MRI use leading up to total knee arthroplasty: a retrospective cohort study.

BACKGROUND: Demand for total knee arthroplasty (TKA) is increasing as it remains the gold-standard treatment for end-stage osteoarthritis (OA) of the knee. Magnetic resonance imaging (MRI) scans of the knee are not indicated for diagnosing knee OA and represent a possible delay to orthopaedic surgeon referral and unnecessary expenditure. The purpose of this study was to determine the proportion of patients who underwent an MRI in the two years prior to their primary TKA for OA and determine patient and physician associations with increased MRI usage. METHODS: This is a population-based cohort study using administrative data from Ontario, Canada. All patients over 40 years old who underwent their first primary TKA between April 1, 2008, and March 31, 2019, were included. Statistical analyses were performed using SAS and included the Cochran-Armitage test for trend of MRI prior to surgery. A predictive multivariable regression model was used to determine features correlated to receiving an MRI. RESULTS: There were 194,989 eligible first-time TKA recipients, of which 38,244 (19.6%) received an MRI in the two years prior to their surgery. The majority of these (69.6%) were ordered by primary care physicians. Patients who received an MRI were younger, had fewer comorbidities and were more affluent than patients who did not (p < 0.001). MRI use prior to TKA increased from 2008 to 2018 (p < 0.001). CONCLUSION: Despite MRIs rarely being indicated for the work-up of end-stage OA, nearly one in five patients have an MRI in the two years prior to their TKA. This may be increasing healthcare expenditure and surgical wait-times.

Association between immigration status and total knee arthroplasty outcomes in Ontario, Canada: a population-based matched cohort study.

BACKGROUND: Immigrants and refugees face unique challenges navigating the health care system to manage severe arthritis, because of unfamiliarity, lack of awareness of surgical options, or access. The purpose of this study was to assess total knee arthroplasty (TKA) uptake, surgical outcomes, and hospital utilization among immigrants and refugees compared with Canadian-born patients. METHODS: We included all adults undergoing primary TKA from January 2011 to December 2020 in Ontario. Cohorts were defined as Canadian-born or immigrants and refugees. We assessed change in yearly TKA utilization for trend. We compared differences in 1-year revision, infection rates, 30-day venous thromboembolism (VTE), presentation to emergency department, and hospital readmission between matched Canadian-born and immigrant and refugee groups. RESULTS: We included 158 031 TKA procedures. A total of 11 973 (7.6%) patients were in the immigrant and refugee group, and 146 058 (92.4%) patients were in the Canadian-born group. The proportion of TKAs in Ontario performed among immigrants and refugees nearly doubled over the 10-year study period (p < 0.001). After matching, immigrants were at relatively lower risk of 1-year revision (0.9% v. 1.6%, p < 0.001), infection (p < 0.001), death (p = 0.004), and surgical complications (p < 0.001). No differences were observed in rates of 30-day VTE or length of hospital stay. Immigrants were more likely to be discharged to rehabilitation (p < 0.001) and less likely to present to the emergency department (p < 0.001) than Canadian-born patients. CONCLUSION: Compared with Canadian-born patients, immigrants and refugees have favourable surgical outcomes and similar rates of resource utilization after TKA. We observed an underutilization of these procedures in Ontario relative to their proportion of the population. This may reflect differences in perceptions of chronic pain or barriers accessing arthroplasty.

Fluoroscopy Versus Imageless Optical Navigation in Direct Anterior Approach Total Hip Arthroplasty.

