Assessment of Risk of Bias in Osteosarcoma and Ewing’s Sarcoma Randomized Controlled Trials: A Systematic Review

Aim: The aim of this study was to systematically assess the risk of bias in osteosarcoma and Ewing’s sarcoma (ES) randomized controlled trials (RCT) and to examine the relationships between bias and conflict of interest/industry sponsorship. Methods: An OVID-MEDLINE search was performed (1976–2019). Using the Cochrane Collaboration guidelines, two reviewers independently assessed the prevalence of risk of bias in different RCT design domains. The relationship between conflicts of interest and industry funding with the frequency of bias was examined. Results: 73 RCTs met inclusion criteria. Prevalence of low-risk bias domains was 47.3%, unclear-risk domains 47.8%, and 4.9% of the domains had a high-risk of bias. Domains with the highest risk of bias were blinding of participants/personnel and outcome assessors, followed by randomization and allocation concealment. Overtime, frequency of unclear-risk of bias domains decreased (χ2 = 5.32, p = 0.02), whilst low and high-risk domains increased (χ2 = 8.13, p = 0.004). Studies with conflicts of interest and industry sponsorships were 4.2 and 3.1 times more likely to have design domains with a high-risk of bias (p < 0.05). Conclusion: This study demonstrates that sources of potential bias are prevalent in both osteosarcoma and ES RCTs. Studies with financial conflicts of interest and industry sponsors were significantly more likely to have domains with a high-risk of bias. Improvements in reporting and adherence to proper methodology will reduce the risk of bias and improve the validity of the results of RCTs in osteosarcoma and ES

The association between preoperative COVID-19-positivity and acute postoperative complication risk among patients undergoing orthopedic surgery: a matched cohort analysis

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

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

Targeting glutathione with the triterpenoid CDDO-Im protects against benzo-a-pyrene-1,6-quinone-induced cytotoxicity in endothelial cells.

Epidemiological studies have exhibited a strong correlation between exposure to air pollution and deaths due to vascular diseases such as atherosclerosis. Benzo-a-pyrene-1,6-quinone (BP-1,6-Q) is one of the components of air pollutio

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

To summarize the research on the effectiveness of virtual reality (VR) therapy for the management of phantom limb pain (PLP). 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. 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. 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. Virtual 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.</p

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