Implementation and first-year screening results of an ocular telehealth system for diabetic retinopathy in China

Risk factors for diabetic retinopathy, diabetic macular edema, and sight-threatening diabetic retinopathy

OBJECTIVE

To identify the risk factors for the development of diabetic retinopathy (DR), diabetic macular edema (DME), and sight-threatening DR (STDR) based on a city-wide diabetes screening program.

RESEARCH DESIGN AND METHODS

Diabetic patients were prospectively recruited between June 2016 and December 2022. All patients underwent dilated fundus photography centered on the disc and macula or macular spectral domain optical coherence tomography (SD-OCT) scan. Complete medical history was documented. Systematic examination, blood analysis, and urinalysis were performed. Multivariate logistic regression analysis adjusting for age and sex was conducted.

RESULTS

Out of 7274 diabetic patients, 6840 had gradable images, among which 3054 (42.0%) were graded as DR, 1153 (15.9%) as DME, and 1500 (20.6%) as STDR. The factors associated with DR, DME, and STDR included younger age (odds ratio [OR]: 0.96, 0.97, and 0.96 respectively), lower BMI (OR: 0.97, 0.95, and 0.95 respectively), longer duration of diabetes (OR: 1.07, 1.03, and 1.05 respectively) and positive of urinary albumin (OR: 2.22, 2.56, and 2.88 respectively). Other associated factors included elevated blood urea nitrogen (OR: 1.22, 1.28, and 1.27 respectively), higher LDL-cholesterol, lower blood hemoglobin (OR: 0.98, 0.98, and 0.98), insulin intake, presence of diabetic foot pathologies and diabetic peripheral neuropathy. We also identified novel risk factors, including high serum potassium (OR: 1.37, 1.46, and 1.55 respectively), high-serum sodium (OR: 1.02, 1.02, and 1.04 respectively). Better family income was a protective factor for DR, DME, and STDR. Alcohol consumption once a week was also identified as a protective factor for DR.

CONCLUSIONS

Similar risk factors for DR, DME, and STDR were found in this study. Our data also indicates high serum sodium, high serum potassium, low blood hemoglobin, and level of family income as novel associated factors for DR, DME, and STDR, which can help with DR monitoring and management.

Evaluating imaging repeatability of fully self-service fundus photography within a community-based eye disease screening setting

PURPOSE

This study aimed to investigate the imaging repeatability of self-service fundus photography compared to traditional fundus photography performed by experienced operators.

DESIGN

Prospective cross-sectional study.

METHODS

In a community-based eye diseases screening site, we recruited 65 eyes (65 participants) from the resident population of Shanghai, China. All participants were devoid of cataract or any other conditions that could potentially compromise the quality of fundus imaging. Participants were categorized into fully self-service fundus photography or traditional fundus photography group. Image quantitative analysis software was used to extract clinically relevant indicators from the fundus images. Finally, a statistical analysis was performed to depict the imaging repeatability of fully self-service fundus photography.

RESULTS

There was no statistical difference in the absolute differences, or the extents of variation of the indicators between the two groups. The extents of variation of all the measurement indicators, with the exception of the optic cup area, were below 10% in both groups. The Bland-Altman plots and multivariate analysis results were consistent with results mentioned above.

CONCLUSIONS

The image repeatability of fully self-service fundus photography is comparable to that of traditional fundus photography performed by professionals, demonstrating promise in large-scale eye disease screening programs.

Changes and related factors of blood CCN1 levels in diabetic patients

Objective

To study the differences in blood cellular communication network factor 1 (CCN1) levels between patients with diabetes mellitus (DM) and healthy individuals and to explore the relationship between CCN1 and diabetic retinopathy (DR).

Methods

Plasma CCN1 levels were detected using ELISA in 50 healthy controls, 74 patients with diabetes without diabetic retinopathy (DM group), and 69 patients with diabetic retinopathy (DR group). Correlations between CCN1 levels and age, body mass index, mean arterial pressure, hemoglobin A1c, and other factors were analyzed. The relationship between CCN1 expression and DR was explored using logistic regression after adjusting for confounding factors. Blood mRNA sequencing analysis was performed for all subjects, and the molecular changes that may be related to CCN1 were explored. The retinal vasculature of streptozotocin-induced diabetic rats was examined using fundus fluorescein angiography; in addition, retinal protein expression was examined using western blotting.

Results

Plasma CCN1 levels in patients with DR were significantly higher than in the control and DM groups; however, no significant differences were observed between healthy controls and patients with DM. CCN1 levels negatively correlated with body mass index and positively correlated with the duration of diabetes and urea levels. It was observed that high (OR 4.72, 95% CI: 1.10-20.25) and very high (OR 8.54, 95% CI: 2.00-36.51) levels of CCN1 were risk factors for DR. Blood mRNA sequencing analysis revealed that CCN1-related pathways were significantly altered in the DR group. The expression of hypoxia-, oxidative stress-, and dephosphorylation-related proteins were elevated, while that of tight junction proteins were reduced in the retinas of diabetic rats.

Conclusion

Blood CCN1 levels are significantly elevated in patients with DR. High and very high levels of plasma CCN1 are risk factors for DR. Blood CCN1 level may be a potential biomarker for diagnosis of DR. The effects of CCN1 on DR may be related to hypoxia, oxidative stress, and dephosphorylation.

Inclusion of diabetic retinopathy screening strategies in national-level diabetes care planning in low- and middle-income countries: a scoping review

BACKGROUND

Diabetes is a major public health concern, with approximately 80% of the burden falling on low- and middle-income countries (LMICs). Diabetic retinopathy (DR) is one of the most common microvascular complications of diabetes, and early detection through diabetic eye screening programmes is essential to prevent visual impairment and blindness. Careful planning at a national level is crucial for effective implementation of such programmes.

