Evidence map›Paper›PMID 39741912›Full record

ArticleJournal of experimental orthopaedics2025

Assessing ChatGPT responses to common patient questions regarding total ankle arthroplasty.

Elena Artioli, Francesca Veronesi, Antonio Mazzotti, Silvia Brogini, Simone Ottavio Zielli, Gianluca Giavaresi, Cesare Faldini

Registry-linked trialAbstract read
In one paragraph

Article in Journal of experimental orthopaedics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07012577 (Observational Study on the Accuracy and Completeness of General Artificial Intelligence in the Diagnosis and Therapeutic Recommendations for Failed or Painful Total Hip Arthroplasty), which is not on this map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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.

NCT07012577 completednot on this map

Observational Study on the Accuracy and Completeness of General Artificial Intelligence in the Diagnosis and Therapeutic Recommendations for Failed or Painful Total Hip Arthroplasty

TypeobservationalSponsorIstituto Ortopedico RizzoliRan2025 to 2025Enrolled20ConditionsTotal Hip Arthroplasty (THA)ArmsGPT-4 Assessment, Arthroplasty Fellow Assessment, Specializing Resident (4th year) Assessment, Junior Resident (3rd year) Assessment
3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Review
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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.

Elena Artioli1st Orthopaedics and Traumatologic Clinic, IRCCS Istituto Ortopedico Rizzoli Bologna Italy.
Francesca VeronesiSurgical Sciences and Technologies, IRCCS Istituto Ortopedico Rizzoli Bologna Italy.ORCID 0000-0002-6750-9376
Antonio Mazzotti1st Orthopaedics and Traumatologic Clinic, IRCCS Istituto Ortopedico Rizzoli Bologna Italy.
Silvia BroginiSurgical Sciences and Technologies, IRCCS Istituto Ortopedico Rizzoli Bologna Italy.
Simone Ottavio Zielli1st Orthopaedics and Traumatologic Clinic, IRCCS Istituto Ortopedico Rizzoli Bologna Italy.
Gianluca GiavaresiSurgical Sciences and Technologies, IRCCS Istituto Ortopedico Rizzoli Bologna Italy.
Cesare Faldini1st Orthopaedics and Traumatologic Clinic, IRCCS Istituto Ortopedico Rizzoli Bologna Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Artificial Intelligence is becoming increasingly integrated into healthcare, making it essential to assess its potential as a reliable information source for patient queries in the ambit of orthopaedic surgery. In literature, it is being employed in foot and ankle surgery and total hip arthroplasty. The aim of the present study was to evaluate the ability of Chat Generative Pretrained Transformer (ChatGPT) version 3.5 to give accurate, complete and comprehensive responses to the most common questions which are usually asked by the patient to the surgeon regarding total ankle arthroplasty. Methods: Ten most common questions were selected by two ankle surgeons and then ChatGPT was used to answer these questions. The responses were analyzed using an accuracy score and the modified DISCERN score to assess clarity. WordCalc software package (educational-level indices) was used to assess the readability of the responses. Results: Most of ChatGPT's responses were considered excellent not requiring clarification or satisfactory requiring minimal clarification. Indeed, the accuracy score was 2, suggesting that the overall responses were satisfactory requiring minimal clarification, and DISCERN score mean was 51, which is considered good-fair. Conclusions: ChatGPT demonstrates potential as a tool for responding to common patient questions related to total ankle arthroplasty, offering clear and mostly accurate information. While its current performance is based on the available literature, ongoing advancements in artificial intelligence may further enhance its utility in healthcare communication. However, further studies are required to evaluate its role more precisely in patient information and clinical settings. Levels of Evidence: Not applicable.

Indexed as

artificial intelligenceChatGPTtotal ankle arthroplasty

Identifiers

PMID39741912
PMCPMC11685840

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Registered trials

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.