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National projections of future joint replacement use can help us understand the changing burden of severe osteoarthritis. This study aimed to compare actual utilisation rates for primary total hip replacement (THR) and total knee replacement (TKR) to previously forecast estimates for Australia. Data from the Australian Orthopaedic Association National Joint Replacement Registry and Australian Bureau of Statistics were used to calculate 'actual' THR and TKR utilisation rates for the years 2014-2019, by sex and age group. 'Forecast' utilisation rates for 2014-2019 were derived from an earlier study that modelled two alternate scenarios for THR and TKR in Australia: Scenario 1 assumed a constant rate of surgery; Scenario 2 assumed continued growth in surgery rates. Actual utilisation rates were compared descriptively to forecast rates for females and males (overall and by age group). Rate ratios were calculated to indicate the association between actual and forecast THR and TKR rates, with a rate ratio of 1.00 reflecting perfect alignment. Over the study period, 191,996 THRs (53% in females) and 312,203 TKRs (55% in females) were performed. For both sexes, actual rates lay clearly between the Scenario 1 and 2 forecast estimates. In 2019, actual THR utilisation rates were 179 per 100,000 females (Scenario 1: 156; Scenario 2: 200) and 158 per 100,000 males (Scenario 1: 139; Scenario 2: 191). Actual TKR utilisation rates in 2019 were 289 per 100,000 females (Scenario 1: 275; Scenario 2: 387) and 249 per 100,000 males (Scenario 1: 216; Scenario 2: 312). Age-specific rate ratios were close to 1.00 for all age groups, indicating good alignment between forecast and actual joint replacement rates. These validation analyses showed that linear plus exponential growth forecasting scenarios provided an efficient approximation of actual joint replacement utilisation. This indicates our modelling techniques can be used to judiciously predict future surgery demand, including for age

BACKGROUND: Advances in digital technology and the use of multimedia platforms to deliver information provide clinicians with a unique opportunity to develop innovative ways to consistently provide high-quality, accessible, and evidence-based information to support patient participation. Introducing new technologies into everyday acute care clinical practice can be difficult. OBJECTIVE: The aim of this paper was to provide a description of an implementation strategy and the subsequent evaluation undertaken to examine the contextual factors important to the successful adoption of new technology by nurses in the context of acute postoperative care. METHODS: Implementation of the intervention and process evaluation was undertaken in 3 phases: phase 1, preimplementation stakeholder engagement and identification of barriers and enablers to implementation; phase 2, supported implementation of the intervention; and phase 3, evaluation of uptake, usability, and acceptability of the intervention in clinical practice. RESULTS: The outcomes of the implementation of the multimedia intervention in the context of acute postoperative care were positive. Of the 104 patients in the intervention group, 103 (99%) received the intervention. All 103 patients completed the 8-item intervention questionnaire and 93.3% (97/103) were interviewed on day 3 to evaluate usability, uptake, and acceptability. Of these 97 patients, almost all (n=94, 91%) found the program easy to use and most (n=64, 62%) could view the MyStay Total Knee Replacement program as often as they wanted. The findings also suggest that the time to implement the program was minimal (5-10 minutes). Collaboration with nurses and patients before and during implementation to identify potential barriers to successful implementation of the intervention was essential to develop timely strategies to overcome these barriers. To ensure end-user engagement, careful consideration was given to nurses' views on who was responsible for fa

AIM: The Anatomique Benoist Girard (ABG) II femoral implant was a commonly used stem for primary total hip replacement (THR) at our institution (Launceston, Tasmania Australia). We identified peri-prosthetic fracture as the main cause of late failure. METHODS: The late periprosthetic fracture rate for ABG II implants was reviewed with national statistics, using Australian Orthopaedic Association National Joint Replacement Registry (AOANJRR) data. National revision rates for periprosthetic fracture were used to compare ABG II with all other cementless femoral stems. RESULT: ABG II stems accounted for 1% (2719 implants) of all femoral stem implants in Australia during the 12-year review period, compared to 23% (587 implants) in Launceston Hospitals. Although the Launceston cumulative percent revision rate for the ABG II stem was lower than the National rate at all time points, the reasons for revision were similar. The most common reason for revision of ABG II was fracture (56.8%), followed by loosening (15.3%). This differs from the reasons for revision in other cementless prostheses (loosening 23.9%, fracture 20.8%, dislocation 18.7%). Cumulative percent revision rates from late periprosthetic fracture, were higher for the ABG II stem than other cementless femoral prostheses. CONCLUSION: This review of the AOANJRR has confirmed a local and national higher revision rate of the ABG II stem due to late periprosthetic fracture compared with other cementless stems. Stem design must be considered to reduce the risk of late periprosthetic fracture.