METHODS

A scoping review was conducted, and the protocol was published previously to explain the methods in detail. Data were collected from databases and searches, including grey literature. Furthermore, consultations were conducted with key informants from LMICs.

RESULTS

Lower-middle-income countries (29/50, 58%) and upper-middle-income countries (27/59, 45.8%) are making more progress than low-income countries (4/29, 13.8%) in terms of DR policy planning. However, no identified data for published policies have actually implemented national DR policies. Compared to low-income and lower-middle-income countries, upper-middle-income countries are making the most progress in implementing national diabetic eye screening programmes; however, their progress is still slow, with only 5/59 (8.5%) having such programmes.

CONCLUSION

There are significant gaps in the literature, with no data reported for 78/138 (56.5%) LMICs. Further research is clearly needed to support and document DR policy development in LMICs.

Effective Low-Cost Ophthalmological Screening With a Novel iPhone Fundus Camera at Community Centers

Ophthalmologic care is inaccessible to many people due to a variety of factors, including the availability of providers, cost of equipment for ophthalmologic care, and transportation to clinics and appointments. Because many causes of blindness are both highly prevalent and preventable once identified, it is essential to address gaps in care for underserved populations. We developed a novel 3D-printed mobile retinal camera. In this study, we organized recurring student-run screening events around New York City that took place in community centers and churches, at which we utilized our device to take retinal images. Our screening events reached a diverse population of New Yorkers, disproportionately those with lower household income, many of whom had not had recent eye exams. To validate the device for use in telehealth ophthalmologic visits, we transmitted the images to a remote ophthalmologist for evaluation and compared the result with an on-site attending physician’s dilated eye exam. The subjective assessment indicated that 97% of images captured with the mobile retinal camera were acceptable for telehealth analysis. Remote image assessment by achieved 92% sensitivity and 83% specificity in detecting optic disc cupping, compared to the gold-standard on-site dilated eye exam. In addition, the device was portable, affordable, and able to be used by those with relatively little ophthalmologic training. We have demonstrated the utility of this affordable mobile retinal camera for telehealth ophthalmologic evaluation during community screening events that reached an underserved population to detect disease and connect with long-term care.

Cost-effectiveness and cost-utility of traditional and telemedicine combined population-based age-related macular degeneration and diabetic retinopathy screening in rural and urban China

BACKGROUND

To assess the cost-effectiveness and cost-utility of a population-level traditional and telemedicine combined age-related macular degeneration (AMD) and diabetic retinopathy (DR) screening program in rural and urban China.

METHODS

Decision-analytic Markov models were conducted to evaluate the costs and benefits of traditional and telemedicine combined AMD and DR screening from a societal perspective. A cohort of all participants aged 50 years old and above was followed through a total of 30 1-year Markov cycles. Separate analyses were performed for rural and urban settings. Relevant parameters such as the prevalence of AMD and DR, transition probability, compliance with screening and treatment, screening sensitivity, specificity, utility, and mortality were collected from published studies specific to China, other Asian counties' studies, or unpublished data sources such as the National Committee for the Prevention of Blindness. Costs of screening, full examination, and treatment come from the real medical environments and unified pricing of Beijing Municipal Medical Insurance Bureau. Primary outcomes were incremental cost-utility ratios (ICURs) using quality-adjusted life-years (QALYs) and incremental cost-effectiveness ratios (ICERs) using years of blindness avoided. One-way deterministic and simulated probabilistic sensitivity analyses were conducted to reflect uncertainty.

FINDINGS

Under the status quo, the total expected medical costs for a 50-year-old patient with AMD or DR were $869·59 and $1,514·18 in rural and urban settings, respectively. Both traditional and telemedicine screening were highly cost-effective. In rural settings, ICURs were $191 (95% confidence interval [CI]: $66 to $239) and $199 (95% CI: $-12 to $217), and ICERs were $2,436 (95% CI: $1,089 to $3,254) and $2,441 (95% CI: $1,452 to $3,900) for traditional and telemedicine screening separately. Even more surprising, both screening strategies dominated no screening in urban settings. Our results were insensitive and robust to extensive sensitivity analyses. Among all acceptable screening intervals (from 1 to 5 years), annual screening could not only produce biggest benefits but also keep ICERs less than three times and one time the per capita gross domestic product (GDP) in rural and urban settings separately. When compared with traditional screening, ICERs of telescreening were less than three times the per capita GDP in rural settings ($2,559 to $8,809) and less than one time the per capita GDP in urban settings (less than $5,564), annual telescreening produced the biggest benefits, it could avert 119 and 270 years of blindness in rural and urban areas separately when 100,000 people were screened.

INTERPRETATION

We performed decision-analytic Markov models for combined AMD and DR screening in rural and urban China, and the results showed that population-level combined screening for AMD and DR is likely to be highly cost-effective in both rural and urban China for people over 50 years old. Optimal screening may have an interval of every year based on teleophthalmology platforms. In the future, China should pay more attention to chronic eye diseases and the government should establish a sound chronic disease management system and make every patient enjoy equal medical services.

FUNDING

National Natural Science Foundation of China, NSFC (82171051); the Major Innovation Platform of Public Health & Disease Control and Prevention, Renmin University of China and Beijing Nova program (Z191100001119072).

The Validation of Deep Learning-Based Grading Model for Diabetic Retinopathy

Purpose

To evaluate the performance of a deep learning (DL)-based artificial intelligence (AI) hierarchical diagnosis software, EyeWisdom V1 for diabetic retinopathy (DR).

