Aims. National hip fracture registries audit similar aspects of care but there is variation in the actual data collected; these differences restrict international comparison, benchmarking, and research. The Fragility Fracture Network (FFN) published a revised minimum common dataset (MCD) in 2022 to improve consistency and interoperability. Our aim was to assess compatibility of existing registries with the MCD. Methods. We compared 17 hip fracture registries covering 20 countries (Argentina; Australia and New Zealand; China; Denmark; England, Wales, and Northern Ireland; Germany; Holland; Ireland; Japan; Mexico; Norway; Pakistan; the Philippines; Scotland; South Korea; Spain; and Sweden), setting each of these against the 20 core and 12 optional fields of the MCD. Results. The highest MCD adherence was demonstrated by the most recently established registries. The first-generation registries in Scandinavia collect data for 60% of MCD fields, second-generation registries (UK, other European, and Australia and New Zealand) collect for 75%, and third-generation registries collect data for 85% of MCD fields. Five of the 20 core fields were collected by all 17 registries (age; sex; surgery date/time of operation; surgery type; and death during acute admission). Two fields were collected by most (16/17; 94%) registries (date/time of presentation and American Society of Anesthesiologists grade), and five more by the majority (15/17; 88%) registries (type, side, and pathological nature of fracture; anaesthetic modality; and discharge destination). Three core fields were each collected by only 11/17 (65%) registries: prefracture mobility/activities of daily living; cognition on admission; and bone protection medication prescription. Conclusion. There is moderate but improving compatibility between existing registries and the FFN MCD, and its introduction in 2022 was associated with an improved level of adherence among the most recently established programmes. Greater interoperability could be facilitated by improving consistency of data collection relating to prefracture function, cognition, bone protection, and follow-up duration, and this could improve international collaborative benchmarking, research, and quality improvement. Cite this article: Bone Joint J 2023;105-B(9):1013–1019

Data of high quality are critical for the meaningful interpretation of registry information. The National Joint Registry (NJR) was established in 2002 as the result of an unexpectedly high failure rate of a cemented total hip arthroplasty. The NJR began data collection in 2003. In this study we report on the outcomes following the establishment of a formal data quality (DQ) audit process within the NJR, within which each patient episode entry is validated against the hospital unit’s Patient Administration System and vice-versa. This process enables bidirectional validation of every NJR entry and retrospective correction of any errors in the dataset. In 2014/15 baseline average compliance was 92.6% and this increased year-on-year with repeated audit cycles to 96.0% in 2018/19, with 76.4% of units achieving > 95% compliance. Following the closure of the audit cycle, an overall compliance rate of 97.9% was achieved for the 2018/19 period. An automated system was initiated in 2018 to reduce administrative burden and to integrate the DQ process into standard workflows. Our processes and quality improvement results demonstrate that DQ may be implemented successfully at national level, while minimizing the burden on hospitals. Cite this article: Bone Jt Open 2022;3(9):716–725

