Utility score is a preference-based measure of general health state – where 0 is equal to death, and 1 is equal to perfect health. To understand a patient's smallest perceptible change in utility score, the minimal clinically important difference (MCID) can be calculated. However, there are multiple methods to calculate MCID with no consensus about which method is most appropriate. The aim of this study is to calculate MCID values for the Veterans-RAND 12 (VR12) utility score using varying methods. Our hypothesis is that different methods will yield different MCID values.

A tertiary institutional registry (SMART) was used as the study cohort. Patients who underwent unilateral TKA for osteoarthritis from January 2012 to January 2020 were included. Utility score was calculated from VR12 responses using the standardised Brazier's method. Distribution and anchor methods were used for the MCID calculation. For distribution methods, 0.5 standard deviations of the baseline and change scores were used. For anchor methods, the physical and emotional anchor questions in the VR12 survey were used to benchmark utility score outcomes. Anchor methods included mean difference in change score, mean difference in 12 month score, and receiver operating characteristics (ROC) analysis with the Youden index.

Complete case analysis of 1735 out of 1809 eligible patients was performed. Significant variation in the MCID estimates for VR12 utility score were reported dependent on the calculation method used. The MCID estimate from 0.5 standard deviations of the change score was 0.083. The MCID estimate from the ROC analysis method using physical or emotional anchor question improvement was 0.115 (CI95 0.08-0.14; AUC 0.656).

Different MCID calculation methods yielded different MCID values. Our results suggest that MCID is not an umbrella concept but rather many distinct concepts. A general consensus is required to standardise how MCID is defined, calculated, and applied in clinical practice.

Approximately 20% of patients feel unsatisfied 12 months after primary total knee arthroplasty (TKA). Current predictive tools for TKA focus on the clinician as the intended user rather than the patient. The aim of this study is to develop a tool that can be used by patients without clinician assistance, to predict health-related quality of life (HRQoL) outcomes 12 months after total knee arthroplasty (TKA).

All patients with primary TKAs for osteoarthritis between 2012 and 2019 at a tertiary institutional registry were analysed. The predictive outcome was improvement in Veterans-RAND 12 utility score at 12 months after surgery. Potential predictors included patient demographics, co-morbidities, and patient reported outcome scores at baseline. Logistic regression and three machine learning algorithms were used. Models were evaluated using both discrimination and calibration metrics. Predictive outcomes were categorised into deciles from 1 being the least likely to improve to 10 being the most likely to improve.

3703 eligible patients were included in the analysis. The logistic regression model performed the best in out-of-sample evaluation for both discrimination (AUC = 0.712) and calibration (gradient = 1.176, intercept = −0.116, Brier score = 0.201) metrics. Machine learning algorithms were not superior to logistic regression in any performance metric. Patients in the lowest decile (1) had a 29% probability for improvement and patients in the highest decile (10) had an 86% probability for improvement.

Logistic regression outperformed machine learning algorithms in this study. The final model performed well enough with calibration metrics to accurately predict improvement after TKA using deciles. An ongoing randomised controlled trial (ACTRN12622000072718) is evaluating the effect of this tool on patient willingness for surgery. Full results of this trial are expected to be available by April 2023.

A free-to-use online version of the tool is available at smartchoice.org.au.

Use of anticoagulants for thromboembolic prophylaxis is strongly supported by evidence. However, the use of these medications beyond the prophylactic period is poorly understood.

We identified anticoagulant naïve patients that underwent hip or knee replacement between 2012 and 2019 from an arthroplasty registry and probabilistically linked 3,018 surgeries with nationwide pharmaceutical claims data. Rates of anticoagulation use were examined during the early (<= 60 days post-discharge), mid-term (61–180 days post-discharge) and long-term (181–360 days post-discharge) periods. Multivariable logistic regression analysis was performed to identify patient- and surgery-related factors associated with long-term anticoagulant use.

Anticoagulants were supplied to 20% of arthroplasties within 60 days of discharge, 7% between 61-180 days, and 10% between 181–360 days. Older age, obesity, increased comorbidity burden, a longer length of stay, occurrence of a complication necessitating anticoagulation and dispensation of an anticoagulant within 60 days of discharge were all risk factors for long-term anticoagulant use.