AIMS: The aim of this study was to estimate the 90-day periprosthetic joint infection (PJI) rates following total knee arthroplasty (TKA) and total hip arthroplasty (THA) for osteoarthritis (OA). METHODS: This was a data linkage study using the New South Wales (NSW) Admitted Patient Data Collection (APDC) and the Australian Orthopaedic Association National Joint Replacement Registry (AOANJRR), which collect data from all public and private hospitals in NSW, Australia. Patients who underwent a TKA or THA for OA between 1 January 2002 and 31 December 2017 were included. The main outcome measures were 90-day incidence rates of hospital readmission for: revision arthroplasty for PJI as recorded in the AOANJRR; conservative definition of PJI, defined by T84.5, the PJI diagnosis code in the APDC; and extended definition of PJI, defined by the presence of either T84.5, or combinations of diagnosis and procedure code groups derived from recursive binary partitioning in the APDC. RESULTS: The mean 90-day revision rate for infection was 0.1% (0.1% to 0.2%) for TKA and 0.3% (0.1% to 0.5%) for THA. The mean 90-day PJI rates defined by T84.5 were 1.3% (1.1% to 1.7%) for TKA and 1.1% (0.8% to 1.3%) for THA. The mean 90-day PJI rates using the extended definition were 1.9% (1.5% to 2.2%) and 1.5% (1.3% to 1.7%) following TKA and THA, respectively. CONCLUSION: When reporting the revision arthroplasty for infection, the AOANJRR substantially underestimates the rate of PJI at 90 days. Using combinations of infection codes and PJI-related surgical procedure codes in linked hospital administrative databases could be an alternative way to monitor PJI rates.Cite this article: Bone Joint J 2022;104-B(9):1060-1066.

Background: Guidelines for acute postoperative pain management recommend administering analgesics in multimodal combination to facilitate synergistic benefit, reduce opioid requirements and decrease side-effects. However, limited observational research has examined the extent to which multimodal analgesics are prescribed and administered postoperatively following joint replacement. Method(s): In this longitudinal study, we used three-point prevalence surveys to observe the 6-year trends in prescribing and use of multimodal analgesics on the orthopaedic wards of a single Australian private hospital. We collected baseline postoperative data from total hip and knee arthroplasty patients in May/June 2010 (Time 1, n = 86), and follow-up data at 1 year (Time 2, n = 199) and 5 years (Time 3, n = 188). During the follow-up, data on prescribing practices were presented to anaesthetists. Result(s): We found a statistically significant increase in the prescribing (p < 0.001) and use (p < 0.001) of multimodal analgesics over time. The use of multimodal analgesics was associated with lower rest pain (p = 0.027) and clinically significant reduction in interference with activities (p < 0.001) and sleep (p < 0.001). However, dynamic pain was high and rescue opioids were likely under-administered at all time points. Furthermore, while patients reported high levels of side-effects, use of adjuvant medications was low. Conclusion(s): We observed significant practice change in inpatient analgesic prescribing in favour of multimodal analgesia, in keeping with contemporary recommendations. Surveys, however, appeared to identify a clinical gap in the bedside assessment and management of breakthrough pain and medication side-effects, requiring additional targeted interventions. Significance: Evaluation of 6-year trends in a large Australian metropolitan private hospital indicated substantial growth in postoperative multimodal analgesic prescribing. In the context of growing global awarenes

Background Distal radius (wrist) fractures are the second most common fracture admitted to hospital. The anatomical pattern of these types of injuries is diverse, with variation in clinical management, guidelines for management remain inconclusive, and the uptake of findings from clinical trials into routine practice limited. Robust predictive modelling, which considers both the characteristics of the fracture and patient, provides the best opportunity to reduce variation in care and improve patient outcomes. This type of data is housed in unstructured data sources with no particular format or schema. The “Predicting fracture outcomes from clinical Registry data using Artificial Intelligence (AI) Supplemented models for Evidence-informed treatment (PRAISE)” study aims to use AI methods on unstructured data to describe the fracture characteristics and test if using this information improves identification of key fracture characteristics and prediction of patient-reported outcome measures and clinical outcomes following wrist fractures compared to prediction models based on standard registry data. Methods and design Adult (16+ years) patients presenting to the emergency department, treated in a short stay unit, or admitted to hospital for >24h for management of a wrist fracture in four Victorian hospitals will be included in this study. The study will use routine registry data from the Victorian Orthopaedic Trauma Outcomes Registry (VOTOR), and electronic medical record (EMR) information (e.g. X-rays, surgical reports, radiology reports, images). A multimodal deep learning fracture reasoning system (DLFRS) will be developed that reasons on EMR information. Machine learning prediction models will test the performance with/without output from the DLFRS. Discussion

