The diagnosis of periprosthetic joint infection after the arthroplasty of knee joint
DOI:
https://doi.org/10.12775/JEHS.2023.13.02.018Keywords
joint infection, diagnostic criteria, knee arthroplasty, total knee arthroplasty, periprostethicAbstract
Total knee replacement is one of the most widely performed surgeries. It is stated as the most efficient method of treating end-stage osteoarthritis of the knee joint. Due to the aging of the population and the prevalence of osteoarthritis, the number of arthroplasties is increasing every day. Such extensive surgical procedures are associated with a large number of postoperative complications, one of which is periprosthetic joint infection. The reported prevalence of PJI out to 2 years after knee replacement is 1.55 %. Misconceptions in the management of periprosthetic joint infection (PJI) can compromise the treatment success. The aim of the following article was to provide an overview of the medical knowledge on the periprosthetic joint infection after the arthroplasty of knee joint.
Infections are caused by microbes that can enter the joint, which are most often coagulase-negative Staphylococci, Staphylococcus Aureus, Streptococci, Enterococci and Gram-negative bacteria. Fungal infections are much less common. The diagnostic process requires the involvement of a large group of medical personnel, which is why protocols with algorithms have been created to facilitate and standardize the diagnosis in the direction of periprosthetic joint infections. Mainly used tests from the patient's serum, synovial tests and histology. The positive results of the above tests are taken into account in the assessment of the fulfillment of the major and minor criteria to assess the likelihood of the occurrence of periprosthetic infection. This research paper aims to analyze the latest medical reports on the PJI diagnostic algorithm, laboratory and imaging studies of their effectiveness. This article was written based on analyzing data available in publications in Pubmed and Google Scholar databases
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