Aims. Supracondylar fractures are the most frequently occurring paediatric fractures about the elbow and may be associated with a neurovascular injury. The British Orthopaedic Association Standards for Trauma 11 (BOAST 11) guidelines describe best practice for supracondylar fracture management. This study aimed to assess whether emergency departments in the United Kingdom adhere to BOAST 11 standard 1: a documented assessment, performed on presentation, must include the status of the radial pulse, digital capillary refill time, and the individual function of the radial, median (including the anterior interosseous), and ulnar nerves. . Materials and Methods. Stage 1: We conducted a multicentre, retrospective audit of adherence to BOAST 11 standard 1. Data were collected from eight hospitals in the United Kingdom. A total of 433 children with Gartland type 2 or 3 supracondylar fractures were eligible for inclusion. A centrally created data collection sheet was used to guide objective analysis of whether BOAST 11 standard 1 was adhered to. Stage 2: We created a quality improvement proforma for use in emergency departments. This was piloted in one of the hospitals used in the primary audit and was re-audited using equivalent methodology. In all, 102 patients presenting between January 2016 and July 2017 were eligible for inclusion in the re-audit. Results. Stage 1: Of 433 patient notes audited, adherence to BOAST 11 standard 1 was between 201 (46%) and 232 (54%) for the motor and sensory function of the individual nerves specified, 318 (73%) for radial pulse, and 247 (57%) for digital capillary refill time. Stage 2: Of 102 patient notes audited, adherence to BOAST 11 standard 1 improved to between 72 (71%) and 80 (78%) for motor and sensory function of the nerves, to 84 (82%) for radial pulse, and to 82 (80%) for digital capillary refill time. Of the 102 case notes reviewed in stage 2, only 44 (43%) used the quality improvement proforma; when the proforma was used, adherence improved to between 40 (91%) and 43 (98%) throughout. Conclusion. Adherence to BOAST 11 standard 1 is poor in hospitals across the country. This is concerning as neurovascular deficit may be an indication for emergent surgery, and missed neurovascular injury can cause long-term, or even permanent, functional impairment. We present a simple proforma that improves adherence to this standard, can easily be implemented into emergency departments, and may improve patient safety. Cite this article: Bone Joint J 2018;100-B:346–51

Aims

Elective orthopaedic surgery was cancelled early in the COVID-19 pandemic and is currently running at significantly reduced capacity in most institutions. This has resulted in a significant backlog to treatment, with some hospitals projecting that waiting times for arthroplasty is three times the pre-COVID-19 duration. There is concern that the patient group requiring arthroplasty are often older and have more medical comorbidities—the same group of patients advised they are at higher risk of mortality from catching COVID-19. The aim of this study is to investigate the morbidity and mortality in elective patients operated on during the COVID-19 pandemic and compare this to a pre-pandemic cohort. Primary outcome was 30-day mortality. Secondary outcomes were perioperative complications, including nosocomial COVID-19 infection. These operations were performed in a district general hospital, with COVID-19 acute admissions in the same building.

Aims

The aim of this study is to assess the impact of a pilot enhanced recovery after surgery (ERAS) programme on length of stay (LOS) and post-discharge resource usage via service evaluation and cost analysis.

Aims

Surgical costs are a major component of healthcare expenditures in the USA. Intraoperative communication is a key factor contributing to patient outcomes. However, the effectiveness of communication is only partially determined by the surgeon, and understanding how non-surgeon personnel affect intraoperative communication is critical for the development of safe and cost-effective staffing guidelines. Operative efficiency is also dependent on high-functioning teams and can offer a proxy for effective communication in highly standardized procedures like primary total hip and knee arthroplasty. We aimed to evaluate how the composition and dynamics of surgical teams impact operative efficiency during arthroplasty.

Aims. The primary aim of this paper was to outline the processes involved in building the Partners Arthroplasty Registry (PAR), established in April 2016 to capture baseline and outcome data for patients undergoing arthroplasty in a regional healthcare system. A secondary aim was to determine the quality of PAR’s data. A tertiary aim was to report preliminary findings from the registry and contributions to quality improvement initiatives and research up to March 2019. Methods. Structured Query Language was used to obtain data relating to patients who underwent total hip or knee arthroplasty (THA and TKA) from the hospital network’s electronic medical record (EMR) system to be included in the PAR. Data were stored in a secure database and visualized in dashboards. Quality assurance of PAR data was performed by review of the medical records. Capture rate was determined by comparing two months of PAR data with operating room schedules. Linear and binary logistic regression models were constructed to determine if length of stay (LOS), discharge to a care home, and readmission rates improved between 2016 and 2019. Results. The PAR captured 16,163 THAs and TKAs between April 2016 and March 2019, performed in seven hospitals by 110 surgeons. Manual comparison to operating schedules showed a 100% capture rate. Review of the records was performed for 2,603 random operations; 2,298 (88.3%) had complete and accurate data. The PAR provided the data for three abstracts presented at international conferences and has led to preoperative mental health treatment as a quality improvement initiative in the participating institutions. For primary THA and TKA surgeries, the LOS decreased significantly (p < 0.001) and the rate of home discharge increased significantly (p < 0.001) between 2016 and 2019. Readmission rates did not correlated with the date of surgery (p = 0.953). Conclusion. The PAR has high rates of coverage (the number of patients treated within the Partners healthcare network) and data completion and can be used for both research purposes and quality improvement. The same method of creating a registry that was used in the PAR can be applied to hospitals using similar EMR systems. Cite this article: Bone Joint J 2020;102-B(7 Supple B):90–98

