Evidence mapPaperPMID 41339829Full record

ArticleBMC public health2025

Diabetic retinopathy screening model in low and middle-income countries: a scoping review.

Yeni Dwi Lestari, Ratna Sitompul, Indah Suci Widyahening, Dicky Levenus Tahapary, Prasandhya Astagiri Yusuf, Muhammad Bayu Sasongko, Pandu Riono, Yosilia Nursakina, Gratcheva Alexandra

Abstract readScoping Review
In one paragraph

Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
field-weighted citation impact
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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
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

9 authors.

Yeni Dwi LestariDoctoral Program in Medical Sciences, Faculty of Medicine, Universitas Indonesia, Jakarta, Indonesia. yeni2lestari@yahoo.com.
Ratna SitompulDepartment of Ophthalmology, Faculty of Medicine, Universitas Indonesia Dr. Cipto Mangunkusumo Hospital, Jakarta, Indonesia.
Indah Suci WidyaheningDepartment of Community Medicine, Faculty of Medicine, Universitas Indonesia, Jakarta, Indonesia.
Dicky Levenus TahaparyDr. Cipto Mangunkusumo General Hospital, Jakarta, Indonesia.
Prasandhya Astagiri YusufMedical Technology Cluster Institute of Medical Education and Research Indonesia, Faculty of Medicine, Universitas Indonesia, Jakarta, Indonesia.
Muhammad Bayu SasongkoDepartment of Ophthalmology, Faculty of Medicine Public Health and Nursing, University of Gadjah Mada, Yogyakarta, Indonesia.
Pandu RionoDepartment of Epidemiology, Faculty of Public Health, Universitas Indonesia, Depok, Indonesia.
Yosilia NursakinaSchool of Public Health, Imperial College London, South Kensington, UK.
Gratcheva AlexandraFaculty of Medicine, Gadjah Mada University, Yogyakarta, Indonesia.

Funding

Universitas Indonesia NKB-294/UN2.RST/HKP.05.00/2024
6 · The paper itself

Abstract

backgroundDiabetic retinopathy (DR), a leading cause of blindness in working-age adults, disproportionately affects low- and middle-income countries (LMICs). While preventable through early intervention, DR screening programs are often lacking in these resource-constrained settings.

objectiveThis scoping review examines DR screening models implemented in LMICs, identifying evidence, research gaps, and potential improvement strategies.

methodsA literature search across multiple databases identified studies on DR screening in LMICs, limited to peer-reviewed articles from the past 20 years focusing on DR screening model effectiveness or implementation. Key data (study design, screening techniques, outcomes) were extracted and synthesized narratively.

resultsThis review synthesized 30 studies on DR screening in LMICs, mainly from India, South Africa, Pakistan, and Bangladesh. These studies explored diverse screening methods, from traditional techniques (ophthalmoscopy, funduscopy, slit lamp exams) to telemedicine and AI. Non-mydriatic fundus photography, often with AI-assisted grading, was common, as were remote grading and store-and-forward systems. Given the resource constraints in these settings, non-mydriatic methods were often preferred. Many studies optimized resources by training non-physicians for image acquisition, followed by specialist grading. The reviewed studies highlighted the effectiveness of community-based screening programs in expanding coverage and improving patient adherence. Furthermore, they demonstrated the cost-effectiveness of smartphone-based imaging devices and AI-driven systems. However, challenges remained, including limited infrastructure, inconsistent training, and follow-up difficulties.

conclusionsLMIC DR screening utilizes traditional and innovative technologies, with community-based approaches, telemedicine, and AI enhancing reach and accuracy. Transitioning from case-finding to population-based screening requires stronger diabetes surveillance and integration within primary care.

Indexed as

Developing CountriesDiabetic RetinopathyMass ScreeningHumansTelemedicineDiabetesDiabetic retinopathyLow and middle-income country (LMIC)Screening

Identifiers

PMID41339829
PMCPMC12676764

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.