagnosed with diabetic retinopathy (75.1% of internal and 46.8% of external referrals). Of the internal referrals, 14.6% were discharged, 54.5% continued in VMRC and 30.9% were brought to a F2FC. Of the external referrals, 45.5% were discharged, 37.1% continued in VMRC and 17.4% were brought to a F2FC. The main reason for F2FC referrals was image quality (34.7%), followed by detection of potentially treatable disease (20.2%).

CONCLUSION

VMRC can be implemented successfully using existing resources within a hospital eye service. It may also serve as a first-line rapid-access clinic for low-risk referrals. This would enable medical retinal services to cope with increasing demand and efficiently allocate resources to those who require treatment.

Individualised variable-interval risk-based screening for sight-threatening diabetic retinopathy: the Liverpool Risk Calculation Engine

AIMS/HYPOTHESIS

Individualised variable-interval risk-based screening offers better targeting and improved cost-effectiveness in screening for diabetic retinopathy. We developed a generalisable risk calculation engine (RCE) to assign personalised intervals linked to local population characteristics, and explored differences in assignment compared with current practice.

METHODS

Data from 5 years of photographic screening and primary care for people with diabetes, screen negative at the first of > 1 episode, were combined in a purpose-built near-real-time warehouse. Covariates were selected from a dataset created using mixed qualitative/quantitative methods. Markov modelling predicted progression to screen-positive (referable diabetic retinopathy) against the local cohort history. Retinopathy grade informed baseline risk and multiple imputation dealt with missing data. Acceptable intervals (6, 12, 24 months) and risk threshold (2.5%) were established with patients and professional end users.

RESULTS

Data were from 11,806 people with diabetes (46,525 episodes, 388 screen-positive). Covariates with sufficient predictive value were: duration of known disease, HbA1c, age, systolic BP and total cholesterol. Corrected AUC (95% CIs) were: 6 months 0.88 (0.83, 0.93), 12 months 0.90 (0.87, 0.93) and 24 months 0.91 (0.87, 0.94). Sensitivities/specificities for a 2.5% risk were: 6 months 0.61, 0.93, 12 months 0.67, 0.90 and 24 months 0.82, 0.81. Implementing individualised RCE-based intervals would reduce the proportion of people becoming screen-positive before the allocated screening date by > 50% and the number of episodes by 30%.

CONCLUSIONS/INTERPRETATION

The Liverpool RCE shows sufficient performance for a local introduction into practice before wider implementation, subject to external validation. This approach offers potential enhancements of screening in improved local applicability, targeting and cost-effectiveness.

Screening Intervals for Diabetic Retinopathy and Implications for Care

PURPOSE OF REVIEW

The purpose of this study is to review the evidence that lower risk groups who could safely be screened less frequently for sight-threatening diabetic retinopathy (DR) than annually.

RECENT FINDINGS

Data have demonstrated that people with no DR in either eye are at a low risk of progression to sight-threatening DR over a 2-year period (event rate 4.8 per 1000 person years), irrespective of whether the screening method is one-field non-mydriatic or two-field mydriatic digital photography. Low risk has been defined as no retinopathy on two consecutive screening episodes or no retinopathy on one screening episode combined with risk factor data. The risk of an extension to 2 years is less than 5 per 1000 person years in a population with a national screening programme, and the general standard of diabetes care is relatively good, whether low risk is defined as no retinopathy on two consecutive screening episodes or no retinopathy on one screening episode combined with other risk factor data. The definition used in different populations is likely to depend on the availability of data.

A decade-long telemedicine screening program for diabetic retinopathy in the north-east of Italy

AIM

To describe a decade long telemedicine screening for diabetic retinopathy (DR) in the metropolitan area of Padova (North-East Italy) and to report about prevalence/incidence of DR and maculopathy, rate of progression to STDR and optimal screening interval in patients with no DR at first examination.

METHODS

Observational, longitudinal, cohort study; 9347 patients with Type 1 and Type 2 diabetes mellitus (DM) underwent 17,344 fundus exams (three-45° color photos per eye) in two diabetes clinics and were graded in the Reading Centre, by certified personnel. The incidence of STDR, progression of maculopathy and risk factors were evaluated by log Rank test (Kaplan-Meier method). A receiver operating curve was used to determine the optimal screening interval in patients who at the first examination had no DR.