Aims. This study aimed to investigate the risk of postoperative complications in COVID-19-positive patients undergoing common orthopaedic procedures. Methods. Using the National Surgical Quality Improvement Programme (NSQIP) database, patients who underwent common orthopaedic surgery procedures from 1 January to 31 December 2021 were extracted. Patient preoperative COVID-19 status, demographics, comorbidities, type of surgery, and postoperative complications were analyzed. Propensity score matching was conducted between COVID-19-positive and -negative patients. Multivariable regression was then performed to identify both patient and provider risk factors independently associated with the occurrence of 30-day postoperative adverse events. Results. Of 194,121 included patients, 740 (0.38%) were identified to be COVID-19-positive. Comparison of comorbidities demonstrated that COVID-19-positive patients had higher rates of diabetes, heart failure, and pulmonary disease. After propensity matching and controlling for all preoperative variables, multivariable analysis found that COVID-19-positive patients were at increased risk of several postoperative complications, including: any adverse event, major adverse event, minor adverse event, death, venous thromboembolism, and pneumonia. COVID-19-positive patients undergoing hip/knee arthroplasty and trauma surgery were at increased risk of 30-day adverse events. Conclusion. COVID-19-positive patients undergoing orthopaedic surgery had increased odds of many 30-day postoperative complications, with hip/knee arthroplasty and trauma surgery being the most high-risk procedures. These data reinforce prior literature demonstrating increased risk of venous thromboembolic events in the acute postoperative period. Clinicians caring for patients undergoing orthopaedic procedures should be mindful of these increased risks, and attempt to improve patient care during the ongoing global pandemic. Cite this article: Bone Jt Open 2023;4(9):704–712

Aims. 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. Methods. 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. Results. Of the 5,600 patients included in this study, 342 (6.1%) underwent SDD. The random forest (RF) model performed the best overall, with an internally validated AUC of 0.810. The ten crucial factors favoring SDD in the RF model include operating time, anaesthesia type, age, BMI, American Society of Anesthesiologists grade, race, history of diabetes, rTKA type, sex, and smoking status. Eight of these variables were also found to be significant in the MLR model. Conclusion. The RF model displayed excellent accuracy and identified clinically important variables for determining candidates for SDD following rTKA. Machine learning techniques such as RF will allow clinicians to accurately risk-stratify their patients preoperatively, in order to optimize resources and improve patient outcomes. Cite this article: Bone Jt Open 2023;4(6):399–407

Aims. Frailty greatly increases the risk of adverse outcome of trauma in older people. Frailty detection tools appear to be unsuitable for use in traumatically injured older patients. We therefore aimed to develop a method for detecting frailty in older people sustaining trauma using routinely collected clinical data. Methods. We analyzed prospectively collected registry data from 2,108 patients aged ≥ 65 years who were admitted to a single major trauma centre over five years (1 October 2015 to 31 July 2020). We divided the sample equally into two, creating derivation and validation samples. In the derivation sample, we performed univariate analyses followed by multivariate regression, starting with 27 clinical variables in the registry to predict Clinical Frailty Scale (CFS; range 1 to 9) scores. Bland-Altman analyses were performed in the validation cohort to evaluate any biases between the Nottingham Trauma Frailty Index (NTFI) and the CFS. Results. In the derivation cohort, five of the 27 variables were strongly predictive of the CFS (regression coefficient B = 6.383 (95% confidence interval 5.03 to 7.74), p < 0.001): age, Abbreviated Mental Test score, admission haemoglobin concentration (g/l), pre-admission mobility (needs assistance or not), and mechanism of injury (falls from standing height). In the validation cohort, there was strong agreement between the NTFI and the CFS (mean difference 0.02) with no apparent systematic bias. Conclusion. We have developed a clinically applicable tool using easily and routinely measured physiological and functional parameters, which clinicians and researchers can use to guide patient care and to stratify the analysis of quality improvement and research projects. Cite this article: Bone Joint J 2024;106-B(4):412–418

