ArticleFrontiers in digital health2025
Acute Achilles tendon rupture: how well can artificial intelligence chatbots answer patient inquiries?
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.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
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
Identifiers
What OpenQuestion holds
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.