BACKGROUND: Utilization of the direct anterior approach (DAA) for total hip arthroplasty (THA) has risen in popularity. Accurate implant placement is a critical factor that influences patient outcomes. The goal of this study was to compare the accuracy and precision of fluoroscopy with imageless optical navigation in DAA THA. METHODS: This was a cohort study of 640 consecutive primary DAA THAs performed with intraoperative fluoroscopy (n = 300 patients) or imageless optical navigation (n = 304 patients). Accuracy was compared by measuring acetabular cup inclination, anteversion, and leg-length discrepancy (LLD). The proportion of implants placed within the Lewinnek safe zone and those placed within a more precise target of 40 ± 5° inclination and 20 ± 5° anteversion was evaluated. RESULTS: According to the Lewinnek criteria, there was no difference in the percentage of implants placed within both inclination and anteversion targets (fluoroscopy: 90.3%; navigation: 88.8%, P = 0.519). Using the more precise targets, navigation increased the implants positioned correctly for both inclination and anteversion (fluoroscopy: 50.3%; navigation: 65.6%, P < 0.001). Navigation increased the proportion of implants positioned within the target anteversion zone (fluoroscopy: 71.3%; navigation: 83.8%, P < 0.001) but not inclination (fluoroscopy: 71.9%; navigation: 76.9%, P = 0.147). The mean LLD was higher with the use of fluoroscopy compared with navigation (5.5 mm, standard deviation: 4.1; 4.6 mm, SD: 3.4, P < 0.005). No difference in dislocation rate was observed ( P = 0.643). CONCLUSION: Both fluoroscopy and imageless optical navigation demonstrated accurate acetabular implant positioning during DAA THA. Navigation was more precise and associated with improved acetabular anteversion placement and restoration of LLD. Navigation is an accurate alternative to fluoroscopy with decreased radiation exposure.

Use of virtual reality for the management of phantom limb pain: a systematic review.

PURPOSE: To summarize the research on the effectiveness of virtual reality (VR) therapy for the management of phantom limb pain (PLP). METHODS: Three databases (SCOPUS, Ovid Embase, and Ovid MEDLINE) were searched for studies investigating the use of VR therapy for the treatment of PLP. Original research articles fulfilling the following criteria were included: (i) patients 18 years and older; (ii) all etiologies of amputation; (iii) any level of amputation; (iv) use of immersive VR as a treatment modality for PLP; (v) self-reported objective measures of PLP before and after at least one VR session; (vi) written in English. RESULTS: A total of 15 studies were included for analysis. Fourteen studies reported decreases in objective pain scores following a single VR session or a VR intervention consisting of multiple sessions. Moreover, combining VR with tactile stimulation had a larger beneficial effect on PLP compared with VR alone. CONCLUSIONS: Based on the current literature, VR therapy has the potential to be an effective treatment modality for the management of PLP. However, the low quality of studies, heterogeneity in subject population and intervention type, and lack of data on long-term relief make it difficult to draw definitive conclusions.IMPLICATION FOR REHABILITATIONVirtual reality (VR) therapy has emerged as a new potential treatment option for phantom limb pain (PLP) that circumvents some limitations of mirror therapy.VR therapy was shown to decrease PLP following a single VR session as well as after an intervention consisting of multiple sessions.The addition of vibrotactile stimuli to VR therapy may lead to larger decreases in PLP scores compared with VR therapy alone.

The association between preoperative COVID-19-positivity and acute postoperative complication risk among patients undergoing orthopedic surgery.

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.

In-office needle arthroscopy is a cost-effective alternative for operating room diversion in medial meniscectomy: a financial analysis.

BACKGROUND: In-office needle arthroscopy (IONA) has been described as a diagnostic alternative to magnetic resonance imaging (MRI) for intra-articular pathology. However, few studies have analyzed its impact on cost and wait times when used as a therapeutic intervention. The purpose of this study was to investigate the impact on cost and wait times associated with offering IONA for partial medial meniscectomy as an alternative to traditional operating room (OR) arthroscopy for patients with irreparable medial meniscus tears on MRI. METHODS: Two models were created comparing the existing care pathway (current state) to a proposed future state utilizing IONA. Data sources were accounting data from an academically affiliated hospital in Canada and supplemented with literature values. A Monte Carlo simulation combined with DuPont analysis running 10,000 simulations was conducted to calculate the revenue, expenses, profits, and effect on surgical waitlists (i.e., throughput) between the states. Sensitivity analyses examined the influence of patient preference and revision rates on profit and throughput. Two-sample Student's t test was performed (p < .05). RESULTS: An average of 198 (standard deviation (SD) 31) patients underwent arthroscopic meniscectomy or repair each year from 2016 to 2020. The IONA revision rate was calculated as 20.3%. Compared to the current state, annual expenses in the IONA pathway were significantly reduced ($266,912.68 versus $281,415.23, p < .0001), while improving throughput by 21.2% (3.54%). Sensitivity analysis revealed 10% of patients need to select IONA over traditional OR arthroscopy with the revision rate remaining below 40% for the proposed state profit to be higher than the current state. CONCLUSIONS: IONA is a cost-effective alternative to traditional OR arthroscopy in patients undergoing partial medial meniscectomy. The next steps are to assess patients' perceptions of IONA as an alternative to traditional OR arthroscopy, and to carry out clinical trials to determine the efficacy, patient-reported outcome metrics, and complications of IONA.

