Aims

Patients with proximal femoral fractures (PFFs) are often multimorbid, thus unplanned readmissions following surgery are common. We therefore aimed to analyze 30-day and one-year readmission rates, reasons for, and factors associated with, readmission risk in a cohort of patients with surgically treated PFFs across Austria.

Aims

Machine-learning (ML) prediction models in orthopaedic trauma hold great promise in assisting clinicians in various tasks, such as personalized risk stratification. However, an overview of current applications and critical appraisal to peer-reviewed guidelines is lacking. The objectives of this study are to 1) provide an overview of current ML prediction models in orthopaedic trauma; 2) evaluate the completeness of reporting following the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) statement; and 3) assess the risk of bias following the Prediction model Risk Of Bias Assessment Tool (PROBAST) tool.

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

The August 2023 Trauma Roundup³⁶⁰ looks at: A comparison of functional cast and volar-flexion ulnar deviation for dorsally displaced distal radius fractures; Give your stable ankle fractures some AIR!; Early stabilization of rib fractures – an effective thing to do?; Locked plating versus nailing for proximal tibia fractures: A multicentre randomized controlled trial; Time to flap coverage in open tibia fractures; Does tranexamic acid affect the incidence of heterotropic ossification around the elbow?; High BMI – good or bad in surgical fixation of hip fractures?

Aims

Delirium is associated with adverse outcomes following hip fracture, but the prevalence and significance of delirium for the prognosis and ongoing rehabilitation needs of patients admitted from home is less well studied. Here, we analyzed relationships between delirium in patients admitted from home with 1) mortality; 2) total length of hospital stay; 3) need for post-acute inpatient rehabilitation; and 4) hospital readmission within 180 days.

The April 2023 Spine Roundup³⁶⁰ looks at: Percutaneous transforaminal endoscopic discectomy versus microendoscopic discectomy; Spine surgical site infections: a single debridement is not enough; Lenke type 5, anterior, or posterior: systematic review and meta-analysis; Epidural steroid injections and postoperative infection in lumbar decompression or fusion; Noninferiority of posterior cervical foraminotomy versus anterior cervical discectomy; Identifying delays to surgical treatment for metastatic disease; Cervical disc replacement and adjacent segment disease: the NECK trial; Predicting complication in adult spine deformity surgery.

Aims

The aim of this study is to report the implant survival and factors associated with revision of total elbow arthroplasty (TEA) using data from the Dutch national registry.

The February 2023 Knee Roundup³⁶⁰ looks at: Machine-learning models: are all complications predictable?; Positive cultures can be safely ignored in revision arthroplasty patients that do not meet the 2018 International Consensus Meeting Criteria; Spinal versus general anaesthesia in contemporary primary total knee arthroplasty; Preoperative pain and early arthritis are associated with poor outcomes in total knee arthroplasty; Risk factors for infection and revision surgery following patellar tendon and quadriceps tendon repairs; Supervised versus unsupervised rehabilitation following total knee arthroplasty; Kinematic alignment has similar outcomes to mechanical alignment: a systematic review and meta-analysis; Lifetime risk of revision after knee arthroplasty influenced by age, sex, and indication; Risk factors for knee osteoarthritis after traumatic knee injury.