Appropriate soft tissue tension in total knee replacement (TKR) is an important factor for a successful outcome. The purpose of our study was to assess both the reproducibility of a modern intraoperative pressure sensor (IOP) and if a surgeon could unconsciously influence measurement. A consecutive series of 80 TKRs were assessed with an IOP between January 2018 and December 2020. In the first scenario, two blinded sequential measurements in 48 patients were taken; in a second scenario, an initial blinded measurement and a subsequent unblinded measurement in 32 patients were taken while looking at the sensor monitor screen. Reproducibility was assessed by intraclass correlation coefficients (ICCs). In the first scenario, the ICC ranged from 0.83 to 0.90, and in the second scenario it ranged from 0.80 to 0.90. All ICCs were 0.80 or higher, indicating reproducibility using a IOP and that a surgeon may not unconsciously influence the measurement. The use of a modern IOP to measure soft tissue tension in TKRs is a reproducible technique. A surgeon observing the measurements while performing IOP may not significantly influence the result. An IOP gives additional information that the surgeon can use to optimize outcomes in TKR.

BACKGROUND: Obesity is a major public health issue and has considerable implications on outcomes of total knee arthroplasty (TKA). However, there has been conflicting evidence and conclusions on the effects of obesity on TKA. This meta-analysis compares the outcomes, complications, and peri-operative parameters of TKA in the obese (body mass index [BMI] ≥ 30 kg/m2 ) versus non-obese (BMI < 30 kg/m2 ) population as well as subgroup analysis of morbidly obese (BMI ≥ 40 kg/m2 ) versus non-obese population. METHODS: A meta-analysis was conducted with a multi-database search according to PRISMA guidelines on 12 September 2019. Data from all published literature meeting inclusion criteria were extracted and analysed. RESULTS: Ninety-one studies were included, consisting of 917 447 obese and 2 188 834 non-obese TKA. Obese patients had higher risk of all-cause revisions (odds ratio [OR] = 1.15, 95% CI: 1.08-1.24, p < 0.0001), all complications (OR = 1.21, 95% CI: 1.06-1.38, p = 0.004), deep infections (OR = 1.47, 95% CI: 1.27-1.69, p < 0.0001), superficial infections (OR = 1.59, 95% CI: 1.32-1.91, p < 0.0001), wound dehiscence (OR = 1.46, 95% CI: 1.24-1.72, p < 0.0001) and readmissions (OR = 1.21, 95% CI: 1.05-1.40, p = 0.009). Subgroup analysis of morbidly obese patients revealed greater risks of all-cause revisions (OR = 1.25, 95% CI: 1.10-1.43, p = 0.0009), deep infections (OR = 1.98, 95% CI: 1.05-3.75, p = 0.04), superficial infections (OR = 2.44, 95% CI: 2.08-2.88, p < 0.0001) and readmissions (OR = 1.33, 95% CI: 1.20-1.47, p < 0.0001). No analysis was performed on patient reported outcome measures due to heterogeneous reporting methods. CONCLUSION: Obese and morbidly obese patients have higher risks of revisions and infections post TKA. Surgeons should counsel patients of these risks during the informed consenting process and adopt preventative strategies into clinical practice to reduce risks where possible. In conclusion, obesity is a significant, modifiable risk fa

BACKGROUND: This a priori statistical analysis plan describes the analysis for CRISTAL. METHODS: CRISTAL (cluster-randomised, crossover, non-inferiority trial of aspirin compared to low molecular weight heparin for venous thromboembolism prophylaxis in hip or knee arthroplasty, a registry nested study) aims to determine whether aspirin is non-inferior to low molecular weight heparin (LMWH) in preventing symptomatic venous thromboembolism (VTE) following hip arthroplasty (HA) or knee arthroplasty (KA). The study is nested within the Australian Orthopaedic Association National Joint Replacement Registry. The trial was commenced in April 2019 and after an unplanned interim analysis, recruitment was stopped (December 2020), as the stopping rule was met for the primary outcome. The clusters comprised hospitals performing > 250 HA and/or KA procedures per annum, whereby all adults (> 18 years) undergoing HA or KA were recruited. Each hospital was randomised to commence with aspirin, orally, 85-150 mg daily or LMWH (enoxaparin), 40 mg, subcutaneously, daily within 24 h postoperatively, for 35 days after HA and 14 days after KA. Crossover was planned once the registration target was met for the first arm. The primary end point is symptomatic VTE within 90 days. Secondary outcomes include readmission, reoperation, major bleeding and death within 90 days, and reoperation and patient-reported pain, function and health status at 6 months. The main analyses will focus on the primary and secondary outcomes for patients undergoing elective primary total HA and KA for osteoarthritis. The analysis will use an intention-to-treat approach with cluster summary methods to compare treatment arms. As the trial stopped early, analyses will account for incomplete cluster crossover and unequal cluster sizes. CONCLUSIONS: This paper provides a detailed statistical analysis plan for CRISTAL. TRIAL REGISTRATION: Australian and New Zealand Clinical Trials Registry ACTRN12618001879257 . Registere

Background Guidelines for acute postoperative pain management recommend administering analgesics in multimodal combination to facilitate synergistic benefit, reduce opioid requirements and decrease side‐effects. However, limited observational research has examined the extent to which multimodal analgesics are prescribed and administered postoperatively following joint replacement. Methods In this longitudinal study, we used three‐point prevalence surveys to observe the 6‐year trends in prescribing and use of multimodal analgesics on the orthopaedic wards of a single Australian private hospital. We collected baseline postoperative data from total hip and knee arthroplasty patients in May/June 2010 (Time 1, n = 86), and follow‐up data at 1 year (Time 2, n = 199) and 5 years (Time 3, n = 188). During the follow‐up, data on prescribing practices were presented to anaesthetists. Results We found a statistically significant increase in the prescribing (p < 0.001) and use (p < 0.001) of multimodal analgesics over time. The use of multimodal analgesics was associated with lower rest pain (p = 0.027) and clinically significant reduction in interference with activities (p < 0.001) and sleep (p < 0.001). However, dynamic pain was high and rescue opioids were likely under‐administered at all time points. Furthermore, while patients reported high levels of side‐effects, use of adjuvant medications was low. Conclusions We observed significant practice change in inpatient analgesic prescribing in favour of multimodal analgesia, in keeping with contemporary recommendations. Surveys, however, appeared to identify a clinical gap in the bedside assessment and management of breakthrough pain and medication side‐effects, requiring additional targeted interventions. Significance Evaluation of 6‐year trends in a large Australian metropolitan private hospital indicated substantial growth in postoperative multimodal analgesic prescribing. In the context of growing global awareness concernin

BACKGROUND: Distal radius (wrist) fractures are the second most common fracture admitted to hospital. The anatomical pattern of these types of injuries is diverse, with variation in clinical management, guidelines for management remain inconclusive, and the uptake of findings from clinical trials into routine practice limited. Robust predictive modelling, which considers both the characteristics of the fracture and patient, provides the best opportunity to reduce variation in care and improve patient outcomes. This type of data is housed in unstructured data sources with no particular format or schema. The "Predicting fracture outcomes from clinical Registry data using Artificial Intelligence (AI) Supplemented models for Evidence-informed treatment (PRAISE)" study aims to use AI methods on unstructured data to describe the fracture characteristics and test if using this information improves identification of key fracture characteristics and prediction of patient-reported outcome measures and clinical outcomes following wrist fractures compared to prediction models based on standard registry data. METHODS AND DESIGN: Adult (16+ years) patients presenting to the emergency department, treated in a short stay unit, or admitted to hospital for >24h for management of a wrist fracture in four Victorian hospitals will be included in this study. The study will use routine registry data from the Victorian Orthopaedic Trauma Outcomes Registry (VOTOR), and electronic medical record (EMR) information (e.g. X-rays, surgical reports, radiology reports, images). A multimodal deep learning fracture reasoning system (DLFRS) will be developed that reasons on EMR information. Machine learning prediction models will test the performance with/without output from the DLFRS. DISCUSSION: The PRAISE study will establish the use of AI techniques to provide enhanced information about fracture characteristics in people with wrist fractures. Prediction models using AI derived characteristics are

IntroductionPatient comobidity at time of primary joint replacement (JR) impacts on outcomes including revision and mortality. Understanding changes in comorbidity profiles is important when assessing change in outcomes over time. Most arthroplasty registries have limited comorbidity information due to their minimum dataset. One approach to obtaining additional comorbidity data is linking registry data with national administrative data. Objectives and ApproachObjectives were to quantify pre-operative comorbidity profile of patients undergoing primary total hip replacement (THR) and total knee replacement (TKR) for osteoarthritis. Also, to examine temporal trends in individual comorbidities for THR and TKR patients. National pharmaceutical dispensing data were linked with THR and TKR arthroplasty patients. Medication dispensing histories in 12-months preceding JR (2003-2017) for 237,333 THR and 394,965 TKR patients, were mapped to 47 comorbidity classes using the Rx-Risk-V measure - a pharmacy-based measure of comorbidity. Comorbidity scores were calculated by summing comorbidity categories for individual patients. Trends in comorbidity scores/categories were described, with comorbidity information presented by PBS beneficiary category (concessional/general), stratified by age (<65/≥65 years). ResultsMedian (interquartile range) comorbidity scores were higher in concessional patients ≥65y, THR:5(3-6), TKR:5(3-7); <65y,TKR:5(3-6) but not THR:4(2-6). Comparative scores for general patients (both ages) were THR:4(2-6) and TKR:3(2-5). Trends in median comorbidity scores were consistent across study period, THR:4- 5(concessional)/2-3(general) and TKR:4-5(concessional)/4(general). Commonly identified comorbidities in younger concessional THR patients were pain, measured by opioid use (62.4%), inflammation/pain, measured by use of non-steroidal anti-inflammatories (62.2%), GORD (36.2%) and hypertension (36.1%). Individual comorbidities remained generally stable over t

IntroductionMonitoring of joint replacement (JR) data from the Australian Orthopaedic Association National Joint Replacement Registry (AOANJRR) has reduced revision rates and improved surgical practice. Outcome assessment post-arthroplasty is limited however, to revision (reoperation) surgery and mortality outcomes. The AOANJRR National Data Linkage project seeks to broaden the scope of outcomes investigation in Australia by linking registry and health administrative datasets. Objectives and ApproachUsing linked registry and administrative data, the project seeks to describe and quantify national/regional trends and variation in major complications (infection, dislocation, arthrofibrosis, chronic pain, venous thromboembolism, cardiac events), malignancy and health service utilisation (readmissions, emergency encounters and inpatient rehabilitation) following hip, knee and shoulder joint replacement surgery. Evidence will be generated on how these outcomes are associated with and vary according to patient, surgical, implant, hospital and pharmacological factors. As Australia lacks a national identifier, seven linkage agencies are probabilistically linking AOANJRR hip, knee and shoulder replacement data (1999-2017) with 20 datasets. Datasets include government-subsidised health services, procedural and prescription data. Hospital separations and emergency attendance data from Australia’s eight jurisdictions together with national cancer registry and rehabilitation service data are also planned for linkage. Linked data are maintained in a secure remote access computing environment. ResultsTo date, national Medicare Benefits Schedule, Pharmaceutical Benefits Scheme and the Australian Cancer Database data have been linked with >900,000 AOANJRR patients, representing 607.6 million health service records (1999-2018), 467.7 million prescriptions (2002-2018) and 184,000 cancer records, respectively. Remaining linked data will be available in mid-2020. So

IntroductionInfection is a major complication following joint replacement (JR) surgery. However, little data exist on baseline use of antibiotics following primary JR and how use changes with subsequent revision surgery. Objectives & ApproachOur study objectives were to describe community use of antibiotics before and after primary total hip replacement (THR) and change in use pre and post revision procedure. Registry data were linked with national medication dispensing data using probabilistic record linkage. Patients with THR for osteoarthritis in a private hospital between 1999 and 2017 were included. Three groups were analysed: patients with primary procedures revised for infection, revised for non-infection reasons and those not revised. Rate of antibiotic dispensing/month was calculated as number of patients dispensed at least one antibiotic in a given month divided by number of patients at-risk. ResultsThere were 102,577 patients included in the non-revised group, 3,156 revised for non-infection and 520 revised for infection. Prior to primary THR, baseline antibiotic dispensing rate was 9-11%/month in all groups. Post-primary rates were similar (10-11%) for non-revised and revised non-infection patients but higher (16-17%) for revised-infection patients. In 1, 6 and 12 months preceding revision for infection, antibiotic use was 55%, 27% and 22%, respectively. For patients revised for non-infection, antibiotic use was 21%, 14%, 13%, respectively. One-month following revision for infection, 82% of patients were dispensed antibiotics, remaining high (38%) at 6-months and 28% at 12-months. In the revision non-infection group, antibiotic use was 48% first month post-surgery, reducing rapidly to 15% at 6-months. Conclusion / ImplicationsNon-revision and revision non-infection patients had similar antibiotic dispensing before and after surgery. Revision infection patients however, maintained higher antibiotic dispensing post-primary, pre

BACKGROUND: To provide an estimate of the population at risk for late complications of arthroplasty, we aimed to determine the prevalence of Australians living with one or more joint replacements. METHODS: Data included all arthroplasty procedures performed in Australia from 2003 to 2016 recorded by the Australian Orthopaedic Association National Joint Replacement Registry. The age- and gender-specific Australian population was obtained from the Australian Bureau of Statistics and used as denominator data. Survival data for each joint replacement, and of individuals, were used to estimate the arthroplasty prevalence. Analyses by age, gender and joint replacement site were undertaken. Prevalence estimates were augmented with procedural data captured before 2003 modelled with assumptions accounting for age and gender distributions, overall survival and arthroplasty revision rates. RESULTS: By the end of 2016, there were 824 769 Australians living with at least one joint replacement, representing 3.4% of the total population. The prevalence of joint replacement is increasing in all age groups, but was highest amongst older Australians, with an overall prevalence of 22.5%, and 13.3% in those aged >85 years and 65-84 years, respectively. The prevalence of people living with multiple joint replacements is increasing more rapidly than patients who have undergone only one joint replacement procedure. CONCLUSION: The prevalence of older Australians living with joint replacements is rapidly increasing, providing an estimate of the population-at-risk for late complications of arthroplasty including peri-prosthetic infection and fracture.

BACKGROUND: Total hip arthroplasty (THA) is traditionally associated with a low complication rate, with complications such as infection, fracture and dislocation requiring readmission or reoperation. We seek to identify the complication rate among the anterior, direct lateral and posterior surgical approaches. METHODS: We reviewed all THAs performed at the Epworth Healthcare from 1 July 2014 to 30 June 2016. There were 2437 THAs performed by a variety of approaches. No hips were excluded from this study. We surveyed the hospital database and the Australian Orthopaedic Association National Joint Replacement Registry (AOANJRR) to identify those patients who had been readmitted and/or reoperated on. Details collected included age, gender, laterality of the surgery (left/right/bilateral), surgical approach utilised, complications which occurred. RESULTS: There were 29 peri-prosthetic fractures detected (13 anterior, 9 lateral, 7 posterior) and 10 underwent revision of implant, 19 were fixed. The increased rate of revision in the anterior group was statistically significant. There were 14 dislocations (5 anterior, 1 lateral, 8 posterior) of which 8 prostheses were revised. Three cases operated via the anterior approach and 1 by the lateral had early subsidence without fracture, necessitating revision of the femoral prostheses. Operative site infection occurred in 12 cases (2 anterior, 4 lateral, 6 posterior) with 6 requiring revision of implants. CONCLUSION: The complication rates between the 3 main approaches are similar, but individual surgeons should be vigilant for complications unique to their surgical approaches, such as femoral fractures in the anterior approach and dislocations in the posterior approach.

BACKGROUND: We aimed to measure the period effect (change over time) in 30-day mortality after total hip arthroplasty (THA) and total knee arthroplasty (TKA) using data from the Australian Orthopaedic Association National Joint Replacement Registry. METHODS: We performed an observational study using national registry data from all hospitals performing THA and TKA in Australia including people undergoing primary elective conventional THA and TKA for osteoarthritis from 2003 to 2017, inclusive. Data from the Australian Orthopaedic Association National Joint Replacement Registry, the National Death Index and the Australian Bureau of Statistics were used to generate unadjusted 30-day mortality, the incident rate ratio for mortality adjusted for age and gender, and the standardized mortality ratio at 30 days for each year separately. RESULTS: For the years 2003 and 2017, respectively, for THA, the unadjusted 30-day mortality was 0.23% and 0.06%, and the standardized mortality ratio was 1.11 (95% CI: 0.73, 1.49) and 0.38 (95% CI: 0.16, 0.59). The incident rate ratio was significantly higher than the reference year (2017) from 2003 to 2010, and for 2012, 2013 and 2016, decreasing over time. For the years 2003 and 2017, respectively, for TKA, the unadjusted 30-day mortality was 0.17% and 0.08%, and the standardized mortality ratio was 0.84 (95% CI: 0.55, 1.13) and 0.61 (95% CI: 0.38, 0.83). The incident rate ratio was significantly higher than the reference year (2017) from 2003 to 2009 inclusive, decreasing over time. CONCLUSIONS: Thirty-day mortality after THA and TKA declined from 2003 to 2017. This may be due to improvements in intra-operative and post-operative patient management.

BACKGROUND: Comprehensive national joint replacement registries with well-validated data offer unique opportunities for examining the potential future burden of hip and knee osteoarthritis (OA) at a population level. This study aimed to forecast the burden of primary total knee (TKR) and hip replacements (THR) performed for OA in Australia to the year 2030, and to model the impact of contrasting obesity scenarios on TKR burden. METHODS: De-identified TKR and THR data for 2003-2013 were obtained from the Australian Orthopaedic Association National Joint Replacement Registry. Population projections and obesity trends were obtained from the Australian Bureau of Statistics, with public and private hospital costs sourced from the National Hospital Cost Data Collection. Procedure rates were projected according to two scenarios: (1) constant rate of surgery from 2013 onwards; and (2) continued growth in surgery rates based on 2003-2013 growth. Sensitivity analyses were used to estimate future TKR burden if: (1) obesity rates continued to increase linearly; or (2) 1-5% of the overweight or obese population attained a normal body mass index. RESULTS: Based on recent growth, the incidence of TKR and THR for OA is estimated to rise by 276% and 208%, respectively, by 2030. The total cost to the healthcare system would be $AUD5.32 billion, of which $AUD3.54 billion relates to the private sector. Projected growth in obesity rates would result in 24,707 additional TKRs totalling $AUD521 million. A population-level reduction in obesity could result in up to 8062 fewer procedures and cost savings of up to $AUD170 million. CONCLUSIONS: If surgery trends for OA continue, Australia faces an unsustainable joint replacement burden by 2030, with significant healthcare budget and health workforce implications. Strategies to reduce national obesity could produce important TKR savings.

The aim of this study was to determine the association between patient-reported outcome measures (PROMs) six months following femoral neck fracture after a low fall and future arthroplasty, and the factors associated with this. Six-month post-fracture PROMs were collected from the Victorian Orthopaedic Trauma Outcomes Registry (VOTOR) for patients aged >55 years who were admitted for a femoral neck fracture after a low fall between March 2007 and June 2015. These cases were linked with those registered by Australian Orthopaedic Association National Joint Replacement Registry (AOANJRR) up to October 2016. Multivariable analysis was performed using a Cox proportional hazards model to determine factors associated with future arthroplasty, including six-month PROMs. Of the 7077 hip fracture patients registered by VOTOR during the study period, 2325 met the inclusion criteria. Internal fixation being used for the initial hip fracture surgery, being younger and having no pre-injury disability were all independently associated with future revision or conversion to arthroplasty. Out of all PROMs, reporting pain and discomfort six months post-fracture was associated with a 9.5-fold increase in the risk of future arthroplasty (95% CI: 3.81, 23.67). The value of clinical registries can be enhanced via data linkage, in this case by using PROMs to predict arthroplasty following femoral neck fracture.

Total hip arthroplasty (THA) registers are established in several countries to collect data aiming to improve the results after THA. Monitoring of adverse outcomes after THA has focused mainly on revision surgery, but patient-reported outcomes have also been investigated.Several surgery-related factors influencing the survival of the THA have been thoroughly investigated and have changed clinical practice. These factors include surgical approach, specific implants, the size of the components, type of fixation and different bone cements.Register data have been used to examine the risk of venous thromboembolism and bleeding after THA. These investigations have resulted in shorter duration of thromboprophylaxis and a reduced frequency of blood transfusion.Registers may provide specific information to surgeons on the outcome of all THAs that they have performed with a detailed analysis of revisions rates and reasons for the revisions.A number of other stakeholders can use register data to provide benchmarks. The National Joint Registry for England, Wales, Northern Ireland and the Isle of Man supplies data to the Orthopaedic Device Evaluation Panel (ODEP), which provides benchmarks at 3, 5, 7, 10, and 13 years graded from A*, A, B and C.Future perspectives: National registers have to play a major role in documenting the quality of THA in order to describe best practice and report implant outliers. The registers have to be used for research and post-market surveillance and register data may be a source for intelligent decision tools. Cite this article: EFORT Open Rev 2019;4 DOI: 10.1302/2058-5241.4.180091.

