Cited by 34Retinal Imaging and AnalysisRetinal Diseases and TreatmentsOphthalmology and Visual Health Research

The DOI matches its Crossref record.

Effectiveness of Teleretinal Imaging–Based Hospital Referral Compared With Universal Referral in Identifying Diabetic Retinopathy: A Cluster Randomized Clinical Trial

Open access

Abstract

Importance: Studies in high-income countries provide limited evidence from randomized clinical trials on the benefits of teleretinal screening to identify diabetic retinopathy (DR). Objective: To evaluate the effectiveness of teleretinal-screening hospital referral (TR) compared with universal hospital referral (UR) in people with diabetes. Design, Setting, and Participants: A cluster randomized clinical trial of 8 diabetes clinics within 10 km from Aravind Eye Hospital (AEH), Madurai, India, was conducted. Participants included 801 patients older than 50 years. The study was conducted from May 21, 2014, to February 7, 2015; data analysis was performed from March 12 to June 16, 2015. Interventions: In the TR cohort, nonmydriatic, 3-field, 45° retinal images were remotely graded by a retinal specialist and patients with DR, probable DR, or ungradable images were referred to AEH for a retinal examination. In the UR cohort, all patients were referred for a retinal examination at AEH. Main Outcomes and Measures: Hospital-diagnosed DR. Results: Of the 801 participants, 401 were women (50.1%) (mean [SD] age, 60.0 [7.3] years); mean diabetes duration was 8.6 (6.6) years. In the TR cohort, 96 of 398 patients (24.1%) who underwent teleretinal imaging were referred with probable DR (53 [13.3%]) or nongradable images (43 [10.8%]). Hospital attendance at AEH was proportionately higher with TR (54 of 96 referred [56.3%]) compared with UR (150 of 400 referred [37.5%]). The intention-to-treat analysis based on all patients eligible for referral in each arm showed that proportionately more patients with TR (36 of 96 [37.5]%) were diagnosed with DR compared with UR (50 of 400 [12.5%]) (unadjusted risk ratio [RR], 3.00; 95% CI, 2.01-4.48). These results were little changed by inclusion of covariates (RR, 2.72; 95% CI, 1.90-3.91). The RR was lower in the per-protocol analysis based on all patients who adhered to referral (covariate-adjusted RR, 1.75; 95% CI, 1.12-2.74). Diagnoses of DR were predominantly mild or moderate nonproliferative DR (36 in TR and 43 in UR). In the UR arm, there were 4 cases of severe nonproliferative DR and 2 cases of proliferative DR. Age (RR, 0.98; 95% CI, 0.95-0.99), female sex (RR, 0.79; 95% CI, 0.64-0.98), and hypertension diagnosis (RR, 0.81; 95% CI, 0.68-0.95) were factors associated with lower attendance. Those with higher secondary educational level or more were twice as likely to attend (RR, 2.00; 95% CI, 1.32-3.03). Conclusions and Relevance: The proportionate yield of DR cases was higher in the TR arm, confirming the potential benefit, at least in the setting of eye hospitals in India, of a targeted referral approach using teleretinal screening to identify patients with DR. Trial Registration: ClinicalTrials.gov identifier: NCT02085681.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1001/jamaophthalmol.2019.1070

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Most included studies employed cross-sectional designs (n = 27), while three adopted clinical trials.

    “Most employed cross-sectional designs (n = 27), while three adopted clinical trials [24, 29, 32].”
  • Remote grading of retinal images was widely utilized, with 18 out of 30 studies relying on this approach.

    “Remote grading of retinal images is widely utilized, with 18 out of 30 studies relying on this approach [10, 15, 16, 18, 21–27, 29–35, 37]”
  • Among 14 studies conducted in tertiary hospitals or specialized clinics, most adopted a cross-sectional design; two employed randomized controlled trials and one was a validation study.

    “Among the 14 studies conducted in tertiary hospitals or specialized clinics, most adopted a cross-sectional design. Two studies (Joseph et al. [24] and Mathenge et al. [32]) employed randomized controlled trials (RCTs), while Begum et al. [31] conducted a validation study.”
  • Mydriasis was employed in 17 out of 30 studies, while the remainder used non-mydriatic techniques when clinically appropriate.

    “Mydriasis was employed in 17/30 studies, while the remainder used non-mydriatic techniques when clinically appropriate [9, 12, 18, 22, 24, 27, 33, 35, 36].”
  • The predominant method for managing remotely graded images was store and forward (14 out of 30 studies), with seven studies adopting real-time processing.

    “The predominant method for managing these remotely graded images is ‘store and forward’ (14 out of 30 studies) [15, 16, 18, 22–24, 26–30, 33, 35, 37], with seven studies adopting the ‘real-time’ processing method [8, 10, 11, 25, 31, 32, 34]”

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

No references could be resolved yet.