Aims. 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. Methods. 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. Results. Of 21,610 aseptic revision TKAs evaluated, 530 were discharged within 24 hours. Short-stay patients were younger (63.1 years (49 to 78) vs 65.1 years (18 to 94)), with lower BMI (32.3 kg/m. 2. (17 to 47) vs 33.6 kg/m. 2. (19 to 54) and lower ASA grades. Diabetes, chronic obstructive pulmonary disease, hypertension, and cancer were all associated with a hospital stay over 24 hours. Single component revisions (56.8% (n = 301) vs 32.4% (n = 6,823)), and shorter mean operating time (89.7 minutes (25 to 275) vs 130.2 minutes (30 to 517)) were associated with accelerated discharge. Accelerated discharge was not associated with 30-day readmission and reoperation. Conclusion. Accelerated discharge after revision TKA did not increase short-term complications, readmissions, or reoperations. Further efforts to decrease hospital stays in this setting should be evaluated. Cite this article: Bone Joint J 2022;104-B(12):1323–1328

Aims. 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). Methods. 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. Results. The predictability of the ANN model, area under the curve (AUC) = 0.801, was similar to the logistic regression model (AUC = 0.796) and identified certain variables as important factors to predict same-day discharge. The ten most important factors favouring same-day discharge in the ANN model include preoperative sodium, preoperative international normalized ratio, BMI, age, anaesthesia type, operating time, dyspnoea status, functional status, race, anaemia status, and chronic obstructive pulmonary disease (COPD). Six of these variables were also found to be significant on logistic regression analysis. Conclusion. Both ANN modelling and logistic regression analysis revealed clinically important factors in predicting patients who can undergo safely undergo same-day discharge from an outpatient TKA. The ANN model provides a beneficial approach to help determine which perioperative factors can predict same-day discharge as of 2018 perioperative recovery protocols. Cite this article: Bone Joint J 2021;103-B(8):1358–1366

Aims. The aim of this study to compare 30-day survival and recovery of mobility between patients mobilized early (on the day of, or day after surgery for a hip fracture) and patients mobilized late (two days or more after surgery), and to determine whether the presence of dementia influences the association between the timing of mobilization, 30-day survival, and recovery. Methods. Analysis of the National Hip Fracture Database and hospital records for 126,897 patients aged ≥ 60 years who underwent surgery for a hip fracture in England and Wales between 2014 and 2016. Using logistic regression, we adjusted for covariates with a propensity score to estimate the association between the timing of mobilization, survival, and recovery of walking ability. Results. A total of 99,667 patients (79%) mobilized early. Among those mobilized early compared to those mobilized late, the weighted odds ratio of survival was 1.92 (95% confidence interval (CI) 1.80 to 2.05), of recovering outdoor ambulation was 1.25 (95% CI 1.03 to 1.51), and of recovering indoor ambulation was 1.53 (95% CI 1.32 to 1.78) by 30 days. The weighted probabilities of survival at 30 days post-admission were 95.9% (95% CI 95.7% to 96.0%) for those who mobilized early and 92.4% (95% CI 92.0% to 92.8%) for those who mobilized late. The weighted probabilities of regaining the ability to walk outdoors were 9.7% (95% CI 9.2% to 10.2%) and indoors 81.2% (95% CI 80.0% to 82.4%), for those who mobilized early, and 7.9% (95% CI 6.6% to 9.2%) and 73.8% (95% CI 71.3% to 76.2%), respectively, for those who mobilized late. Patients with dementia were less likely to mobilize early despite observed associations with survival and ambulation recovery for those with and without dementia. Conclusion. Early mobilization is associated with survival and recovery for patients (with and without dementia) after hip fracture. Early mobilization should be incorporated as a measured indicator of quality. Reasons for failure to mobilize early should also be recorded to inform quality improvement initiatives. Cite this article: Bone Joint J 2021;103-B(7):1317–1324

