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Shaunton Stubbs

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Review Open access Jul 2026

Superior Sensitivity of the Forgotten Joint Score in Total Knee Arthroplasty: A Meta-Analysis of Randomized Controlled Trials

Background The Forgotten Joint Score (FJS) is a patient-reported outcome (PRO) measure assessing joint awareness after total knee arthroplasty (TKA). Unlike traditional PROs, it is particularly sensitive to the “forgotten” quality of the joint, correlating with patient satisfaction and long-term success. This systematic review evaluates the FJS compared to conventional PROs in assessing TKA outcomes. Methods A systematic search of PubMed, Embase, and the Cochrane Library identified randomized controlled trials reporting FJS alongside other PROs in primary TKA. Studies included various alignment techniques, implants, and robotic assistance. Independent reviewers performed data extraction and risk of bias assessments. Pooled FJS scores were analyzed using random-effects models, with subgroup analyses by surgical technique and prosthesis type. Results Fourteen randomized controlled trials (1244 knees) met inclusion criteria. FJS scores ranged from 19.00 to 98.00, with a mean of 73.61. Unlike Western Ontario and McMaster Universities, Oxford Knee Score, and Knee Society Score, the FJS showed no significant ceiling effect. Chi-square tests demonstrated that FJS detected significant postoperative improvements compared to Western Ontario and McMaster Universities and Knee Society Score (P = .011 and P = .037). Subgroup analyses found no significant differences in FJS or other PROs, though recent studies suggest a trend favoring kinematic alignment. Conclusions The FJS demonstrates superior sensitivity and avoids ceiling effects compared to traditional PROs, making it a valuable tool for evaluating subtle differences in TKA outcomes. Its ability to detect nuanced improvements highlights its clinical relevance in optimizing surgical techniques and enhancing patient-centered care. Future research should prioritize the FJS to refine alignment strategies and implant designs.

Anand Dhaliwal, Alexander J. Baur, Brendan J. Liakos et al. · 0 citations