Research works printed but not linked: 33

  1. Anjana, 2011, Prevalence of diabetes and prediabetes (impaired fasting glucose and/or impaired glucose tolerance) in urban and rural India: phase I results of the Indian Council of Medical Research-INdia DIABetes (ICMR-INDIAB) study., Diabetologia, 54, 3022, 10.1007/s00125-011-2291-5 · DOI
  2. Namperumalsamy, 2009, Prevalence and risk factors for diabetic retinopathy: a population-based assessment from Theni District, south India., Br J Ophthalmol, 93, 429
  3. Raman, 2009, Prevalence of diabetic retinopathy in India: Sankara Nethralaya Diabetic Retinopathy Epidemiology and Molecular Genetics Study report 2., Ophthalmology, 116, 311, 10.1016/j.ophtha.2008.09.010 · DOI
  4. Rani, 2009, Risk factors for diabetic retinopathy in self-reported rural population with diabetes., J Postgrad Med, 55, 92, 10.4103/0022-3859.48787 · DOI
  5. Rema, 2005, Prevalence of diabetic retinopathy in urban India: the Chennai Urban Rural Epidemiology Study (CURES) eye study, I., Invest Ophthalmol Vis Sci, 46, 2328, 10.1167/iovs.05-0019 · DOI
  6. Sunita, 2017, Prevalence of diabetic retinopathy in urban slums: the Aditya Jyot Diabetic Retinopathy in Urban Mumbai Slums Study—report 2., Ophthalmic Epidemiol, 24, 303, 10.1080/09286586.2017.1290258 · DOI
  7. Jonas, 2013, Prevalence and associated factors of diabetic retinopathy in rural central India., Diabetes Care, 36, e69, 10.2337/dc12-2377 · DOI
  8. Nadarajan, 2017, Prevalence of diabetic retinopathy and its associated factors in a rural area of Villupuram District of Tamil Nadu, India., J Clin Diagn Res, 11, LC23
  9. Gadkari, 2016, Prevalence of diabetic retinopathy in India: the All India Ophthalmological Society Diabetic Retinopathy Eye Screening Study 2014., Indian J Ophthalmol, 64, 38, 10.4103/0301-4738.178144 · DOI
  10. Namperumalsamy, 2003, Developing a screening program to detect sight-threatening diabetic retinopathy in South India., Diabetes Care, 26, 1831, 10.2337/diacare.26.6.1831 · DOI · Paper page
  11. Raman, 2016, Diabetic retinopathy: an epidemic at home and around the world., Indian J Ophthalmol, 64, 69, 10.4103/0301-4738.178150 · DOI
  12. Namperumalsamy, 2004, A pilot study on awareness of diabetic retinopathy among non-medical persons in South India: the challenge for eye care programmes in the region., Indian J Ophthalmol, 52, 247
  13. Gilbert, 2016, Eye care infrastructure and human resources for managing diabetic retinopathy in India: The India 11-city 9-state study., Indian J Endocrinol Metab, 20, S3, 10.4103/2230-8210.179768 · DOI
  14. Das, 2016, Telemedicine in diabetic retinopathy: access to rural India., Indian J Ophthalmol, 64, 84, 10.4103/0301-4738.178151 · DOI
  15. Mohan, 2014, Tele-diabetology to screen for diabetes and associated complications in rural India: The Chunampet Rural Diabetes Prevention Project Model., J Diabetes Sci Technol, 8, 256, 10.1177/1932296814525029 · DOI
  16. Conlin, 2006, Nonmydriatic teleretinal imaging improves adherence to annual eye examinations in patients with diabetes., J Rehabil Res Dev, 43, 733, 10.1682/JRRD.2005.07.0117 · DOI
  17. Crossland, 2016, Diabetic retinopathy screening and monitoring of early stage disease in Australian general practice: tackling preventable blindness within a chronic care model., J Diabetes Res, 2016, 8405395, 10.1155/2016/8405395 · DOI
  18. Davis, 2003, Telemedicine improves eye examination rates in individuals with diabetes: a model for eye-care delivery in underserved communities., Diabetes Care, 26, 2476, 10.2337/diacare.26.8.2476 · DOI
  19. Mansberger, 2013, Comparing the effectiveness of telemedicine and traditional surveillance in providing diabetic retinopathy screening examinations: a randomized controlled trial., Telemed J E Health, 19, 942, 10.1089/tmj.2012.0313 · DOI
  20. Mansberger, 2015, Long-term comparative effectiveness of telemedicine in providing diabetic retinopathy screening examinations: a randomized clinical trial., JAMA Ophthalmol, 133, 518, 10.1001/jamaophthalmol.2015.1 · DOI · Paper page
  21. World Medical Association, 2013, World Medical Association Declaration of Helsinki: ethical principles for medical research involving human subjects., JAMA, 310, 2191, 10.1001/jama.2013.281053 · DOI · Paper page
  22. Wilkinson, 2003, Proposed international clinical diabetic retinopathy and diabetic macular edema disease severity scales., Ophthalmology, 110, 1677, 10.1016/S0161-6420(03)00475-5 · DOI
  23. Guariguata, 2014, Global estimates of diabetes prevalence for 2013 and projections for 2035., Diabetes Res Clin Pract, 103, 137, 10.1016/j.diabres.2013.11.002 · DOI · Paper page
  24. Srinivasan, 2017, Diabetes and diabetic retinopathy: knowledge, attitude, practice (KAP) among diabetic patients in a tertiary eye care centre., J Clin Diagn Res, 11, NC01
  25. Raman, 2017, Incidence and progression of diabetic retinopathy in urban India: Sankara Nethralaya—Diabetic Retinopathy Epidemiology and Molecular Genetics Study (SN-DREAMS II), report 1., Ophthalmic Epidemiol, 24, 294, 10.1080/09286586.2017.1290257 · DOI
  26. Ting, 2016, Diabetic retinopathy: global prevalence, major risk factors, screening practices and public health challenges: a review., Clin Exp Ophthalmol, 44, 260, 10.1111/ceo.12696 · DOI · Paper page
  27. Tozer, 2015, Telemedicine and diabetic retinopathy: review of published screening programs., J Endocrinol Diabetes, 2, 1, 10.15226/2374-6890/2/4/00131 · DOI
  28. Liu, 2017, A randomised trial of non-mydriatic ultra-wide field retinal imaging versus usual care to screen for diabetic eye disease: rationale and protocol for the Clearsight trial., BMJ Open, 7, e015382, 10.1136/bmjopen-2016-015382 · DOI
  29. Gosheva, 2017, Quality and learning curve of handheld versus stand-alone non-mydriatic cameras., Clin Ophthalmol, 11, 1601, 10.2147/OPTH.S140064 · DOI
  30. Sengupta, 2018, Screening for vision-threatening diabetic retinopathy in South India: comparing portable non-mydriatic and standard fundus cameras and clinical exam., Eye (Lond), 32, 375, 10.1038/eye.2017.199 · DOI
  31. Ryan, 2015, Comparison Among Methods of Retinopathy Assessment (CAMRA) Study: smartphone, nonmydriatic, and mydriatic photography., Ophthalmology, 122, 2038, 10.1016/j.ophtha.2015.06.011 · DOI
  32. 2005, Recommendations on Prevention of Blindness from Diabetes Mellitus: report of a WHO consultation
  33. DeyS, NambiarD, LakshmiJK, SheikhK, ReddyKS. Health of the elderly in India: challenges of access and affordability. https://www.ncbi.nlm.nih.gov/books/NBK109208/. Published 2012. Accessed January 14, 2018.

