Literature surrounding artificial intelligence (AI)-related applications for
Aims. We investigated the efficacy and safety profile of commonly used venous thromboembolism (VTE) prophylaxis agents following
Aims. The aim of this study was to report health-related quality of life (HRQoL) and joint-specific function in patients waiting for total
Aims. Histology is widely used for diagnosis of persistent infection during reimplantation in two-stage revision
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Aims. Elective orthopaedic services have had to adapt to significant system-wide pressures since the emergence of COVID-19 in December 2019. Length of stay is often recognized as a key marker of quality of care in patients undergoing arthroplasty. Expeditious discharge is key in establishing early rehabilitation and in reducing infection risk, both procedure-related and from COVID-19. The primary aim was to determine the effects of the COVID-19 pandemic length of stay following
Aims. 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. Methods. Data pre-processing and analyses were conducted according to the Artificial intelligence to Revolutionize the patient Care pathway in
Aims. The aim of this study is to assess the impact of a pilot enhanced recovery after surgery (ERAS) programme on length of stay (LOS) and post-discharge resource usage via service evaluation and cost analysis. Methods. Between May and December 2019, 100 patients requiring
A substantial fraction of patients undergoing knee arthroplasty (KA) or hip arthroplasty (HA) do not achieve an improvement as high as the minimal clinically important difference (MCID), i.e. do not achieve a meaningful improvement. Using three patient-reported outcome measures (PROMs), our aim was: 1) to assess machine learning (ML), the simple pre-surgery PROM score, and logistic-regression (LR)-derived performance in their prediction of whether patients undergoing HA or KA achieve an improvement as high or higher than a calculated MCID; and 2) to test whether ML is able to outperform LR or pre-surgery PROM scores in predictive performance. MCIDs were derived using the change difference method in a sample of 1,843 HA and 1,546 KA patients. An artificial neural network, a gradient boosting machine, least absolute shrinkage and selection operator (LASSO) regression, ridge regression, elastic net, random forest, LR, and pre-surgery PROM scores were applied to predict MCID for the following PROMs: EuroQol five-dimension, five-level questionnaire (EQ-5D-5L), EQ visual analogue scale (EQ-VAS), Hip disability and Osteoarthritis Outcome Score-Physical Function Short-form (HOOS-PS), and Knee injury and Osteoarthritis Outcome Score-Physical Function Short-form (KOOS-PS).Aims
Methods
The aim of this study was to conduct a cross-sectional, observational cohort study of patients presenting for revision of a total hip, or total or unicompartmental knee arthroplasty, to understand current routes to revision surgery and explore differences in symptoms, healthcare use, reason for revision, and the revision surgery (surgical time, components, length of stay) between patients having regular follow-up and those without. Data were collected from participants and medical records for the 12 months prior to revision. Patients with previous revision, metal-on-metal articulations, or hip hemiarthroplasty were excluded. Participants were retrospectively classified as ‘Planned’ or ‘Unplanned’ revision. Multilevel regression and propensity score matching were used to compare the two groups.Aims
Methods
The aims were to assess whether preoperative joint-specific function (JSF) and health-related quality of life (HRQoL) were associated with level of clinical frailty in patients waiting for a primary total hip arthroplasty (THA) or knee arthroplasty (KA). Patients waiting for a THA (n = 100) or KA (n = 100) for more than six months were prospectively recruited from the study centre. Overall,162 patients responded to the questionnaire (81 THA; 81 KA). Patient demographics, Oxford score, EuroQol five-dimension (EQ-5D) score, EuroQol visual analogue score (EQ-VAS), Rockwood Clinical Frailty Score (CFS), and time spent on the waiting list were collected.Aims
Methods
Routinely collected patient-reported outcome measures (PROMs) have been useful to quantify and quality-assess provision of total hip arthroplasty (THA) and total knee arthroplasty (TKA) in the UK for the past decade. This study aimed to explore whether the outcome following primary THA and TKA had improved over the past seven years. Secondary data analysis of 277,430 primary THAs and 308,007 primary TKAs from the NHS PROMs programme was undertaken. Outcome measures were: postoperative Oxford Hip/Knee Score (OHS/OKS); proportion of patients achieving a clinically important improvement in joint function (responders); quality of life; patient satisfaction; perceived success; and complication rates. Outcome measures were compared based on year of surgery using multiple linear and logistic regression models.Aims
Methods
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
The overall aim of this study was to determine the impact of deprivation with regard to quality of life, demographics, joint-specific function, attendances for unscheduled care, opioid and antidepressant use, having surgery elsewhere, and waiting times for surgery on patients awaiting total hip arthroplasty (THA) and total knee arthroplasty (TKA). Postal surveys were sent to 1,001 patients on the waiting list for THA or TKA in a single Northern Ireland NHS Trust, which consisted of the EuroQol five-dimension five-level questionnaire (EQ-5D-5L), visual analogue scores (EQ-VAS), and Oxford Hip and Knee Scores. Electronic records determined prescriptions since addition to the waiting list and out-of-hour GP and emergency department attendances. Deprivation quintiles were determined by the Northern Ireland Multiple Deprivation Measure 2017 using postcodes of home addresses.Aims
Methods
Tranexamic acid (TXA) is now commonly used in major surgical operations including orthopaedics. The TRAC-24 randomized control trial (RCT) aimed to assess if an additional 24 hours of TXA postoperatively in primary total hip (THA) and total knee arthroplasty (TKA) reduced blood loss. Contrary to other orthopaedic studies to date, this trial included high-risk patients. This paper presents the results of a cost analysis undertaken alongside this RCT. TRAC-24 was a prospective RCT on patients undergoing TKA and THA. Three groups were included: Group 1 received 1 g intravenous (IV) TXA perioperatively and an additional 24-hour postoperative oral regime, Group 2 received only the perioperative dose, and Group 3 did not receive TXA. Cost analysis was performed out to day 90.Aims
Methods
Aims. This study aimed to investigate patients’ attitudes towards day-case
Aims. The influence of metabolic syndrome (MetS) on the outcome after
Aims. To review the evidence and reach consensus on recommendations for follow-up after total
The National Health Service produces over 500,000 tonnes of waste and 25 mega tonnes of CO2 annually. Operating room waste is segregated into different streams which are recycled, disposed of in landfill sites, or undergo costly and energy-intensive incineration processes. By assessing the quantity and recyclability of waste from primary