Receive monthly Table of Contents alerts from Bone & Joint Open
Comprehensive article alerts can be set up and managed through your account settings
View my account settingsVisit Bone & Joint Open at:
The aim of the present study was to analyze the oncological and neurological outcome of patients undergoing interdisciplinary treatment for primary malignant bone and soft-tissue tumours of the spine within the last seven decades, and changes over time. We retrospectively analyzed our single-centre experience of prospectively collected data by querying our tumour registry (Medical University of Vienna). Therapeutic, pathological, and demographic variables were examined. Descriptive data are reported for the entire cohort. Kaplan-Meier analysis and multivariate Cox regression analysis were applied to evaluate survival rates and the influence of potential risk factors.Aims
Methods
To establish cut-off values for lateral pubofemoral distance (PFD) measurements for detecting hip dysplasia in early (four days) and standard care (six weeks) screening for developmental dysplasia of the hip (DDH). All newborns, during a one-year period (October 2021 to October 2022), were offered a PFD ultrasound (US) examination in addition to the existing screening programme for DDH. Newborns who were referred for standard care hip US, suspected for DDH, received a secondary PFD US examination in conjunction with the standard care Graf/Harcke hip US examination. Receiver operating characteristic curves and empirically optimal cut-off values were calculated with a true positive defined as a Graf type ≥ IIc hip.Aims
Methods
Machine learning (ML) holds significant promise in optimizing various aspects of total shoulder arthroplasty (TSA), potentially improving patient outcomes and enhancing surgical decision-making. The aim of this systematic review was to identify ML algorithms and evaluate their effectiveness, including those for predicting clinical outcomes and those used in image analysis. We searched the PubMed, EMBASE, and Cochrane Central Register of Controlled Trials databases for studies applying ML algorithms in TSA. The analysis focused on dataset characteristics, relevant subspecialties, specific ML algorithms used, and their performance outcomes.Aims
Methods