Materials and Methods

The prospective study was a multicenter, double-blind, and self-controlled clinical trial. Non-dilated posterior pole fundus images were evaluated by ophthalmologists and EyeWisdom V1, respectively. The diagnosis of manual grading was considered as the gold standard. Primary evaluation index (sensitivity and specificity) and secondary evaluation index like positive predictive values (PPV), negative predictive values (NPV), etc., were calculated to evaluate the performance of EyeWisdom V1.

Results

A total of 1,089 fundus images from 630 patients were included, with a mean age of (56.52 ± 11.13) years. For any DR, the sensitivity, specificity, PPV, and NPV were 98.23% (95% CI 96.93-99.08%), 74.45% (95% CI 69.95-78.60%), 86.38% (95% CI 83.76-88.72%), and 96.23% (95% CI 93.50-98.04%), respectively; For sight-threatening DR (STDR, severe non-proliferative DR or worse), the above indicators were 80.47% (95% CI 75.07-85.14%), 97.96% (95% CI 96.75-98.81%), 92.38% (95% CI 88.07-95.50%), and 94.23% (95% CI 92.46-95.68%); For referral DR (moderate non-proliferative DR or worse), the sensitivity and specificity were 92.96% (95% CI 90.66-94.84%) and 93.32% (95% CI 90.65-95.42%), with the PPV of 94.93% (95% CI 92.89-96.53%) and the NPV of 90.78% (95% CI 87.81-93.22%). The kappa score of EyeWisdom V1 was 0.860 (0.827-0.890) with the AUC of 0.958 for referral DR.

Conclusion

The EyeWisdom V1 could provide reliable DR grading and referral recommendation based on the fundus images of diabetics.

Update on Current and Future Management for Diabetic Maculopathy

Diabetic macular edema (DME) remains the major cause of preventable blindness in the working-age population in developed countries, and screening programs are extremely important in the management of this complication of diabetic retinopathy. The introduction of modern imaging modalities and technological advances have facilitated both the early detection and the follow-up of patients with DME, particularly optical coherence tomography angiography and artificial intelligence. Intravitreal therapy is the gold standard treatment for DME, but not all patients respond equally to this therapy, and sometimes it is not easy to apply treatment protocols correctly; for these reasons, clinical practice results may differ from those of clinical trials in terms of vision gain. One approach has been to implement new treatment regimens, such as treat and extend, and new molecules and therapeutic targets are constantly being developed. The main goal of this review paper is to describe the current treatment options and management strategies for DME in Europe and to provide a brief oversight of the novel therapeutic options on the horizon.

Artificial intelligence for teleophthalmology-based diabetic retinopathy screening in a national programme: an economic analysis modelling study

BACKGROUND

Deep learning is a novel machine learning technique that has been shown to be as effective as human graders in detecting diabetic retinopathy from fundus photographs. We used a cost-minimisation analysis to evaluate the potential savings of two deep learning approaches as compared with the current human assessment: a semi-automated deep learning model as a triage filter before secondary human assessment; and a fully automated deep learning model without human assessment.

METHODS

In this economic analysis modelling study, using 39 006 consecutive patients with diabetes in a national diabetic retinopathy screening programme in Singapore in 2015, we used a decision tree model and TreeAge Pro to compare the actual cost of screening this cohort with human graders against the simulated cost for semi-automated and fully automated screening models. Model parameters included diabetic retinopathy prevalence rates, diabetic retinopathy screening costs under each screening model, cost of medical consultation, and diagnostic performance (ie, sensitivity and specificity). The primary outcome was total cost for each screening model. Deterministic sensitivity analyses were done to gauge the sensitivity of the results to key model assumptions.

FINDINGS

From the health system perspective, the semi-automated screening model was the least expensive of the three models, at US$62 per patient per year. The fully automated model was $66 per patient per year, and the human assessment model was $77 per patient per year. The savings to the Singapore health system associated with switching to the semi-automated model are estimated to be $489 000, which is roughly 20% of the current annual screening cost. By 2050, Singapore is projected to have 1 million people with diabetes; at this time, the estimated annual savings would be $15 million.

INTERPRETATION

This study provides a strong economic rationale for using deep learning systems as an assistive tool to screen for diabetic retinopathy.

FUNDING

Ministry of Health, Singapore.

Health Economic and Safety Considerations for Artificial Intelligence Applications in Diabetic Retinopathy Screening

Systematic screening for diabetic retinopathy (DR) has been widely recommended for early detection in patients with diabetes to address preventable vision loss. However, substantial manpower and financial resources are required to deploy opportunistic screening and transition to systematic DR screening programs. The advent of artificial intelligence (AI) technologies may improve access and reduce the financial burden for DR screening while maintaining comparable or enhanced clinical effectiveness. To deploy an AI-based DR screening program in a real-world setting, it is imperative that health economic assessment (HEA) and patient safety analyses are conducted to guide appropriate allocation of resources and design safe, reliable systems. Few studies published to date include these considerations when integrating AI-based solutions into DR screening programs. In this article, we provide an overview of the current state-of-the-art of AI technology (focusing on deep learning systems), followed by an appraisal of existing literature on the applications of AI in ophthalmology. We also discuss practical considerations that drive the development of a successful DR screening program, such as the implications of false-positive or false-negative results and image gradeability. Finally, we examine different plausible methods for HEA and safety analyses that can be used to assess concerns regarding AI-based screening.

Patients' perspectives on the barriers to referral after telescreening for diabetic retinopathy in communities

OBJECTIVE

To understand the referral completion and explore the associated barriers to the referral after telescreening for diabetic retinopathy (DR) among people with vision-threatening DR (VTDR).

RESEARCH DESIGN AND METHODS

All participants with VTDR after DR telescreening in the communities completed the self-reported questionnaires to assess referral completion and their perspectives on referral barriers. Sociodemographic characteristics and perceived barriers related to incomplete referrals were identified by conducting univariate analysis and multiple logistic regression model. The final model was then built to predict incomplete referral.

