Telemedicine and Artificial Intelligence for Retinopathy of Prematurity Screening in Low-Resource Settings: A Systematic Review and Meta-Analysis of Diagnostic Accuracy with Cost-Effectiveness Perspectives
DOI:
https://doi.org/10.37275/cmej.v7i2.953Keywords:
Artificial intelligence, Cost-benefit analysis, Retinopathy of prematurity, Sensitivity and specificity, TelemedicineAbstract
Background: Screening for retinopathy of prematurity (ROP) in low- and middle-income countries (LMICs) is limited by the shortage of trained examiners.
Objective: We assessed the diagnostic accuracy of telemedicine and artificial intelligence (AI) for ROP screening in LMICs and summarised economic evaluations of screening.
Methods: PubMed, Europe PMC, OpenAlex and Scopus were searched for accuracy studies from LMICs comparing remote grading of retinal images (telemedicine) or AI with ophthalmoscopy or expert grading, and for economic evaluations. Sensitivity and specificity were pooled with bivariate random-effects models; risk of bias was assessed with QUADAS-2 and certainty with GRADE.
Results: Twenty-four accuracy studies from nine countries and 13 economic evaluations were included. For clinically significant ROP, telemedicine (6 datasets; 927 units) had a sensitivity of 92.8% (95% CI 82.6–97.3) and a specificity of 95.8 (87.6–98.7)%; AI (6 datasets; 7,346 units) had a sensitivity of 93.0 (81.5–97.6)% and a specificity of 77.3 (55.6–90.3)%. Specificity was higher in upper-middle-income settings. For any-stage ROP and plus disease, pooled sensitivities were 92.2% and 81.4%, and specificities 97.6% and 99.1%. Fifteen studies were at high risk of bias, and certainty was low to very low. Telemedicine was cost-effective in all five cost-utility analyses; no economic evaluation of AI from LMICs was found.
Conclusion: Telemedicine detected clinically significant ROP with high sensitivity and specificity and was cost-effective in LMICs, although the certainty of evidence was low. AI achieved similar sensitivity with more false-positive referrals; its use as a triage step within telemedicine programmes requires prospective evaluation.
Authors
- I Wayan Eka Sutyawan1
- Ni Made Ayu Surasmiati1
- Ivana Beatrice Alberta2*
- Calvin Prasetio2
- 1Pediatric Ophthalmology and Strabismus Division, Department of Ophthalmology, Faculty of Medicine, Universitas Udayana, Denpasar, Indonesia
- 2Resident of Ophthalmology, Faculty of Medicine, Universitas Udayana, Denpasar, Indonesia
Corresponding author Ivana Beatrice Alberta — ivanabeatricealberta@gmail.com
Downloads
Published
Issue
Section
License
Copyright (c) 2026 I Wayan Eka Sutyawan, Ni Made Ayu Surasmiati, Ivana Beatrice Alberta, Calvin Prasetio
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
As our aim is to disseminate original research article, hence the publishing right is a necessary one. The publishing right is needed in order to reach the agreement between the author and publisher. As the journal is fully open access, the authors will sign an exclusive license agreement.
The authors have the right to:
- Share their article in the same ways permitted to third parties under the relevant user license.
- Retain copyright, patent, trademark and other intellectual property rights including research data.
- Proper attribution and credit for the published work.
For the open access article, the publisher is granted to the following right.
- The non-exclusive right to publish the article and grant right to others.
- For the published article, the publisher applied for the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
How to Cite
Article Metrics
Views and downloads recorded by this journal.
