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Bone & Joint Open
Vol. 5, Issue 1 | Pages 9 - 19
16 Jan 2024
Dijkstra H van de Kuit A de Groot TM Canta O Groot OQ Oosterhoff JH Doornberg JN

Aims

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.

Methods

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.


Bone & Joint Open
Vol. 2, Issue 10 | Pages 785 - 795
1 Oct 2021
Matar HE Porter PJ Porter ML

Aims

Metal allergy in knee arthroplasty patients is a controversial topic. We aimed to conduct a scoping review to clarify the management of metal allergy in primary and revision total knee arthroplasty (TKA).

Methods

Studies were identified by searching electronic databases: Cochrane Central Register of Controlled Trials, Ovid MEDLINE, and Embase, from their inception to November 2020, for studies evaluating TKA patients with metal hypersensitivity/allergy. All studies reporting on diagnosing or managing metal hypersensitivity in TKA were included. Data were extracted and summarized based on study design, study population, interventions and outcomes. A practical guide is then formulated based on the available evidence.


Bone & Joint Open
Vol. 1, Issue 11 | Pages 683 - 690
1 Nov 2020
Khan SA Asokan A Handford C Logan P Moores T

Background

Due to the overwhelming demand for trauma services, resulting from increasing emergency department attendances over the past decade, virtual fracture clinics (VFCs) have become the fashion to keep up with the demand and help comply with the BOA Standards for Trauma and Orthopaedics (BOAST) guidelines. In this article, we perform a systematic review asking, “How useful are VFCs?”, and what injuries and conditions can be treated safely and effectively, to help decrease patient face to face consultations. Our primary outcomes were patient satisfaction, clinical efficiency and cost analysis, and clinical outcomes.

Methods

We performed a systematic literature search of all papers pertaining to VFCs, using the search engines PubMed, MEDLINE, and the Cochrane Database, according to the Preferred Reporting Items for Systematic review and Meta-Analysis (PRISMA) checklist. Searches were carried out and screened by two authors, with final study eligibility confirmed by the senior author.