Evidence map›Paper›PMID 38272554›Full record

ArticleBMJ open2024

Artificial intelligence-supported diabetic retinopathy screening in Tanzania: rationale and design of a randomised controlled trial.

Charles R Cleland, Covadonga Bascaran, William Makupa, Bernadetha Shilio, Frank A Sandi, Heiko Philippin, Ana Patricia Marques, Catherine Egan, Adnan Tufail, Pearse A Keane and 3 more

Open access · goldAbstract readClinical Trial Protocol
In one paragraph

Article in BMJ open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
5.7field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 14 citations in OpenAlex.

  1. Review
  2. Artificial intelligence in ophthalmology clinical trials: a narrative review.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2026
    Review
  3. Review
  4. Implementing an artificial intelligence system into a diabetic eye screening programme in Tanzania.Transactions of the Royal Society of Tropical Medicine and Hygiene · 2025
    Article
  5. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 6 institutions in 3 countries.

Charles R ClelandInternational Centre for Eye Health, London School of Hygiene & Tropical Medicine, London, UK charles.cleland@lshtm.ac.uk.ORCID 0000-0002-2761-8092
Covadonga BascaranInternational Centre for Eye Health, London School of Hygiene & Tropical Medicine, London, UK.
William MakupaEye Department, Kilimanjaro Christian Medical Centre, Moshi, Tanzania.
Bernadetha ShilioMinistry of Health, Community Development, Gender, Elderly and Children, Dodoma, Tanzania.
Frank A SandiDepartment of Ophthalmology, University of Dodoma School of Medicine and Nursing, Dodoma, Tanzania.ORCID 0000-0003-2073-2041
Heiko PhilippinInternational Centre for Eye Health, London School of Hygiene & Tropical Medicine, London, UK.ORCID 0000-0002-5380-6994
Ana Patricia MarquesInternational Centre for Eye Health, London School of Hygiene & Tropical Medicine, London, UK.ORCID 0000-0001-8242-7021
Catherine EganNational Institute for Health and Care Research (NIHR) Biomedical Research Centre (BRC) for Ophthalmology, University College London, Moorfields Hospital London NHS Foundation Trust and Institute of Ophthalmology, London, UK.
Adnan TufailNational Institute for Health and Care Research (NIHR) Biomedical Research Centre (BRC) for Ophthalmology, University College London, Moorfields Hospital London NHS Foundation Trust and Institute of Ophthalmology, London, UK.
Pearse A KeaneNational Institute for Health and Care Research (NIHR) Biomedical Research Centre (BRC) for Ophthalmology, University College London, Moorfields Hospital London NHS Foundation Trust and Institute of Ophthalmology, London, UK.
Alastair K DennistonNational Institute for Health and Care Research (NIHR) Biomedical Research Centre (BRC) for Ophthalmology, University College London, Moorfields Hospital London NHS Foundation Trust and Institute of Ophthalmology, London, UK.
David MacleodDepartment of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.
Matthew J BurtonInternational Centre for Eye Health, London School of Hygiene & Tropical Medicine, London, UK.
National Institute for Health Research · GBLondon School of Hygiene & Tropical Medicine · GBKilimanjaro Christian Medical Centre · TZMinistry of Health, Community Development, Gender, Elderly and Children · TZThe University of Dodoma · TZUniversity of Freiburg · DE

Funding

Medical Research Council MR/T019050/1Wellcome Trust
6 · The paper itself

Abstract

introductionGlobally, diabetic retinopathy (DR) is a major cause of blindness. Sub-Saharan Africa is projected to see the largest proportionate increase in the number of people living with diabetes over the next two decades. Screening for DR is recommended to prevent sight loss; however, in many low and middle-income countries, because of a lack of specialist eye care staff, current screening services for DR are not optimal. The use of artificial intelligence (AI) for DR screening, which automates the grading of retinal photographs and provides a point-of-screening result, offers an innovative potential solution to improve DR screening in Tanzania. METHODS AND ANALYSIS: We will test the hypothesis that AI-supported DR screening increases the proportion of persons with true referable DR who attend the central ophthalmology clinic following referral after screening in a single-masked, parallel group, individually randomised controlled trial. Participants (2364) will be randomised (1:1 ratio) to either AI-supported or the standard of care DR screening pathway. Participants allocated to the AI-supported screening pathway will receive their result followed by point-of-screening counselling immediately after retinal image capture. Participants in the standard of care arm will receive their result and counselling by phone once the retinal images have been graded in the usual way (typically after 2-4 weeks). The primary outcome is the proportion of persons with true referable DR attending the central ophthalmology clinic within 8 weeks of screening. Secondary outcomes, by trial arm, include the proportion of persons attending the central ophthalmology clinic out of all those referred, sensitivity and specificity, number of false positive referrals, acceptability and fidelity of AI-supported screening. ETHICS AND DISSEMINATION: The London School of Hygiene & Tropical Medicine, Kilimanjaro Christian Medical Centre and Tanzanian National Institute of Medical Research ethics committees have approved the trial. The results will be submitted to peer-reviewed journals for publication. TRIAL REGISTRATION NUMBER: ISRCTN18317152.

Indexed as

Diabetes MellitusDiabetic RetinopathyArtificial IntelligenceHumansMass ScreeningRandomized Controlled Trials as TopicSensitivity and SpecificityTanzaniaclinical trialdiabetic retinopathyophthalmologypublic health

Identifiers

PMID38272554
PMCPMC10824006
OpenAlexW4391235175

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.