ArticleInternational orthopaedics2026
Evaluating ChatGPT responses to patient-oriented questions on one-stage revision arthroplasty for periprosthetic joint infection.
Article in International orthopaedics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Exploring large language models as a prescription decision support tool for rational antibiotic use: A dual-framework analysis using standardized examinations and real-world clinical cases.Exploratory research in clinical and social pharmacy · 2026Article
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5 authors.
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Abstract
backgroundLarge language model based chatbots are increasingly used by patients seeking information about periprosthetic joint infection (PJI) and revision strategies, yet the quality of patient-facing answers for one-stage revision remains uncertain.
methodsThis expert based, cross sectional exploratory study evaluated ChatGPT generated answers to 12 patient-oriented questions on one-stage revision arthroplasty for PJI. Questions were purposively selected from a pool of 30 commonly asked items to maximize topic coverage while minimizing redundancy. All questions were entered ad verbatim into ChatGPT on January 3, 2026 (freely accessible web interface; GPT-5.2), using a new session per question; only the first response was recorded without follow-up prompts or browsing. Four raters (two senior orthopaedic surgeons, one junior orthopaedic surgeon, one infectious diseases specialist) independently graded each response using a predefined ordinal rubric and recorded brief comments when limitations were identified. Inter-rater reliability was assessed using Krippendorff's alpha (ordinal).
resultsResponses were rated positively overall. Answers addressing procedural steps, postoperative antibiotic management, and recovery expectations received the most consistently high ratings. Clarification was most frequently requested in domains where decision making is conditional or evolving, including indications/contraindications and patient selection, culture-negative PJI framing, protocol dependent weight bearing recommendations, and management options after failure. Inter-rater agreement was modest (α = 0.375; 95% CI - 0.012 to 0.651).
conclusionIn this exploratory study, ChatGPT provided generally clear patient-facing explanations for one-stage revision PJI topics, with stronger performance in standardized and procedural domains and more limited performance in areas requiring individualized clinical judgment. These findings suggest that it may have a supportive role in patient education, although clinician oversight remains important to ensure appropriate contextualization and to avoid overgeneralization.
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