RESULTS

The overall prevalence of DR was 27.6%:12.5% mild non proliferative (NPDR), 11.3% moderate NPDR, 2.9% severe NPDR and 0.9% proliferative (PDR). The overall prevalence of maculopathy was 5.7%: 2.8% mild, 2.2% moderate, and 0.7% severe maculopathy. The 10-year incidence of STDR was: 0.6% in no DR, 5.5% in mild NPDR and 21.1% in moderate NPDR at first examination. The 10-year incidence of maculopathy was: 2.1% mild, 1.7% moderate and 0.2% severe. The incidence of STDR in patients with type 1 and type 2 DM and duration>10years was 8.21% and 8.15%;in type 1 DM with duration <10years was 5.5% and in type 2 DM and duration <10years was 1.91%.In patients with no DR at first screening, the best (sensitivity-specificity) follow-up interval is 2.5years.

CONCLUSIONS

Screening every 2.5-year in patients without DR at the first examination seems to be adequate. Duration of disease is a relevant risk factor for progression to STDR, however patients with type 1 DM and duration <10years have greater incidence of STDR than patients with type 2 DM and similar disease duration. Epidemiologic data from this decade-long screening program in the North East of Italy may serve for implementing a national screening program.

Update on Diagnosis and Treatment of Diabetic Retinopathy: A Consensus Guideline of the Working Group of Ocular Health (Spanish Society of Diabetes and Spanish Vitreous and Retina Society)

A group of members of the Spanish Retina and Vitreous Society (SERV) and of the Working Group of Ocular Health of the Spanish Society of Diabetes (SED) updated knowledge regarding the diagnosis and treatment of diabetic retinopathy (DR) based on recent evidence reported in the literature. A synthesis of this consensus forms the basis of the present review, which is intended to inform clinicians on current advances in the field of DR and their clinical applicability to patients with this disease. Aspects presented in this article include screening procedures of DR, new technologies in the early diagnosis of DR, control of risk factors in the different stages of the disease, indications of panretinal laser photocoagulation, efficacy of intravitreal antiangiogenic agents and steroids, and surgical options for treating DR-related complications. Practical information regarding periodicity of screening procedures in patients with type 1 and type 2 diabetes, ophthalmological controls according to the stage of retinopathy and complications, and criteria and degree of urgency for referral of a DR patient to the ophthalmologist are also presented.

MicroRNA-126: a promising novel biomarker in peripheral blood for diabetic retinopathy

AIM

To investigate the content of serum microRNA-126 (miR-126) and its role in screening retinal endothelial injury and early diagnosis of proliferative diabetic retinopathy.

METHODS

The study included 184 serum samples, 59 samples from healthy individuals, 44 samples from diabetes mellitus (DM) patients without diabetic retinopathy (NDR), 42 from non-proliferative diabetic retinopathy (NPDR) patients and 39 samples from proliferative diabetic retinopathy (PDR) patients. The expression of miR-126 was evaluated using a real-time quantitative polymerase chain reaction.

RESULTS

The serum content of miR-126 declined as the damage degree in the retina. There was significant difference between the two retinopathy groups (P<0.001). No difference was observed in miR-126 content between healthy individuals and NDR patients (P>0.05). Receiver operating characteristic curve (ROC) analyses indicated that serum miR-126 had significant diagnostic value for PDR. It yielded an area under the curve (AUC) of ROC of 0.976 with 81.21% sensitivity and 90.34% specificity in discriminating PDR from healthy controls, and an AUC of ROC of 0.919 with 84.75% sensitivity and 94.41% specificity in discriminating NDR and NPDR from healthy controls. When the diagnostic threshold was greater than or equal to 8.43, there was an increase in the possibility of NPDR. When the content of miR-126 was less than or equal to 5.02, the possibility of the occurrence of PDR increased.

CONCLUSION

Serum miR-126 can serve as a non-invasive biomarker for screening retinal endothelial injury and early diagnosis PDR.

Diabetic Retinopathy in Italy: Epidemiology Data and Telemedicine Screening Programs

In Italy, the number of people living with diabetes is about 3.5 million (5.5% of the population), with an increase by about 60% in the last 20 years and with 1 person out of 3 older than 65 years. The Italian Health Service system estimates that 10 billion euros is spent annually on caring for patients with diabetes, a figure that increases yearly. No national data on prevalence and incidence of legal blindness in patients with diabetes and no national registry of patients with diabetic retinopathy (DR) are currently available. However, the available epidemiological data (in several locations throughout the country) are consistent with those reported in other European countries. The use of telemedicine for the screening of DR in Italy is confined to geographically limited locations. The available data in the literature on implementation and use of telematic screening proved to be successful from patient, caregiver, and authorities point of view. This review addresses the available epidemiological data on DR and telematic screening realities in Italy and thus may help in establishing a national screening program.

