Machine-learning (ML) prediction models in orthopaedic trauma hold great promise in assisting clinicians in various tasks, such as personalized risk stratification. However, an overview of current applications and critical appraisal to peer-reviewed guidelines is lacking. The objectives of this study are to 1) provide an overview of current ML prediction models in orthopaedic trauma; 2) evaluate the completeness of reporting following the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) statement; and 3) assess the risk of bias following the Prediction model Risk Of Bias Assessment Tool (PROBAST) tool. A systematic search screening 3,252 studies identified 45 ML-based prediction models in orthopaedic trauma up to January 2023. The TRIPOD statement assessed transparent reporting and the PROBAST tool the risk of bias.Aims
Methods
The aim of this systematic review and meta-analysis was to gather epidemiological information on selected musculoskeletal injuries and to provide pooled injury-specific incidence rates. PubMed (National Library of Medicine) and Scopus (Elsevier) databases were searched. Articles were eligible for inclusion if they reported incidence rate (or count with population at risk), contained data on adult population, and were written in English language. The number of cases and population at risk were collected, and the pooled incidence rates (per 100,000 person-years) with 95% confidence intervals (CIs) were calculated by using either a fixed or random effects model.Aims
Methods
The purpose of this systematic review was to determine the rates of union for vascularized versus non-vascularized grafting techniques in the operative management of scaphoid nonunion. Secondary aims were to determine the effect of the fixation techniques used, the source of grafting, as well as the influence of fracture location (proximal pole) and avascular necrosis (AVN). A search of PubMed, MEDLINE, and Embase was performed in June 2021 using the Preferred Reporting Items for Systematic Review and Meta-Analyses statement and registered using the PROSPERO International prospective register of systematic reviews. The primary outcome was union rate.Aims
Methods
The aim of this study was to assess the quality and scope of the current cost-effectiveness analysis (CEA) literature in the field of hand and upper limb orthopaedic surgery. We conducted a systematic review of MEDLINE and the CEA Registry to identify CEAs that were conducted on or after 1 January 1997, that studied a procedure pertaining to the field of hand and upper extremity surgery, that were clinical studies, and that reported outcomes in terms of quality-adjusted life-years. We identified a total of 33 studies that met our inclusion criteria. The quality of these studies was assessed using the Quality of Health Economic Analysis (QHES) scale.Aims
Materials and Methods
