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Bone & Joint Open
Vol. 3, Issue 7 | Pages 515 - 528
1 Jul 2022
van der Heijden L Bindt S Scorianz M Ng C Gibbons MCLH van de Sande MAJ Campanacci DA

Aims. Giant cell tumour of bone (GCTB) treatment changed since the introduction of denosumab from purely surgical towards a multidisciplinary approach, with recent concerns of higher recurrence rates after denosumab. We evaluated oncological, surgical, and functional outcomes for distal radius GCTB, with a critically appraised systematic literature review. Methods. We included 76 patients with distal radius GCTB in three sarcoma centres (1990 to 2019). Median follow-up was 8.8 years (2 to 23). Seven patients underwent curettage, 38 curettage with adjuvants, and 31 resection; 20 had denosumab. Results. Recurrence rate was 71% (5/7) after curettage, 32% (12/38) after curettage with adjuvants, and 6% (2/31) after resection. Median time to recurrence was 17 months (4 to 77). Recurrences were treated with curettage with adjuvants (11), resection (six), or curettage (two). Overall, 84% (38/45) was cured after one to thee intralesional procedures. Seven patients had 12 months neoadjuvant denosumab (5 to 15) and sixmonths adjuvant denosumab; two recurred (29%). Twelve patients had six months neoadjuvant denosumab (4 to 10); five recurred (42%). Two had pulmonary metastases (2.6%), both stable after denosumab. Complication rate was 18% (14/76, with 11 requiring surgery). At follow-up, median MusculoSkeletal Tumour Society score was 28 (18 to 30), median Short Form-36 Health Survey was 86 (41 to 95), and median Disability of Arm, Shoulder, and Hand was 7.8 (0 to 58). Conclusion. Distal radius GCTB treatment might deviate from general GCTB treatment because of complexity of wrist anatomy and function. Novel insights on surgical treatment are presented in this multicentre study and systematic review. Intralesional surgery resulted in high recurrence-rate for distal radius GCTB, also with additional denosumab. The large majority of patients however, were cured after repeated curettage. Cite this article: Bone Jt Open 2022;3(7):515–528


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. 5, Issue 5 | Pages 374 - 384
1 May 2024
Bensa A Sangiorgio A Deabate L Illuminati A Pompa B Filardo G

Aims

Robotic-assisted unicompartmental knee arthroplasty (R-UKA) has been proposed as an approach to improve the results of the conventional manual UKA (C-UKA). The aim of this meta-analysis was to analyze the studies comparing R-UKA and C-UKA in terms of clinical outcomes, radiological results, operating time, complications, and revisions.

Methods

The literature search was conducted on three databases (PubMed, Cochrane, and Web of Science) on 20 February 2024 according to the guidelines for Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA). Inclusion criteria were comparative studies, written in the English language, with no time limitations, on the comparison of R-UKA and C-UKA. The quality of each article was assessed using the Downs and Black Checklist for Measuring Quality.


Bone & Joint Open
Vol. 5, Issue 7 | Pages 570 - 580
10 Jul 2024
Poursalehian M Ghaderpanah R Bagheri N Mortazavi SMJ

Aims

To systematically review the predominant complication rates and changes to patient-reported outcome measures (PROMs) following osteochondral allograft (OCA) transplantation for shoulder instability.

Methods

This systematic review, following PRISMA guidelines and registered in PROSPERO, involved a comprehensive literature search using PubMed, Embase, Web of Science, and Scopus. Key search terms included “allograft”, “shoulder”, “humerus”, and “glenoid”. The review encompassed 37 studies with 456 patients, focusing on primary outcomes like failure rates and secondary outcomes such as PROMs and functional test results.


Bone & Joint Open
Vol. 3, Issue 7 | Pages 549 - 556
1 Jul 2022
Poacher AT Bhachoo H Weston J Shergill K Poacher G Froud J

Aims

Evidence exists of a consistent decline in the value and time that medical schools place upon their undergraduate orthopaedic placements. This limited exposure to trauma and orthopaedics (T&O) during medical school will be the only experience in the speciality for the majority of doctors. This review aims to provide an overview of undergraduate orthopaedic training in the UK.

Methods

This review summarizes the relevant literature from the last 20 years in the UK. Articles were selected from database searches using MEDLINE, EMBASE, ERIC, Cochrane, and Web of Science. A total of 16 papers met the inclusion criteria.


Bone & Joint Open
Vol. 2, Issue 10 | Pages 806 - 812
1 Oct 2021
Gerritsen M Khawar A Scheper H van der Wal R Schoones J de Boer M Nelissen R Pijls B

Aims

The aim of this meta-analysis is to assess the association between exchange of modular parts in debridement, antibiotics, and implant retention (DAIR) procedure and outcomes for hip and knee periprosthetic joint infection (PJI).

Methods

We conducted a systematic search on PubMed, Embase, Web of Science, and Cochrane library from inception until May 2021. Random effects meta-analyses and meta-regression was used to estimate, on a study level, the success rate of DAIR related to component exchange. Risk of bias was appraised using the (AQUILA) checklist.