Determining diabetic retinopathy screening interval based on time from no retinopathy to laser therapy

Objectives To determine the necessary screening interval for retinopathy in diabetic patients with no retinopathy based on time to laser therapy and to assess long-term visual outcome following screening. Methods In a population-based community screening programme in North Wales, 2917 patients were followed until death or for approximately 12 years. At screening, 2493 had no retinopathy; 424 had mostly minor degrees of non-proliferative retinopathy. Data on timing of first laser therapy and visual outcome following screening were obtained from local hospitals and ophthalmology units. Results Survival analysis showed that very few of the no retinopathy at screening group required laser therapy in the early years compared with the non-proliferative retinopathy group ( p < 0.001). After two years, <0.1% of the no retinopathy at screening group required laser therapy, and at three years 0.2% (cumulative), lower rates of treatment than have been suggested by analyses of sight-threatening retinopathy determined photographically. At follow-up (mean 7.8 ± 4.6 years), mild to moderate visual impairment in one or both eyes due to diabetic retinopathy was more common in those with retinopathy at screening (26% vs. 5%, p < 0.001), but blindness due to diabetes occurred in only 1 in 1000. Conclusions Optimum screening intervals should be determined from time to active treatment. Based on requirement for laser therapy, the screening interval for diabetic patients with no retinopathy can be extended to two to three years. Patients who attend for retinal screening and treatment who have no or non-proliferative retinopathy now have a very low risk of eventual blindness from diabetes.

Development of a cost-effectiveness model for optimisation of the screening interval in diabetic retinopathy screening

BACKGROUND

The English NHS Diabetic Eye Screening Programme was established in 2003. Eligible people are invited annually for digital retinal photography screening. Those found to have potentially sight-threatening diabetic retinopathy (STDR) are referred to surveillance clinics or to Hospital Eye Services.

OBJECTIVES

To determine whether personalised screening intervals are cost-effective.

DESIGN

Risk factors were identified in Gloucestershire, UK using survival modelling. A probabilistic decision hidden (unobserved) Markov model with a misgrading matrix was developed. This informed estimation of lifetime costs and quality-adjusted life-years (QALYs) in patients without STDR. Two personalised risk stratification models were employed: two screening episodes (SEs) (low, medium or high risk) or one SE with clinical information (low, medium-low, medium-high or high risk). The risk factor models were validated in other populations.

SETTING

Gloucestershire, Nottinghamshire, South London and East Anglia (all UK).

PARTICIPANTS

People with diabetes in Gloucestershire with risk stratification model validation using data from Nottinghamshire, South London and East Anglia.

MAIN OUTCOME MEASURES

Personalised risk-based algorithm for screening interval; cost-effectiveness of different screening intervals.

RESULTS

Data were obtained in Gloucestershire from 12,790 people with diabetes with known risk factors to derive the risk estimation models, from 15,877 people to inform the uptake of screening and from 17,043 people to inform the health-care resource-usage costs. Two stratification models were developed: one using only results from previous screening events and one using previous screening and some commonly available GP data. Both models were capable of differentiating groups at low and high risk of development of STDR. The rate of progression to STDR was 5 per 1000 person-years (PYs) in the lowest decile of risk and 75 per 1000 PYs in the highest decile. In the absence of personalised risk stratification, the most cost-effective screening interval was to screen all patients every 3 years, with a 46% probability of this being cost-effective at a £30,000 per QALY threshold. Using either risk stratification models, screening patients at low risk every 5 years was the most cost-effective option, with a probability of 99-100% at a £30,000 per QALY threshold. For the medium-risk groups screening every 3 years had a probability of 43-48% while screening high-risk groups every 2 years was cost-effective with a probability of 55-59%.

CONCLUSIONS

The study found that annual screening of all patients for STDR was not cost-effective. Screening this entire cohort every 3 years was most likely to be cost-effective. When personalised intervals are applied, screening those in our low-risk groups every 5 years was found to be cost-effective. Screening high-risk groups every 2 years further improved the cost-effectiveness of the programme. There was considerable uncertainty in the estimated incremental costs and in the incremental QALYs, particularly with regard to implications of an increasing proportion of maculopathy cases receiving intravitreal injection rather than laser treatment. Future work should focus on improving the understanding of risk, validating in further populations and investigating quality issues in imaging and assessment including the potential for automated image grading.

STUDY REGISTRATION

Integrated Research Application System project number 118959.