RESULTS

Of the 3362 participants, 46.1% had incomplete referral. Old age and lower education level showed significant association with incomplete referral. Almost all participants had at least one barrier during the referral process. Knowledge-related and attitude-related barriers, including 'Too old to want any more treatment', 'Difficulty in getting time to referral', 'No serious illness requiring treatment at present', 'My eyes are okay', 'Distrust the recommended hospital' and 'Have not been diagnosed or treated before', and logistics-related barrier 'Mobility or transportation difficulties' showed significant association with incomplete referral.

CONCLUSIONS

The issue of incomplete referral after DR telescreening is serious among individuals with VTDR, particularly in the elder and low education level population. The negativity of knowledge-related and attitude-related factors might be more prominent than logistic barriers in predicting incomplete referral. Therefore, new strategies to improve the compliance with referral assist in optimizing the referral accessibility, and the ongoing educational support to improve the awareness of disease and increase the effectiveness of physician-patient communication.

Artificial Intelligence in Ophthalmology: Evolutions in Asia

Artificial intelligence (AI) has been studied in ophthalmology since availability of digital information in ophthalmic care. The significant turning point was availability of commercial digital color fundus photography in the late 1990s, which caused digital screening for diabetic retinopathy (DR) to take off. Automated Retinal Disease Assessment software was then developed using machine learning to detect abnormal lesions in fundus to screen DR. The use of this version of AI had not been generalized because the specificity at 45% was not high enough, although the sensitivity reached 90%. The recent breakthrough in machine learning is the invent of deep learning, which accelerates its performance to be on par with experts. The first 2 breakthrough studies on deep learning for screening DR were conducted in Asia. The first represented collaboration of datasets between Asia and the United States for algorithms development, whereas the second represented algorithms developed in Asia but validated in different populations across the world. Both found accuracy for detecting referable DR of >95%. Diversity and variety are unique strengths of Asia for AI studies. There are many more studies of AI ongoing in Asia not only as prospective deployments in DR but in glaucoma, age-related macular degeneration, cataract, and systemic disease, such as Alzheimer's disease. Some Asian countries have laid out plans for digital health care system using AI as one of the puzzle pieces for solving blindness. More studies on AI and digital health are expected to come from Asia in this new decade.

Artificial intelligence-based screening for diabetic retinopathy at community hospital

OBJECTIVES

The purpose of this study is to assess the accuracy of artificial intelligence (AI)-based screening for diabetic retinopathy (DR) and to explore the feasibility of applying AI-based technique to community hospital for DR screening.

METHODS

Nonmydriatic fundus photos were taken for 889 diabetic patients who were screened in community hospital clinic. According to DR international classification standards, ophthalmologists and AI identified and classified these fundus photos. The sensitivity and specificity of AI automatic grading were evaluated according to ophthalmologists' grading.

RESULTS

DR was detected by ophthalmologists in 143 (16.1%) participants and by AI in 145 (16.3%) participants. Among them, there were 101 (11.4%) participants diagnosed with referable diabetic retinopathy (RDR) by ophthalmologists and 103 (11.6%) by AI. The sensitivity, specificity and area under the curve (AUC) of AI for detecting DR were 90.79% (95% CI 86.4-94.1), 98.5% (95% CI 97.8-99.0) and 0.946 (95% CI 0.935-0.956), respectively. For detecting RDR, the sensitivity, specificity and AUC of AI were 91.18% (95% CI 86.4-94.7), 98.79% (95% CI 98.1-99.3) and 0.950 (95% CI 0.939-0.960), respectively.

CONCLUSION

AI has high sensitivity and specificity in detecting DR and RDR, so it is feasible to carry out AI-based DR screening in outpatient clinic of community hospital.

Complications of diabetes in China: health system and economic implications

BACKGROUND

The prevalence of diabetes and diabetic complications increased alarmingly which also brought heavy burden to patients and health system.

METHODS

We used mix approaches to summarize evidence from published articles and policy documents on the extent and trends of diabetic complications, potential causes, and awareness and services utilization of diabetes in China.

RESULTS

The annual direct medical expense per patient varied among different types of complications and increased dramatically with the number of diabetic complication and patients were exposed to great financial risk. The number of health policies and strategies on diabetes and its complications at the national level is limited. Primary and secondary preventions such as health education and early diagnosis are necessary.

CONCLUSIONS

With an increasingly burden of non-communicable diseases such as diabetes and its complications, efforts should be invested in education, early screening mechanism and patient management programs to improve the primary and secondary prevention of diabetes and its complications. An integrated services delivery system centered on primary level is recommended to promote education, early case-detection and screening, patient management, referral and care-coordination between primary, secondary and tertiary health care providers.

Use of Expectation Disconfirmation Theory to Test Patient Satisfaction with Asynchronous Telemedicine for Diabetic Retinopathy Detection

OBJECTIVE

The purpose of the study is to extend research on patient satisfaction with telemedicine services by employing the theoretical framework of Expectation Disconfirmation Theory (EDT) for diabetic retinopathy screenings focusing on rural patients.

METHOD

Adult subjects (n=220) with diabetes were recruited from a single family practice office in rural Iowa. Subjects completed a "pre" survey concerning their forward-looking perceptions of telemedicine prior to using telemedicine for detection of diabetic retinopathy and a "post" survey after they received recommendations from the distant ophthalmologists.

RESULTS

All hypotheses of the EDT model were supported. Patient satisfaction is influenced by both patients' expectations (P<.001) and disconfirmation of expectations (P<.001), and patient satisfaction has a positive impact on patient preference for telemedicine services (P<.001). Overall, patients who received telemedicine services were highly satisfied with telemedicine and developed a favorable disposition towards telemedicine services.

