Aims

This study aims to evaluate the impact of metabolic syndrome in the setting of obesity on in-hospital outcomes and resource use after total joint replacement (TJR).

Aims

The COVID-19 pandemic has disrupted the provision of arthroplasty services in England, Wales, and Northern Ireland. This study aimed to quantify the backlog, analyze national trends, and predict time to recovery.

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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.

Aims. 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. Methods. 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). Results. Predictive performance of the best models per outcome ranged from 0.71 for HOOS-PS to 0.84 for EQ-VAS (HA sample). ML statistically significantly outperformed LR and pre-surgery PROM scores in two out of six cases. Conclusion. MCIDs can be predicted with reasonable performance. ML was able to outperform traditional methods, although only in a minority of cases. Cite this article: Bone Joint Res 2023;12(9):512–521

Aims. Total hip arthroplasty (THA) and total knee arthroplasty (TKA) are common orthopaedic procedures requiring postoperative radiographs to confirm implant positioning and identify complications. Artificial intelligence (AI)-based image analysis has the potential to automate this postoperative surveillance. The aim of this study was to prepare a scoping review to investigate how AI is being used in the analysis of radiographs following THA and TKA, and how accurate these tools are. Methods. The Embase, MEDLINE, and PubMed libraries were systematically searched to identify relevant articles. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews and Arksey and O’Malley framework were followed. Study quality was assessed using a modified Methodological Index for Non-Randomized Studies tool. AI performance was reported using either the area under the curve (AUC) or accuracy. Results. Of the 455 studies identified, only 12 were suitable for inclusion. Nine reported implant identification and three described predicting risk of implant failure. Of the 12, three studies compared AI performance with orthopaedic surgeons. AI-based implant identification achieved AUC 0.992 to 1, and most algorithms reported an accuracy > 90%, using 550 to 320,000 training radiographs. AI prediction of dislocation risk post-THA, determined after five-year follow-up, was satisfactory (AUC 76.67; 8,500 training radiographs). Diagnosis of hip implant loosening was good (accuracy 88.3%; 420 training radiographs) and measurement of postoperative acetabular angles was comparable to humans (mean absolute difference 1.35° to 1.39°). However, 11 of the 12 studies had several methodological limitations introducing a high risk of bias. None of the studies were externally validated. Conclusion. These studies show that AI is promising. While it already has the ability to analyze images with significant precision, there is currently insufficient high-level evidence to support its widespread clinical use. Further research to design robust studies that follow standard reporting guidelines should be encouraged to develop AI models that could be easily translated into real-world conditions. Cite this article: Bone Joint J 2022;104-B(8):929–937

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To determine the trajectories of patient reported pain and functional disability over five years following total hip arthroplasty (THA) or total knee arthroplasty (TKA).

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As a proven and comprehensive molecular technique, metagenomic next-generation sequencing (mNGS) has shown its potential in the diagnosis of pathogens in patients with periprosthetic joint infection (PJI), using a single type of specimen. However, the optimal use of mNGS in the management of PJI has not been explored. In this study, we evaluated the diagnostic value of mNGS using three types of specimen with the aim of achieving a better choice of specimen for mNGS in these patients.

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To develop and validate patient-centred algorithms that estimate individual risk of death over the first year after elective joint arthroplasty surgery for osteoarthritis.

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To calculate how the likelihood of obtaining measurable benefit from hip or knee arthroplasty varies with preoperative patient-reported scores.

Total knee arthroplasty (TKA) and total hip arthroplasty (THA) are recognised and proven interventions for patients with advanced arthritis. Studies to date have demonstrated a steady increase in the requirement for primary and revision procedures. Projected estimates made for the United States show that by 2030 the demand for primary TKA will grow by 673% and for revision TKA by 601% from the level in 2005. For THA the projected estimates are 174% and 137% for primary and revision surgery, respectively. The purpose of this study was to see if those predictions were similar for England and Wales using data from the National Joint Registry and the Office of National Statistics. . Analysis of data for England and Wales suggest that by 2030, the volume of primary and revision TKAs will have increased by 117% and 332%, respectively between 2012 and 2030. The data for the United States translates to a 306% cumulative rate of increase between 2012 and 2030 for revision surgery, which is similar to our predictions for England and Wales. . The predictions from the United States for primary TKA were similar to our upper limit projections. For THA, we predicted an increase of 134% and 31% for primary and revision hip surgery, respectively. Our model has limitations, however, it highlights the economic burden of arthroplasty in the future in England and Wales as a real and unaddressed problem. This will have significant implications for the provision of health care and the management of orthopaedic services in the future. Cite this article: Bone Joint J 2015;97-B:1076–1081

Peri-prosthetic fracture after joint replacement in the lower limb is associated with significant morbidity. The primary aim of this study was to investigate the incidence of peri-prosthetic fracture after total hip replacement (THR) and total knee replacement (TKR) over a ten-year period using a population-based linked dataset.

Between 1 April 1997 and 31 March 2008, 52 136 primary THRs, 8726 revision THRs, 44 511 primary TKRs, and 3222 revision TKRs were performed. Five years post-operatively, the rate of fracture was 0.9% after primary THR, 4.2% after revision THR, 0.6% after primary TKR and 1.7% after revision TKR. Comparison of survival analysis for all primary and revision arthroplasties showed peri-prosthetic fractures were more likely in females, patients aged > 70 and after revision arthroplasty.

Female patients aged > 70 should be warned of a significantly increased risk of peri-prosthetic fracture after hip or knee replacement. The use of adjuvant medical treatment to reduce the effect of peri-prosthetic osteoporosis may be a direction of research for these patients.

The National Institute for Clinical Excellence (NICE) produces recommendations on appropriate treatment within the National Health Service (NHS) in England and Wales. The NICE guidelines on prophylaxis for venous thromboembolism in orthopaedic surgery recommend that all patients be offered a low molecular weight heparin (LMWH). The linked hospital episode statistics of 219 602 patients were examined to determine the rates of complications following lower limb arthroplasty for the 12-month periods prior to and following the publication of these guidelines. These were compared with data from the National Joint Registry (England and Wales) regarding the use of LMWH during the same periods. There was a significant increase in the reported use of LMWH (59.5% to 67.6%, p < 0.001) following the publication of the guidelines. However, the 90-day venous thromboembolism events actually increased slightly following total hip replacement (THR, 1.69% to 1.84%, p = 0.06) and remained unchanged following total knee replacement (TKR, 1.99% to 2.04%). Return to theatre in the first 30 days for infection did not show significant changes. There was an increase in the number of patients diagnosed with thrombocytopenia, which was significant following THR (0.11% to 0.16%, p = 0.04). The recommendations from NICE are based on predicted reductions in venous thromboembolism events, reducing morbidity, mortality and costs to the NHS. The early results in orthopaedic patients do not support these predictions, but do show an increase in complications

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.