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Aims: Knee osteoarthritis (OA) is characterized by a chronic inflammatory process involving multiple cytokine pathways, leading to articular cartilage degeneration. Intra-articular therapies using pharmaceutical or autologous anti-inflammatory factors offer potential non-surgical treatment options. Autologous protein solution (APS) is one such product that uses the patient's blood to produce a concentrate of cells and anti-inflammatory cytokines. This study evaluated the effect of a specific APS intra-articular injection (nSTRIDE) on patient-reported outcome measures compared to saline in moderate knee OA., Methods: A parallel, double-blinded, placebo-controlled randomized controlled trial was conducted, where patients with unilateral moderate knee OA (Kellgren-Lawrence grade 2 or 3) received either nSTRIDE or saline (placebo) injection to their symptomatic knee. The primary outcome was the difference in Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) total score at 12 months post-intervention. Secondary outcomes included WOMAC component scores, Knee injury and Osteoarthritis Outcome Score (KOOS), and visual analogue scale (VAS) scores at all follow-up timepoints (three, six, and 12 months)., Results: A total of 40 patients were analyzed (21 nSTRIDE; 19 saline) in the study. No significant difference was found between nSTRIDE and saline groups for WOMAC total score at 12 months (mean difference -10.4 (95% CI -24.4 to 3.6; p = 0.141). There were no significant differences in WOMAC or KOOS scores across all timepoints. VAS scores favoured the saline group for both rest and worst pain scales at 12 months post-injection (mean difference (worst) 12 months 21.5 (95% CI 6.2 to 36.8; p = 0.008); mean difference (rest) 12 months 17.8 (95% CI 2.2 to 33.4; p = 0.026)). There were no adverse events recorded in either study group., Conclusion: Our study demonstrates no significant differences between nSTRIDE and saline groups in KOOS and WOMAC scores over time. Notably, APS injection resulted in significantly worse pain symptoms at 12 months compared to saline injection., Competing Interests: M. Hirner reports payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from Arthrex and Zimmer Biomet, unrelated to this study., (© 2024 The British Editorial Society of Bone & Joint Surgery.)

Background: Recent advancements in artificial intelligence (AI) have sparked interest in its integration into clinical medicine and education. This study evaluates the performance of three AI tools compared to human clinicians in addressing complex orthopaedic decisions in real-world clinical cases., Questions/purposes: To evaluate the ability of commonly used AI tools to formulate orthopaedic clinical decisions in comparison to human clinicians., Patients and Methods: The study used OrthoBullets Cases, a publicly available clinical cases collaboration platform where surgeons from around the world choose treatment options based on peer-reviewed standardised treatment polls. The clinical cases cover various orthopaedic categories. Three AI tools, (ChatGPT 3.5, ChatGPT 4, and Bard), were evaluated. Uniform prompts were used to input case information including questions relating to the case, and the AI tools' responses were analysed for alignment with the most popular response, within 10%, and within 20% of the most popular human responses., Results: In total, 8 clinical categories comprising of 97 questions were analysed. ChatGPT 4 demonstrated the highest proportion of most popular responses (proportion of most popular response: ChatGPT 4 68.0%, ChatGPT 3.5 40.2%, Bard 45.4%, P value < 0.001), outperforming other AI tools. AI tools performed poorer in questions that were considered controversial (where disagreement occurred in human responses). Inter-tool agreement, as evaluated using Cohen's kappa coefficient, ranged from 0.201 (ChatGPT 4 vs. Bard) to 0.634 (ChatGPT 3.5 vs. Bard). However, AI tool responses varied widely, reflecting a need for consistency in real-world clinical applications., Conclusions: While AI tools demonstrated potential use in educational contexts, their integration into clinical decision-making requires caution due to inconsistent responses and deviations from peer consensus. Future research should focus on specialised clinical AI tool development to maximise utility in clinical decision-making., Level of Evidence: IV., Competing Interests: All authors declare they have no conflicts of interest relating to this study., (© 2023 The Authors.)