Total hip arthroplasty (THA) is performed under general anesthesia (GA) or spinal anesthesia (SA). The first objective of this study was to determine which patient factors are associated with receiving SA versus GA. The second objective was to discern the effect of anesthesia type on short-term postoperative complications and readmission. The third objective was to elucidate factors that impact the effect of anesthesia type on outcome following arthroplasty. This retrospective cohort study included 108,905 patients (median age, 66 years; IQR 60-73 years; 56.0% females) who underwent primary THA for treatment of primary osteoarthritis in the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) database during the period of 2013-2018. Multivariable logistic regression analysis was performed to evaluate variables associated with anesthesia type and outcomes following arthroplasty. Anesthesia type administered during THA was significantly associated with race. Specifically, Black and Hispanic patients were less likely to receive SA compared to White patients (White: OR 1.00; Black: OR 0.73; 95% confidence interval [CI] 0.71-0.75; Hispanic: OR 0.81; CI, 0.75-0.88), while Asian patients were more likely to receive SA (OR 1.44, CI 1.31-1.59). Spinal anesthesia was associated with increased age (OR 1.01; CI 1.00-1.01). Patients with less frailty and lower comorbidity were more likely to receive SA based on the modified frailty index ([mFI-5]=0: OR 1.00; mFI-5=1: OR 0.90, CI 0.88-0.93; mFI-5=2 or greater: OR 0.86, CI 0.83-0.90) and American Society of Anesthesiologists (ASA) class (ASA=1: OR 1.00; ASA=2: OR 0.85, CI 0.79-0.91; ASA=3: OR 0.64, CI 0.59-0.69; ASA=4-5: OR 0.47; CI 0.41-0.53). With increased BMI, patients were less likely to be treated with SA (OR 0.99; CI 0.98-0.99). Patients treated with SA had less post-operative complications than GA (OR 0.74; CI 0.67-0.81) and a lower risk of readmission than GA (OR 0.88; CI 0.82-0.95) following THA. Race, age, BMI, and ASA class were found to affect the impact of anesthesia type on post-operative complications. Stratified analysis demonstrated that the reduced risk of complications following arthroplasty noted in patients treated with SA compared to GA was more pronounced in Black, Asian, and Hispanic patients compared to White patients. Furthermore, the positive effect of SA compared to GA was stronger in patients who had reduced age, elevated BMI, and lower ASA class. Among patients undergoing THA for management of primary osteoarthritis, factors including race, BMI, and frailty appear to have impacted the type of anesthesia received. Patients treated with SA had a significantly lower risk of readmission to hospital and adverse events within 30 days of surgery compared to those treated with GA. Furthermore, the positive effect on outcome afforded by SA was different between patients depending on race, age, BMI, and ASA class. These findings may help to guide selection of anesthesia type in subpopulations of patients undergoing primary THA

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

To describe the longitudinal trends in patients with obesity and Metabolic Syndrome (MetS) undergoing TKA and the associated impact on complications and lengths of hospital stay. We identified patients who underwent primary TKA between 2006 – 2017 within the American College of Surgeons National Surgical Quality Improvement Program (NSQIP) database. We recorded patient demographics, length of stay (LOS), and 30-day major and minor complications. We labelled those with an obese Body Mass Index (BMI ≥ 30), hypertension, and diabetes as having MetS. We evaluated mean BMI, LOS, and 30-day complication rates in all patients, obese patients, and those with MetS from 2006-2017. We used multivariable regression to evaluate the trends in BMI, complications, and LOS over time in all patients and those with MetS, and the effect of BMI and MetS on complication rates and LOS, stratified by year. 270,846 patients underwent primary TKA at hospitals participating in the NSQIP database. 63.71% of patients were obese (n = 172,333), 15.21% were morbidly obese (n = 41,130), and 12.37% met criteria for MetS (n = 33,470). Mean BMI in TKA patients increased at a rate of 0.03 per year (0.02-0.05; p < 0 .0001). Despite this, the rate of adverse events in obese patients decreased: major complications by an odds ratio (OR) of 0.94 (0.93-0.96; p < 0 .0001) and minor complications by 0.94 (0.93-0.95; p < 0 .001). LOS also decreased over time at an average rate of −0.058 days per year (-0.059 to −0.057; p < 0 .0001). The proportion of patients with MetS did not increase, however similar improvements in major complications (OR 0.94 [0.91-0.97] p < 0 .0001), minor complications (OR 0.97 [0.94-1.00]; p < 0 .0330), and LOS (mean −0.055 [-0.056 to −0.054] p < 0 .0001) were found. In morbidly obese patients (BMI ≥ 40), there was a decreased proportion per year (OR 0.989 [0.98-0.994] p < 0 .0001). Factors specifically associated with major complications in obese patients included COPD (OR 1.75 [1.55-2.00] p < 0.0001) and diabetes (OR 1.10 [1.02-1.1] p = 0.017). Hypertension (OR 1.12 [1.03-1.21] p = 0.0079) was associated with minor complications. Similarly, in patients with MetS, major complications were associated with COPD (OR 1.72 [1.35-2.18] p < 0.0001). Neuraxial anesthesia was associated with a lower risk for major complications in the obese cohort (OR 0.87 [0.81-0.92] p < 0.0001). BMI ≥ 40 was associated with a greater risk for minor complications (OR 1.37 [1.26-1.50] p < 0.0001), major complications (1.11 [1.02-1.21] p = 0.015), and increased LOS (+0.08 days [0.07-0.09] p < 0.0001). Mean BMI in patients undergoing primary TKA increased from 2006 - 2017. MetS comorbidities such as diabetes and hypertension elevated the risk for complications in obese patients. COPD contributed to higher rates of major complications. The obesity-specific risk reduction with spinal anesthesia suggests an improved post-anesthetic clinical course in obese patients with pre-existing pulmonary pathology. Encouragingly, the overall rates of complications and LOS in patients with obesity and MetS exhibited a longitudinal decline. This finding may be related to the decreased proportion of patients with BMI ≥ 40 treated over the same period, possibly the result of quality improvement initiatives aimed at delaying high-risk surgery in morbidly obese patients until healthy weight loss is achieved. These findings may also reflect increased awareness and improved management of these patients and their elevated risk profiles

Total knee and hip arthroplasty (TKA and THA) are two of the highest volume and resource intensive surgical procedures. Key drivers of the cost of surgical care are duration of surgery (DOS) and postoperative inpatient length of stay (LOS). The ability to predict TKA and THA DOS and LOS has substantial implications for hospital finances, scheduling and resource allocation. The goal of this study was to predict DOS and LOS for elective unilateral TKAs and THAs using machine learning models (MLMs) constructed on preoperative patient factors using a large North American database. The American College of Surgeons (ACS) National Surgical and Quality Improvement (NSQIP) database was queried for elective unilateral TKA and THA procedures from 2014-2019. The dataset was split into training, validation and testing based on year. Multiple conventional and deep MLMs such as linear, tree-based and multilayer perceptrons (MLPs) were constructed. The models with best performance on the validation set were evaluated on the testing set. Models were evaluated according to 1) mean squared error (MSE), 2) buffer accuracy (the number of times the predicted target was within a predesignated buffer of the actual target), and 3) classification accuracy (the number of times the correct class was predicted by the models). To ensure useful predictions, the results of the models were compared to a mean regressor. A total of 499,432 patients (TKA 302,490; THA 196,942) were included. The MLP models had the best MSEs and accuracy across both TKA and THA patients. During testing, the TKA MSEs for DOS and LOS were 0.893 and 0.688 while the THA MSEs for DOS and LOS were 0.895 and 0.691. The TKA DOS 30-minute buffer accuracy and ≤120 min, >120 min classification accuracy were 78.8% and 88.3%, while the TKA LOS 1-day buffer accuracy and ≤2 days, >2 days classification accuracy were 75.2% and 76.1%. The THA DOS 30-minute buffer accuracy and ≤120 min, >120 min classification accuracy were 81.6% and 91.4%, while the THA LOS 1-day buffer accuracy and ≤2 days, >2 days classification accuracy were 78.3% and 80.4%. All models across both TKA and THA patients were more accurate than the mean regressors for both DOS and LOS predictions across both buffer and classification accuracies. Conventional and deep MLMs have been effectively implemented to predict the DOS and LOS of elective unilateral TKA and THA patients based on preoperative patient factors using a large North American database with a high level of accuracy. Future work should include using operational factors to further refine these models and improve predictive accuracy. Results of this work will allow institutions to optimize their resource allocation, reduce costs and improve surgical scheduling. Acknowledgements:. The American College of Surgeons National Surgical Quality Improvement Program and the hospitals participating in the ACS NSQIP are the source of the data used herein; they have not verified and are not responsible for the statistical validity of the data analysis or the conclusions derived by the authors

Reported incidence of blood transfusion following primary and revision total hip arthroplasty (pTHA, rTHA) has decreased considerably compared to historical rates. However, it is not known if further adoption of techniques to limit transfusions has resulted in further reduction on a large scale. The purpose of this study was to assess recent trends in blood transfusions and contemporary risk factors for transfusions using a large, national database. The American College of Surgeons National Surgical Quality Improvement Program was queried to identify patients undergoing pTHA and rTHA between 2011 to 2019. pTHA for fracture, infection, tumor, and bilateral procedures were excluded. Only aseptic rTHA were included. Annual incidence of transfusions and proportion of patients with optimized preoperative hematocrit (HCT) (defined as ≥33%) were assessed. Risk factors for transfusion were evaluated with 2018 and 2019 data using multivariate analyses. 234,352 pTHA and 16,322 rTHA were included. Transfusion following pTHA decreased from 21.4% in 2011 to 2.5% in 2019 and from 33.5% in 2011 to 12.0% in 2019 for rTHA (p<0.0001). Patients with optimized HCT increased for pTHA (96.7% in 2011 vs 98.1% in 2019, p<0.0001) and did not change for rTHA (91.5% in 2011 vs 91.6% in 2019, p=0.27). Decreased HCT was most strongly associated with transfusions, with each three-point change corresponding to odds ratio of 1.90 and 1.78 for pTHA and rTHA, respectively. Increased age, female sex, history of bleeding disorders or preoperative transfusion, ASA score ≥3, non-spinal anesthesia, and longer operative times were also associated with increased odds for transfusion. Incidence of blood transfusion has continued to decrease following pTHA and rTHA. Despite care improvements, transfusions still occur in certain high-risk patients. While transfusion in pTHA may have reached the lower asymptote, further reduction in rTHA may be possible through further improvements in preoperative optimization and surgical technique

Aims

The incidence of bone metastases is between 20% to 75% depending on the type of cancer. As treatment improves, the number of patients who need surgical intervention is increasing. Identifying patients with a shorter life expectancy would allow surgical intervention with more durable reconstructions to be targeted to those most likely to benefit. While previous scoring systems have focused on surgical and oncological factors, there is a need to consider comorbidities and the physiological state of the patient, as these will also affect outcome. The primary aim of this study was to create a scoring system to estimate survival time in patients with bony metastases and to determine which factors may adversely affect this.

Aims

To compare rates of serious adverse events in patients undergoing revision knee arthroplasty with consideration of the indication for revision (urgent versus elective indications), and compare these with primary arthroplasty and re-revision arthroplasty.

In recent years, machine learning (ML) and artificial neural networks (ANNs), a particular subset of ML, have been adopted by various areas of healthcare. A number of diagnostic and prognostic algorithms have been designed and implemented across a range of orthopaedic sub-specialties to date, with many positive results. However, the methodology of many of these studies is flawed, and few compare the use of ML with the current approach in clinical practice. Spinal surgery has advanced rapidly over the past three decades, particularly in the areas of implant technology, advanced surgical techniques, biologics, and enhanced recovery protocols. It is therefore regarded an innovative field. Inevitably, spinal surgeons will wish to incorporate ML into their practice should models prove effective in diagnostic or prognostic terms. The purpose of this article is to review published studies that describe the application of neural networks to spinal surgery and which actively compare ANN models to contemporary clinical standards allowing evaluation of their efficacy, accuracy, and relatability. It also explores some of the limitations of the technology, which act to constrain the widespread adoption of neural networks for diagnostic and prognostic use in spinal care. Finally, it describes the necessary considerations should institutions wish to incorporate ANNs into their practices. In doing so, the aim of this review is to provide a practical approach for spinal surgeons to understand the relevant aspects of neural networks.

Cite this article: Bone Joint J 2021;103-B(9):1442–1448.

Aims

In 2020, the COVID-19 pandemic meant that proceeding with elective surgery was restricted to minimize exposure on wards. In order to maintain throughput of elective cases, our hospital (St Michaels Hospital, Toronto, Canada) was forced to convert as many cases as possible to same-day procedures rather than overnight admission. In this retrospective analysis, we review the cases performed as same-day arthroplasty surgeries compared to the same period in the previous 12 months.