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Bone & Joint Open
Vol. 5, Issue 7 | Pages 565 - 569
9 Jul 2024
Britten S

Two discrete legal factors enable the surgeon to treat an injured patient the fully informed, autonomous consent of the adult patient with capacity via civil law; and the medical exception to the criminal law. This article discusses current concepts in consent in trauma; and also considers the perhaps less well known medical exception to the Offences against the Person Act 1861, which exempts surgeons from criminal liability as long as they provide ‘proper medical treatment’.

Cite this article: Bone Jt Open 2024;5(7):565–569.


The Bone & Joint Journal
Vol. 105-B, Issue 4 | Pages 347 - 355
15 Mar 2023
Birch NC Cheung JPY Takenaka S El Masri WS

Initial treatment of traumatic spinal cord injury remains as controversial in 2023 as it was in the early 19th century, when Sir Astley Cooper and Sir Charles Bell debated the merits or otherwise of surgery to relieve cord compression. There has been a lack of high-class evidence for early surgery, despite which expeditious intervention has become the surgical norm. This evidence deficit has been progressively addressed in the last decade and more modern statistical methods have been used to clarify some of the issues, which is demonstrated by the results of the SCI-POEM trial. However, there has never been a properly conducted trial of surgery versus active conservative care. As a result, it is still not known whether early surgery or active physiological management of the unstable injured spinal cord offers the better chance for recovery. Surgeons who care for patients with traumatic spinal cord injuries in the acute setting should be aware of the arguments on all sides of the debate, a summary of which this annotation presents.

Cite this article: Bone Joint J 2023;105-B(4):347–355.


Bone & Joint Open
Vol. 3, Issue 1 | Pages 93 - 97
10 Jan 2022
Kunze KN Orr M Krebs V Bhandari M Piuzzi NS

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.