Immersive Virtual Reality and Cadaveric Bone are Equally Effective in Skeletal Anatomy Education: A Randomized Crossover Noninferiority Trial.

OBJECTIVE: Immersive virtual reality (IVR) technology is transforming medical education. Our aim was to compare the effectiveness of IVR with cadaveric bone models in teaching skeletal anatomy. DESIGN: A randomized crossover noninferiority trial was conducted. SETTING: Anatomy laboratory of a large medical school. PARTICIPANTS: Incoming first-year medical students. Participants were randomized to IVR or cadaveric groups studying upper limb skeletal anatomy, and then were crossed over to use the opposite tool, to study lower limb skeletal anatomy. Participants in both groups completed a pre-and postintervention knowledge test. The primary endpoint of the study was change in performance from the pre-to postintervention knowledge test. Surveys were completed to assess participant's impressions on IVR as an educational tool. RESULTS: Fifty first-year medical students met inclusion criteria and were randomized. Among all students, the average score on the preintervention knowledge test was 14.6% (standard deviation (SD) = 18.2%) and 25.0% (SD = 17%) for upper and lower limbs, respectively. Percentage increase in scores between pre-and postintervention knowledge test, was 15.0% in the upper limb IVR group, and 16.7% for upper limb cadaveric bones (p = 0.286). For the lower limb, score increase was 22.6% in the IVR and 22.5% in the cadaveric bone group (p = 0.936). 79% of participants found that IVR was most valuable for teaching 3-dimensional orientation, anatomical relationships, and key landmarks. Majority of participants were favorable towards combination use of traditional methods and IVR technology for learning skeletal anatomy (LSM>3). CONCLUSIONS: In this randomized controlled trial, there was no significant difference in knowledge after using IVR or cadaveric bones for skeletal anatomy education. These findings have further implications for medical schools that face challenges in acquiring human cadavers and cadaveric parts.

Complications and early recovery following hip hemiarthroplasty through the direct anterior approach: a systematic review and meta-analysis.

PURPOSE: Minimizing complications is an important focus in hip hemiarthroplasty (HHA) for femoral neck fracture (FNF) patients given the associated high morbidity and mortality rates. This systematic review and meta-analysis aimed to compare the clinical and functional outcomes associated with the direct anterior approach (DAA) compared to other surgical approaches used for HHA. METHODS: Studies evaluating HHA-treated FNFs using the DAA were compared through meta-analysis to all other surgical approaches combined and as distinct subgroups. Outcomes included overall complication rate, mortality rate, dislocation rate, reoperation rate, periprosthetic fracture rate, infection rate, length of stay (LOS), mobility, perioperative blood loss, operative time, and postoperative pain. RESULTS: Nineteen studies met the inclusion criteria, totaling 2,018 HHAs. DAA significantly reduced the overall complication rate (odds ratio (OR) = 0.73, 95% confidence interval (CI) 0.57 to 0.94, p = 0.01), dislocation rate (OR = 0.34, 95% CI 0.15 to 0.77, p = 0.01), and LOS (mean difference (MD) = -1.31 days, 95% CI - 2.12 to - 0.50, p = 0.002). Findings from studies that were not appropriate for meta-analysis were qualitatively summarized and suggested improved mobility and reduced postoperative pain with the DAA. Significant differences were not detected in any of the remaining outcomes. CONCLUSION: The DAA HHA appears to be safer, reduces hospital stay, and may improve early functional recovery. This article supports the DAA HHA as a safe option for the management of displaced intracapsular FNFs.

Optimizing spine surgery instrument trays to immediately increase efficiency and reduce costs in the operating room.

