Evidence map›Paper›PMID 41323534›Full record

ArticleJournal of experimental orthopaedics2025

ChatGPT provides high-quality answers to FAQs about high tibial osteotomy despite low inter-rater agreement.

Serhat Akcaalan, Yavuz Şahbat, Glauco Loddo, Tunay Erden, Baris Kocaoglu

Abstract 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. 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

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

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

5 authors.

Serhat AkcaalanDepartment of Orthopaedics and Traumatology Ankara Bilkent City Hospital Ankara Turkey.ORCID https://orcid.org/0000-0001-7350-6422
Yavuz ŞahbatDepartment of Orthopaedics and Traumatology Istinye University Bahcesehir Liv Hospital Istanbul Turkey.ORCID https://orcid.org/0000-0002-9963-5334
Glauco LoddoDepartment of Orthopaedics and Traumatology Alessandria AOU SS Antonio e Biagio e Cesare Arrigo Alessandria Italy.
Tunay ErdenFIFA Medical Center of Excellence Acıbadem Fulya Hospital Sports Medicine Center Istanbul Turkey.ORCID https://orcid.org/0000-0002-0926-5879
Baris KocaogluDepartment of Orthopedics and Traumatology, Faculty of Medicine Acibadem Mehmet Ali Aydinlar University Istanbul Turkey.ORCID https://orcid.org/0000-0002-2537-0660

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: High tibial osteotomy (HTO) is frequently used to treat knee malalignment in younger patients. Given the rise in online health information-seeking behaviour, this study aimed to evaluate the quality of ChatGPT-generated responses to frequently asked questions (FAQs) about HTO and to assess the reliability of two scoring systems used by orthopaedic surgeons. Methods: Twenty-four FAQs were submitted to ChatGPT (GPT-4-turbo). Four orthopaedic surgeons independently rated the responses at two time points using: (1) a 4-point categorical scale (1 = excellent, 4 = poor), and (2) a 100-point numerical scale (0 = worst, 100 = best). Intra-observer reliability was assessed using weighted kappa ( Results: Most responses were rated positively, with over 70% considered 'excellent' or requiring minimal clarification. Intra-observer agreement was variable, ranging from Conclusion: ChatGPT responses to HTO-related FAQs were rated as high quality by most evaluators. However, the low inter-observer agreement highlights the need for standardised evaluation tools and suggests that expert oversight remains essential when integrating AI-generated content into patient education. Level of Evidence: Level V.

Indexed as

artificial intelligenceChatGPThigh tibial osteotomyscoring system

Identifiers

PMID41323534
PMCPMC12661211

What Socratic holds

Textmetadata
Read underepoch 390

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 Socratic graph.