Evidence map›Paper›PMID 40475332›Full record

ArticleJournal of hand and microsurgery2025

Comparison of hand surgery certification exams in Europe and the United States using ChatGPT 4.0.

Salman Hasan, Kyros Ipaktchi, Nicolas Meyer, Philippe Liverneaux

Abstract read
In one paragraph

Article in Journal of hand and microsurgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Salman HasanDepartment of Hand Surgery, Strasbourg University Hospitals, FMTS, 1 Avenue Molière, 67200, Strasbourg, France.
Kyros IpaktchiDepartment of Hand, Upper Extremity & Microvascular Surgery, Dept. of Orthopaedic Surgery, Denver Health Medical Center, 777 Bannock Street, Denver, CO, 80204, USA.
Nicolas MeyerDepartment of Public Health, Strasbourg University Hospital, GMRC, 67091, Strasbourg, France.
Philippe LiverneauxDepartment of Hand Surgery, Strasbourg University Hospitals, FMTS, 1 Avenue Molière, 67200, Strasbourg, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Certification in hand surgery in Europe (EBHS) and the United States (HSE) requires a subspecialty examination. These exams differ in format, and practice exams, such as those published by the Journal of Hand Surgery (European Volume) and the ASSH, are used for preparation. This study aimed to compare the difficulty of the multiple-choice questions (MCQs) for the EBHS and HSE practice exams under the assumption that European MCQs are more challenging. ChatGPT 4.0 answered 94 MCQs (34 EBHS and 60 HSE practice exams) across five attempts. We excluded MCQs with visual aids. Performance was analyzed both quantitatively (overall and by section) and qualitatively. ChatGPT's scores improved after being provided with correct answers, from 59 % to 71 % for EBHS and 97 % for HSE practice exams by the 5th attempt. The European MCQs proved more difficult, with limited progress (<50 % accuracy up to the 5th attempt), while ChatGPT demonstrated better learning with the HSE questions. The complexity of the European MCQs raises questions about the harmonization of certification standards. ChatGPT can help standardize evaluations, though its performance remains inferior to that of humans. The findings confirm the hypothesis that EBHS MCQs are more challenging than the HSE practice exam. Level of evidence: Exploratory study, level of evidence IV.

Indexed as

Artificial intelligenceChatGPTEBHSHand surgeryHSEMCQsMedical education

Identifiers

PMID40475332
PMCPMC12133689

What OpenQuestion holds

Textmetadata
Read underepoch 390

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 OpenQuestion graph.