Background: Over-crowded surgical trays result in perioperative inefficiency and unnecessary costs. While methodologies to reduce the size of surgical trays have been described in the literature, they each have their own drawbacks. In this study, we compared three methods: (1) clinician review (CR), (2) mathematical programming (MP), and (3) a novel hybrid model (HM) based on surveys and cost analysis. While CR and MP are well documented, CR can yield suboptimal reductions and MP can be laborious and technically challenging. We hypothesized our easy-to-implement HM would result in a reduction of surgical instruments in both the laminectomy tray (LT) and basic neurosurgery tray (BNT) that is comparable to CR and MP. Methods: Three approaches were tested: CR, MP, and HM. We interviewed 5 neurosurgeons and 3 orthopedic surgeons, at our institution, who performed a total of 5437 spine cases, requiring the use of the LT and BNT over a 4-year (2017-2021) period. In CR, surgeons suggested which surgical instruments should be removed. MP was performed via the mathematical analysis of 25 observations of the use of a LT and BNT tray. The HM was performed via a structured survey of the surgeons' estimated instrument usage, followed by a cost-based inflection point analysis. Results: The CR, MP, and HM approaches resulted in a total instrument reduction of 41%, 35%, and 38%, respectively, corresponding to total cost savings per annum of $50,211.20, $46,348.80, and $44,417.60, respectively. Conclusions: While hospitals continue to examine perioperative services for potential inefficiencies, surgical inventory will be increasingly scrutinized. Despite MP being the most accurate methodology to do so, our results suggest that savings were similar across all three methods. CR and HM are significantly less laborious and thus are practical alternatives.

Improving Resource Utilization for Arthroplasty Care by Leveraging Machine Learning and Optimization: A Systematic Review.

Background: There is a growing demand for total joint arthroplasty (TJA) surgery. The applications of machine learning (ML), mathematical optimization, and computer simulation have the potential to improve efficiency of TJA care delivery through outcome prediction and surgical scheduling optimization, easing the burden on health-care systems. The purpose of this study was to evaluate strategies using advances in analytics and computational modeling that may improve planning and the overall efficiency of TJA care. Methods: A systematic review including MEDLINE, Embase, and IEEE Xplore databases was completed from inception to October 3, 2022, for identification of studies generating ML models for TJA length of stay, duration of surgery, and hospital readmission prediction. A scoping review of optimization strategies in elective surgical scheduling was also conducted. Results: Twenty studies were included for evaluating ML predictions and 17 in the scoping review of scheduling optimization. Among studies generating linear or logistic control models alongside ML models, only 1 found a control model to outperform its ML counterpart. Furthermore, neural networks performed superior to or at the same level as conventional ML models in all but 1 study. Implementation of mathematical and simulation strategies improved the optimization efficiency when compared to traditional scheduling methods at the operational level. Conclusions: High-performing predictive ML-based models have been developed for TJA, as have mathematical strategies for elective surgical scheduling optimization. By leveraging artificial intelligence for outcome prediction and surgical optimization, there exist greater opportunities for improved resource utilization and cost-savings in TJA than when using traditional modeling and scheduling methods.

Artificial Intelligence for Hip Fracture Detection and Outcome Prediction: A Systematic Review and Meta-analysis.

