The aim of this study was to estimate the 90-day periprosthetic joint infection (PJI) rates following total knee arthroplasty (TKA) and total hip arthroplasty (THA) for osteoarthritis (OA). This was a data linkage study using the New South Wales (NSW) Admitted Patient Data Collection (APDC) and the Australian Orthopaedic Association National Joint Replacement Registry (AOANJRR), which collect data from all public and private hospitals in NSW, Australia. Patients who underwent a TKA or THA for OA between 1 January 2002 and 31 December 2017 were included. The main outcome measures were 90-day incidence rates of hospital readmission for: revision arthroplasty for PJI as recorded in the AOANJRR; conservative definition of PJI, defined by T84.5, the PJI diagnosis code in the APDC; and extended definition of PJI, defined by the presence of either T84.5, or combinations of diagnosis and procedure code groups derived from recursive binary partitioning in the APDC.Aims
Methods
To examine whether natural language processing (NLP) using a clinically based large language model (LLM) could be used to predict patient selection for total hip or total knee arthroplasty (THA/TKA) from routinely available free-text radiology reports. Data pre-processing and analyses were conducted according to the Artificial intelligence to Revolutionize the patient Care pathway in Hip and knEe aRthroplastY (ARCHERY) project protocol. This included use of de-identified Scottish regional clinical data of patients referred for consideration of THA/TKA, held in a secure data environment designed for artificial intelligence (AI) inference. Only preoperative radiology reports were included. NLP algorithms were based on the freely available GatorTron model, a LLM trained on over 82 billion words of de-identified clinical text. Two inference tasks were performed: assessment after model-fine tuning (50 Epochs and three cycles of k-fold cross validation), and external validation.Aims
Methods
Total joint arthroplasty (TJA) is commonly performed in elderly
patients. Frailty, an aggregate expression of vulnerability, becomes
increasingly common with advanced age, and independently predicts
adverse outcomes and the use of resources after a variety of non-cardiac
surgical procedures. Our aim was to assess the impact of frailty
on outcomes after TJA. We analysed the impact of pre-operative frailty on death and
the use of resources after elective TJA in a population-based cohort
study using linked administrative data from Ontario, Canada.Aims
Patients and Methods
We compared the length of hospitalisation, rate
of infection, dislocation of the hip and revision, and mortality following
primary hip and knee arthroplasty for osteoarthritis in patients
with Alzheimer’s disease (n = 1064) and a matched control group
(n = 3192). The data were collected from nationwide Finnish health
registers. Patients with Alzheimer’s disease had a longer peri-operative
hospitalisation (median 13 days Cite this article:
The aim of this study was to perform a cost–utility
analysis of total hip (THR) and knee replacement (TKR). Arthritis is
a disabling condition that leads to long-term deterioration in quality
of life. Total joint replacement, despite being one of the greatest
advances in medicine of the modern era, has recently come under
scrutiny. The National Health Service (NHS) has competing demands,
and resource allocation is challenging in times of economic restraint. Patients
who underwent THR (n = 348) or TKR (n = 323) between January and
July 2010 in one Scottish region were entered into a prospective
arthroplasty database. A health–utility score was derived from the
EuroQol (EQ-5D) score pre-operatively and at one year, and was combined
with individual life expectancy to derive the quality-adjusted life years
(QALYs) gained. Two-way analysis of variance was used to compare
QALYs gained between procedures, while controlling for baseline
differences. The number of QALYs gained was higher after THR than
after TKR (6.5 Cite this article:
