Evaluation of ChatGPT-5 responses to patient-centered questions on stromal vascular fraction for knee osteoarthritis: fair to good quality and content.

Early human evidence such as case series or small samples is exploring possible benefits.

• Level A · Stronger Clinical Evidence
• Level B · Emerging clinical evidence with positive signals
• Level C · Early human research exploring benefits
• Level D · Scientific groundwork from lab and animal studies
• Emerging · Emerging topic under active research

Abstract (original English)

BACKGROUND: The global burden of symptomatic knee osteoarthritis (KOA) continues to grow, driving clinical interest in biological treatment options. Stromal vascular fraction (SVF), derived from adipose tissue, has gained attention as a potential therapy for KOA. As patients increasingly utilize large language models (LLMs) like ChatGPT for health information, this study aimed to evaluate the patient-information quality and readability of AI-generated responses to a curated set of patient-centered questions on SVF therapy for KOA. METHODS: Thirty patient-centered questions were developed through literature review by two experts and then posed to ChatGPT-5 after asking it to answer from an orthopaedic specialist perspective. Responses from ChatGPT-5 were evaluated by four orthopaedic specialists using three quality instruments: DISCERN, NLAT-AI (assessing five domains: Accuracy, Safety, Appropriateness, Actionability, and Effectiveness), and the Mika et al. scoring system. Readability was assessed using five standard metrics. RESULTS: Mean scores were as follows: DISCERN 44.61 ± 4.94 (Fair); for NLAT-AI domains, Accuracy 3.92 ± 0.50 (Good), Safety 3.23 ± 0.78 (Fair), Appropriateness 4.14 ± 0.32 (Good), Actionability 3.20 ± 0.67 (Fair), and Effectiveness 4.46 ± 0.35 (Excellent); NLAT-AI (Total/ sum of five domains) 18.95 ± 1.93 (Good); Mika et al. 2.45 ± 0.49 (Fair). Readability

Evidence level

Early human evidence such as case series or small samples is exploring possible benefits.

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