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The Bone & Joint Journal
Vol. 103-B, Issue 9 | Pages 1442 - 1448
1 Sep 2021
McDonnell JM Evans SR McCarthy L Temperley H Waters C Ahern D Cunniffe G Morris S Synnott K Birch N Butler JS

In recent years, machine learning (ML) and artificial neural networks (ANNs), a particular subset of ML, have been adopted by various areas of healthcare. A number of diagnostic and prognostic algorithms have been designed and implemented across a range of orthopaedic sub-specialties to date, with many positive results. However, the methodology of many of these studies is flawed, and few compare the use of ML with the current approach in clinical practice. Spinal surgery has advanced rapidly over the past three decades, particularly in the areas of implant technology, advanced surgical techniques, biologics, and enhanced recovery protocols. It is therefore regarded an innovative field. Inevitably, spinal surgeons will wish to incorporate ML into their practice should models prove effective in diagnostic or prognostic terms. The purpose of this article is to review published studies that describe the application of neural networks to spinal surgery and which actively compare ANN models to contemporary clinical standards allowing evaluation of their efficacy, accuracy, and relatability. It also explores some of the limitations of the technology, which act to constrain the widespread adoption of neural networks for diagnostic and prognostic use in spinal care. Finally, it describes the necessary considerations should institutions wish to incorporate ANNs into their practices. In doing so, the aim of this review is to provide a practical approach for spinal surgeons to understand the relevant aspects of neural networks.

Cite this article: Bone Joint J 2021;103-B(9):1442–1448.


The Bone & Joint Journal
Vol. 102-B, Issue 5 | Pages 568 - 572
1 May 2020
McDonnell JM Ahern DP Ó Doinn T Gibbons D Rodrigues KN Birch N Butler JS

Continuous technical improvement in spinal surgical procedures, with the aim of enhancing patient outcomes, can be assisted by the deployment of advanced technologies including navigation, intraoperative CT imaging, and surgical robots. The latest generation of robotic surgical systems allows the simultaneous application of a range of digital features that provide the surgeon with an improved view of the surgical field, often through a narrow portal.

There is emerging evidence that procedure-related complications and intraoperative blood loss can be reduced if the new technologies are used by appropriately trained surgeons. Acceptance of the role of surgical robots has increased in recent years among a number of surgical specialities including general surgery, neurosurgery, and orthopaedic surgeons performing major joint arthroplasty. However, ethical challenges have emerged with the rollout of these innovations, such as ensuring surgeon competence in the use of surgical robotics and avoiding financial conflicts of interest. Therefore, it is essential that trainees aspiring to become spinal surgeons as well as established spinal specialists should develop the necessary skills to use robotic technology safely and effectively and understand the ethical framework within which the technology is introduced.

Traditional and more recently developed platforms exist to aid skill acquisition and surgical training which are described.

The aim of this narrative review is to describe the role of surgical robotics in spinal surgery, describe measures of proficiency, and present the range of training platforms that institutions can use to ensure they employ confident spine surgeons adequately prepared for the era of robotic spinal surgery.

Cite this article: Bone Joint J 2020;102-B(5):568–572.


The Bone & Joint Journal
Vol. 102-B, Issue 10 | Pages 1281 - 1288
3 Oct 2020
Chang JS Kayani B Plastow R Singh S Magan A Haddad FS

Injuries to the hamstring muscle complex are common in athletes, accounting for between 12% and 26% of all injuries sustained during sporting activities. Acute hamstring injuries often occur during sports that involve repetitive kicking or high-speed sprinting, such as American football, soccer, rugby, and athletics. They are also common in watersports, including waterskiing and surfing. Hamstring injuries can be career-threatening in elite athletes and are associated with an estimated risk of recurrence in between 14% and 63% of patients. The variability in prognosis and treatment of the different injury patterns highlights the importance of prompt diagnosis with magnetic resonance imaging (MRI) in order to classify injuries accurately and plan the appropriate management.

Low-grade hamstring injuries may be treated with nonoperative measures including pain relief, eccentric lengthening exercises, and a graduated return to sport-specific activities. Nonoperative management is associated with highly variable times for convalescence and return to a pre-injury level of sporting function. Nonoperative management of high-grade hamstring injuries is associated with poor return to baseline function, residual muscle weakness and a high-risk of recurrence. Proximal hamstring avulsion injuries, high-grade musculotendinous tears, and chronic injuries with persistent weakness or functional compromise require surgical repair to enable return to a pre-injury level of sporting function and minimize the risk of recurrent injury.

This article reviews the optimal diagnostic imaging methods and common classification systems used to guide the treatment of hamstring injuries. In addition, the indications and outcomes for both nonoperative and operative treatment are analyzed to provide an evidence-based management framework for these patients.

Cite this article: Bone Joint J 2020;102-B(10):1281–1288.


The Bone & Joint Journal
Vol. 101-B, Issue 2 | Pages 124 - 131
1 Feb 2019
Isaacs J Cochran AR

Abstract

Nerve transfer has become a common and often effective reconstructive strategy for proximal and complex peripheral nerve injuries of the upper limb. This case-based discussion explores the principles and potential benefits of nerve transfer surgery and offers in-depth discussion of several established and valuable techniques including: motor transfer for elbow flexion after musculocutaneous nerve injury, deltoid reanimation for axillary nerve palsy, intrinsic re-innervation following proximal ulnar nerve repair, and critical sensory recovery despite non-reconstructable median nerve lesions.


The Bone & Joint Journal
Vol. 98-B, Issue 10 | Pages 1320 - 1325
1 Oct 2016
Nousiainen MT McQueen SA Hall J Kraemer W Ferguson P Marsh JL Reznick RR Reed MR Sonnadara R

As residency training programmes around the globe move towards competency-based medical education (CBME), there is a need to review current teaching and assessment practices as they relate to education in orthopaedic trauma. Assessment is the cornerstone of CBME, as it not only helps to determine when a trainee is fit to practice independently, but it also provides feedback on performance and guides the development of competence. Although a standardised core knowledge base for trauma care has been developed by the leading national accreditation bodies and international agencies that teach and perform research in orthopaedic trauma, educators have not yet established optimal methods for assessing trainees’ performance in managing orthopaedic trauma patients.

This review describes the existing knowledge from the literature on assessment in orthopaedic trauma and highlights initiatives that have recently been undertaken towards CBME in the United Kingdom, Canada and the United States.

In order to support a CBME approach, programmes need to improve the frequency and quality of assessments and improve on current formative and summative feedback techniques in order to enhance resident education in orthopaedic trauma.

Cite this article: Bone Joint J 2016;98-B:1320–5.