JOEI The Journal
Will robotic-assistance improve outcomes in knee replacement over traditional optical navigation?
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5 -Minute Summary: High-Volume Total Joint Arthroplasty in Resource-Limited Settings: A Systems-Based Framework for International Surgical Collaboration
This review describes a systems-based framework for delivering high-volume total hip and knee arthroplasty in a resource-limited environment through long-term international collaboration.
5-Min Summary: A Look at the Outliers: Optimal Placement for Reverse Total Shoulder Arthroplasty
The purpose of this study was to identify pre- and post-operative radiographic measurements in patients who achieved excellent range of motion to optimize implant positioning in patients undergoing rTSA. We hypothesized that restoring the lateral humeral offset to closely align with the patient’s pre-operative anatomy, along with achieving optimal lateralization and distalization shoulder angles as outlined in the literature, would correlate with excellent clinical outcomes.
Standardizing the Unstandardized: Can We Create a Universal PJI Pathway?
The recording of The Journal of Orthopaedic Experience & Innovation Zoom "Open Mic" featuring Nathanael Heckmann, MD (moderator), James Baker, MD, & Chris Hoedt, MD.
5-Min Summary: Computer Navigation in Revision Total Joint Arthroplasty: National Utilization and Comparative Mid-Term Outcomes
Computer navigation (CN), with or without the use of robotics, is increasingly utilized in primary total joint arthroplasty (TJA). Although evidence supporting its clinical benefit remains limited, its role in the revision setting is even less defined. This study evaluates national utilization trends and compares 2-year implant-related complications of CN and conventional revision total hip (rTHA) and knee arthroplasty (rTKA).
5-Minute Summary: Citation Inaccuracies in Orthopaedic Surgery: A Novel Classification and Precautions for AI-Generated Bibliographies.
This study identifies a 20.1% overall citation error rate in orthopaedic surgery literature, with nearly 10% classified as major errors. A new classification system for citation accuracy is introduced, revealing significant pre-existing inaccuracies. The research also shows that current AI tools, like ChatGPT, cannot reliably verify citations due to limited access and the rubric used.
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