Importance: Artificial intelligence (AI) enables powerful models for establishment of clinical diagnostic and prognostic tools for hip fractures; however the performance and potential impact of these newly developed algorithms are currently unknown. Objective: To evaluate the performance of AI algorithms designed to diagnose hip fractures on radiographs and predict postoperative clinical outcomes following hip fracture surgery relative to current practices. Data Sources: A systematic review of the literature was performed using the MEDLINE, Embase, and Cochrane Library databases for all articles published from database inception to January 23, 2023. A manual reference search of included articles was also undertaken to identify any additional relevant articles. Study Selection: Studies developing machine learning (ML) models for the diagnosis of hip fractures from hip or pelvic radiographs or to predict any postoperative patient outcome following hip fracture surgery were included. Data Extraction and Synthesis: This study followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses and was registered with PROSPERO. Eligible full-text articles were evaluated and relevant data extracted independently using a template data extraction form. For studies that predicted postoperative outcomes, the performance of traditional predictive statistical models, either multivariable logistic or linear regression, was recorded and compared with the performance of the best ML model on the same out-of-sample data set. Main Outcomes and Measures: Diagnostic accuracy of AI models was compared with the diagnostic accuracy of expert clinicians using odds ratios (ORs) with 95% CIs. Areas under the curve for postoperative outcome prediction between traditional statistical models (multivariable linear or logistic regression) and ML models were compared. Results: Of 39 studies that met all criteria and were included in this analysis, 18 (46.2%) used AI models to diagnose hip fractures on plain radiographs and 21 (53.8%) used AI models to predict patient outcomes following hip fracture surgery. A total of 39 598 plain radiographs and 714 939 hip fractures were used for training, validating, and testing ML models specific to diagnosis and postoperative outcome prediction, respectively. Mortality and length of hospital stay were the most predicted outcomes. On pooled data analysis, compared with clinicians, the OR for diagnostic error of ML models was 0.79 (95% CI, 0.48-1.31; P = .36; I2 = 60%) for hip fracture radiographs. For the ML models, the mean (SD) sensitivity was 89.3% (8.5%), specificity was 87.5% (9.9%), and F1 score was 0.90 (0.06). The mean area under the curve for mortality prediction was 0.84 with ML models compared with 0.79 for alternative controls (P = .09). Conclusions and Relevance: The findings of this systematic review and meta-analysis suggest that the potential applications of AI to aid with diagnosis from hip radiographs are promising. The performance of AI in diagnosing hip fractures was comparable with that of expert radiologists and surgeons. However, current implementations of AI for outcome prediction do not seem to provide substantial benefit over traditional multivariable predictive statistics.

An automated, web-based triage tool may optimise referral pathways in elective orthopaedic surgery: A proof-of-concept study.

Introduction: Knee pain is caused by various pathologies, making evaluation in primary-care challenging. Subsequently, an over-reliance on imaging, such as radiographs and MRI exists. Electronic-triage tools represent an innovative solution to this problem. The aims of this study were to establish the magnitude of unnecessary knee imaging prior to orthopaedic surgeon referral, and ascertain whether an e-triage tool outperforms existing clinical pathways to recommend correct imaging. Methods: Patients ≥18 years presenting with knee pain treated with arthroscopy or arthroplasty at a single academic hospital between 2015 and 2020 were retrospectively identified. The timing and appropriateness of imaging were assessed according to national guidelines, and classified as 'necessary', 'unnecessary' or 'required MRI'. Based on an eDelphi consensus study, a symptom-based e-triage tool was developed and piloted to preliminarily diagnose five common knee pathologies and suggest appropriate imaging. Results: 1462 patients were identified. 17.2% (n = 132) of arthroplasty patients received an 'unnecessary MRI', 27.6% (n = 192) of arthroscopy patients did not have a 'necessary MRI', requiring follow-up. Forty-one patients trialled the e-triage pilot (mean age: 58.4 years, 58.5% female). Preliminary diagnoses were available for 33 patients. The e-triage tool correctly identified three of the four knee pathologies (one pathology did not present). 79.2% (n = 19) of participants would use the tool again. Conclusion: A substantial number of knee pain patients receive incorrect imaging, incurring delays and unnecessary costs. A symptom-based e-triage tool was developed, with promising performance and user feedback. With refinement using larger datasets, this tool has the potential to improve wait-times, referral quality and reduce cost.

Clinical applications of augmented reality in orthopaedic surgery: a comprehensive narrative review.

PURPOSE: The development of augmented reality (AR) technology allows orthopaedic surgeons to incorporate and visualize surgical data, assisting the execution of both routine and complex surgical operations. Uniquely, AR technology allows a surgeon to view the surgical field and superimpose peri-operative imaging, anatomical landmarks, navigation guidance, and more, all in one view without the need for conjugate gaze between multiple screens. The aim of this literature review was to introduce the fundamental requirements for an augmented reality system and to assess the current applications, outcomes, and potential limitations to this technology. METHODS: A literature search was performed using MEDLINE and Embase databases, by two independent reviewers, who then collaboratively synthesized and collated the results of the literature search into a narrative review focused on the applications of augmented reality in major orthopaedic sub-specialties. RESULTS: Current technology requires that pre-operative patient data be acquired, and AR-compatible models constructed. Intra-operatively, to produce manipulatable virtual images into the user's view in real time, four major components are required including a camera, computer image processing technology, tracking tools, and an output screen. The user is provided with a heads-up display, which is a transparent display, enabling the user to look at both their natural view and the computer-generated images. Currently, high-quality evidence for clinical implementation of AR technology in the orthopaedic surgery operating room is lacking; however, growing in vitro literature highlights a multitude of potential applications, including increasing operative accuracy, improved biomechanical angular and alignment parameters, and potentially reduced operative time. CONCLUSION: While the application of AR systems in surgery is currently in its infancy, we anticipate rapid and widespread implementation of this technology in various orthopaedic sub-specialties.