FUNDING DETAILS

The National Institute for Health Research Health Technology Assessment programme.

Uncovering heart failure with preserved ejection fraction in patients with type 2 diabetes in primary care: time for a change

Undetected heart failure appears to be an important health problem in patients with type 2 diabetes and aged ≥ 60 years. The prevalence of previously unknown heart failure in these patients is high, steeply rises with age, and is overall higher in women than in men. The majority of the patients with newly detected heart failure have a preserved ejection fraction. A diagnostic algorithm to detect or exclude heart failure in these patients with variables from the medical files combined with items from history taking and physical examination provides a good to excellent accuracy. Annual screening appears to be cost-effective. Both unrecognised heart failure with reduced and with preserved ejection fraction were associated with a clinically relevant lower health status in patients with type 2 diabetes. Also the prognosis of these patients was worse than of those without heart failure. Existing disease-management programs for type 2 diabetes pay insufficient attention to early detection of cardiovascular diseases, including heart failure. We conclude that more attention is needed for detection of heart failure in older patients with type 2 diabetes.

Centralized Reading Center Improves Quality in a Real-World Setting

BACKGROUND AND OBJECTIVE

Diabetic retinopathy (DR) screening is standard of care, but its utility diminishes unless high quality is maintained. This project describes the improvement in diagnostic accuracy achieved at a large health maintenance organization by implementing a centralized reading center.

PATIENTS AND METHODS

Data were extracted from the electronic health records of patients with diabetes who underwent DR screening between January 1, 2009, and December 31, 2013, at 13 medical centers. Certified ophthalmic assistants and technicians were trained to read DR images under the supervision of a retinal specialist. This program was pilot-tested prior to full implementation.

RESULTS

DR prevalence among the 13 centers in 2009 was 10.1%, far below the national average. After implementation, prevalence increased to 22.1%. The program also resulted in improved access to follow-up.

CONCLUSION

The results demonstrate the value of a reading center in decreasing diagnostic error and achieving other improvements in a real-world setting.

The Diabetic Retinopathy Screening Workflow: Potential for Smartphone Imaging

Complications of diabetes mellitus, namely diabetic retinopathy and diabetic maculopathy, are the leading cause of blindness in working aged people. Sufferers can avoid blindness if identified early via retinal imaging. Systematic screening of the diabetic population has been shown to greatly reduce the prevalence and incidence of blindness within the population. Many national screening programs have digital fundus photography as their basis. In the past 5 years several techniques and adapters have been developed that allow digital fundus photography to be performed using smartphones. We review recent progress in smartphone-based fundus imaging and discuss its potential for integration into national systematic diabetic retinopathy screening programs. Some systems have produced promising initial results with respect to their agreement with reference standards. However further multisite trialling of such systems' use within implementable screening workflows is required if an evidence base strong enough to affect policy change is to be established. If this were to occur national diabetic retinopathy screening would, for the first time, become possible in low- and middle-income settings where cost and availability of trained eye care personnel are currently key barriers to implementation. As diabetes prevalence and incidence is increasing sharply in these settings, the impact on global blindness could be profound.

Individualised risk assessment for diabetic retinopathy and optimisation of screening intervals: a scientific approach to reducing healthcare costs

Objective

To validate a mathematical algorithm that calculates risk of diabetic retinopathy progression in a diabetic population with UK staging (R0–3; M1) of diabetic retinopathy. To establish the utility of the algorithm to reduce screening frequency in this cohort, while maintaining safety standards.

Research design and methods

The cohort of 9690 diabetic individuals in England, followed for 2 years. The algorithms calculated individual risk for development of preproliferative retinopathy (R2), active proliferative retinopathy (R3A) and diabetic maculopathy (M1) based on clinical data. Screening intervals were determined such that the increase in risk of developing certain stages of retinopathy between screenings was the same for all patients and identical to mean risk in fixed annual screening. Receiver operating characteristic curves were drawn and area under the curve calculated to estimate the prediction capability.

Results

The algorithm predicts the occurrence of the given diabetic retinopathy stages with area under the curve =80% for patients with type II diabetes (CI 0.78 to 0.81). Of the cohort 64% is at less than 5% risk of progression to R2, R3A or M1 within 2 years. By applying a 2 year ceiling to the screening interval, patients with type II diabetes are screened on average every 20 months, which is a 40% reduction in frequency compared with annual screening.

