ArticleJoint diseases and related surgery2026
Evaluating deepresearch and deepthink in total knee arthroplasty patient education: ChatGPT-4o excels in comprehensiveness, Deepseek R1 leads in clarity and readability of orthopedic information.
Article in Joint diseases and related surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07631585 (Longitudinal Pre-Post Patient AI Trust Dynamics in Orthopedic Outpatients), which is not on this map. Cited by 1 paper.
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.
Longitudinal Pre-Post Patient AI Trust Dynamics in Orthopedic Outpatients: A Mixed-Methods Observational Study With Matched Physician-Patient Dyads
Who cites it
1 citing paper in PubMed.
- Artificial Intelligence in Arthroplasty: A Comprehensive Structured Critical Review and Descriptive Evidence Map of Validation, Uncertainty, and Workflow Integration.Bioengineering (Basel, Switzerland) · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesThis study aims to directly compare ChatGPT and DeepSeek, both equipped with DeepResearch/DeepThink capabilities, based on their responses to frequently asked questions (FAQs) on total knee arthroplasty (TKA). MATERIALS AND
methodsThirty frequently asked questions related to TKA were compiled from validated patient education sources, including American Academy of Orthopaedic Surgeons (AAOS) OrthoInfo, National Institute for Health and Care Excellence (NICE) guidelines, and popular patient discussion forums, and verified for clinical relevance by two independent arthroplasty surgeons. Two orthopedic surgeons, blinded to model identity, evaluated each response using a five-point Likert scale across five domains: accuracy, comprehensiveness, readability, relevance, and ethical and safety considerations. The maximum total score per response was 25. Readability was also assessed using the Flesch-Kincaid Grade Level (FKGL) and Flesch Reading Ease Score (FRES). Inter-rater and intra-rater reliability were calculated using intraclass correlation coefficients (ICCs).
resultsThe ChatGPT-4o scored significantly higher in comprehensiveness and clinical detail, whereas DeepSeek R1 produced responses with superior readability, indicated by a lower FKGL (7.5 vs. 10.2) and higher FRES (62.3 vs. 45.6) (p < 0.05). Both models demonstrated high accuracy and safety, with no factual errors identified. Intra-rater reliability was excellent (ICC > 0.81), and inter-rater agreement ranged from fair to substantial (ICC 0.31 to 0.63).
conclusionBoth ChatGPT-4o and DeepSeek R1 are capable of generating accurate, ethically sound, and clinically relevant educational content for patients undergoing TKA. While ChatGPT-4o offers more comprehensive information, DeepSeek R1 provides content that is more accessible to patients with lower health literacy. Model selection should be tailored to the target population to optimize educational effectiveness in clinical practice. The ability of real-time data retrieval to incorporate the most current clinical evidence and guideline updates may further enhance the educational quality, reliability, and clinical relevance of AI-generated patient information.
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