The aim of this retrospective study was to evaluate the medium-term clinical and functional outcomes of patients with closed, displaced, and unstable, simple or complex, intra- and extra-articular distal radius fractures (DRFs) treated with a bridging external fixator (BEF) and optional K-wires (KWs). AO classification was used to differentiate the injuries radiographically. Clinical-functional outcomes were evaluated using the Patient-Rated Wrist and Hand Evaluation Score (PRWHE Score) and the Quick Disabilities of the Arm Shoulder and Hand Score (QuickDASH). A total of 269 dorsally displaced fractures of 202 female (75%) and 67 male subjects (25%) were included, with a mean follow-up of 58.0 months. Seventy-five patients (28%) were treated by additional KWs. No differences were found comparing the two groups of patients (BEF vs. BEF + KWs) regarding age, sex, and fracture side (dominant vs. non-dominant). PRWHE and QuickDASH scores were lower in the BEF + KWs group compared to the BEF group (p < 0.0001 and p = 0.0007, respectively). Thus, patients treated with KWs had a better clinical outcome. Beta multivariate regression analysis confirmed that patients of the BEF + KWs group exhibited a better PRWHE score but not a better QuickDASH score. Patients treated by the BEF + KWs with the fracture on the dominant site were characterised by better clinical outcomes. Older patients had a better PRWHE score independently from the treatment. Our findings suggest that the use of BEF for DRFs with optional KWs can be indicated in both young and elderly patients of any gender, independent of limb side and fracture pattern. As the best functional results were achieved in the elderly when KWs were added, the combination of BEF and KWs seems to be mainly indicated for the treatment of DRF, also complex, in the elderly population.

Background/Objectives: Assessing the learning curve is essential for surgical techniques that require precision and technical adaptation. Although modified Reverdin–Isham and Akin percutaneous osteotomies (RIAOs) are well-established procedures for the treatment of hallux valgus (HV), their percutaneous nature and specific technical demands justify the evaluation of the learning curve. Therefore, this study aimed to assess the learning curve of RIAOs for the HV correction, using for the first time a Bayesian approach. Methods: Modified RIAOs were applied to treat mild-to-moderate HV in patients who were prospectively enrolled. The hallux valgus angle (HVA), inter-metatarsal angle (IMA), distal metatarsal articular angle (DMAA) and tibial sesamoid position were assessed. Clinical outcomes were evaluated with the American Orthopaedic Foot & Ankle Society (AOFAS) Scale, Visual Analog Scale (VAS) and Numerical Rating Scale (NRS). Surgery and fluoroscopy times were recorded. To evaluate the learning curve, a Bayesian analysis using a change point model was performed. Results: Analysis of 142 patients revealed three distinct phases in the learning curve, with a plateau reached after 112 procedures. Over time, the mean operation duration decreased from 55 to 27 min, and fluoroscopy time decreased from 60 to 28 s. Conclusions: A flexible change point model was used to model a learning curve, guaranteeing a robust interpretation of the data. The correction of the HV angles showed similar results in the three phases of the curve, demonstrating that the surgeon achieved positive results from the beginning of the surgery.

This work presents a novel simulation-based approach for constructing confidence regions in parametric models, which is particularly suited for generative models and situations where limited data and conventional asymptotic approximations fail to provide accurate results. The method leverages the concept of data depth and depends on creating random hyper-rectangles, i.e. boxes, in the sample space generated through simulations from the model, varying the input parameters. A probabilistic acceptance rule allows to retrieve a Depth-Confidence Distribution for the model parameters from which point estimators as well as calibrated confidence sets can be read-off. The method is designed to address cases where both the parameters and test statistics are multivariate.