Aims. While preoperative bloodwork is routinely ordered, its value in determining which patients are at risk of postoperative readmission following total knee arthroplasty (TKA) and total hip arthroplasty (THA) is unclear. The objective of this study was to determine which routinely ordered preoperative blood markers have the strongest association with acute hospital readmission for patients undergoing elective TKA and THA. Methods. Two population-based retrospective cohorts were assembled for all adult primary elective TKA (n = 137,969) and THA (n = 78,532) patients between 2011 to 2018 across 678 North American hospitals using the American College of Surgeons National Quality Improvement Programme (ACS-NSQIP) registry. Six routinely ordered preoperative blood markers - albumin, haematocrit, platelet count, white blood cell count (WBC), estimated glomerular filtration rate (eGFR), and sodium level - were queried. The association between preoperative blood marker values and all-cause readmission within 30 days of surgery was compared using univariable analysis and multivariable logistic regression adjusted for relevant patient and treatment factors. Results. The mean TKA age was 66.6 years (SD 9.6) with 62% being females (n = 85,163/137,969), while in the THA cohort the mean age was 64.7 years (SD 11.4) with 54% being female (n = 42,637/78,532). In both cohorts, preoperative hypoalbuminemia (< 35 g/l) was associated with a 1.5- and 1.8-times increased odds of 30-day readmission following TKA and THA, respectively. In TKA patients, decreased eGFR demonstrated the strongest association with acute readmission with a standardized odds ratio of 0.75 per two standard deviations increase (p < 0.0001). Conclusion. In this population level cohort analysis of arthroplasty patients, low albumin demonstrated the strongest association with acute readmission in comparison to five other commonly ordered preoperative blood markers. Identification and optimization of preoperative hypoalbuminemia could help healthcare providers recognize and address at-risk patients undergoing TKA and THA. This is the most comprehensive and rigorous examination of the association between preoperative blood markers and readmission for TKA and THA patients to date. Cite this article: Bone Jt Open 2021;2(6):388–396

Aims. 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. Methods. 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/m. 2. and ≥ 40 kg/m. 2. 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. Results. In total, 314,695 patients underwent TKA and 46,362 (15%) had BMI ≥ 40 kg/m. 2. The prevalence of morbid obesity among TKA patients did not change greatly, ranging between 14% and 16%. Reoperation rate decreased from 1.16% to 0.96% (odds ratio (OR) 0.81 (95% confidence interval (CI) 0.66 to 0.99)) for patients with BMI < 40 kg/m. 2. , as did rates of readmission (4.46% to 2.87%; OR 0.61 (0.55 to 0.69)). Patients with BMI ≥ 40 kg/m. 2. also had fewer readmissions over the study period (4.87% to 3.34%; OR 0.64 (0.49 to 0.83)); however, the rate of reoperation did not change (1.37% to 1.41%; OR 0.99 (0.62 to 1.56)). Significant improvements were not observed for infective complications over time for either group; patients with BMI ≥ 40 kg/m. 2. had increased risk of both deep infection and wound complications compared to non-morbidly obese patients. Rate of any complication decreased for all patients. Conclusion. The proportion of TKAs in morbidly obese patients has not significantly changed over the past decade. Although readmission rates improved for all patients, reductions in reoperation in non-morbidly obese patients were not experienced by the morbidly obese, resulting in a widening of the complication gap between these cohorts. Care improvements have not lowered the differential risk of infective complications in the morbidly obese. Cite this article: Bone Joint J 2021;103-B(6 Supple A):38–44

