Aims. The primary aims of this study were to determine the time to sonographic correction of decentred hips during treatment with Pavlik harness for developmental dysplasia of the hip (DDH) and investigate potential risk factors for a delayed response to treatment. Methods. This was a retrospective cohort study of infants with decentred hips who underwent a comprehensive management protocol with Pavlik harness between 2012 and 2016. Ultrasound assessments were performed at standardized intervals and time to correction from centring of the femoral head was quantified. Hips with < 40% femoral head coverage (FHC) were considered decentred, and hips with > 50% FHC and α angles > 60° were considered corrected. Survival analyses using log-rank tests and Cox regression were performed to investigate potential risk factors for delayed time to correction. Results. A total of 108 infants (158 hips) successfully completed the bracing protocol and were included in the study. Mean age at treatment initiation was 6.9 weeks (SD 3.8). All included hips centred within two weeks of treatment initiation. At two, five, eight, and 12 weeks following centring of the femoral head, 13% (95% CI 8 to 19), 67% (95% CI 60 to 74), 98% (95% CI 95 to 99), and 99% (95% CI 98 to 100) of hips had cumulatively achieved sonographic correction, respectively. Low α angles at presentation were found to be a risk factor for delayed time to correction (hazard ratio per 1° decrease in α angle 1.04 (95% CI 1.01 to 1.06); p = 0.006). Conclusion. The majority of decentred hips undergoing Pavlik treatment achieved sonographic correction within eight weeks of centring and radiological severity at presentation was a predictor for slower recovery. These findings provide valuable insights into hip development during Pavlik treatment and will inform the design of future prospective studies investigating the optimal time required in harness. Cite this article: Bone Joint J 2025;107-B(1):118–123

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The metabolic variations between the cartilage of osteoarthritis (OA) and Kashin-Beck disease (KBD) remain largely unknown. Our study aimed to address this by conducting a comparative analysis of the metabolic profiles present in the cartilage of KBD and OA.

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The use of technology to assess balance and alignment during total knee surgery can provide an overload of numerical data to the surgeon. Meanwhile, this quantification holds the potential to clarify and guide the surgeon through the surgical decision process when selecting the appropriate bone recut or soft tissue adjustment when balancing a total knee. Therefore, this paper evaluates the potential of deploying supervised machine learning (ML) models to select a surgical correction based on patient-specific intra-operative assessments.