Aims. This study used an artificial neural network (ANN) model to determine the most important pre- and perioperative variables to predict
Aims. The volume of ambulatory total hip arthroplasty (THA) procedures is increasing due to the emphasis on value-based care. The purpose of the study is to identify the causes for failed
Aims. To identify variables independently associated with
Aims. Day-case arthroplasty is gaining popularity in Europe. We report outcomes from the first 12 months following implementation of a day-case pathway for unicompartmental knee arthroplasty (UKA) and total hip arthroplasty (THA) in an NHS hospital. Methods. A total of 47 total hip arthroplasty (THA) and 24 unicompartmental knee arthroplasty (UKA) patients were selected for the day-case arthroplasty pathway, based on preoperative fitness and agreement to participate. Data were likewise collected for a matched control group (n = 58) who followed the standard pathway three months prior to the implementation of the day-case pathway. We report
Aims. This study aimed to evaluate whether an enhanced recovery protocol (ERP) for arthroplasty established during the COVID-19 pandemic at a safety net hospital can be associated with a decrease in hospital length of stay (LOS) and an increase in
Aims. Intra-articular administration of antibiotics during primary total knee arthroplasty (TKA) may represent a safe, cost-effective strategy to reduce the risk of acute periprosthetic joint infection (PJI). Vancomycin with an aminoglycoside provides antimicrobial cover for most organisms isolated from acute PJI after TKA. However, the intra-articular doses required to achieve sustained therapeutic intra-articular levels while remaining below toxic serum levels is unknown. The purpose of this study is to determine the intra-articular and serum levels of vancomycin and tobramycin over the first 24 hours postoperatively after intra-articular administration in primary cementless TKA. Methods. A prospective cohort study was performed. Patients were excluded if they had poor renal function, known allergic reaction to vancomycin or tobramycin, received intravenous vancomycin, or were scheduled for
Aims. The proportion of arthroplasties performed in the ambulatory setting has increased considerably. However, there are concerns whether
Aims. The aim of this prospective multicentre study was to describe trends in length of stay and early complications and readmissions following unicompartmental knee arthroplasty (UKA) performed at eight different centres in Denmark using a fast-track protocol and to compare the length of stay between centres with high and low utilization of UKA. Methods. We included data from eight dedicated fast-track centres, all reporting UKAs to the same database, between 2010 and 2018. Complete ( > 99%) data on length of stay, 90-day readmission, and mortality were obtained during the study period. Specific reasons for a length of stay of > two days, length of stay > four days, and 30- and 90-day readmission were recorded. The use of UKA in the different centres was dichotomized into ≥ 20% versus < 20% of arthroplasties which were undertaken being UKAs, and ≥ 52 UKAs versus < 52 UKAs being undertaken annually. Results. A total of 3,927 procedures were included. Length of stay (mean 1.1 days (SD 1.1), median 1 (IQR 0 to 1)) was unchanged during the study period. The proportion of procedures with a length of stay > two days was also largely unchanged during this time. The percentage of patients discharged on the day of surgery varied greatly between centres (0% to 50% (0 to 481)), with centres with high UKA utilization (both usage and volume) having a larger proportion of
The August 2023 Research Roundup360 looks at: Can artificial intelligence improve the readability of patient education materials?; What is the value of radiology input during a multidisciplinary orthopaedic oncology conference?; Periprosthetic joint infection in patients with multiple arthroplasties; Orthopedic Surgery and Anesthesiology Surgical Improvement Strategies Project - Phase III outcomes; Knot tying in arthroplasty and arthroscopy causes lesions to surgical gloves: a potential risk of infection; Vascular calcification of the ankle in plain radiographs equals diabetes mellitus?
This study aims to determine difference in annual rate of early-onset (≤ 90 days) deep surgical site infection (SSI) following primary total knee arthroplasty (TKA) for osteoarthritis, and to identify risk factors that may be associated with infection. This is a retrospective population-based cohort study using prospectively collected patient-level data between 1 January 2013 and 1 March 2020. The diagnosis of deep SSI was defined as per the Centers for Disease Control/National Healthcare Safety Network criteria. The Mann-Kendall Trend test was used to detect monotonic trends in annual rates of early-onset deep SSI over time. Multiple logistic regression was used to analyze the effect of different patient, surgical, and healthcare setting factors on the risk of developing a deep SSI within 90 days from surgery for patients with complete data. We also report 90-day mortality.Aims
Methods
The February 2023 Spine Roundup360 looks at: S2AI screws: At what cost?; Just how good is spinal deformity surgery?; Is 80 years of age too late in the day for spine surgery?; Factors affecting the accuracy of pedicle screw placement in robot-assisted surgery; Factors causing delay in discharge in patients eligible for ambulatory lumbar fusion surgery; Anterior cervical discectomy or fusion and selective laminoplasty for cervical spondylotic myelopathy; Surgery for cervical radiculopathy: what is the complication burden?; Hypercholesterolemia and neck pain; Return to work after surgery for cervical radiculopathy: a nationwide registry-based observational study.
