Evidence map›Paper›PMID 42247090›Full record

ArticleIrish journal of medical science2026

Evaluation of the quality of information provided by ChatGPT on distal biceps repair surgery.

Conor J Kilkenny, Sean P Whealan, Danilo Vukanic, Alex Stapleton, Kieran O'Sullivan, Eoghan T Hurly, Diarmuid C Molony

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Article in Irish journal of medical science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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.

Conor J KilkennyRCSI: RCSI Dublin, Dublin, Ireland. conorkilkenny@rcsi.ie.
Sean P WhealanRCSI: RCSI Dublin, Dublin, Ireland.
Danilo VukanicRCSI: RCSI Dublin, Dublin, Ireland.
Alex StapletonRCSI: RCSI Dublin, Dublin, Ireland.
Kieran O'SullivanRCSI: RCSI Dublin, Dublin, Ireland.
Eoghan T HurlyRCSI: RCSI Dublin, Dublin, Ireland.
Diarmuid C MolonyRCSI: RCSI Dublin, Dublin, Ireland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDistal biceps tendon rupture is a rare injury, typically occurring during forceful, eccentric contraction of the biceps brachii muscle. This study aimed to assess the information AI software (ChatGPT) provides when searching for distal bicep injuries and their management. Using standardised scoring systems, we evaluated the quality of the information provided, its trustworthiness, and its readability.

methodsAn open AI model (ChatGPT) was used to answer 25 commonly asked questions from patients about distal biceps surgery. These answers were evaluated for medical accuracy, quality, and readability using the JAMA Benchmark criteria, DISCERN score, Flesch-Kincaid Reading Ease Score (FRES), and Grade Level (FKGL).

resultsThe JAMA Benchmark criteria score was 0, the lowest score, indicating no reliable resources cited. The DISCERN score was 44.3, which is considered a good score. The areas in the open AI model that did not achieve full marks were related to the lack of available source material used to compile the answers and, finally, some shortcomings with information not fully supported by the literature. The FRES was 38.5, and the FKGL was at a college reading level.

conclusionA high reading level was required to comprehend the information provided by ChatGPT about distal biceps repair, and the evidence supplied was of fair quality. With no citations provided, it remains unclear where these answers originate. However, ChatGPT continued to safety-net patients by encouraging the importance of further discussion with a surgeon. More high-quality sources that patients can easily comprehend are required to educate patients concerning distal bicep repair.

Indexed as

Artificial intelligenceChatGPTDistal biceps repairDistal biceps tendon rupturePatient educationReadability

Identifiers

PMID42247090

What OpenQuestion holds

Textmetadata
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.