CONCLUSIONS

The EDT model is a viable framework to study patient satisfaction of telemedicine services. While previous feasibility studies have shown that telemedicine for diabetic retinopathy screenings yields diagnostic efficacy, this study applies a theoretical framework to demonstrate the viability of telemedicine for diabetic retinopathy screenings in rural areas.

Analysis of reasons for noncompliance with laser treatment in patients of diabetic retinopathy

OBJECTIVE

To identify the underlying reasons for noncompliance among Chinese patients undergoing laser photocoagulation treatment for diabetic retinopathy (DR).

DESIGN

Prospective cohort study.

PARTICIPANTS

A total of 262 patients with DR with indications for panretinal photocoagulation and focal laser treatment were recruited.

METHODS

Those who did not complete the prescribed laser treatment were categorized into 2 types of defaulters: Type 1 defaulters were those who did not initiate laser treatment as scheduled; type 2 defaulters were those who did not complete the entire laser sessions, including terminating midterm or defaulting prompt supplement of laser treatment. A standardized questionnaire was given to the 2 types of defaulters to collect information about the reasons for noncompliance. Data were analyzed and subjected to χ² test or Fisher exact statistical tests.

RESULTS

The noncompliance rate was 45.5%, which is significantly greater than some developed countries. Unawareness of the necessity for treatment and unawareness of the importance to complete treatment were 2 main reasons leading to noncompliance, representing 28.8% and 36.0%, respectively. Unawareness of the necessity for treatment and fear of laser treatment were more important for type 1 defaulters (29 vs 6 and 11 vs 0, respectively), whereas unawareness of completeness of laser treatment was overweighed in type 2 defaulters (27 vs 13 patients; all P<0.01). These results were likely related to the lack of knowledge about the potential consequences of DR, the underlying principle of laser treatment, and panretinal photocoagulation procedures.

CONCLUSIONS

Developing appropriate education programs targeting specific reasons will help to improve the compliance in patients with DR.

Automated Diabetic Retinopathy Image Assessment Software: Diagnostic Accuracy and Cost-Effectiveness Compared with Human Graders

OBJECTIVE

With the increasing prevalence of diabetes, annual screening for diabetic retinopathy (DR) by expert human grading of retinal images is challenging. Automated DR image assessment systems (ARIAS) may provide clinically effective and cost-effective detection of retinopathy. We aimed to determine whether ARIAS can be safely introduced into DR screening pathways to replace human graders.

DESIGN

Observational measurement comparison study of human graders following a national screening program for DR versus ARIAS.

PARTICIPANTS

Retinal images from 20 258 consecutive patients attending routine annual diabetic eye screening between June 1, 2012, and November 4, 2013.

METHODS

Retinal images were manually graded following a standard national protocol for DR screening and were processed by 3 ARIAS: iGradingM, Retmarker, and EyeArt. Discrepancies between manual grades and ARIAS results were sent to a reading center for arbitration.

MAIN OUTCOME MEASURES

Screening performance (sensitivity, false-positive rate) and diagnostic accuracy (95% confidence intervals of screening-performance measures) were determined. Economic analysis estimated the cost per appropriate screening outcome.

RESULTS

Sensitivity point estimates (95% confidence intervals) of the ARIAS were as follows: EyeArt 94.7% (94.2%-95.2%) for any retinopathy, 93.8% (92.9%-94.6%) for referable retinopathy (human graded as either ungradable, maculopathy, preproliferative, or proliferative), 99.6% (97.0%-99.9%) for proliferative retinopathy; Retmarker 73.0% (72.0 %-74.0%) for any retinopathy, 85.0% (83.6%-86.2%) for referable retinopathy, 97.9% (94.9%-99.1%) for proliferative retinopathy. iGradingM classified all images as either having disease or being ungradable. EyeArt and Retmarker saved costs compared with manual grading both as a replacement for initial human grading and as a filter prior to primary human grading, although the latter approach was less cost-effective.

CONCLUSIONS

Retmarker and EyeArt systems achieved acceptable sensitivity for referable retinopathy when compared with that of human graders and had sufficient specificity to make them cost-effective alternatives to manual grading alone. ARIAS have the potential to reduce costs in developed-world health care economies and to aid delivery of DR screening in developing or remote health care settings.

Clinical Components of Telemedicine Programs for Diabetic Retinopathy

Diabetic retinopathy is a leading cause of new-onset vision loss worldwide. Treatments supported by large clinical trials are effective in preserving vision, but many persons do not receive timely diagnosis and treatment of diabetic retinopathy, which is typically asymptomatic when most treatable. Telemedicine evaluation to identify diabetic retinopathy has the potential to improve access to care, but there are no universal standards regarding camera choice or protocol for ocular telemedicine. We review the literature regarding the impact of imaging device, number and size of retinal images, pupil dilation, type of image grader, and diagnostic accuracy on telemedicine assessment for diabetic retinopathy. Telemedicine assessment of diabetic retinopathy has the potential to preserve vision, but further development of telemedicine specific technology and standardization of operations are needed to better realize its potential.

Tele-ophthalmology for diabetic retinopathy screening: 8 years of experience

PURPOSE

To describe the results of a diabetic retinopathy screening program implemented in a primary care area.

METHODS

A retrospective study was conducted using data automatically collected since the program began on 1 January 2007 until 31 December 2015.

RESULTS

The number of screened diabetic patients has progressively increased, from 7,173 patients in 2007 to 42,339 diabetic patients in 2015. Furthermore, the ability of family doctors to correctly interpret retinographies has improved, with the proportion of retinal images classified as normal having increased from 55% in 2007 to 68% at the end of the study period. The proportion of non-evaluable retinographies decreased to 7% in 2015, having peaked at 15% during the program. This was partly due to a change in the screening program policy that allowed the use of tropicamide. The number of severe cases detected has declined, from 14% with severe non-proliferative and proliferativediabetic retinopathy in the initial phase of the program to 3% in 2015.

