ArticleCureus2024
Assessing the Efficacy of an AI-Powered Chatbot (ChatGPT) in Providing Information on Orthopedic Surgeries: A Comparative Study With Expert Opinion.
Article in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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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
8 citing papers in PubMed.
- Review
- Diagnostic Performance of Artificial Intelligence (AI) Chatbot Compared to Orthopedic Trauma Surgeons in Evaluating Indication for Surgery for Isolated Lateral Malleolar Fractures: a Retrospective Study.Acta chirurgiae orthopaedicae et traumatologiae Cechoslovaca · 2026Observational
- Applications of Artificial Intelligence in Pediatric Orthopaedics.Indian journal of orthopaedics · 2026Review
- Evaluation of ChatGPT-5.2 responses to frequently asked questions about benign bone tumors.Frontiers in oncology · 2026Article
- High patient and surgeon satisfaction with ChatGPT-generated responses to real patient questions regarding total knee arthroplasty.Journal of orthopaedic surgery and research · 2025Article
- A structured evaluation of LLM-generated step-by-step instructions in cadaveric brachial plexus dissection.BMC medical education · 2025Article
- Is it a pediatric orthopaedic urgency or not? Can ChatGPT answer this question?Journal of orthopaedic surgery and research · 2025Article
- Review
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background The use of artificial intelligence (AI) as a tool for patient care has continued to rapidly expand. The technology has proven its utility in various applications across several specialties in a variety of applications. However, its practicality in orthopedics remains widely unknown. This study seeks to determine if the open-access software Chat Generative Pre-Trained Transformer (ChatGPT) can be a reliable source of data for patients. Questions/purposes This study aims to determine: (1) Is the open-access AI software ChatGPT capable of accurately answering commonly posed patient questions? (2) Will there be a significant difference in agreement among the study experts in the answers generated by ChatGPT? Methods A standard list of questions for six different procedures across six subspecialties is posed to ChatGPT. The procedures chosen were anterior cruciate ligament (ACL) reconstruction, microdiscectomy, total hip arthroplasty (THA), rotator cuff repair, carpal tunnel release, and ankle fracture open reduction and internal fixation. The generated answers are then compared to expert opinion using a Likert scale based on the agreement of the aforementioned experts. Results On a three-point Likert scale with 1 being disagree and 3 being agree, the mean score across all subspecialties is 2.43, indicating at least partial agreement with expert opinion. There was no significant difference in the Likert scale mean across the six subspecialties surveyed (p = 0.177). Conclusions This study shows promise in using ChatGPT as an aid in answering patient questions regarding their surgical procedures. This opens doors for the use of the software by patients for understanding and increased shared decision-making with their surgeons. However, studies with larger participation groups are necessary to ensure accuracy on a larger and broader scale as well as studies involving specific application of AI within surgeon's practice.
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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.