Evidence map›Paper›PMID 42364201›Full record

ArticleActa orthopaedica et traumatologica turcica2026

Evaluation of surgical recommendation algorithms in hallux valgus cases using ChatGPT models: an artificial intelligence approach based on 50 simulated scenarios.

Ömer Levent Karadamar, Ali Aydilek

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Article in Acta orthopaedica et traumatologica turcica, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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2 authors.

Ömer Levent Karadamar
Ali Aydilek

Funding

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6 · The paper itself

Abstract

objectiveThe integration of large language models (LLMs) into orthopedic surgical decision-making represents a growing area of research. This study aimed to compare the surgical recommendation capabilities of ChatGPT-4.0, ChatGPT-4o, and ChatGPT-5 models in simulated cases of hallux valgus deformity.

methodsA total of 50 simulated cases were constructed using fundamental clinical data related to hallux valgus pathology and were individually submitted to 3 models. For each case, a surgical recommendation and a brief rationale were obtained. The responses were compared based on content alignment, adequacy of justification, and consistency with established surgical algorithms. Additionally, textual outputs were evaluated using DISCERN and multiple readability indices.

resultsAll 3 models demonstrated overall algorithmic consistency. However, the ChatGPT-5 model provided the most context-aware and clinically consistent recommendations, followed by ChatGPT-4o and ChatGPT-4.0. Concordance rates with surgical algorithms were 70% for ChatGPT-4.0, 82% for ChatGPT-4o, and 90% for ChatGPT-5. DISCERN scores were 51, 56, and 62, respectively. ChatGPT-5 also achieved superior performance across readability metrics, including Flesch Reading Ease Score, Simple Measure of Gobbledygook, and Gunning-Fog Index, indicating improved textual clarity and reduced complexity.

conclusionThe ChatGPT-5 model demonstrated the highest contextual accuracy, consistency, and readability in surgical decision support for hallux valgus surgery, highlighting the progressive improvements of newer LLMs. Nonetheless, ChatGPT-4.0 and ChatGPT-4o also exhibited compatibility with surgical algorithms, indicating potential utility in generating patient education and informational content.   Cite this article as: Karadamar ÖL, Aydilek A. Evaluation of surgical recommendation algorithms in hallux valgus cases using ChatGPT models: an artificial intelligence approach based on 50 simulated scenarios. Acta Orthop Traumatol Turc. 2026; 60(2), 0580, doi: 10.5152/j.aott.2026.25580.

Indexed as

AlgorithmsArtificial IntelligenceClinical Decision-MakingHallux ValgusOrthopedic ProceduresGenerative Artificial IntelligenceHumansLarge Language Models

Identifiers

PMID42364201
PMCPMC13295165

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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.