CONCLUSIONS

Diabetic eye disease screening by tele-ophthalmology has shown to be a valuable method in a growing population of diabetics. It leads to a regular medical examination of patients, helps ease the workload of specialised care services and favours the early detection of treatable cases. However, the results of implementing a program of this type are not immediate, achieving only modest results in the early years of the project that have improved over subsequent years.

Disparities between Ophthalmologists and Patients in Estimating Quality of Life Associated with Diabetic Retinopathy

Background

This study aimed to evaluate and compare the utility values associated with diabetic retinopathy (DR) in a sample of Chinese patients and ophthalmologists.

Methods

Utility values were evaluated by both the time trade-off (TTO) and rating scale (RS) methods for 109 eligible patients with DR and 2 experienced ophthalmologists. Patients were stratified by Snellen best-corrected visual acuity (BCVA) in the better-seeing eye. The correlations between the utility values and general vision-related health status measures were analyzed. These utility values were compared with data from two other studies.

Results

The mean utility values elicited from the patients themselves with the TTO (0.81; SD 0.10) and RS (0.81; SD 0.11) methods were both statistically lower than the mean utility values assessed by ophthalmologists. Significant predictors of patients’ TTO and RS utility values were both LogMAR BCVA in the affected eye and average weighted LogMAR BCVA. DR grade and duration of visual dysfunction were also variables that significantly predicted patients’ TTO utility values. For ophthalmologists, patients’ LogMAR BCVA in the affected eye and in the better eye were the variables that significantly predicted both the TTO and RS utility values. Patients’ education level was also a variable that significantly predicted RS utility values. Moreover, both diabetic macular edema and employment status were significant predictors of TTO and RS utility values, whether from patients or ophthalmologists. There was no difference in mean TTO utility values compared to our American and Canadian patients.

Conclusions

DR caused a substantial decrease in Chinese patients’ utility values, and ophthalmologists substantially underestimated its effect on patient quality of life.

A five-year prospective study of diabetic retinopathy progression in chinese type 2 diabetes patients with "well-controlled" blood glucose

Purpose

To determine the progression rate and risk factors for diabetic retinopathy (DR) in Chinese type 2 diabetic patients who have reached the target hemoglobin A1c (HbA1c) level recommended by the American Diabetes Association.

Methods

This was a 5-year community-based prospective study. The study population consisted of patients with type 2 diabetes with HbA1c less than 7.0%. Demographic information, systemic examination results and ophthalmological test results for each participant were collected. The outcome of this study was the progression of DR, which was defined as an increase in DR grade in one or both eyes at the final visit in comparison to the baseline status. The association between each potential risk factor and DR progression was studied.

Results

A total of 453 patients with HbA1c less than 7.0% were included in the study group. In 146 patients (32.22%), DR developed or progressed during the five-year follow-up. Baseline HbA1c level was the only independent risk factor for DR progression (p<0.01, OR = 2.84, 95%CI: 2.11~3.82). The logistic regression function suggested that the possibility of DR progression increased fastest when baseline HbA1c increased from 5.2% to 6.4%. The 5-year DR progression rate in patients with baseline HbA1c less than 5.2%, between 5.2% and 6.4%, and over 6.4% were 19.62%, 24.41%, and 76.83%, respectively.

Conclusions

To slow the progression of DR in Chinese patients with type 2 diabetes, more intensive glucose control is recommended.

Optical coherence tomography (OCT) for detection of macular oedema in patients with diabetic retinopathy

BACKGROUND

Diabetic macular oedema (DMO) is a thickening of the central retina, or the macula, and is associated with long-term visual loss in people with diabetic retinopathy (DR). Clinically significant macular oedema (CSMO) is the most severe form of DMO. Almost 30 years ago, the Early Treatment Diabetic Retinopathy Study (ETDRS) found that CSMO, diagnosed by means of stereoscopic fundus photography, leads to moderate visual loss in one of four people within three years. It also showed that grid or focal laser photocoagulation to the macula halves this risk. Recently, intravitreal injection of antiangiogenic drugs has also been used to try to improve vision in people with macular oedema due to DR.Optical coherence tomography (OCT) is based on optical reflectivity and is able to image retinal thickness and structure producing cross-sectional and three-dimensional images of the central retina. It is widely used because it provides objective and quantitative assessment of macular oedema, unlike the subjectivity of fundus biomicroscopic assessment which is routinely used by ophthalmologists instead of photography. Optical coherence tomography is also used for quantitative follow-up of the effects of treatment of CSMO.

OBJECTIVES

To determine the diagnostic accuracy of OCT for detecting DMO and CSMO, defined according to ETDRS in 1985, in patients referred to ophthalmologists after DR is detected. In the update of this review we also aimed to assess whether OCT might be considered the new reference standard for detecting DMO.

SEARCH METHODS

We searched the Cochrane Database of Systematic Reviews (CDSR), the Database of Abstracts of Reviews of Effects (DARE), the Health Technology Assessment Database (HTA) and the NHS Economic Evaluation Database (NHSEED) (The Cochrane Library 2013, Issue 5), Ovid MEDLINE, Ovid MEDLINE In-Process and Other Non-Indexed Citations, Ovid MEDLINE Daily, Ovid OLDMEDLINE (January 1946 to June 2013), EMBASE (January 1950 to June 2013), Web of Science Conference Proceedings Citation Index - Science (CPCI-S) (January 1990 to June 2013), BIOSIS Previews (January 1969 to June 2013), MEDION and the Aggressive Research Intelligence Facility database (ARIF). We did not use any date or language restrictions in the electronic searches for trials. We last searched the electronic databases on 25 June 2013. We checked bibliographies of relevant studies for additional references.