Aims. Natural Language Processing (NLP) offers an automated method to extract data from unstructured free text fields for arthroplasty registry participation. Our objective was to investigate how accurately NLP can be used to extract structured clinical data from unstructured clinical notes when compared with manual data extraction. Methods. A group of 1,000 randomly selected clinical and hospital notes from eight different surgeons were collected for patients undergoing primary arthroplasty between 2012 and 2018. In all, 19 preoperative, 17 operative, and two postoperative variables of interest were manually extracted from these notes. A NLP algorithm was created to automatically extract these variables from a training sample of these notes, and the algorithm was tested on a random test sample of notes. Performance of the NLP algorithm was measured in Statistical Analysis System (SAS) by calculating the accuracy of the variables collected, the ability of the algorithm to collect the correct information when it was indeed in the note (sensitivity), and the ability of the algorithm to not collect a certain data element when it was not in the note (specificity). Results. The NLP algorithm performed well at extracting variables from unstructured data in our random test dataset (accuracy = 96.3%, sensitivity = 95.2%, and specificity = 97.4%). It performed better at extracting data that were in a structured, templated format such as range of movement (ROM) (accuracy = 98%) and implant brand (accuracy = 98%) than data that were entered with variation depending on the author of the note such as the presence of deep-vein thrombosis (DVT) (accuracy = 90%). Conclusion. The NLP algorithm used in this study was able to identify a subset of variables from randomly selected unstructured notes in arthroplasty with an accuracy above 90%. For some variables, such as objective exam data, the accuracy was very high. Our findings suggest that automated algorithms using NLP can help orthopaedic practices retrospectively collect information for registries and quality improvement (QI) efforts. Cite this article: Bone Joint J 2020;102-B(7 Supple B):99–104

Aims. Rates of readmission and reoperation following primary total knee arthroplasty (TKA) are under scrutiny due to new payment models, which penalize these negative outcomes. Some risk factors are more modifiable than others, and some conditions considered modifiable such as obesity may not be as modifiable in the setting of advanced arthritis as many propose. We sought to determine whether controlling for hypoalbuminaemia would mitigate the effect that prior authors had identified in patients with obesity. Methods. We reviewed the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database for the period of January 2008 to December 2016 to evaluate the rates of reoperation and readmission within 30 days following primary TKA. Multivariate logistic regression modelling controlled for preoperative albumin, age, sex, and comorbidity status. Results. Readmission rates only differed significantly between patients with Normal Weight and Obesity Class II, with a decreased rate of readmission in this group (odds ratio (OR) 0.82; 95% confidence interval (CI) 0.71 to 0.96; p = 0.010). The only group demonstrating association with increased risk of reoperation within 30 days was the Obesity Class III group (OR 1.38; 95% CI 1.05 to 1.82; p = 0.022). Hypoalbuminaemia (preoperative albumin < 35 g/L) was significantly associated with readmission (OR 1.62; 95% CI 1.41 to 1.86; p < 0.001) and reoperation (OR 1.52; 95% CI 1.18 to 1.96; p = 0.001) within 30 days. Conclusion. In this study, hypoalbuminaemia appears to be a more significant risk factor for readmission and reoperation than even the highest obesity categories. Future studies may assess whether preoperative albumin restoration or weight loss may improve outcomes for patients with hypoalbuminaemia. The implications of this study may allow surgeons to discuss risk of surgery with obese patients planning to undergo primary TKA procedures if other comorbidities are adequately controlled. Cite this article: Bone Joint J 2020;102-B(6 Supple A):31–35

