Referral uptake after diabetic retinopathy screening with artificial intelligence-assisted care pathways: a systematic review and meta-analysis.

James A Leigh, Alex Sherrington, Angus R J Barber, Angus W Turner, Michael Kidd, John Powell, Catherine Pope

Abstract read

In one paragraph

Article in NPJ digital medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

James A LeighNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK. james.leigh@phc.ox.ac.uk.

Alex SherringtonLions Eye Institute, Lions Outback Vision, Nedlands, WA, Australia.

Angus R J BarberSchool of Biomedical Sciences, University of Western Australia, Crawley, WA, Australia.

Angus W TurnerLions Eye Institute, Lions Outback Vision, Nedlands, WA, Australia.

Michael KiddNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.

John PowellNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.

Catherine PopeNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.

Funding

Clarendon Fund Clarendon scholarshipRhodes Trust Rhodes scholarship

6 · The paper itself

Abstract

Artificial intelligence (AI) is an accurate screening tool for diabetic retinopathy (DR), the leading cause of blindness among working-aged adults. However, its impact on referral uptake is uncertain. We searched Embase, MEDLINE, Scopus, Web of Science and Cochrane Library databases from year 2000 to February 17, 2025. Randomised and non-randomised studies comparing referral uptake after AI-assisted DR screening versus standard of care were included. 2644 articles were identified, and six included for analysis. The relative risk of DR referral uptake with AI-assisted screening compared with the status quo was 1.89 (95% CI, 1.18, 3.03, I

Identifiers

PMID41998218

DOI10.1038/s41746-026-02616-3

PMCPMC13272687

What Socratic holds

Textmetadata

LicenceCC BY

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Registered trials

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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.