Given the risks associated with unnecessary use of these medications, certain patients who are prescribed anticoagulants beyond prophylactic period may benefit from specialist medication review in the months following surgery.

This study aimed to evaluate the month-to-month prevalence of antibiotic dispensation in the 12 months before and after total knee arthroplasty (TKA) and total hip arthroplasty (THA) and to identify factors associated with antibiotic dispensation in the month immediately following the surgical procedure.

In total, 4,115 THAs and TKAs performed between April 2013 and June 2019 from a state-wide arthroplasty referral centre were analysed. A cross-sectional study used data from an institutional arthroplasty registry, which was linked probabilistically to administrative dispensing data from the Australian Pharmaceutical Benefits Scheme. Multivariable logistic regression was carried out to identify patient and surgical risk factors for oral antibiotic dispensation.

Oral antibiotics were dispensed in 18.3% of patients following primary TKA and 12.0% of patients following THA in the 30 days following discharge. During the year after discharge, 66.7% of TKA patients and 58.2% of THA patients were dispensed an antibiotic at some point. Patients with poor preoperative health status were more likely to have antibiotics dispensed in the month following THA or TKA. Older age, undergoing TKA rather than THA, obesity, inflammatory arthritis, and experiencing an in-hospital wound-related or other infectious complications were associated with increased antibiotic dispensation in the 30 days following discharge.

A high rate of antibiotic dispensation in the 30 days following THA and TKA has been observed. Although resource constraints may limit routine wound review for all patients by a surgeon, a select cohort may benefit from timely specialist review postoperatively. Several risk factors identified in this study may aid in identifying appropriate candidates for such changes to follow-up care.

INTRODUCTION

The medial-stabilised (MS) knee implant, characterised by a spherical medial condyle on the femoral component and a medially congruent tibial bearing, was developed to improve knee kinematics and stability relative to performance obtained in posterior-stabilised (PS) and cruciate-retaining (CR) designs. We aimed to compare in vivo six-degree-of-freedom (6-DOF) kinematics during overground walking for these three knee designs.

The triple taper polished cemented stem (C-stem, DePuy) was developed to promote calcar loading, and reduce proximal femoral bone resorption and aseptic loosening. We aimed to evaluate the changes in peri-prosthetic bone mineral density using Dual Energy X-ray Absorbtiometry (DEXA) after total hip arthroplasty (THA) using the C-stem prosthesis.

One hundred and three patients were recruited voluntarily through and single institution for THA. The prosthesis used was the triple-taper polished cemented C-Stem (De Puy, Warsaw, Indiana, USA). DEXA scans were performed pre- operatively, then at day for, three months, nine months, 18 months and 24 months post-operativley. Scans were analysed with specialised software (Lunar DPX) to measure bone mineral density (BMD) in all seven Gruen zones at each time interval. Changes in calcar BMD were also correlated with patient age, sex, surgical approach, pre-operative BMD and post-operative mobility to identify risk factors for periprosthetic bone resorption.

One hundred and three patients underwent 103 primary THA over a five-year period (98 osteoarthritis; 5 AVN). No femoral components were loose at the two year review and none were revised. The most marked bone resorption occured in Gruen zones 1 and 7, and was best preserved in zone 5. BMD decreased rapidly in all zones in the first three months post-operatively, after which the rate of decline slowed substantially. BMD was better preserved medially (zones 6 and 5) than laterally (zones 2 and 3) at 24 months. There was delayed recovery of BMD in all zones except zones 4 and 5.

High pre-operative T-scores (>2.0) in the spine, ipsilateral and contralateral femoral neck were associated with the higher post-operative BMD and less bone resorption at all time intervals in Gruen zone 7. Pre-operative osteopenia and osteoporosis were associated with low BMD and accelerated post-operative bone resorption in zone 7.

Patients whose mobility rendered them housebound had lower post-operative BMD, and accelerated post-operative BMD loss in zone 7 when compared to non-housebound patients. Females had a lower post-operative BMD and greater loss of BMD in zone 7. Patient age and surgical approach did not effect post-operative BMD or rate of bone resorption in zone 7.

The triple-taper femoral stem design did not show an increase in periprosthetic bone density at the proximal femur at two years post-operative. Calcar bone resorption is accelerated by low pre-operative BMD, poor post-operative mobility, and in females. Age and surgical approach do not have significant effects on calcar bone remodelling.