SELECTION CRITERIA

We selected studies that assessed the diagnostic accuracy of any OCT model for detecting DMO or CSMO in patients with DR who were referred to eye clinics. Diabetic macular oedema and CSMO were diagnosed by means of fundus biomicroscopy by ophthalmologists or stereophotography by ophthalmologists or other trained personnel.

DATA COLLECTION AND ANALYSIS

Three authors independently extracted data on study characteristics and measures of accuracy. We assessed data using random-effects hierarchical sROC meta-analysis models.

MAIN RESULTS

We included 10 studies (830 participants, 1387 eyes), published between 1998 and 2012. Prevalence of CSMO was 19% to 65% (median 50%) in nine studies with CSMO as the target condition. Study quality was often unclear or at high risk of bias for QUADAS 2 items, specifically regarding study population selection and the exclusion of participants with poor quality images. Applicablity was unclear in all studies since professionals referring patients and results of prior testing were not reported. There was a specific 'unit of analysis' issue because both eyes of the majority of participants were included in the analyses as if they were independent.In nine studies providing data on CSMO (759 participants, 1303 eyes), pooled sensitivity was 0.78 (95% confidence interval (CI) 0.72 to 0.83) and specificity was 0.86 (95% CI 0.76 to 0.93). The median central retinal thickness cut-off we selected for data extraction was 250 µm (range 230 µm to 300 µm). Central CSMO was the target condition in all but two studies and thus our results cannot be applied to non-central CSMO.Data from three studies reporting accuracy for detection of DMO (180 participants, 343 eyes) were not pooled. Sensitivities and specificities were about 0.80 in two studies and were both 1.00 in the third study.Since this review was conceived, the role of OCT has changed and has become a key ingredient of decision-making at all levels of ophthalmic care in this field. Moreover, disagreements between OCT and fundus examination are informative, especially false positives which are referred to as subclinical DMO and are at higher risk of developing clinical CSMO.

AUTHORS' CONCLUSIONS

Using retinal thickness thresholds lower than 300 µm and ophthalmologist's fundus assessment as reference standard, central retinal thickness measured with OCT was not sufficiently accurate to diagnose the central type of CSMO in patients with DR referred to retina clinics. However, at least OCT false positives are generally cases of subclinical DMO that cannot be detected clinically but still suffer from increased risk of disease progression. Therefore, the increasing availability of OCT devices, together with their precision and the ability to inform on retinal layer structure, now make OCT widely recognised as the new reference standard for assessment of DMO, even in some screening settings. Thus, this review will not be updated further.

The 5-year onset and regression of diabetic retinopathy in Chinese type 2 diabetes patients

PURPOSE

To determine the rate and risk factors of diabetic retinopathy (DR) onset and regression in Chinese type 2 diabetes mellitus patients.

METHODS

This is a 5-year community-based prospective study. The demographic information, systemic examination results and ophthalmological test results of each participant were collected. The study outcomes were DR incidence, defined as the onset of DR in at least one eye, and DR regression, defined as full regression from existing DR to no retinopathy without invasive treatments. The associations between each potential risk factor and the outcomes were studied.

RESULTS

In total, 778 participants were enrolled. There were 322 patients without DR at baseline, of which 151 participants developed DR during follow-up (DR incidence rate = 46.89%). Baseline hyperglycemia and high blood pressure were two independent risk factors associated with DR incidence. Among the 456 participants with existing DR at entry, 110 fully recovered after 5 years (DR regression rate = 24.12%). Low baseline glucose and low serum triglyceride were two independent factors associated with DR regression.

CONCLUSIONS

DR incidence occurred more frequently in patients with hyperglycemia and high blood pressure. DR regression occurred mostly in patients with lower glucose and lower serum triglyceride levels among Chinese type 2 diabetes patients.

Marked reductions in visual impairment due to diabetic retinopathy achieved by efficient screening and timely treatment

PURPOSE

Diabetic retinopathy (DR) is the most common complication of diabetes and needs to be diagnosed early to prevent severe sight-threatening retinopathy. Digital photography with telemedicine connections is a novel way to deliver cost-effective, accessible screening to remote areas. Screening for DR in a mobile eye examination unit (EyeMo) is compared to traditional service models (i.e. local municipal services or a commercial service provider). The quality of images, delays from screening to treatment, the stage of DR, coverage of screening and the rate of visual impairment due to DR are evaluated.

METHODS

EyeMo utilizes telemedicine technology. The electronic databases of the hospital and information from the Finnish Register of Visual Impairment were used to determine delays and the rate of visual impairment.

RESULTS

Fourteen thousand eight hundred and sixty-six fundus photographs were taken in EyeMo in 2007-2011. Coverage reached 78% of potential clients. No DR was detected in 43%, mild background retinopathy in 23%, moderate or severe background retinopathy in 31% and proliferative retinopathy in 3% of the evaluations. The quality of images was higher (p < 0.01) and delays shorter (p < 0.01) in EyeMo as compared to traditional service models. The rate of visual impairment due to DR decreased by 86% in the area covered by EyeMo, and the change compared favourably to the situation in the entire Finland (p < 0.0005).

CONCLUSION

EyeMo is a feasible model of telemedicine application for screening of DR. Effective screening and timely access to care may indeed have influenced the reduced rate of visual damage.

Prevalence of ocular fundus pathology with type 2 diabetes in a Chinese urban community as assessed by telescreening

OBJECTIVE

To describe the telescreening model and assess the prevalence of ocular fundus pathology in patients with type 2 diabetes within a Chinese urban community.

DESIGN

Community-based cross-sectional study.

SETTING

Healthcare centre of Fengyutan Community, Shenyang, China.

