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Author Spotlight: Advancing Research on Candida albicans Biofilm-Associated Prosthetic Joint Infections
Published on: February 2, 2024
Periprosthetic joint infection: the algorithmic approach and emerging evidence
Javad Parvizi1, Snir Heller, Keith R Berend
1Vice Chairman and Director of Clinical Research, Rothman Institute, Thomas Jefferson University, Philadelphia, Pennsylvania.
Abstract:
Periprosthetic joint infections (PJIs) continue to affect patients, result in accelerated mortality, and consume approximately $1 billion of annual healthcare resources. The future of otherwise successful total joint arthroplasties can be jeopardized by PJI. In recent years, the issue of hospital-acquired infections has gained increasing attention in the United States and the rest of the world, and numerous efforts are being made to address this problem. The orthopaedic community continues to partner with societies, professional organizations, and industry to address this challenge. Recently, an international group of more than 300 surgical experts produced a 350-page document that outlines some of the best practices and identifies the evidence gap related to the management of PJIs. The document, using an algorithmic approach, outlines effective strategies for the prevention, diagnosis, and surgical management of PJIs. It is anticipated that the application of this algorithmic approach will lead to a reduction in the incidence of PJIs, will allow clinicians to diagnose PJI effectively and expeditiously, and will improve the outcome of patients affected by PJIs.
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