In-hospital length of stay (LOS) and discharge dispositions following arthroplasty could act as surrogate measures for improvement in patient pathways, and have major cost saving implications for healthcare providers. With the ever-growing adoption of robotic technology in arthroplasty, it is imperative to evaluate its impact on LOS. The objectives of this study were to compare LOS and discharge dispositions following robotic arm-assisted total knee arthroplasty (RO TKA) and unicompartmental arthroplasty (RO UKA) versus conventional technique (CO TKA and UKA). This large-scale, single-institution study included patients of any age undergoing primary TKA (n = 1,375) or UKA (n = 337) for any cause between May 2019 and January 2023. Data extracted included patient demographics, LOS, need for post anaesthesia care unit (PACU) admission, anaesthesia type, readmission within 30 days, and discharge dispositions. Univariate and multivariate logistic regression models were also employed to identify factors and patient characteristics related to delayed discharge.Aims
Methods
Robotic-assisted total knee arthroplasty (TKA) has proven higher accuracy, fewer alignment outliers, and improved short-term clinical outcomes when compared to conventional TKA. However, evidence of cost-effectiveness and individual superiority of one system over another is the subject of further research. Despite its growing adoption rate, published results are still limited and comparative studies are scarce. This review compares characteristics and performance of five currently available systems, focusing on the information and feedback each system provides to the surgeon, what the systems allow the surgeon to modify during the operation, and how each system then aids execution of the surgical plan. Cite this article: Abstract
The primary aim is to estimate the current and potential number of patients on NHS England orthopaedic elective waiting lists by November 2020. The secondary aims are to model recovery strategies; review the deficit of hip and knee arthroplasty from National Joint Registry (NJR) data; and assess the cost of returning to pre-COVID-19 waiting list numbers. A model of referral, waiting list, and eventual surgery was created and calibrated using historical data from NHS England (April 2017 to March 2020) and was used to investigate the possible consequences of unmet demand resulting from fewer patients entering the treatment pathway and recovery strategies. NJR data were used to estimate the deficit of hip and knee arthroplasty by August 2020 and NHS tariff costs were used to calculate the financial burden.Aims
Methods
The primary aim was to assess the rate of patient deferral of elective orthopaedic surgery and whether this changed with time during the coronavirus disease 2019 (COVID-19) pandemic. The secondary aim was to explore the reasons why patients wanted to defer surgery and what measures/circumstances would enable them to go forward with surgery. Patients were randomly selected from elective orthopaedic waiting lists at three centres in the UK in April, June, August, and September 2020 and were contacted by telephone. Patients were asked whether they wanted to proceed or defer surgery. Patients who wished to defer were asked seven questions relating to potential barriers to proceeding with surgery and were asked whether there were measures/circumstances that would allow them to go forward with surgery.Aims
Methods
Many aspects of total knee arthroplasty have
changed since its inception. Modern prosthetic design, better fixation techniques,
improved polyethylene wear characteristics and rehabilitation, have
all contributed to a large change in revision rates. Arthroplasty
patients now expect longevity of their prostheses and demand functional
improvement to match. This has led to a re-examination of the long-held
belief that mechanical alignment is instrumental to a successful
outcome and a focus on restoring healthy joint kinematics. A combination
of kinematic restoration and uncemented, adaptable fixation may
hold the key to future advances. Cite this article:
