Evidence map›Paper›PMID 40160854›Full record

ArticleFoot & ankle orthopaedics2025

ChatGPT-4 Effectively Responds to Common Patient Questions on Total Ankle Arthroplasty: A Surgeon-Based Assessment of AI in Patient Education.

Heidi C Ventresca, Harley T Davis, Chase W Gauthier, Justin Kung, Joseph S Park, Nicholas L Strasser, Tyler A Gonzalez, J Benjamin Jackson

Abstract read
In one paragraph

Article in Foot & ankle orthopaedics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

8 authors.

Heidi C VentrescaDepartment of Orthopaedic Surgery, School of Medicine, University of South Carolina, Columbia, SC, USA.ORCID https://orcid.org/0009-0003-1980-7621
Harley T DavisDepartment of Orthopaedic Surgery, Prisma Health-Midlands, Columbia, SC, USA.ORCID https://orcid.org/0009-0003-1980-7621
Chase W GauthierDepartment of Orthopaedic Surgery, School of Medicine, University of South Carolina, Columbia, SC, USA.ORCID https://orcid.org/0009-0004-4738-8468
Justin KungDepartment of Orthopaedic Surgery, School of Medicine, University of South Carolina, Columbia, SC, USA.ORCID https://orcid.org/0000-0003-2536-5076
Joseph S ParkDepartment of Orthopaedic Surgery, School of Medicine, University of Virginia, Charlottesville, VA, USA.
Nicholas L StrasserDepartment of Orthopaedic Surgery, School of Medicine, Vanderbilt University, Nashville, TN, USA.ORCID https://orcid.org/0000-0002-3454-2049
Tyler A GonzalezDepartment of Orthopaedic Surgery, Prisma Health-Midlands, Columbia, SC, USA.ORCID https://orcid.org/0000-0002-3210-8097
J Benjamin JacksonDepartment of Orthopaedic Surgery, School of Medicine, University of South Carolina, Columbia, SC, USA.ORCID https://orcid.org/0000-0002-9444-087X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Patient reliance on internet resources for clinical information has steadily increased. The recent widespread accessibility of artificial intelligence (AI) tools like ChatGPT has increased patient reliance on these resources while also raising concerns about the accuracy, reliability, and appropriateness of the information they provide. Previous studies have evaluated ChatGPT and found it could accurately respond to questions on common surgeries, such as total hip arthroplasty, but is untested for uncommon procedures like total ankle arthroplasty (TAA). This study evaluates ChatGPT-4's performance in answering patient questions on TAA and further explores the opportunity for physician involvement in guiding the implementation of this technology. Methods: Twelve commonly asked patient questions regarding TAA were collated from established sources and posed to ChatGPT-4 without additional input. Four fellowship-trained surgeons independently rated the responses using a 1-4 scale, assessing accuracy and need for clarification. Interrater reliability, divergence, and trends in response content were analyzed to evaluate consistency across responses. Results: The mean score across all responses was 1.8, indicating an overall satisfactory performance by ChatGPT-4. Ratings were consistently good on factual questions, such as infection risk and success rates, whereas questions requiring nuanced information, such as postoperative protocols and prognosis, received poorer ratings. Significant variability was observed among surgeons' ratings and between questions, reflecting differences in interpretation and expectations. Conclusion: ChatGPT-4 demonstrates its potential to reliably provide discrete information for uncommon procedures such as TAA, but it lacks the capability to effectively respond to questions requiring patient- or surgeon-specific insight. This limitation, paired with the growing reliance on AI, highlights the need for AI tools tailored to specific clinical practices to enhance accuracy and relevance in patient education.

Indexed as

accuracyartificial intelligenceChatGPTpatient educationpatient questionstotal ankle arthroplasty

Identifiers

PMID40160854
PMCPMC11951880

What OpenQuestion holds

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LicenceCC BY-NC
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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 OpenQuestion graph.