Machine learning (ML), a branch of artificial intelligence that uses algorithms to learn from data and make predictions, offers a pathway towards more personalized and tailored surgical treatments. This approach is particularly relevant to prevalent joint diseases such as osteoarthritis (OA). In contrast to end-stage disease, where joint arthroplasty provides excellent results, early stages of OA currently lack effective therapies to halt or reverse progression. Accurate prediction of OA progression is crucial if timely interventions are to be developed, to enhance patient care and optimize the design of clinical trials. A systematic review was conducted in accordance with PRISMA guidelines. We searched MEDLINE and Embase on 5 May 2024 for studies utilizing ML to predict OA progression. Titles and abstracts were independently screened, followed by full-text reviews for studies that met the eligibility criteria. Key information was extracted and synthesized for analysis, including types of data (such as clinical, radiological, or biochemical), definitions of OA progression, ML algorithms, validation methods, and outcome measures.Aims
Methods
Factors associated with high mortality rates in geriatric hip fracture patients are frequently unmodifiable. Time to surgery, however, might be a modifiable factor of interest to optimize clinical outcomes after hip fracture surgery. This study aims to determine the influence of postponement of surgery due to non-medical reasons on clinical outcomes in acute hip fracture surgery. This observational cohort study enrolled consecutively admitted patients with a proximal femoral fracture, for which surgery was performed between 1 January 2018 and 11 January 2021 in two level II trauma teaching hospitals. Patients with medical indications to postpone surgery were excluded. A total of 1,803 patients were included, of whom 1,428 had surgery < 24 hours and 375 had surgery ≥ 24 hours after admission.Aims
Methods
Literature surrounding artificial intelligence (AI)-related applications for hip and knee arthroplasty has proliferated. However, meaningful advances that fundamentally transform the practice and delivery of joint arthroplasty are yet to be realized, despite the broad range of applications as we continue to search for meaningful and appropriate use of AI. AI literature in hip and knee arthroplasty between 2018 and 2021 regarding image-based analyses, value-based care, remote patient monitoring, and augmented reality was reviewed. Concerns surrounding meaningful use and appropriate methodological approaches of AI in joint arthroplasty research are summarized. Of the 233 AI-related orthopaedics articles published, 178 (76%) constituted original research, while the rest consisted of editorials or reviews. A total of 52% of original AI-related research concerns hip and knee arthroplasty (n = 92), and a narrative review is described. Three studies were externally validated. Pitfalls surrounding present-day research include conflating vernacular (“AI/machine learning”), repackaging limited registry data, prematurely releasing internally validated prediction models, appraising model architecture instead of inputted data, withholding code, and evaluating studies using antiquated regression-based guidelines. While AI has been applied to a variety of hip and knee arthroplasty applications with limited clinical impact, the future remains promising if the question is meaningful, the methodology is rigorous and transparent, the data are rich, and the model is externally validated. Simple checkpoints for meaningful AI adoption include ensuring applications focus on: administrative support over clinical evaluation and management; necessity of the advanced model; and the novelty of the question being answered. Cite this article:
The aim of this study was to review the current evidence surrounding curve type and morphology on curve progression risk in adolescent idiopathic scoliosis (AIS). A comprehensive search was conducted by two independent reviewers on PubMed, Embase, Medline, and Web of Science to obtain all published information on morphological predictors of AIS progression. Search items included ‘adolescent idiopathic scoliosis’, ‘progression’, and ‘imaging’. The inclusion and exclusion criteria were carefully defined. Risk of bias of studies was assessed with the Quality in Prognostic Studies tool, and level of evidence for each predictor was rated with the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach. In all, 6,286 publications were identified with 3,598 being subjected to secondary scrutiny. Ultimately, 26 publications (25 datasets) were included in this review.Aims
Methods
Total hip arthroplasties (THAs) are performed by surgeons at various stages in training with varying levels of supervision, but we do not know if this is safe practice with comparable outcomes to consultant-performed THA. Our aim was to examine the association between surgeon grade, the senior supervision of trainees, and the risk of revision following THA. We performed an observational study using National Joint Registry (NJR) data. We included adult patients who underwent primary THA for osteoarthritis, recorded in the NJR between 2003 and 2016. Exposures were operating surgeon grade (consultant or trainee) and whether or not trainees were directly supervised by a scrubbed consultant. Outcomes were all-cause revision and the indication for revision up to ten years. We used methods of survival analysis, adjusted for patient, operation, and healthcare setting factors.Aims
Methods
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:
The purpose of this study is to evaluate early outcomes with the use of a smartphone-based exercise and educational care management system after total hip arthroplasty (THA) and demonstrate decreased use of in-person physiotherapy (PT). A multicentre, prospective randomized controlled trial was conducted to evaluate a smartphone-based care platform for primary THA. Patients randomized to the control group (198) received the institution’s standard of care. Those randomized to the treatment group (167) were provided with a smartwatch and smartphone application. PT use, THA complications, readmissions, emergency department/urgent care visits, and physician office visits were evaluated. Outcome scores include the Hip disability and Osteoarthritis Outcome Score (HOOS, JR), health-related quality-of-life EuroQol five-dimension five-level score (EQ-5D-5L), single leg stance (SLS) test, and the Timed Up and Go (TUG) test.Aims
