In the last decade, perioperative advancements have expanded the use of outpatient primary total knee arthroplasty (TKA). Despite this, there remains limited data on expedited discharge after revision TKA. This study compared 30-day readmissions and reoperations in patients undergoing revision TKA with a hospital stay greater or less than 24 hours. The authors hypothesized that expedited discharge in select patients would not be associated with increased 30-day readmissions and reoperations. Aseptic revision TKAs in the National Surgical Quality Improvement Program database were reviewed from 2013 to 2020. TKAs were stratified by length of hospital stay (greater or less than 24 hours). Patient demographic details, medical comorbidities, American Society of Anesthesiologists (ASA) grade, operating time, components revised, 30-day readmissions, and reoperations were compared. Multivariate analysis evaluated predictors of discharge prior to 24 hours, 30-day readmission, and reoperation.Aims
Methods
To identify variables independently associated with same-day discharge (SDD) of patients following revision total knee arthroplasty (rTKA) and to develop machine learning algorithms to predict suitable candidates for outpatient rTKA. Data were obtained from the American College of Surgeons National Quality Improvement Programme (ACS-NSQIP) database from the years 2018 to 2020. Patients with elective, unilateral rTKA procedures and a total hospital length of stay between zero and four days were included. Demographic, preoperative, and intraoperative variables were analyzed. A multivariable logistic regression (MLR) model and various machine learning techniques were compared using area under the curve (AUC), calibration, and decision curve analysis. Important and significant variables were identified from the models.Aims
Methods
The purpose of this study was to assess total knee arthroplasty (TKA) volume and rates of early complications in morbidly obese patients over the last decade, where the introduction of quality models influencing perioperative care pathways occurred. Patients undergoing TKA between 2011 to 2018 were identified in the American College of Surgeons National Surgical Quality Improvement Program database. Patients were stratified by BMI < 40 kg/m2 and ≥ 40 kg/m2 and evaluated by the number of cases per year. The 30-day rates of any complication, wound complications, readmissions, and reoperation were assessed. Trends in these endpoints over the study period were compared between groups using odds ratios (ORs) and multivariate analyses.Aims
Methods
This study used an artificial neural network (ANN) model to determine the most important pre- and perioperative variables to predict same-day discharge in patients undergoing total knee arthroplasty (TKA). Data for this study were collected from the National Surgery Quality Improvement Program (NSQIP) database from the year 2018. Patients who received a primary, elective, unilateral TKA with a diagnosis of primary osteoarthritis were included. Demographic, preoperative, and intraoperative variables were analyzed. The ANN model was compared to a logistic regression model, which is a conventional machine-learning algorithm. Variables collected from 28,742 patients were analyzed based on their contribution to hospital length of stay.Aims
Methods
To compare rates of serious adverse events in patients undergoing revision knee arthroplasty with consideration of the indication for revision (urgent versus elective indications), and compare these with primary arthroplasty and re-revision arthroplasty. Patients undergoing primary knee arthroplasty were identified in the national Hospital Episode Statistics (HES) between 1 April 1997 to 31 March 2017. Subsequent revision and re-revision arthroplasty procedures in the same patients and same knee were identified. The primary outcome was 90-day mortality and a logistic regression model was used to investigate factors associated with 90-day mortality and secondary adverse outcomes, including infection (undergoing surgery), pulmonary embolism, myocardial infarction, and stroke. Urgent indications for revision arthroplasty were defined as infection or fracture, and all other indications (e.g. loosening, instability, wear) were included in the elective indications cohort.Aims
Methods
To evaluate the influence of discharge timing on 30-day complications following total knee arthroplasty (TKA). We identified patients aged 18 years or older who underwent TKA between 2005 and 2016 from the American College of Surgeons’ National Surgical Quality Improvement Program (NSQIP) database. We propensity score-matched length-of-stay (LOS) groups using all relevant covariables. We used multivariable regression to determine if the rate of complications and re-admissions differed depending on LOS.Aims
Patients and Methods
Patellofemoral arthroplasty (PFA) has experienced significant
improvements in implant survivorship with second generation designs.
This has renewed interest in PFA as an alternative to total knee
arthroplasty (TKA) for younger active patients with isolated patellofemoral
osteoarthritis (PF OA). We analysed the cost-effectiveness of PFA We used a Markov transition state model to compare cost-effectiveness
between PFA and TKA. Simulated patients were aged 60 (base case)
and 50 years. Lifetime costs (2015 United States dollars), quality-adjusted
life year (QALY) gains and incremental cost-effectiveness ratio
(ICER) were calculated from a healthcare payer perspective. Annual rates
of revision were derived from the National Joint Registry for England,
Wales, Northern Ireland and the Isle of Man. Deterministic and probabilistic
sensitivity analysis was performed for all parameters against a
$50 000/QALY willingness to pay. Aims
Patients and Methods
