Evidence map›Paper›PMID 40678718›Full record

ArticleFrontiers in digital health2025

Acute Achilles tendon rupture: how well can artificial intelligence chatbots answer patient inquiries?

Wojciech K Dzieza, Hailey Hampton, Kevin W Farmer, Ryan P Roach, John Y Kwon, Ahmet Toygun Yildirim, MaryBeth Horodyski, Rull James Toussaint

Abstract read
In one paragraph

Article in Frontiers in digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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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

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Wojciech K DziezaDepartment of Orthopaedic Surgery and Sports Medicine, College of Medicine, University of Florida, Gainesville, FL, United States.
Hailey HamptonDepartment of Orthopaedic Surgery and Sports Medicine, College of Medicine, University of Florida, Gainesville, FL, United States.
Kevin W FarmerDepartment of Orthopaedic Surgery and Sports Medicine, College of Medicine, University of Florida, Gainesville, FL, United States.
Ryan P RoachDepartment of Orthopaedic Surgery and Sports Medicine, College of Medicine, University of Florida, Gainesville, FL, United States.
John Y KwonDepartment of Orthopaedic Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States.
Ahmet Toygun YildirimDepartment of Orthopaedic Surgery and Sports Medicine, College of Medicine, University of Florida, Gainesville, FL, United States.
MaryBeth HorodyskiDepartment of Orthopaedic Surgery and Sports Medicine, College of Medicine, University of Florida, Gainesville, FL, United States.
Rull James ToussaintDepartment of Orthopaedic Surgery and Sports Medicine, College of Medicine, University of Florida, Gainesville, FL, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: Artificial intelligence (AI) chatbots have gained popularity as a source of information that is easily accessed by patients. The best treatment of acute Achilles tendon ruptures (AATR) remains controversial due to varying surgical repair techniques, postoperative protocols, nonoperative treatment options, and surgeon and patient factors. Given that patients will continue to turn towards AI for answers to medical questions, the purpose of this study is to evaluate whether popular AI engines can provide adequate responses to frequently asked questions regarding AATR. Methods: Three AI engines (ChatGPT, Google Gemini, and Microsoft Copilot) were prompted for a concise response to ten common questions regarding AATR management. Four board-certified orthopaedic surgeons were asked to assess the responses using a four-point scale. A Kruskal-Wallis test was used to compare the responses between the three AI systems using the scores assigned by the surgeons. Results: All three engines provided comparable answers to 7 of 10 questions (70%). Significant differences were noted between the AI systems for three of the ten questions (Question 4, overall Conclusions: AI chatbots can appropriately answer concise prompts about diagnosis and management of AATR. The responses provided by the three AI chatbots analyzed in our study were largely uniform and satisfactory, with only one of the engines scoring lower on three of the ten questions. As AI engines advance, they will become an important tool for patient education in orthopaedics.

Indexed as

Achilles tendon ruptureartificial intelligencechatbotChatGPTCopilotGeminipatient education

Identifiers

PMID40678718
PMCPMC12267169

What OpenQuestion holds

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LicenceCC BY
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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.