Evidence map›Paper›PMID 41541304›Full record

ArticleOrthopaedic journal of sports medicine2026

A Comparative Analysis of GPT-3.5, GPT-4, GPT-4 Omni, Gemini Advanced, and Gemini 1.5 in Answering Total Knee Replacement-Related Questions.

Hyobeom Lee, Ji-Sun Shin, Young Jin Seo, Seong Hyeon Kim, Jongryul Lee, Seung Yong Shin, Si Young Song

Abstract read
In one paragraph

Article in Orthopaedic journal of sports medicine, 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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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Hyobeom LeeDepartment of Orthopaedic Surgery, Center for Joint Diseases, Kyung Hee University Hospital at Gangdong, Seoul, Republic of Korea.
Ji-Sun ShinDepartment of Orthopaedic Surgery, Dongtan Sacred Heart Hospital, Hallym University College of Medicine, Hwaseong, Gyeonggi-do, Republic of Korea.
Young Jin SeoDepartment of Orthopaedic Surgery, Dongtan Sacred Heart Hospital, Hallym University College of Medicine, Hwaseong, Gyeonggi-do, Republic of Korea.
Seong Hyeon KimDepartment of Orthopaedic Surgery, Dongtan Sacred Heart Hospital, Hallym University College of Medicine, Hwaseong, Gyeonggi-do, Republic of Korea.
Jongryul LeeCollege of Medicine, Hallym University, Chuncheon, Gangwon-do, Republic of Korea.
Seung Yong ShinDepartment of Orthopaedic Surgery, Dongtan Sacred Heart Hospital, Hallym University College of Medicine, Hwaseong, Gyeonggi-do, Republic of Korea.
Si Young SongDepartment of Orthopaedic Surgery, Dongtan Sacred Heart Hospital, Hallym University College of Medicine, Hwaseong, Gyeonggi-do, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Artificial intelligence (AI) chatbots are increasingly used for medical information provision. However, systematic evaluations of their accuracy and reliability in orthopaedic surgery, particularly in total knee replacement (TKR), remain limited. Purpose: To systematically compare and evaluate performances of various AI chatbots, focusing on their ability to provide accurate and reliable information related to TKR. Study Design: Cohort study; Level of evidence, 2. Methods: A total of 43 clinically relevant TKR-related frequently asked questions (FAQs) were selected based on Google search trends and expert consultation. Questions were categorized into 6 key domains: (1) general/procedure-related information, (2) indications and outcomes, (3) risks and complications, (4) pain and postoperative recovery, (5) specific activities after surgery, and (6) alternatives and variations. Each question was submitted to 5 different chatbot models (GPT-3.5, GPT-4, GPT-4 Omni, Gemini Advanced, and Gemini 1.5) for response generation. Two independent orthopaedic surgeons assessed the chatbot's responses for both accuracy and relevance using a 5-point Likert scale. Responses were anonymized, blinding evaluators to the chatbot identities to prevent bias. Accuracy differences among the chatbot models were analyzed by analysis of variance, and relevance was compared using the Kruskal-Wallis test. Results: GPT-3.5 (4.8 ± 0.5), GPT-4 (4.9 ± 0.4), GPT-4 Omni (4.9 ± 0.3), and Gemini 1.5 (4.8 ± 0.4) demonstrated high accuracy, whereas Gemini Advanced scored significantly lower (4.1 ± 1.4) ( Conclusion: This study demonstrates that GPT-3.5, GPT-4, GPT-4 Omni, and Gemini 1.5 can provide highly accurate and relevant responses to TKR-related queries, while Gemini Advanced underperforms.

Indexed as

artificial intelligencechatbotChatGPTGeminitotal knee replacement

Identifiers

PMID41541304
PMCPMC12799970

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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 OpenQuestion graph.