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The Bone & Joint Journal
Vol. 97-B, Issue 10_Supple_A | Pages 45 - 48
1 Oct 2015
Lavand'homme P Thienpont E

The patient with a painful arthritic knee awaiting total knee arthroplasty (TKA) requires a multidisciplinary approach. Optimal control of acute post-operative pain and the prevention of chronic persistent pain remains a challenge. The aim of this paper is to evaluate whether stratification of patients can help identify those who are at particular risk for severe acute or chronic pain. . Intense acute post-operative pain, which is itself a risk factor for chronic pain, is more common in younger, obese female patients and those suffering from central pain sensitisation. Pre-operative pain, in the knee or elsewhere in the body, predisposes to central sensitisation. Pain due to osteoarthritis of the knee may also trigger neuropathic pain and may be associated with chronic medication like opioids, leading to a state of nociceptive sensitisation called ‘opioid-induced hyperalgesia’. Finally, genetic and personality related risk factors may also put patients at a higher risk for the development of chronic pain. . Those identified as at risk for chronic pain would benefit from specific peri-operative management including reduction in opioid intake pre-operatively, the peri-operative use of antihyperalgesic drugs such as ketamine and gabapentinoids, and a close post-operative follow-up in a dedicated chronic pain clinic. Cite this article: Bone Joint J 2015;97-B(10 Suppl A):45–8


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. 101-B, Issue 2 | Pages 132 - 139
1 Feb 2019
Karczewski D Winkler T Renz N Trampuz A Lieb E Perka C Müller M

Aims

In 2013, we introduced a specialized, centralized, and interdisciplinary team in our institution that applied a standardized diagnostic and treatment algorithm for the management of prosthetic joint infections (PJIs). The hypothesis for this study was that the outcome of treatment would be improved using this approach.

Patients and Methods

In a retrospective analysis with a standard postoperative follow-up, 95 patients with a PJI of the hip and knee who were treated with a two-stage exchange between 2013 and 2017 formed the study group. A historical cohort of 86 patients treated between 2009 and 2011 not according to the standardized protocol served as a control group. The success of treatment was defined according to the Delphi criteria in a two-year follow-up.


The Bone & Joint Journal
Vol. 99-B, Issue 12 | Pages 1571 - 1576
1 Dec 2017
Jacofsky DJ

‘Big data’ is a term for data sets that are so large or complex that traditional data processing applications are inadequate. Billions of dollars have been spent on attempts to build predictive tools from large sets of poorly controlled healthcare metadata. Companies often sell reports at a physician or facility level based on various flawed data sources, and comparative websites of ‘publicly reported data’ purport to educate the public. Physicians should be aware of concerns and pitfalls seen in such data definitions, data clarity, data relevance, data sources and data cleaning when evaluating analytic reports from metadata in health care.

Cite this article: Bone Joint J 2017;99-B:1571–6.


The Bone & Joint Journal
Vol. 99-B, Issue 2 | Pages 171 - 174
1 Feb 2017
Tissingh EK Sudlow A Jones A Nolan JF

Aims

The importance of accurate identification and reporting of surgical site infection (SSI) is well recognised but poorly defined. Public Health England (PHE) mandated collection of orthopaedic SSI data in 2004. Data submission is required in one of four categories (hip prosthesis, knee prosthesis, repair of neck of femur, reduction of long bone fracture) for one quarter per year. Trusts are encouraged to carry out post-discharge surveillance but this is not mandatory. Recent papers in the orthopaedic literature have highlighted the importance of SSI surveillance and the heterogeneity of surveillance methods. However, details of current orthopaedic SSI surveillance practice has not been described or quantified.

Patients and Methods

All 147 NHS trusts in England were audited using a structured questionnaire. Data was collected in the following categories: data collection; data submission to PHE; definitions used; resource constraints; post-discharge surveillance and SSI rates in the four PHE categories. The response rate was 87.7%.


The Bone & Joint Journal
Vol. 99-B, Issue 7 | Pages 856 - 864
1 Jul 2017
Helmerhorst GTT Teunis T Janssen SJ Ring D

The United States and Canada are in the midst of an epidemic of the use, misuse and overdose of opioids, and deaths related to overdose. This is the direct result of overstatement of the benefits and understatement of the risks of using opioids by advocates and pharmaceutical companies. Massive amounts of prescription opioids entered the community and were often diverted and misused. Most other parts of the world achieve comparable pain relief using fewer opioids.

The misconceptions about opioids that created this epidemic are finding their way around the world. There is particular evidence of the increased prescription of strong opioids in Europe.

Opioids are addictive and dangerous. Evidence is mounting that the best pain relief is obtained through resilience. Opioids are often prescribed when treatments to increase resilience would be more effective.

Cite this article: Bone Joint J 2017;99-B:856–64.


The Bone & Joint Journal
Vol. 97-B, Issue 10_Supple_A | Pages 30 - 39
1 Oct 2015
Baldini A Castellani L Traverso F Balatri A Balato G Franceschini V

Primary total knee arthroplasty (TKA) is a reliable procedure with reproducible long-term results. Nevertheless, there are conditions related to the type of patient or local conditions of the knee that can make it a difficult procedure. The most common scenarios that make it difficult are discussed in this review. These include patients with many previous operations and incisions, and those with severe coronal deformities, genu recurvatum, a stiff knee, extra-articular deformities and those who have previously undergone osteotomy around the knee and those with chronic dislocation of the patella.

Each condition is analysed according to the characteristics of the patient, the pre-operative planning and the reported outcomes.

When approaching the difficult primary TKA surgeons should use a systematic approach, which begins with the review of the existing literature for each specific clinical situation.

Cite this article: Bone Joint J 2015;97-B(10 Suppl A):30–9.