The aim of this study was to develop and internally validate a prognostic nomogram to predict the probability of gaining a functional range of motion (ROM ≥ 120°) after open arthrolysis of the elbow in patients with post-traumatic stiffness of the elbow. We developed the Shanghai Prediction Model for Elbow Stiffness Surgical Outcome (SPESSO) based on a dataset of 551 patients who underwent open arthrolysis of the elbow in four institutions. Demographic and clinical characteristics were collected from medical records. The least absolute shrinkage and selection operator regression model was used to optimize the selection of relevant features. Multivariable logistic regression analysis was used to build the SPESSO. Its prediction performance was evaluated using the concordance index (C-index) and a calibration graph. Internal validation was conducted using bootstrapping validation.Aims
Methods
Shoulder arthroplasty is effective in the management of end-stage glenohumeral joint arthritis. However, it is major surgery and patients must balance multiple factors when considering the procedure. An understanding of patients’ decision-making processes may facilitate greater support of those considering shoulder arthroplasty and inform the outcomes of future research. Participants were recruited from waiting lists of three consultant upper limb surgeons across two NHS hospitals. Semi-structured interviews were conducted with 12 participants who were awaiting elective shoulder arthroplasty. Transcribed interviews were analyzed using a grounded theory approach. Systematic coding was performed; initial codes were categorized and further developed into summary narratives through a process of discussion and refinement. Data collection and analyses continued until thematic saturation was reached.Aims
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