Aims. This study reviews the past 30 years of research from the Canadian
Aims. Frailty greatly increases the risk of adverse outcome of
Aims. The primary objective of this study was to develop a validated classification system for assessing iatrogenic bone
Aims. Heterotopic ossification (HO) is a common complication after elbow
This brief annotation summarises the particular contributions made by the annual Edinburgh International
This study examined spinal fractures in patients
admitted to a Major
Aims. The aim of this study was to investigate the relationship between the
Aims. To describe a new objective classification for open fractures of the lower limb and to correlate the classification with patient-centred outcomes. Methods. The proposed classification was investigated within a cohort of adults with open fractures of the lower limb who were recruited as part of two large clinical trials within the UK Major
There is increasing popularity in the use of artificial intelligence and machine-learning techniques to provide diagnostic and prognostic models for various aspects of
Aims. To compare the early management and mortality of older patients
sustaining major
Aims. We aimed to determine whether there is evidence of improved patient
outcomes in Major
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
Aims. The aims of this study were to report the outcomes of patients with a complex fracture of the lower limb in the five years after they took part in the Wound Healing in Surgery for
Aims. To identify the prevalence of neuropathic pain after lower limb fracture surgery, assess associations with pain severity, quality of life and disability, and determine baseline predictors of chronic neuropathic pain at three and at six months post-injury. Methods. Secondary analysis of a UK multicentre randomized controlled trial (Wound Healing in Surgery for
Artificial intelligence (AI) is, in essence, the concept of ‘computer thinking’, encompassing methods that train computers to perform and learn from executing certain tasks, called machine learning, and methods to build intricate computer models that both learn and adapt, called complex neural networks. Computer vision is a function of AI by which machine learning and complex neural networks can be applied to enable computers to capture, analyze, and interpret information from clinical images and visual inputs. This annotation summarizes key considerations and future perspectives concerning computer vision, questioning the need for this technology (the ‘why’), the current applications (the ‘what’), and the approach to unlocking its full potential (the ‘how’). Cite this article:
To determine whether obesity and malnutrition have a synergistic effect on outcomes from skeletal trauma or elective orthopaedic surgery. Electronic databases including MEDLINE, Global Health, Embase, Web of Science, ScienceDirect, and PEDRo were searched up to 14 April 2024, as well as conference proceedings and the reference lists of included studies. Studies were appraised using tools according to study design, including the Oxford Levels of Evidence, the Institute of Health Economics case series quality appraisal checklist, and the CLARITY checklist for cohort studies. Studies were eligible if they reported the effects of combined malnutrition and obesity on outcomes from skeletal trauma or elective orthopaedic surgery.Aims
Methods
Aims. To compare the cost-utility of standard dressing with incisional negative-pressure wound therapy (iNPWT) in adults with closed surgical wounds associated with major
We retrospectively studied the possibility that direct