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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: Current predictive tools for TKA focus on clinicians rather than patients as the intended user. The purpose of this study was to develop a patient-focused model to predict health-related quality of life outcomes at 1-year post-TKA., Methods: Patients who underwent primary TKA for osteoarthritis from a tertiary institutional registry after January 2006 were analysed. The primary outcome was improvement after TKA defined by the minimal clinically important difference in utility score at 1-year post-surgery. Potential predictors included demographic information, comorbidities, lifestyle factors, and patient-reported outcome measures. Four models were developed, including both conventional statistics and machine learning (artificial intelligence) methods: logistic regression, classification tree, extreme gradient boosted trees, and random forest models. Models were evaluated using discrimination and calibration metrics., Results: A total of 3755 patients were included in the study. The logistic regression model performed the best with respect to both discrimination (AUC = 0.712) and calibration (intercept = -0.083, slope = 1.123, Brier score = 0.202). Less than 2% (n = 52) of the data were missing and therefore removed for complete case analysis. The final model used age (categorical), sex, baseline utility score, and baseline Veterans-RAND 12 responses as predictors., Conclusion: The logistic regression model performed better than machine learning algorithms with respect to AUC and calibration plot. The logistic regression model was well calibrated enough to stratify patients into risk deciles based on their likelihood of improvement after surgery. Further research is required to evaluate the performance of predictive tools through pragmatic clinical trials., Level of Evidence: Level II, decision analysis., (© 2023 The Authors. ANZ Journal of Surgery published by John Wiley & Sons Australia, Ltd on behalf of Royal Australasian College of Surgeons.)