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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 Research
Vol. 13, Issue 12 | Pages 750 - 763
11 Dec 2024
Xie C Gong J Zheng C Zhang J Gao J Tian C Guo X Dai S Gao T

Aims

This meta-analysis and systematic review aimed to comprehensively investigate the effects of vitamin K supplementation on bone mineral density (BMD) at various sites and bone metabolism in middle-aged and older adults.

Methods

The databases of PubMed, Web of Science, and Cochrane Library were thoroughly searched from inception to July 2023.