Cited by

Sorted by citations

Metadata

Authors
Joseph, S., Kim, R., Ravindran, R. D., Fletcher, A. E., & Ravilla, T. D.
Affiliations
  • Aravind Eye Hospital (IN)
  • Aravind Eye Care System, Madurai, India
  • London School of Hygiene & Tropical Medicine (GB)
Corresponding author
Ravilla, Thulasiraj D.
Venue
JAMA Ophthalmology
Published
2019-07-01
Volume
137
Issue
7
Pages
786
ISSN
2168-6165 (ISSN-L)
OpenAlex
W2944755366
Cited by
34
References
0
Citations by year
2026: 4 · 2025: 5 · 2024: 4 · 2023: 3 · 2022: 5 · 2021: 10 · 2020: 3
FWCI
2.97
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • JAMA Ophthalmology (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Greater South Information System
Funders
Wellcome Trust (WT097685MF)
Topics
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Retinal Imaging and Analysis
  • Health Sciences › Medicine › Ophthalmology › Retinal Diseases and Treatments
  • Health Sciences › Medicine › Ophthalmology › Ophthalmology and Visual Health Research
Keywords
diabetic retinopathy, retinal screening, hospital referral, diabetes mellitus, older adults, screening effectiveness, hospital visits, India, Madurai, Aravind Eye Hospital, diabetes clinic, retinal examination, health care utilization, quality of life, cost-effectiveness
MeSH terms
Aged, Ambulatory Care Facilities, Diabetic Retinopathy, Diagnostic Imaging, Diagnostic Tests, Routine, Female, Humans, India, Male, Middle Aged, Referral and Consultation, Vision Screening, Program Evaluation, Cluster Analysis, Odds Ratio, Telemedicine

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review