During total knee replacement (TKR), surgeons can choose whether or not to resurface the patella, with advantages and disadvantages of each approach. Recently, the National Institute for Health and Care Excellence (NICE) recommended always resurfacing the patella, rather than never doing so. NICE found insufficient evidence on selective resurfacing (surgeon’s decision based on intraoperative findings and symptoms) to make recommendations. If effective, selective resurfacing could result in optimal individualized patient care. This protocol describes a randomized controlled trial to evaluate the clinical and cost-effectiveness of primary TKR with always patellar resurfacing compared to selective patellar resurfacing. The PAtellar Resurfacing Trial (PART) is a patient- and assessor-blinded multicentre, pragmatic parallel two-arm randomized superiority trial of adults undergoing elective primary TKR for primary osteoarthritis at NHS hospitals in England, with an embedded internal pilot phase (ISRCTN 33276681). Participants will be randomly allocated intraoperatively on a 1:1 basis (stratified by centre and implant type (cruciate-retaining vs cruciate-sacrificing)) to always resurface or selectively resurface the patella, once the surgeon has confirmed sufficient patellar thickness for resurfacing and that constrained implants are not required. The primary analysis will compare the Oxford Knee Score (OKS) one year after surgery. Secondary outcomes include patient-reported outcome measures at three months, six months, and one year (Knee injury and Osteoarthritis Outcome Score, OKS, EuroQol five-dimension five-level questionnaire, patient satisfaction, postoperative complications, need for further surgery, resource use, and costs). Cost-effectiveness will be measured for the lifetime of the patient. Overall, 530 patients will be recruited to obtain 90% power to detect a four-point difference in OKS between the groups one year after surgery, assuming up to 40% resurfacing in the selective group.Aims
Methods
Early large treatment effects can arise in small studies, which lessen as more data accumulate. This study aimed to retrospectively examine whether early treatment effects occurred for two multicentre orthopaedic randomized controlled trials (RCTs) and explore biases related to this. Included RCTs were ProFHER (PROximal Fracture of the Humerus: Evaluation by Randomisation), a two-arm study of surgery versus non-surgical treatment for proximal humerus fractures, and UK FROST (United Kingdom Frozen Shoulder Trial), a three-arm study of two surgical and one non-surgical treatment for frozen shoulder. To determine whether early treatment effects were present, the primary outcome of Oxford Shoulder Score (OSS) was compared on forest plots for: the chief investigator’s (CI) site to the remaining sites, the first five sites opened to the other sites, and patients grouped in quintiles by randomization date. Potential for bias was assessed by comparing mean age and proportion of patients with indicators of poor outcome between included and excluded/non-consenting participants.Aims
Methods
Our objective was to conduct a systematic review and meta-analysis, to establish whether differences arise in clinical outcomes between autologous and synthetic bone grafts in the operative management of tibial plateau fractures. A structured search of MEDLINE, EMBASE, the online archives of Bone & Joint Publishing, and CENTRAL databases from inception until 28 July 2021 was performed. Randomized, controlled, clinical trials that compared autologous and synthetic bone grafts in tibial plateau fractures were included. Preclinical studies, clinical studies in paediatric patients, pathological fractures, fracture nonunion, or chondral defects were excluded. Outcome data were assessed using the Risk of Bias 2 (ROB2) framework and synthesized in random-effect meta-analysis. The Preferred Reported Items for Systematic Review and Meta-Analyses guidance was followed throughout.Aims
Methods
Artificial intelligence and machine-learning analytics have gained extensive popularity in recent years due to their clinically relevant applications. A wide range of proof-of-concept studies have demonstrated the ability of these analyses to personalize risk prediction, detect implant specifics from imaging, and monitor and assess patient movement and recovery. Though these applications are exciting and could potentially influence practice, it is imperative to understand when these analyses are indicated and where the data are derived from, prior to investing resources and confidence into the results and conclusions. In this article, we review the current benefits and potential limitations of machine-learning for the orthopaedic surgeon with a specific emphasis on data quality.
It is important to understand the rate of complications associated with the increasing burden of revision shoulder arthroplasty. Currently, this has not been well quantified. This review aims to address that deficiency with a focus on complication and reoperation rates, shoulder outcome scores, and comparison of anatomical and reverse prostheses when used in revision surgery. A Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) systematic review was performed to identify clinical data for patients undergoing revision shoulder arthroplasty. Data were extracted from the literature and pooled for analysis. Complication and reoperation rates were analyzed using a meta-analysis of proportion, and continuous variables underwent comparative subgroup analysis.Aims
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