The June 2024 Hip & Pelvis Roundup360 looks at: Machine learning did not outperform conventional competing risk modelling to predict revision arthroplasty; Unravelling the risks: incidence and reoperation rates for femoral fractures post-total hip arthroplasty; Spinal versus general anaesthesia for hip arthroscopy: a COVID-19 pandemic- and opioid epidemic-driven study; Development and validation of a deep-learning model to predict total hip arthroplasty on radiographs; Ambulatory centres lead in same-day hip and knee arthroplasty success; Exploring the impact of smokeless tobacco on total hip arthroplasty outcomes: a deeper dive into postoperative complications.
The February 2023 Knee Roundup360 looks at: Machine-learning models: are all complications predictable?; Positive cultures can be safely ignored in revision arthroplasty patients that do not meet the 2018 International Consensus Meeting Criteria; Spinal versus general anaesthesia in contemporary primary total knee arthroplasty; Preoperative pain and early arthritis are associated with poor outcomes in total knee arthroplasty; Risk factors for infection and revision surgery following patellar tendon and quadriceps tendon repairs; Supervised versus unsupervised rehabilitation following total knee arthroplasty; Kinematic alignment has similar outcomes to mechanical alignment: a systematic review and meta-analysis; Lifetime risk of revision after knee arthroplasty influenced by age, sex, and indication; Risk factors for knee osteoarthritis after traumatic knee injury.
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:
The December 2023 Knee Roundup360 looks at: Obesity is associated with greater improvement in patient-reported outcomes following primary total knee arthroplasty; Does mild flexion of the femoral prosthesis in total knee arthroplasty result in better early postoperative outcomes?; Robotic or manual total knee arthroplasty: a randomized controlled trial; Patient-relevant outcomes following first revision total knee arthroplasty, by diagnosis: an analysis of implant survivorship, mortality, serious medical complications, and patient-reported outcome measures using the National Joint Registry data set; Sagittal alignment in total knee arthroplasty: are there any discrepancies between robotic-assisted and manual axis orientation?; Tourniquet use does not impact recovery trajectory in total knee arthroplasty; Impact of proximal tibial varus anatomy on survivorship after medial unicondylar knee arthroplasty; Bone cement directly to the implant in primary total knee arthroplasty?; Maintaining joint line obliquity optimizes outcomes in patients with constitutionally varus knees.
The rate of day-case total knee arthroplasty (TKA) in the UK is currently approximately 0.5%. Reducing length of stay allows orthopaedic providers to improve efficiency, increase operative throughput, and tackle the rising demand for joint arthroplasty surgery and the COVID-19-related backlog. Here, we report safe delivery of day-case TKA in an NHS trust via inpatient wards with no additional resources. Day-case TKAs, defined as patients discharged on the same calendar day as surgery, were retrospectively reviewed with a minimum follow-up of six months. Analysis of hospital and primary care records was performed to determine readmission and reattendance rates. Telephone interviews were conducted to determine patient satisfaction.Aims
Methods
The use of artificial intelligence (AI) is rapidly growing across many domains, of which the medical field is no exception. AI is an umbrella term defining the practical application of algorithms to generate useful output, without the need of human cognition. Owing to the expanding volume of patient information collected, known as ‘big data’, AI is showing promise as a useful tool in healthcare research and across all aspects of patient care pathways. Practical applications in orthopaedic surgery include: diagnostics, such as fracture recognition and tumour detection; predictive models of clinical and patient-reported outcome measures, such as calculating mortality rates and length of hospital stay; and real-time rehabilitation monitoring and surgical training. However, clinicians should remain cognizant of AI’s limitations, as the development of robust reporting and validation frameworks is of paramount importance to prevent avoidable errors and biases. The aim of this review article is to provide a comprehensive understanding of AI and its subfields, as well as to delineate its existing clinical applications in trauma and orthopaedic surgery. Furthermore, this narrative review expands upon the limitations of AI and future direction. Cite this article:
Total hip arthroplasty (THA) is a common procedure to address pain and enhance function in hip disorders such as osteoarthritis. Despite its success, postoperative patient recovery exhibits considerable heterogeneity. This study aimed to investigate whether patients follow distinct pain trajectories following THA and identify the patient characteristics linked to suboptimal trajectories. This retrospective cohort study analyzed THA patients at a large academic centre (NYU Langone Orthopedic Hospital, New York, USA) from January 2018 to January 2023, who completed the Patient-Reported Outcomes Measurement Information System (PROMIS) pain intensity questionnaires, collected preoperatively at one-, three-, six-, 12-, and 24-month follow-up times. Growth mixture modelling (GMM) was used to model the trajectories. Optimal model fit was determined by Bayesian information criterion (BIC), Vuong-Lo-Mendell-Rubin likelihood ratio test (VLMR-LRT), posterior probabilities, and entropy values. Association between trajectory groups and patient characteristics were measured by multinomial logistic regression using the three-step approach.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: