Aims. The aim of this study was to identify modifiable risk factors associated with mortality in patients requiring revision total hip arthroplasty (THA) for periprosthetic hip fracture. Methods. The electronic records of consecutive patients undergoing revision THA for periprosthetic hip fracture between December 2011 and October 2018 were reviewed. The data which were collected included age, sex, body mass index (BMI), American Society of Anesthesiologists (ASA) classification, the preoperative serum level of haemoglobin, time to surgery, operating time, blood transfusion, length of hospital stay, and postoperative surgical and medical complications. Univariate and multivariate logistic regression analyses were used to determine independent modifiable factors associated with mortality at 90 days and one year postoperatively. Results. A total of 203 patients were identified. Their mean age was 78 years (44 to 100), and 108 (53%) were female. The median time to surgery was three days (interquartile range (IQR) 2 to 5). The mortality rate at one year was 13.8% (n = 28). The commonest surgical complication was dislocation (n = 22, 10.8%) and the commonest medical complication within 90 days of surgery was hospital-acquired pneumonia (n = 25, 12%). Multivariate analysis showed that the rate of mortality one year postoperatively was five-fold higher in patients who sustained a dislocation (odds ratio (OR) 5.03 (95% confidence interval (CI) 1.60 to 15.83); p = 0.006). The rate of mortality was also four-fold higher in patients who developed hospital-acquired pneumonia within 90 days postoperatively (OR 4.43 (95% CI 1.55 to 12.67); p = 0.005). There was no evidence that the time to surgery was a risk factor for death at one year. Conclusion. Dislocation and hospital-acquired pneumonia following revision THA for a periprosthetic fracture are potentially modifiable risk factors for mortality. This study suggests that surgeons should consider increasing constraint to reduce the risk of dislocation, and the early involvement of a multidisciplinary team to reduce the risk of hospital-acquired pneumonia. We found no evidence that the time to surgery affected mortality, which may allow time for medical optimization, surgical planning, and resource allocation. Cite this article: Bone Joint J 2020;102-B(5):580–585

Aims

The impact of tobacco use on readmission and medical and surgical complications has been documented in hip and knee arthroplasty. However, there remains little information about the effect of smoking on the outcome after total shoulder arthroplasty (TSA). We hypothesized that active smokers are at an increased risk of poor medical and surgial outcomes after TSA.

Aims

To date, no study has demonstrated an improvement in postoperative outcomes following elective joint arthroplasty with a focus on nutritional intervention for patients with preoperative hypoalbuminaemia. In this prospective study, we evaluated differences in the hospital length of stay (LOS), rate of re-admission, and total patient charges for a malnourished patient study population who received a specific nutrition protocol before surgery.

There is growing interest in the peri-operative management of patients with indications for hip and knee arthroplasty in the setting of modifiable risk factors such as morbid obesity, type 2 diabetes mellitus, and smoking. A recent survey of the American Association of Hip and Knee Surgeons (AAHKS) found that 95% of respondents address modifiable risk factors prior to surgery. The aim of this study was to poll Australian arthroplasty surgeons regarding their approach to patients with modifiable risk factors. The survey tool used in the AAHKS study was adapted for use in the Australian context and distributed to the membership of the Arthroplasty Society of Australia via Survey Monkey. Seventy-seven survey responses were received, representing a response rate of 64%. The majority of respondents were experienced, high volume arthroplasty surgeons. Overall, 91% of respondents restricted access to arthroplasty for patients with modifiable risk factors. Seventy-two percent of surgeons restricted access for excessive body mass index, 85% for poor diabetic control, and 46% for smoking. Most respondents made decisions based on personal experience or literature review rather than hospital or departmental pressures. Despite differences in healthcare systems, our findings were similar to those of the AAHKS survey, although their responses were more restrictive in all domains. Differences were noted in responses concerning financial considerations for potentially underprivileged populations. The survey is currently being administered by arthroplasty societies in six other countries, allowing comparison of orthopaedic practice across different healthcare systems around the world. In conclusion, over 90% of Australian arthroplasty surgeons who responded to the survey address modifiable risk factors prior to surgery

Aims. Postoperative complication rates remain relatively high after adult spinal deformity (ASD) surgery. The extent to which modifiable patient-related factors influence complication rates in patients with ASD has not been effectively evaluated. The aim of this retrospective cohort study was to evaluate the association between modifiable patient-related factors and complications after corrective surgery for ASD. Methods. ASD patients with two-year data were included. Complications were categorized as follows: any complication, major, medical, surgical, major mechanical, major radiological, and reoperation. Modifiable risk factors included smoking, obesity, osteoporosis, alcohol use, depression, psychiatric diagnosis, and hypertension. Patients were stratified by the degree of baseline deformity (low degree of deformity (LowDef)/high degree of deformity (HighDef): below or above 20°) and age (Older/Younger: above or below 65 years). Complication rates were compared for modifiable risk factors in each age/deformity group, using multivariable logistic regression analysis to adjust for confounders. Results. A total of 480 ASD patients met the inclusion criteria. By two years, complication rates were 72% ≥ one complication, 28% major, 21% medical, 27% surgical, 11% major radiological, 8% major mechanical, and 22% required reoperation. Younger LowDef patients with osteoporosis were more likely to suffer either a major mechanical (odds ratio (OR) 5.9 (95% confidence interval (CI) 1.1 to 36.9); p = 0.048) or radiological complication (OR 7.0 (95% CI 1.9 to 25.9); p = 0.003). Younger HighDef patients were much more likely to develop complications if obese, especially major mechanical complications (OR 2.8 (95% CI 1.1 to 8.6); p = 0.044). Older HighDef patients developed more complications when diagnosed with depression, including major radiological complications (OR 3.5 (95% CI 1.1 to 10.6); p = 0.033). Overall, a diagnosis of depression proved to be a risk factor for the development of major radiological complications (OR 2.4 (95% CI 1.3 to 4.5); p = 0.005). Conclusion. Certain modifiable patient-related factors, especially osteoporosis, obesity, and mental health status, are associated with an increased risk of complications after surgery for spinal deformity. Surgeons should look for these conditions when assessing a patient for surgery, and optimize them to the fullest extent possible before proceeding to surgical correction so as to minimize the prospect of postoperative morbidity. Cite this article: Bone Joint J 2022;104-B(11):1249–1255

Aims. Prosthetic joint infection (PJI) remains a serious complication that is associated with high morbidity and costs. The aim of this study was to prepare a systematic review to examine patient-related and perioperative risk factors that can be modified in an attempt to reduce the rate of PJI. Materials and Methods. A search of PubMed and MEDLINE was conducted for articles published between January 1990 and February 2018 with a combination of search terms to identify studies that dealt with modifiable risk factors for reducing the rate of PJI. An evidence-based review was performed on 12 specific risk factors: glycaemic control, obesity, malnutrition, smoking, vitamin D levels, preoperative Staphylococcus aureus screening, the management of anti-rheumatic medication, perioperative antibiotic prophylaxis, presurgical skin preparation, the operating room environment, irrigant options, and anticoagulation. Results. Poor glycaemic control, obesity, malnutrition, and smoking are all associated with increased rates of PJI. Vitamin D replacement has been shown in preliminary animal studies to decrease rates of PJI. Preoperative Staphylococcus aureus screening and appropriate treatment results in decreased rates of PJI. Perioperative variables, such as timely and appropriate dosage of prophylactic antibiotics, skin preparation with chlorohexidine-based solution, and irrigation with dilute betadine at the conclusion of the operation, have all been associated with reduced rates of PJI. Similarly, aggressive anticoagulation and increased operating room traffic should be avoided to help minimize risk of PJI. Conclusion. PJI remains a serious complication of arthroplasty. Surgeons should be vigilant of the modifiable risk factors that can be addressed in an attempt to reduce the risk of PJI

Aims. 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. Methods. 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. Results. Among the 1,249 patients, a piecewise GMM model revealed three distinct pain trajectory groups: 56 patients (4.5%) in group 1; 1,144 patients (91.6%) in group 2; and 49 patients (3.9%) in group 3. Patients in group 2 experienced swift recovery post-THA and minimal preoperative pain. In contrast, groups 1 and 3 initiated with pronounced preoperative pain; however, only group 3 exhibited persistent long-term pain. Multinomial regression indicated African Americans were exceedingly likely to follow trajectory groups 1 (odds ratio (OR) 2.73) and 3 (OR 3.18). Additionally, odds of membership to group 3 increased by 12% for each BMI unit rise, by 19% for each added postoperative day, and by over four if discharged to rehabilitation services (OR 4.07). Conclusion. This study identified three distinct pain trajectories following THA, highlighting the role of individual patient factors in postoperative recovery. This emphasizes the importance of preoperatively addressing modifiable risk factors associated with suboptimal pain trajectories, particularly in at-risk patients. Cite this article: Bone Jt Open 2024;5(3):174–183

Aims. The aim of this study was to perform a systematic review and bias evaluation of the current literature to create an overview of risk factors for re-revision following revision total knee arthroplasty (rTKA). Methods. A systematic search of MEDLINE and Embase was completed in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines. The studies were required to include a population of index rTKAs. Primary or secondary outcomes had to be re-revision. The association between preoperative factors and the effect on the risk for re-revision was also required to be reported by the studies. Results. The search yielded 4,847 studies, of which 15 were included. A majority of the studies were retrospective cohorts or registry studies. In total, 26 significant risk factors for re-revision were identified. Of these, the following risk factors were consistent across multiple studies: age at the time of index revision, male sex, index revision being partial revision, and index revision due to infection. Modifiable risk factors were opioid use, BMI > 40 kg/m. 2. , and anaemia. History of one-stage revision due to infection was associated with the highest risk of re-revision. Conclusion. Overall, 26 risk factors have been associated with an increased risk of re-revision following rTKA. However, various levels of methodological bias were found in the studies. Future studies should ensure valid comparisons by including patients with identical indications and using clear definitions for accurate assessments. Cite this article: Bone Jt Open 2024;5(8):644–651

Aims. Hip fracture commonly affects the frailest patients, of whom many are care-dependent, with a disproportionate risk of contracting COVID-19. We examined the impact of COVID-19 infection on hip fracture mortality in England. Methods. We conducted a cohort study of patients with hip fracture recorded in the National Hip Fracture Database between 1 February 2019 and 31 October 2020 in England. Data were linked to Hospital Episode Statistics to quantify patient characteristics and comorbidities, Office for National Statistics mortality data, and Public Health England’s SARS-CoV-2 testing results. Multivariable Cox regression examined determinants of 90-day mortality. Excess mortality attributable to COVID-19 was quantified using Quasi-Poisson models. Results. Analysis of 102,900 hip fractures (42,630 occurring during the pandemic) revealed that among those with COVID-19 infection at presentation (n = 1,120) there was a doubling of 90-day mortality; hazard ratio (HR) 2.09 (95% confidence interval (CI) 1.89 to 2.31), while the HR for infections arising between eight and 30 days after presentation (n = 1,644) the figure was greater at 2.51 (95% CI 2.31 to 2.73). Malnutrition (1.45 (95% CI 1.19 to 1.77)) and nonoperative treatment (2.94 (95% CI 2.18 to 3.95)) were the only modifiable risk factors for death in COVID-19-positive patients. Patients who had tested positive for COVID-19 more than two weeks prior to hip fracture initially had better survival compared to those who contracted COVID-19 around the time of their hip fracture; however, survival rapidly declined and by 365 days the combination of hip fracture and COVID-19 infection was associated with a 50% mortality rate. Between 1 January and 30 June 2020, 1,273 (99.7% CI 1,077 to 1,465) excess deaths occurred within 90 days of hip fracture, representing an excess mortality of 23% (99.7% CI 20% to 26%), with most deaths occurring within 30 days. Conclusion. COVID-19 infection more than doubles the rate of early hip fracture mortality. Those contracting infection between 8 and 30 days after initial presentation are at even higher mortality risk, signalling the potential for targeted interventions during this period to improve survival. Cite this article: Bone Joint J 2022;104-B(10):1156–1167

Aims. Periprosthetic fractures (PPFs) around the knee are challenging injuries. This study aims to describe the characteristics of knee PPFs and the impact of patient demographics, fracture types, and management modalities on in-hospital mortality. Methods. Using a multicentre study design, independent of registry data, we included adult patients sustaining a PPF around a knee arthroplasty between 1 January 2010 and 31 December 2019. Univariate, then multivariable, logistic regression analyses were performed to study the impact of patient, fracture, and treatment on mortality. Results. Out of a total of 1,667 patients in the PPF study database, 420 patients were included. The in-hospital mortality rate was 6.4%. Multivariable analyses suggested that American Society of Anesthesiologists (ASA) grade, history of peripheral vascular disease (PVD), history of rheumatic disease, fracture around a loose implant, and cerebrovascular accident (CVA) during hospital stay were each independently associated with mortality. Each point increase in ASA grade independently correlated with a four-fold greater mortality risk (odds ratio (OR) 4.1 (95% confidence interval (CI) 1.19 to 14.06); p = 0.026). Patients with PVD have a nine-fold increase in mortality risk (OR 9.1 (95% CI 1.25 to 66.47); p = 0.030) and patients with rheumatic disease have a 6.8-fold increase in mortality risk (OR 6.8 (95% CI 1.32 to 34.68); p = 0.022). Patients with a fracture around a loose implant (Unified Classification System (UCS) B2) have a 20-fold increase in mortality, compared to UCS A1 (OR 20.9 (95% CI 1.61 to 271.38); p = 0.020). Mode of management was not a significant predictor of mortality. Patients managed with revision arthroplasty had a significantly longer length of stay (median 16 days; p = 0.029) and higher rates of return to theatre, compared to patients treated nonoperatively or with fixation. Conclusion. The mortality rate in PPFs around the knee is similar to that for native distal femur and neck of femur fragility fractures. Patients with certain modifiable risk factors should be optimized. A national PPF database and standardized management guidelines are currently required to understand these complex injuries and to improve patient outcomes. Cite this article: Bone Joint J 2024;106-B(2):158–165

Aims. Periprosthetic hip fractures (PPFs) after total hip arthroplasty are difficult to treat. Therefore, it is important to identify modifiable risk factors such as stem selection to reduce the occurrence of PPFs. This study aimed to clarify differences in fracture torque, surface strain, and fracture type analysis between three different types of cemented stems. Methods. We conducted biomechanical testing of bone analogues using six cemented stems of three different types: collarless polished tapered (CPT) stem, Versys Advocate (Versys) stem, and Charnley-Marcel-Kerboull (CMK) stem. Experienced surgeons implanted each of these types of stems into six bone analogues, and the analogues were compressed and internally rotated until failure. Torque to fracture and fracture type were recorded. We also measured surface strain distribution using triaxial rosettes. Results. There was a significant difference in fracture torque between the three stem types (p = 0.036). Particularly, the median fracture torque for the CPT stem was significantly lower than that for the CMK stem (CPT vs CMK: 164.5 Nm vs 200.5 Nm; p = 0.046). The strain values for the CPT stem were higher than those for the other two stems at the most proximal site. The fracture pattern of the CPT and Versys stems was Vancouver type B, whereas that of the CMK stem was type C. Conclusion. Our study suggested that the cobalt-chromium alloy material, polished surface finish, acute-square proximal form, and the absence of a collar may be associated with lower fracture torque, which may be related to PPF. Cite this article: Bone Joint Res 2022;11(5):270–277

Infection following primary total knee arthroplasty (TKA) is fortunately a relatively uncommon complication with an incidence of approximately 1%. However, because the morbidity and cost of treatment of deep prosthetic TKA infections is so high, effective prevention strategies are key quality improvement initiatives. The cause of post-operative infections are multifactorial and complex but can generally be categorised into 1) host, 2) surgical, and 3) environmental factors. The purpose of this abstract to provide an outline of these factors and their influences on the infection risk following TKA. Patient factors and optimization of modifiable risk factors have been shown to decrease the risk for infection. While the individual contributions of factors such as body mass index (BMI), diabetes, nutritional status, Charlson Comorbidity Index (CCI), and renal disease are unknown, together, they have been shown to influence infection risk. Additionally, Tayton et al. analyzed 64,566 primary TKAs in the New Zealand Joint Registry and found that male gender and prior knee surgery were also independent risk factors of development of PJI 12 months following TKA. Finally, Crowe and colleagues also identified tobacco use and Staphylococcus aureus colonization as modifiable risk factors for minimizing PJI following primary TKA. Timely administration of prophylactic antibiotics prior and after surgery has been shown to be the most effective strategy to reduce infection risk. The optimal prophylaxis regimen for all patients is unknown and in certain situations, administration of Vancomycin in additional to a conventional cephalosporin may be beneficial. However, universal administration of Vancomycin has not been shown to decrease the incidence of surgical site infections and could actually increase the risk for renal failure. Conversely, addition of antibiotics to cement during primary TKA has not been shown to reduce long term infection risk. The use of dilute betadine lavage has been shown by some authors to be beneficial. Finally, good surgical technique, proper soft tissue handling, and meticulous wound closure are all critical factors influencing the risk for infectious complications following TKA. Environmental factors have also been shown to affect infection rates following TKA. While the use of laminar flow and body exhaust suits have not been shown to significantly influence the risk for infection, minimizing operating room traffic has been shown effective in reducing the risk for contamination. Some authors have shown ultraviolet light systems to decrease airborne contaminants. In summary, factors influencing infection risk following TKA are complex and multifactorial. Patient selection, optimization of modifiable risk factors, appropriate use of antibiotics, and minimization of OR traffic are among the most common strategies to minimizing infection

Aims. This study aimed to identify risk factors (patient, healthcare system, and socioeconomic) for mortality after hip fractures and estimate their relative importance. Further, we aimed to elucidate mortality and survival patterns following fractures and the duration of excess mortality. Methods. Data on 37,394 hip fractures in the Norwegian Hip Fracture Register from January 2014 to December 2018 were linked to data from the Norwegian Patient Registry, Statistics Norway, and characteristics of acute care hospitals. Cox regression analysis was performed to estimate risk factors associated with mortality. The Wald statistic was used to estimate and illustrate relative importance of risk factors, which were categorized in modifiable (healthcare-related) and non-modifiable (patient-related and socioeconomic). We calculated standardized mortality ratios (SMRs) comparing deaths among hip fracture patients to expected deaths in a standardized reference population. Results. Mean age was 80.2 years (SD 11.4) and 67.5% (n = 25,251) were female. Patient factors (male sex, increasing comorbidity (American Society of Anesthesiologists grade and Charlson Comorbidity Index)), socioeconomic factors (low income, low education level, living in a healthcare facility), and healthcare factors (hip fracture volume, availability of orthogeriatric services) were associated with increased mortality. Non-modifiable risk factors were more strongly associated with mortality than modifiable risk factors. The SMR analysis suggested that cumulative excess mortality among hip fracture patients was 16% in the first year and 41% at six years. SMR was 2.48 for the six-year observation period, most pronounced in the first year, and fell from 10.92 in the first month to 3.53 after 12 months and 2.48 after six years. Substantial differences in median survival time were found, particularly for patient-related factors. Conclusion. Socioeconomic, patient-, and healthcare-related factors all contributed to excess mortality, and non-modifiable factors had stronger association than modifiable ones. Hip fractures contributed to substantial excess mortality. Apparently small survival differences translate into substantial disparity in median survival time in this elderly population. Cite this article: Bone Joint J 2022;104-B(7):884–893

Introduction. Many patients with obesity experience knee pain. Excess body weight is a modifiable risk factor for osteoarthritis (OA) and weight loss is encouraged in patients with OA. Bariatric surgery could improve or limit the progression of these conditions through significant weight loss. The Oxford Knee Score (OKS) is a validated tool in the assessment of knee replacement surgery for OA. We present a novel application of the OKS to assess knee pain & function after weight loss surgery. The primary aim of this study was to assess whether there was a significant difference in mean OKS before and 24 months after weight loss surgery. Method. Eighteen female participants were included in this study. They underwent sleeve gastrectomy or Roux-en-Y gastric bypass. Patient demographics, body mass index (BMI) and OKS were collected pre- and 24 months post operatively. Result. There was an increase in the mean OKS from 31.8 (SD 11.8) pre surgery to 36.6 (SD 12.3) at 24 months. This was statistically significant (95% CI 0.99-10.5, p=0.02). Mean BMI reduced from 46.6 kg/m. 2. (SD 5.8) to 33.0 kg/m. 2. (SD 3.5). Conclusion. A significant improvement in mean OKS was seen after weight loss surgery. These findings demonstrate an improvement in knee pain & function with weight loss. This study contributes to a larger project evaluating the kinetic and kinematic changes to walking gait from weight loss

Infection following primary total knee arthroplasty (TKA) is fortunately a relatively uncommon complication with an incidence of approximately 1%. However, because the morbidity and cost of treatment of deep prosthetic TKA infections is so high, effective prevention strategies are key quality improvement initiatives. The cause of post-operative infections are multifactorial and complex but can generally be categorised into 1) host, 2) surgical, and 3) environmental factors. The purpose of this abstract is to provide an outline of these factors and their influences on the infection risk following TKA. Patient factors and optimization of modifiable risk factors have been shown to decrease the risk for infection. While the individual contributions of factors such as body mass index (BMI), diabetes, nutritional status, Charlson Comorbidity Index (CCI), and renal disease are unknown, together, they have been shown to influence infection risk. Additionally, Tayton et al. analyzed 64,566 primary TKAs in the New Zealand Joint Registry and found that male gender and prior knee surgery were also independent risk factors of development of PJI 12 months following TKA. Finally, Crowe and colleagues also identified tobacco use and Staphylococcus aureus colonization as modifiable risk factors for minimizing PJI following primary TKA. Timely administration of prophylactic antibiotics prior and after surgery has been shown to be the most effective strategy to reduce infection risk. The optimal prophylaxis regimen for all patients is unknown and in certain situations, administration of Vancomycin in additional to a conventional cephalosporin may be beneficial. However, universal administration of Vancomycin has not been shown to decrease the incidence of surgical site infections and could actually increase the risk for renal failure. Conversely, addition of antibiotics to cement during primary TKA has not been shown to reduce long term infection risk. The use of dilute betadine lavage has been shown by some authors to be beneficial. Finally, good surgical technique, proper soft tissue handling, and meticulous wound closure are all critical factors influencing the risk for infectious complications following TKA. Environmental factors have also been shown to affect infection rates following TKA. While the use of laminar flow and body exhaust suits have not been shown to significantly influence the risk for infection, minimizing operating room traffic has been shown effective in reducing the risk for contamination. Some authors have shown ultraviolet light systems to decrease airborne contaminants. In summary, factors influencing infection risk following TKA are complex and multifactorial. Patient selection, optimization of modifiable risk factors, appropriate use of antibiotics, and minimization of OR traffic are among the most common strategies to minimizing infection

Abstract. Introduction. Acute kidney injury (AKI) is a common post-operative complication which, in turn, significantly increases risk of other post-operative complications and mortality. This quality improvement project (QIP) aimed to evaluate and implement measures to decrease the incidence of AKI in post-operative Trauma and Orthopaedics (T&O) patients. Methods. Three data collection cycles were conducted using all T&O patients admitted to a single UK West Midlands NHS trust across three six-month periods between December 2018 and December 2020 (n=8215). Patients developing a post-operative AKI were identified using the Acute Kidney Injury Network criteria. Data was collected for these patients including demographic details and AKI risk factors such as ASA grade, hypovolaemia and use of nephrotoxic medications. Results. The percentage of post-operative AKI decreased from 2% (71 patients from 5899 operations) in the first cycles to 1.5% (19 from 1273 operations) by the final cycle. There was a high prevalence of modifiable risk factors for AKI, including post-operative hypovolaemia (50%) and use of nephrotoxic aminoglycosides (81%). Measures implemented between cycles included a pre-operative medication review identifying nephrotoxic medications, early post-operative assessment for consideration of intravenous fluids and junior doctor teaching on fluid therapy. There was a substantial decrease in use of multiple nephrotoxic medications (98% to 59%) and in use of aminoglycosides (88% to 42%) between the final cycles which may explain the reduction in observed AKI incidence. Conclusion. This QIP highlights the benefits of a multifaceted approach in the peri-operative period, through targeting of risk factors in preventing post-operative AKI

Aims. 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. Methods. 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. Results. A total of 39,038 patients underwent primary TKA for osteoarthritis during the study period. Of these, 275 patients developed a deep SSI within 90 days of surgery, representing a cumulative incidence of 0.7%. The annual infection rate did not significantly decrease over the seven-year study period (p = 0.162). Overall, 13,885 (35.5%) cases were excluded from the risk analysis due to missing data. Risk factors associated with early-onset deep SSI included male sex, American Society of Anesthesiologists grade ≥ 3, blood transfusion, acute length of stay, and surgeon volume < 30 TKAs/year. Early-onset deep SSI was not associated with increased 90-day mortality. Conclusion. This study establishes a reliable baseline infection rate for early-onset deep SSI after TKA for osteoarthritis using robust Infection Prevention and Control surveillance data, and identifies several potentially modifiable risk factors. Cite this article: Bone Joint J 2023;105-B(9):971–976

Introduction. Weight is a modifiable risk factor for osteoarthritis (OA) progression. Despite the emphasis on weight loss, data quantifying the changes seen in joint biomechanics are limited. Bariatric surgery patients experience rapid weight loss. This provides a suitable population to study changes in joint forces and function as weight changes. Method. 10 female patients undergoing gastric bypass or sleeve gastrectomy completed 3D walking gait analysis at a self-selected pace, pre- and 6 months post-surgery. Lower limb and torso kinematic data for 10 walking trials were collected using a Vicon motion capture system and kinetics using a Kistler force plate. An inverse kinematic model in Visual 3D allowed for no translation of the hip joint centre. 6 degrees of freedom were allowed at other joints. Data were analysed using JASP with a paired samples t-test. Result. On average participants lost 28.8±7.60kg. No significant changes were observed in standing knee and hip joint angles. Walking velocity increased from 1.10±0.11 ms. -1. to 1.23±0.17 ms. -1. (t(9)=-3.060, p = 0.014) with no change in step time but a mean increase in stride length of 0.12m (SE: 0.026m; t(9)=-4.476, p = 0.002). A significant decrease of 21.5±4.2% in peak vertical ground reaction forces was observed (t(9)=12.863, p <0.001). Stride width significantly decreased by 0.04m (SE: 0.010m; t(9)=4.316, p = 0.002) along with a decrease in lateral impulse of 21.2Ns (SE: 6.977Ns; t(7), p = 0.019), but no significant difference in knee joint angles were observed. Double limb support time also significantly reduced by 0.02s (SE: 0.006s; t(9) = 3.639, p=0.005). Conclusion. The reduction in stance width and lateral impulse suggests a more sagittal compass-gait walk is being achieved. This would reduce valgus moments on the knee reducing loading in the medial compartment. The reduction in peak ground reaction force would reduce knee contact forces and again potentially slow OA progression

Aims. Using the Australian and New Zealand Hip Fracture Registry (ANZHFR) data, this study aimed to identify patient, fracture, and management factors associated with survival, mobility and residential status at 120 days. This will allow future interventions to target modifiable risk factors to improve the overall care of patients with hip fractures. Methods. All NZ patients from 2018 – 2020 were included. Baseline demographics, management factors, and outcomes were recorded. Key outcomes were change in walking status, residential status and survival at 120 days. Univariate analysis was performed to compare differences in demographics, surgical and management factors for the key variables. Multivariate analysis was conducted to identify factors independently associated with outcomes. Results. Data from 9432 patients were analysed. The average age was 82.8 years (SD 9.8). 70.3% were females. 39.5% of patients were cognitively impaired on admission, 71.4% were from their own residence. At 120 days post injury, 10.9% (1029) had died 1029 (10.9%), 15.3% (1034) had a decrease in their residential status, 44.9% (2966) had a reduction in walking ability. On multivariate analysis; older age (RR1.1/yr, p<0.001), male sex (RR1.7, P<0.001), cognitive impairment (RR2.2, p<0.001) and ASA>3 (RR3.7, p=0.015) were risk factors for death. Similarly, increasing age (RR1.1 per year, p<0.001), cognitive impairment (RR1.2, p=0.04) and ASA>3 (RR2.9, p=0.047) were significant risk factors for worsening residential status. Decreasing mobility was associated with extracapsular fractures (RR1.4, p=0.01). After adjustment for demographics, ASA and fracture type, performing total hip arthroplasty was preventative for both worsening residential status (RR0.23, p<0.001) and decreasing walking ability (RR 0.21, p<0.001). There was no significant survival, functional or revision differences for other fixation types. Conclusion. There is a significant decline in walking ability post hip fracture which may be a key contributor to long-term morbidity. The benefits of THA in preserving mobility and independence should be further investigated. Additional discharge planning and multi-disciplinary team input are likely required for high-risk patients of older age, with cognitive impairment and extracapsular fractures

Aims. The purpose of this study was to develop a personalized outcome prediction tool, to be used with knee arthroplasty patients, that predicts outcomes (lengths of stay (LOS), 90 day readmission, and one-year patient-reported outcome measures (PROMs) on an individual basis and allows for dynamic modifiable risk factors. Methods. Data were prospectively collected on all patients who underwent total or unicompartmental knee arthroplasty at a between July 2015 and June 2018. Cohort 1 (n = 5,958) was utilized to develop models for LOS and 90 day readmission. Cohort 2 (n = 2,391, surgery date 2015 to 2017) was utilized to develop models for one-year improvements in Knee Injury and Osteoarthritis Outcome Score (KOOS) pain score, KOOS function score, and KOOS quality of life (QOL) score. Model accuracies within the imputed data set were assessed through cross-validation with root mean square errors (RMSEs) and mean absolute errors (MAEs) for the LOS and PROMs models, and the index of prediction accuracy (IPA), and area under the curve (AUC) for the readmission models. Model accuracies in new patient data sets were assessed with AUC. Results. Within the imputed datasets, the LOS (RMSE 1.161) and PROMs models (RMSE 15.775, 11.056, 21.680 for KOOS pain, function, and QOL, respectively) demonstrated good accuracy. For all models, the accuracy of predicting outcomes in a new set of patients were consistent with the cross-validation accuracy overall. Upon validation with a new patient dataset, the LOS and readmission models demonstrated high accuracy (71.5% and 65.0%, respectively). Similarly, the one-year PROMs improvement models demonstrated high accuracy in predicting ten-point improvements in KOOS pain (72.1%), function (72.9%), and QOL (70.8%) scores. Conclusion. The data-driven models developed in this study offer scalable predictive tools that can accurately estimate the likelihood of improved pain, function, and quality of life one year after knee arthroplasty as well as LOS and 90 day readmission. Cite this article: Bone Joint J 2020;102-B(9):1183–1193