Methods
The purpose is to determine the non-inferiority of a smartphone-based exercise educational care management system after primary knee arthroplasty compared with a traditional in-person physiotherapy rehabilitation model. A multicentre prospective randomized controlled trial was conducted evaluating the use of a smartphone-based care management system for primary total knee arthroplasty (TKA) and partial knee arthroplasty (PKA). Patients in the control group (n = 244) received the respective institution’s standard of care with formal physiotherapy. The treatment group (n = 208) were provided a smartwatch and smartphone application. Early outcomes assessed included 90-day knee range of movement, EuroQoL five-dimension five-level score, Knee Injury and Osteoarthritis Outcome Score for Joint Replacement (KOOS JR) score, 30-day single leg stance (SLS) time, Time up and Go (TUG) time, and need for manipulation under anaesthesia (MUA).Aims
Methods
Arthroplasty skills need to be acquired safely during training, yet operative experience is increasingly hard to acquire by trainees. Virtual reality (VR) training using headsets and motion-tracked controllers can simulate complex open procedures in a fully immersive operating theatre. The present study aimed to determine if trainees trained using VR perform better than those using conventional preparation for performing total hip arthroplasty (THA). A total of 24 surgical trainees (seven female, 17 male; mean age 29 years (28 to 31)) volunteered to participate in this observer-blinded 1:1 randomized controlled trial. They had no prior experience of anterior approach THA. Of these 24 trainees, 12 completed a six-week VR training programme in a simulation laboratory, while the other 12 received only conventional preparatory materials for learning THA. All trainees then performed a cadaveric THA, assessed independently by two hip surgeons. The primary outcome was technical and non-technical surgical performance measured by a THA-specific procedure-based assessment (PBA). Secondary outcomes were step completion measured by a task-specific checklist, error in acetabular component orientation, and procedure duration.Aims
Patients and Methods
This annotation briefly reviews the history of artificial intelligence and machine learning in health care and orthopaedics, and considers the role it will have in the future, particularly with reference to statistical analyses involving large datasets. Cite this article:
Fracture clinics are often characterised by the referral of large
numbers of unselected patients with minor injuries not requiring
investigation or intervention, long waiting times and recurrent
unnecessary reviews. Our experience had been of an unsustainable
system and we implemented a ‘Trauma Triage Clinic’ (TTC) in order
to rationalise and regulate access to our fracture service. The
British Orthopaedic Association’s guidelines have required a prospective evaluation
of this change of practice, and we report our experience and results. We review the management of all 12 069 patients referred to our
service in the calendar year 2014, with a minimum of one year follow-up
during the calendar year 2015. Aims
Patients and Methods
Aims. The long-term functional outcome of total hip arthroplasty (THA)
performed by trainees is not known. A multicentre retrospective
study of 879 THAs was undertaken to investigate any differences
in outcome between those performed by trainee surgeons and consultants. . Patients and Methods. A total of 879 patients with a mean age of 69.5 years (37 to
94) were included in the study; 584 THAs (66.4%) were undertaken
by consultants, 138 (15.7%) by junior trainees and 148 (16.8%) by
senior trainees. Patients were scored using the Harris Hip Score
(HHS) pre-operatively and at one, three, five, seven and ten years
post-operatively. Surgical outcome, complications and survival were
compared between groups. The effect of supervision was determined
by comparing supervised and
The National Institute for Health and Clinical
Excellence (NICE) guidelines from 2011 recommend the use of cemented
hemi-arthroplasty for appropriate patients with an intracapsular
hip fracture. In our institution all patients who were admitted
with an intracapsular hip fracture and were suitable for a hemi-arthroplasty
between April 2010 and July 2012 received an uncemented prosthesis
according to our established departmental routine practice. A retrospective
analysis of outcome was performed to establish whether the continued
use of an uncemented stem was justified. Patient, surgical and outcome
data were collected on the National Hip Fracture database. A total
of 306 patients received a Cathcart modular head on a Corail uncemented
stem as a hemi-arthroplasty. The mean age of the patients was 83.3
years ( Cite this article:
This brief annotation summarises the particular contributions made by the annual Edinburgh International Trauma Symposium in various areas of research into aspects of orthopaedic trauma and the management of acutely injured patients, during the 25 years since its establishment.
Balancing service provision and surgical training is a challenging issue that affects all healthcare systems. A multicentre prospective study of 1501 total hip replacements was undertaken to investigate whether there is an association between surgical outcome and the grade of the operating surgeon, and whether there is any difference in outcome if surgeons’ assistants assist with the operation, rather than orthopaedic trainees. The primary outcome measure was the change in the Oxford hip score (OHS) at five years. Secondary outcomes included the rate of revision and dislocation, operating time, and length of hospital stay. There was no significant difference in ΔOHS or complication rates between operations undertaken by trainers and trainees, or those at which surgeons’ assistants and trainees were the assistant. However, there was a significant difference in the duration of surgery, with a mean reduction of 28 minutes in those in which a surgeons’ assistant was the assistant. This study provides evidence that total hip replacements can be performed safely and effectively by appropriately trained surgeons in training, and that there are potential benefits of using surgeons’ assistants in orthopaedic surgery.
We have conducted a prospective trial of the management of 135 adult patients who had sustained soft-tissue injuries of the neck in vehicle accidents. Early traction and physiotherapy was compared with rest in a collar and