Conclusions

The algorithm reliably identifies patients at high risk of developing advanced stages of diabetic retinopathy, including preproliferative R2, active proliferative R3A and maculopathy M1. Majority of patients have less than 5% risk of progression between stages within a year and a small high-risk group is identified. Screening visit frequency and presumably costs in a diabetic retinopathy screening system can be reduced by 40% by using a 2 year ceiling. Individualised risk assessment with 2 year ceiling on screening intervals may be a pragmatic next step in diabetic retinopathy screening in UK, in that safety is maximised and cost reduced by about 40%.

External validation of a risk assessment model to adjust the frequency of eye-screening visits in patients with diabetes mellitus

AIMS

To validate a sight-threatening diabetic retinopathy (STDR) risk assessment model to adjust the frequency of eye-screening visits in patients with diabetes mellitus.

METHODS

Retrospective follow-up study of patients with diabetes mellitus attending a diabetes center. Anonimyzed data on gender, type and duration of diabetes, HbA1c, blood pressure and the presence and grade of diabetic retinopathy were gathered to estimate risk for STDR for each individual's worse eye over time by means of a prediction model. Receiver operating characteristics (ROC) analysis was performed to determine the diagnostic ability of the model, and a calibration graph was done to see the model fit.

RESULTS

508 screening intervals were analyzed, median diabetes duration was 10years, 87% were type 2 diabetes mellitus, and 3.1% developed STDR before the next screening visit. The area under the ROC curve was 0.74, and the calibration graph showed that model had a good fit. The reduction in screening frequency was 40% compared with fixed annual screening.

CONCLUSIONS

Current prediction model used to estimate the risk of developing STDR in patients with diabetes performed well. A personalized screening frequency for diabetic retinopathy could be implemented in practice.

Diabetic retinopathy - ocular complications of diabetes mellitus

In industrialized nations diabetic retinopathy is the most frequent microvascular complication of diabetes mellitus and the most common cause of blindness in the working-age population. In the next 15 years, the number of patients suffering from diabetes mellitus is expected to increase significantly. By the year 2030, about 440 million people in the age-group 20-79 years are estimated to be suffering from diabetes mellitus worldwide (prevalence 7.7%), while in 2010 there were 285 million people with diabetes mellitus (prevalence 6.4%). This accounts for an increase in patients with diabetes in industrialized nations by 20% and in developing countries by 69% until the year 2030. Due to the expected rise in diabetic patients, the need for ophthalmic care of patients (i.e., exams and treatments) will also increase and represents a challenge for eye-care providers. Development of optimized screening programs, which respect available resources of the ophthalmic infrastructure, will become even more important. Main reasons for loss of vision in patients with diabetes mellitus are diabetic macular edema and proliferative diabetic retinopathy. Incidence or progression of these potentially blinding complications can be greatly reduced by adequate control of blood glucose and blood pressure levels. Additionally, regular ophthalmic exams are mandatory for detecting ocular complications and initiating treatments such as laser photocoagulation in case of clinical significant diabetic macular edema or early proliferative diabetic retinopathy. In this way, the risk of blindness can considerably be reduced. In advanced stages of diabetic retinopathy, pars-plana vitrectomy is performed to treat vitreous hemorrhage and tractional retinal detachment. In recent years, the advent of intravitreal medication has improved therapeutic options for patients with advanced diabetic macular edema.

Progression of diabetes retinal status within community screening programs and potential implications for screening intervals

OBJECTIVE

This study aimed to follow the natural progression of retinal changes in patients with diabetes. Such information should inform decisions with regard to the screening intervals for such patients.

RESEARCH DESIGN AND METHODS

An observational study was undertaken linking the data from seven diabetes retinal screening programs across the U.K. for retinal grading results between 2005 and 2012. Patients with absent or background retinopathy were followed up for progression to the end points referable retinopathy and treatable retinopathy (proliferative retinopathy).

RESULTS

In total, 354,549 patients were observed for up to 4 years during which 16,196 patients progressed to referable retinopathy. Of patients with no retinopathy in either eye for two successive screening episodes at least 12 months apart, the conditions of between 0.3% (95% CI 0.3-0.8%) and 1.3% (1.0-1.6%) of patients progressed to referable retinopathy, and rates of treatable eye disease were <0.3% at 2 years. The corresponding progression rates for patients with bilateral background retinopathy in successive screening episodes were 13-29% and up to 4%, respectively, in the different programs.

CONCLUSIONS

It may be possible to stratify patients for risk, according to baseline retinal criteria, into groups with low and high risk of their conditions progressing to proliferative retinopathy. Screening intervals for such diverse groups of patients could safely be modified according to their risk.