PARTICIPANTS

A total 528 patients (287 females) with type 2 diabetes mellitus (DM) were randomly recruited using health files from the healthcare centre of Fengyutan community between 8 October and 20 November 2012.

MAIN OUTCOME MEASURES

Signs of any diabetic retinopathy (DR), signs of glaucoma and signs of age-related macular degeneration (AMD).

RESULTS

The main ocular fundus pathologies were DR (75 patients, 14.20%), 65 (86.67%) cases of which were newly detected, AMD (57 patients, 10.79%) and glaucoma (63 patients, 11.93%). The risk factors for fundus pathology were long duration of diabetes (OR 2.31, 95% CI 1.87 to 2.56), and higher fasting plasma glucose (OR 3.64, 95% CI 1.81 to 5.21) and glycated haemoglobin (HbA1c) levels (OR 3.83, 95% CI 1.87 to 6.35).

CONCLUSIONS

There was a high prevalence of fundus pathology among patients with type 2 diabetes, and in most of the cases, this was newly detected. Community screening for fundus pathology among patients with a long duration of type 2 diabetes and high fasting plasma glucose and HbA1c levels using a telescreening model will provide an effective strategy for the prevention and treatment of fundus pathology.

Analysis of reasons for noncompliance with laser treatment in patients of diabetic retinopathy

OBJECTIVE

To identify the underlying reasons for noncompliance among Chinese patients undergoing laser photocoagulation treatment for diabetic retinopathy (DR).

DESIGN

Prospective cohort study.

PARTICIPANTS

A total of 262 patients with DR with indications for panretinal photocoagulation and focal laser treatment were recruited.

METHODS

Those who did not complete the prescribed laser treatment were categorized into 2 types of defaulters: Type 1 defaulters were those who did not initiate laser treatment as scheduled; type 2 defaulters were those who did not complete the entire laser sessions, including terminating midterm or defaulting prompt supplement of laser treatment. A standardized questionnaire was given to the 2 types of defaulters to collect information about the reasons for noncompliance. Data were analyzed and subjected to χ(2) test or Fisher exact statistical tests.

RESULTS

The noncompliance rate was 45.5%, which is significantly greater than some developed countries. Unawareness of the necessity for treatment and unawareness of the importance to complete treatment were 2 main reasons leading to noncompliance, representing 28.8% and 36.0%, respectively. Unawareness of the necessity for treatment and fear of laser treatment were more important for type 1 defaulters (29 vs 6 and 11 vs 0, respectively), whereas unawareness of completeness of laser treatment was overweighed in type 2 defaulters (27 vs 13 patients; all P<0.01). These results were likely related to the lack of knowledge about the potential consequences of DR, the underlying principle of laser treatment, and panretinal photocoagulation procedures.

CONCLUSIONS

Developing appropriate education programs targeting specific reasons will help to improve the compliance in patients with DR.

Prevalence and risk factors of idiopathic epiretinal membranes in Beixinjing blocks, Shanghai, China

Background

To determine the prevalence and risk factors associated with idiopathic epiretinal membranes (iERM) in a Chinese population aged 60 years or older in Beixinjing Blocks, Shanghai.

Methods

This population-based study consisted of 3727 participants (89.7% of the eligible). It was performed to describe the prevalence of iERM and possible demographic, systemic, and ocular factors associated with iERM. Each participant underwent a standardized interview and comprehensive ophthalmic examination. iERM was identified and graded from retinal photographs. Then, a case-control study comparing the participants with vs. without iERM was performed to further study the associations between iERM and blood biochemical test results (including fasting plasma glucose, serum creatinine, total cholesterol, and triglyceride), ocular biological parameters (including the axial length, corneal curvature, refractive diopter, intraocular press, and anterior chamber depth), and the data of optical coherence tomography.

Results

The prevalence of iERM was 1.02%. iERM was significantly associated with diabetes (OR: 2.457; 95% CI: 1.137, 5.309) and a higher level of education (OR: 1.48; 95% CI: 1.123, 1.952). Blood biochemical test results and ocular biological parameters showed no significant differences between the iERM and control groups, whereas the incidence of posterior vitreous detachment in the iERM group was much higher than in the control group (26.5% vs. 8.8%), but this difference was not statistically significant. Moreover, the eyes with iERM had poorer visual acuity than the eyes without iERM (P<0.05).

Conclusions

In Beixinjing Blocks, Shanghai, iERM was relatively rare, was associated with diabetes and a higher level of education, and caused a substantial decrease in visual acuity.

Telemedicine and ocular health in diabetes mellitus

Teleretinal/teleophthalmological programs that use existing health information technology infrastructure solutions for people with diabetes increase access to and adherence to appropriate eye care. Teleophthalmological studies indicate that the single act of patients viewing their own retinal images improves self-management behaviour and clinical outcomes. In some settings this can be done at lower cost and with improved visual outcomes compared with standard eye care. Cost-effective and sustainable teleretinal surveillance for detection of diabetic retinopathy requires a combination of an inexpensive portable device for taking low light-level retinal images without the use of pharmacological dilation of the pupil and a computer-assisted methodology for rapidly detecting and diagnosing diabetic retinopathy. A more holistic telehealth-care paradigm augmented with the use of health information technology, medical devices, mobile phone and mobile health applications and software applications to improve health-care co-ordination, self-care management and education can significantly impact a broad range of health outcomes, including prevention of diabetes-associated visual loss. This approach will require a collaborative, transformational, patient-centred health-care program that integrates data from medical record systems with remote monitoring of data and a longitudinal health record. This includes data associated with social media applications and personal mobile health technology and should support continuous interactions between the patient, health-care team and the patient's social environment. Taken together, this system will deliver contextually and temporally relevant decision support to patients to facilitate their well-being and to reduce the risk of diabetic complications.