A Dedicated Orthopaedic Trauma Room Improves Efficiency While Remaining Financially Net Positive.

OBJECTIVES: To determine the impact of dedicated orthopaedic trauma room (DOTR) implementation on operating room efficiency and finances. DESIGN: Retrospective cost-analysis. SETTING: Single midsized academic-affiliated community hospital in Toronto, Canada. PARTICIPANTS: All patients that underwent the most frequently performed orthopaedic trauma procedures (hip hemiarthroplasty, open reduction internal fixation of the ankle, femur, elbow and distal radius), over a 4-year period from 2016 to 2019 were included. INTERVENTION: Patient data acquired for 2 years before the implementation of a DOTR was compared with data acquired for a 2-year period after its implementation, adjusting for the number of cases performed. MAIN OUTCOME MEASUREMENTS: The primary outcome was surgical duration. The secondary outcome was financial impact, including after-hours costs incurred and opportunity cost of displaced elective surgeries. RESULTS: One thousand nine hundred sixty orthopaedic cases were examined pre- and post-DOTR. All procedures had reduced total operative time post-DOTR (mean improvement of 33.4%). The number of daytime operating hours increased 21%, whereas after-hours decreased by 37.8%. Overtime staffing costs were reduced by $24,976 alongside increase in opportunity costs of $22,500. This resulted in a net profit of $2476. CONCLUSIONS: Our results support the premise that DOTRs improve operating room efficiency and can be cost efficient. Our study also specifically addresses the hesitation regarding potential loss of profit from elective surgeries. Widespread implementation can improve patient care while still remaining financially favorable. LEVEL OF EVIDENCE: Economic Level IV. See Instructions for Authors for a complete description of levels of evidence.

Distal femoral replacement or internal fixation for management of periprosthetic distal femur fractures: A systematic review.

BACKGROUND: The number of periprosthetic fractures above a total knee arthroplasty continues to increase. These fractures are associated with a high risk of morbidity and mortality. Techniques for addressing these fractures include open reduction internal fixation (ORIF) and revision arthroplasty, including distal femoral replacement (DFR). The primary aim of this review is to compare mortality and reoperation rates between ORIF and DFR when used to treat periprosthetic distal femur fractures. METHODS: A systematic review including MEDLINE, Embase and Cochrane Library databases was completed from inception to April 10, 2021. Studies including a comparator cohort were meta-analyzed. RESULTS: Fourteen studies were identified for inclusion, of which, five had sufficient homogeneity for inclusion in a meta-analysis. 30-day and 2-year mortality was 4.1% and 14.6% in the DFR group. There was no statistically significant difference between ORIF and DFR (log Odds-Ratio (OR) = -0.14, 95 %CI: -0.77 to 0.50). The reoperation rate in the DFR group was 9.3% versus 14.8% for ORIF, with no difference between groups (log OR = 0.10, 95 %CI: -0.59 to 0.79). There was no difference in rates of deep infection (log OR = 0.22, 95 %CI: -0.83 to 1.28). Direct comparison of functional outcomes was not possible, though did not appear significant. CONCLUSION: DFR in the setting of periprosthetic distal femur fractures is equivalent to ORIF with respect to mortality and reoperation rate and thus a safe and reliable treatment strategy. DFR may be more reliable in complex fracture patterns where the ability to obtain adequate fixation is difficult.

Megaprosthesis anti-bacterial coatings: A comprehensive translational review.

