The Ideal Total Hip Replacement Bearing Surface in the Young Patient: A Prospective Randomized Trial Comparing Alumina Ceramic-On-Ceramic With Ceramic-On-Conventional Polyethylene: 15-Year Follow-Up

© 2017 Background: The optimum bearing surface for total hip arthroplasty remains debatable. We have previously published our outcome at 10 years and this represents the 15-year follow-up. Methods: A total of 58 hips (in 57 patients with a mean age of 42 years) were randomized to receive either ceramic-on-ceramic (CoC) or ceramic-on-polyethylene (CoP) total hip arthroplasty. We prospectively followed for survivorship, functional outcomes (using the Harris Hip Score and the St Michael\u27s Hip Score [SMH]), and radiological outcomes. Results: At a minimum of 15 years, 3 patients had died, but not been revised. Seven were lost to follow-up. Five cases from the CoP group were revised (4 for polyethylene wear and osteolysis). Four from the CoC were revised; one each for head fracture, instability, infection, and trunnionosis. Both groups showed statistically significant improvements in Harris Hip Score scores and SMH functional scores, with no difference between the 2 bearings. For the CoP group, there was an improvement from 15.6 to 21.5 in the SMH and from 48.8 to 88.7 (P \u3e.05); and for CoC, this improvement was 15.8 to 23.5 and 50.3 to 94.6 (P \u3e.05), respectively. Mean wear rate of the polyethylene was 0.092 mm/y and for the CoC was 0.018 mm/y. Two patients in the CoC group had evidence of acetabular osteolysis vs 3 in the CoP. Six patients had femoral osteolysis in the CoC group and 12 in the CoP group. Conclusion: Survivorship and function of the 2 bearing groups remains comparable; while the polyethylene wear and osteolysis may represent issues in the future

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

The Effect of Computerized Physician Order Entry with Clinical Decision Support on the Rates of Adverse Drug Events: A Systematic Review

CONTEXT: Computerized physician order entry (CPOE) with clinical decision support (CDS) has been promoted as an effective strategy to prevent the development of a drug injury defined as an adverse drug event (ADE). OBJECTIVE: To systematically review studies evaluating the effects of CPOE with CDS on the development of an ADE as an outcome measure. DATA SOURCES: PUBMED versions of MEDLINE (from inception through March 2007) were searched to identify relevant studies. Reference lists of included studies were also searched. METHODS: We searched for original investigations, randomized and nonrandomized clinical trials, and observational studies that evaluated the effect of CPOE with CDS on the rates of ADEs. The studies identified were assessed to determine the type of computer system used, drug categories being evaluated, types of ADEs measured, and clinical outcomes assessed. RESULTS: Of the 543 citations identified, 10 studies met our inclusion criteria. These studies were grouped into categories based on their setting: hospital or ambulatory; no studies related to the long-term care setting were identified. CPOE with CDS contributed to a statistically significant (P \u3c or = .05) decrease in ADEs in 5 (50.0%) of the 10 studies. Four studies (40.0%) reported a nonstatistically significant reduction in ADE rates, and 1 study (10.0%) demonstrated no change in ADE rates. CONCLUSIONS: Few studies have measured the effect of CPOE with CDS on the rates of ADEs, and none were randomized controlled trials. Further research is needed to evaluate the efficacy of CPOE with CDS across the various clinical settings