BACKGROUND: This study determined the contributing factors of hospital sector (private versus public) variation in revision rates after elective total hip replacement (THR) for hip fracture, and elective total knee replacement (TKR). METHODS: Using data from a large national arthroplasty registry, funnel plots for hospitals were generated, displaying the proportion of revised primary procedures. The proportion of outliers for each distribution was defined as the proportion outside the upper 99.7% confidence limit. Survival analyses determined differences between hospital sector revision rates separately for implants with the lowest revision rate, and for all other implants. Multivariate Cox regression determined the role of hospital sector in revision, adjusting for possible confounders. RESULTS: For THR performed for osteoarthritis, 17.4% of private and 4.4% of public hospitals were outliers. For TKR performed for osteoarthritis, 19.6% of private and 10.0% of public hospitals were outliers. For THR for fractured neck of femur, 8.1% of private and 0.0% of public hospitals were outliers. Adjusted and unadjusted Kaplan-Meier analyses showed higher THR revision rates in private hospitals for osteoarthritis and fractured neck of femur, but no difference when restricted to the 10 prostheses with the lowest revision rate. The Kaplan-Meier analysis of TKR showed higher revision rates for private hospitals, with the association reversing when restricted to prostheses with the lowest revision rate. CONCLUSIONS: Considerable variation was seen in the revision rate after THR and TKR between hospital sectors in Australia. The variation was largely due to differences in prosthesis selection.

BACKGROUND: Periprosthetic femur fractures (PFFs) following hip arthroplasty can lead to significant morbidity due to their impact on mobility and the need for surgery. Its incidence often measured by the prosthesis revision rate reported in joint replacement registries. However, many PFFs are also treated with prosthesis retention and internal fixation. Minimally displaced and stable fractures may be treated without surgery. Knowledge of the difference between the number of femoral revisions for PFF (well reported in registries) and the number of surgeries for PFF overall would allow us to estimate the overall surgical burden. This study aims to determine the number of post-operative PFF in three hospitals and compare those treated with revision surgery to those PFF treated with internal fixation and femoral stem retention. By determining this difference, we can ascertain a more accurate estimate of the overall surgical burden of PFF. METHOD: Patients 50 years and older who sustained a post-operative PFF between 1 January 2011 and 31 December 2017 at three public hospitals were extracted from hospital records. The number of revision procedures was compared to the number of re-operations of any type. RESULTS: There were 200 patients admitted for management of PFF. One hundred and forty-three (71.5%) required an operation of which 67 (47%) were revision arthroplasty. CONCLUSION: The overall surgical burden of PFF is approximately twice that represented by the revision rate.

BACKGROUND: Studies have described different recovery profiles of sevoflurane and desflurane typically early after surgery. METHODS: We conducted a randomized superiority trial to determine whether Overall Recovery 3 days after knee arthroscopy would be superior with desflurane. Adult participants undergoing knee arthroscopic surgery with general anesthesia were randomized to either desflurane or sevoflurane general anesthesia. Intraoperative and postoperative drugs and analgesics were administered at the discretion of the anesthesiologist. Postoperative quality of recovery was assessed using the "Postoperative Quality of Recovery Scale". The primary outcome was Overall Recovery 3 days after surgery and secondary outcomes were individual recovery domains at 15 minutes, 40 minutes, 1 day, 3 days, 1 month, and 3 months. Patients and researchers were blinded. RESULTS: 300 patients were randomized to sevoflurane or desflurane (age 51.7±14.1 vs. 47.3±13.5 years; duration of anesthesia 24.9±11.1 vs. 23.3±8.3 minutes). The proportion achieving baseline or better scores in all domains increased over the follow-up period in both groups but was not different at day 3 (sevoflurane 43% vs. desflurane 37%, p = 0.314). Similarly, rates of recovery increased over time in the five subdomains, with no differences between groups for physiological, p = 0.222; nociceptive, p = 0.391; emotive, p = 0.30; Activities-of-daily-living, p = 0.593; and cognitive recovery, p = 0.877. CONCLUSION: No significant difference in the quality of recovery scale could be shown using sevoflurane or desflurane general anesthesia after knee arthroscopy in adult participants.