Evidence map›Paper›PMID 40521295›Full record

ArticleArthroplasty today2025

Comparative Efficacy of ChatGPT and DeepSeek in Addressing Patient Queries on Gonarthrosis and Total Knee Arthroplasty.

Serhat Gurbuz, Hakan Bahar, Ulas Yavuz, Ahmet Keskin, Bulent Karslioglu, Yener Solak

Abstract read
In one paragraph

Article in Arthroplasty today, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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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

6 authors.

Serhat GurbuzDepartment of Orthopedics and Traumatology, Baltalimanı Bone Diseases Training and Research Hospital, Istanbul, Turkey.
Hakan BaharDepartment of Orthopedics and Traumatology, Baltalimanı Bone Diseases Training and Research Hospital, Istanbul, Turkey.
Ulas YavuzDepartment of Orthopedics and Traumatology, Baltalimanı Bone Diseases Training and Research Hospital, Istanbul, Turkey.
Ahmet KeskinDepartment of Orthopedics and Traumatology, Baltalimanı Bone Diseases Training and Research Hospital, Istanbul, Turkey.
Bulent KarsliogluDepartment of Orthopedics and Traumatology, Baltalimanı Bone Diseases Training and Research Hospital, Istanbul, Turkey.
Yener SolakDepartment of Orthopedics and Traumatology, Baltalimanı Bone Diseases Training and Research Hospital, Istanbul, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The advent of artificial intelligence (AI) in healthcare has opened new avenues for patient education and anxiety reduction. This study aims to compare the efficacy of 2 prominent AI platforms, ChatGPT and DeepSeek, in providing accurate and satisfactory responses to patients with gonarthrosis contemplating total knee arthroplasty (TKA). Methods: A prospective, comparative trial was conducted involving 100 patients diagnosed with gonarthrosis and indicated for TKA. Each patient posed 5 questions regarding the surgery and postoperative rehabilitation to both ChatGPT and DeepSeek. Responses were evaluated by 2 blinded orthopaedic specialists on a 10-point scale for accuracy and patient satisfaction. Patients also rated their satisfaction with each response on a 10-point scale. The primary outcome measures were the mean accuracy scores from specialists and mean satisfaction scores from patients. Results: Statistical analysis revealed significant differences between ChatGPT and DeepSeek in both accuracy and patient satisfaction ( Conclusions: This study demonstrates that ChatGPT offers more accurate and satisfactory responses to patient queries regarding gonarthrosis and TKA compared to DeepSeek. The findings suggest that AI platforms, particularly ChatGPT, can serve as valuable tools in augmenting patient education and potentially reducing preoperative anxiety. Future research should explore the integration of AI-assisted information delivery in clinical practice and its long-term impact on patient outcomes.

Indexed as

Artificial intelligenceChatGPTDeepSeekGonarthrosisPatient educationTotal knee arthroplasty

Identifiers

PMID40521295
PMCPMC12167088

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Registered trials

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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.