Aims. The aim of this study was to determine the impact of the severity of anaemia on postoperative complications following total hip arthroplasty (THA) and total knee arthroplasty (TKA). Methods. A retrospective cohort study was conducted using the American College of Surgeons National Quality Improvement Program (ACS-NSQIP) database. All patients who underwent primary TKA or THA between January 2012 and December 2017 were identified and stratified based upon hematocrit level. In this analysis, we defined anaemia as packed cell volume (Hct) < 36% for women and < 39% for men, and further stratified anaemia as mild anaemia (Hct 33% to 36% for women, Hct 33% to 39% for men), and moderate to severe (Hct < 33% for both men and women). Univariate and multivariate analyses were used to evaluate the incidence of multiple adverse events within 30 days of arthroplasty. Results. Following adjustment, patients in the THA cohort with moderate to severe anaemia had an increased odds of 6.194 (95% confidence interval (CI) 5.679 to 6.756; p < 0.001) for developing any postoperative complication. Following adjustment, patients in the TKA cohort with moderate to severe anaemia had an increased odds of 5.186 (95% CI 4.811 to 5.590; p < 0.001) for developing any postoperative complication. Among both cohorts, as severity increased, there was an increased risk of postoperative complications. Conclusion. Preoperative anaemia is a risk factor for complications following primary arthroplasty. There is a significant relationship between the severity of anaemia and the odds of postoperative complications. Patients who had moderate to severe anaemia were at increased risk of developing postoperative complications relative to patients with mild anaemia. When considering elective primary THA or TKA in a moderately or severely anaemic patient, surgeons should strongly consider correcting anaemia prior to surgery if possible. Cite this article: Bone Joint J 2020;102-B(4):485–494

Aims. The aim of this study was to investigate the differences in 30-day outcomes between patients undergoing revision for an infected total hip arthroplasty (THA) compared with an aseptic revision THA. Patients and Methods. This was a retrospective review of prospectively collected data from the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) database, between 2012 and 2017, using Current Procedural Terminology (CPT) codes for patients undergoing a revision THA (27134, 27137, 27138). International Classification of Diseases Ninth Revision/Tenth Revision (ICD-9-CM, ICD-10-CM) diagnosis codes for infection of an implant or device were used to identify patients undergoing an infected revision THA. CPT-27132 coupled with ICD-9-CM/ICD-10-CM codes for infection were used to identify patients undergoing a two-stage revision. A total of 13 556 patients were included; 1606 (11.8%) underwent a revision THA due to infection and there were 11 951 (88.2%) aseptic revisions. Results. Patients undergoing an infected revision had a significantly greater length of stay of more than three days (p < 0.001), higher odds of any 30-day complication (p < 0.001), readmission within 30 days (p < 0.001), 30-day reoperations (p < 0.001), and discharge to a destination other than the patient’s home (p < 0.001). Conclusion. The findings suggest the need for enhanced risk adjustment based on the indication of revision THA prior to setting prices in bundled payment models of total joint arthroplasty. This risk adjustment should be used to reduce the chance of financial disincentives in clinical practice. Cite this article: Bone Joint J 2019;101-B:547–551

Aims. To evaluate the influence of discharge timing on 30-day complications following total knee arthroplasty (TKA). Patients and Methods. 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. Results. Our matched cohort consisted of 76 246 TKA patients (mean age 67 years . (sd. 9)). Patients whose LOS was zero and four days had an increased risk of major complications by an odds ratio (OR) of 1.8 (95% confidence interval (CI) 1.0 to 3.2) and 1.5 (95% CI 1.2 to 1.7), respectively, compared with patients whose LOS was two days. Patients whose LOS was zero, three, and four days had an increased risk of minor complications (OR 1.8 (95% CI 1.3 to 2.7), 1.2 (95% CI 1.0 to 1.4), and 1.6 (95% CI 1.4 to 1.9), respectively), compared with patients whose LOS was two days. In addition, a LOS of three days increased the risk of re-admission by an OR of 1.2 (95% CI 1.0 to 1.3), and a LOS of four days increased the risk of re-admission by an OR of 1.5 (95% CI 1.3 to 1.6), compared with a LOS of two days. Conclusion. Patients discharged on days one to two postoperatively following TKA appear to have reduced major and minor complications compared with discharge on the day of surgery, or on days three to four. Prospective clinical data are required to confirm these findings. Cite this article: Bone Joint J 2019;101-B(7 Supple C):70–76