Evidence map›Paper›PMID 42633015›Full record

ArticleDigital health

ChatGPT as a source of surgical information: Evaluation of responses to patient questions on hallux rigidus fusion.

Kamil Balaban, Mehmet Batu Ertan, Mahmut Kalem

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Article in Digital health. 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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1 · What the graph read from it

What it found

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2 · The registry

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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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5 · Who and what money

Authors and funding

3 authors.

Kamil BalabanDepartment of Orthopedics and Traumatology, Ministry of Health Finike State Hospital, Antalya, Turkey.ORCID https://orcid.org/0000-0002-5179-2058
Mehmet Batu ErtanDepartment of Orthopedics and Traumatology, Atilim University School of Medicine, Ankara, Turkey.
Mahmut KalemDepartment of Orthopedics and Traumatology, Ankara University School of Medicine, Ankara, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Patients are increasingly turning to online resources and artificial intelligence (AI)-based tools to obtain information about orthopedic conditions and surgical options. Large language models, such as ChatGPT, are becoming prominent in patient education; however, their reliability and readability remain uncertain. This study evaluated the quality and readability of responses generated by ChatGPT-4o and ChatGPT-5 to frequently asked patient questions regarding hallux rigidus fusion surgery. Methods: Twenty commonly asked patient questions were compiled and presented to ChatGPT-4o and ChatGPT-5. Readability was assessed using the Flesch-Kincaid Grade Level, Gunning Fog, Coleman-Liau, and Simple Measure of Gobbledygook indices. Quality was evaluated with the DISCERN tool, response accuracy scores, and Journal of the American Medical Association (JAMA) criteria. Interrater agreement was measured using the Intraclass Correlation Coefficient (ICC). Results: ChatGPT-4o generated longer responses (802 vs. 242 words; p<0.001) with slightly higher readability grade levels (10.81 vs. 10.37; p=0.031). Accuracy (2.00 vs. 1.85; p=0.323) and DISCERN scores (49.35 vs. 48.93; p=0.747) showed no significant differences. All responses received a JAMA score of 0 due to the absence of citations, authorship, or transparency indicators. Interrater reliability indicated moderate to good agreement (ICC: 0.68-0.80). Conclusion: ChatGPT-4o and ChatGPT-5 provide generally satisfactory yet non-comprehensive, limited-quality information at a level above tenth-grade regarding hallux rigidus fusion surgery. Although linguistically coherent, responses lack evidence-based detail and individualized guidance. These models may supplement, but cannot replace, expert orthopedic counseling. Ensuring physician oversight and integrating validated, updated clinical content remain essential for safe implementation of AI-generated patient information.

Indexed as

arthrodesisartificial intelligenceChatGPTfrequently asked questionshallux rigidusreadability

Identifiers

PMID42633015
PMCPMC13498785

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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.