Periprosthetic joint infections (PJI) are catastrophic complications for patients with implanted megaprostheses and pose significant challenges in the management of orthopaedic oncology patients. Despite various preventative strategies, with the increasing rate of implanted orthopaedic prostheses, the number of PJIs may be increasing. PJIs are associated with a high rate of amputation. Therefore, novel strategies to combat bacterial colonization and biofilm formation are required. A promising strategy is the utilization of anti-bacterial coatings on megaprosthetic implants. In this translational review, a brief overview of the mechanism of bacterial colonization of implants and biofilm formation will be provided, followed by a discussion and classification of major anti-bacterial coatings currently in use and development. In addition, current in vitro outcomes, clinical significance, economic importance, evolutionary perspectives, and future directions of anti-bacterial coatings will also be discussed. Megaprosthetic anti-bacterial coating strategies will help reduce infection rates following the implantation of megaprostheses and would positively impact sarcoma care. STATEMENT OF SIGNIFICANCE: This review highlights the clinical challenges and a multitude of potential solutions to combating peri-prosthetic join infections in megaprotheses using anti-bacterial coatings. Reducing infection rates following the implantation of megaprostheses would have a major impact on sarcoma care and major trauma surgeries that require reconstruction of large skeletal defects.

Machine learning using preoperative patient factors can predict duration of surgery and length of stay for total knee arthroplasty.

BACKGROUND: Total knee arthroplasty (TKA) is one of the most resource-intensive, high-volume surgical procedures. Two drivers of the cost of TKAs are duration of surgery (DOS) and postoperative inpatient length of stay (LOS). The ability to predict TKA 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 using machine learning models (MLMs) based on preoperative factors. METHODS: The American College of Surgeons (ACS) National Surgical and Quality Improvement (NSQIP) database was queried for unilateral TKAs from 2014 to 2019. The dataset was split into training, validation, and testing based on year. Models (linear, tree-based, and multilayer perceptron (MLP)) were fitted to the training set in scikit-learn and PyTorch, with hyperparameters tuned on the validation set. The models were trained to minimize the mean squared error (MSE). Models with the best performance on the validation set were evaluated on the testing set according to 1) MSE, 2) buffer accuracy, and 3) classification accuracy, with results compared to a mean regressor. RESULTS: A total of 302,300 patients were included in this study. During validation, the PyTorch MLPs had the best MSEs for DOS (0.918) and LOS (0.715). During testing, the PyTorch MLPs similarly performed best based on MSEs for DOS (0.896) and LOS (0.690). While the scikit-learn MLP yielded the best 30-minute buffer accuracy for DOS (78.8%), the PyTorch MLP provided the best 1-day buffer accuracy for LOS (75.2%). Nearly all the ML models were more accurate than the mean regressors for both DOS and LOS. CONCLUSION: Conventional and deep learning models performed better than mean regressors for predicting DOS and LOS of unilateral elective TKA patients based on preoperative factors. Future work should include operational factors to improve overall predictions.

Frequency and reason for reoperation following non-invasive expandable endoprostheses: A systematic review.

BACKGROUND: Non-invasive expandable endoprostheses (NIEPR) utilize an external electromagnetic field to drive an innate mechanical gearbox. This lengthens the extremity following oncological resections in children with a predicted limb length discrepancy (LLD), facilitating limb-salvage. This review was conducted to assess NIEPR implant survival rates and identify modes of implant failure unique to these prostheses. METHODS: Medline, EMBASE and the Cochrane Library databases were searched for all manuscripts evaluating implant survival of NIEPRs implanted into skeletally immature patients following resection of extremity sarcomas. Minimum follow-up of 12 months or implant failure was required for inclusion. Failures were classified using the latest ISOLS classification and exact implant-specific failure modality was also identified. RESULTS: 19 studies met inclusion criteria. Mean age was 10.0 years (7.7 - 11.4 years). The most common locations for NIEPR implantation were the distal femur (343, 76.7%) and proximal tibia (53, 119%). Mean follow-up was 65.3 months (19.4 - 163 months). The overall implant revision rate was 46.2% (0 - 100%); implant specific revisions included maximal prosthesis lengthening with persistent LLD (10.4%), failed extension mechanism (6.1%), implant fracture (7.7%), hinge fracture (1.4%) and bushing wear (0.9%). Persistent clinically significant (>20 mm) LLD at final follow-up was present in 19.2% (0 - 50%) of patients. The mean MSTS score was 85.1% (66.7-96.3%) at final follow-up. CONCLUSION: Implant-related failures are the most common reason for NIEPR revision. Implant reliability appears to be improved with current designs. A sub-classification to the current classification system based on implant-specific failures for NIEPRs is proposed.