Development and Validation of an Evidence-Based Algorithm for Diagnosing Periprosthetic Joint Infection |
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| Institution: | 1. Rothman Orthopaedic Institute at Thomas Jefferson University, Philadelphia, PA;2. Sackler Faculty of Medicine, Tel Aviv University, Ramat Aviv, Israel;3. Rush University Medical Center, Chicago, IL;4. Cleveland Clinic, Cleveland, OH;1. Exponent, Inc, Philadelphia, PA;2. School of Biomedical Engineering, Science, and Health Systems, Drexel University, Philadelphia, PA;3. Exponent, Inc, Menlo Park, CA;4. Kantonsspital Baselland, Basel University Medical Clinic and Interdisciplinary Unit for Orthopaedic Infections, Liestal, Switzerland;5. Rothman Institute, Philadelphia, PA;1. University of Pittsburgh School of Medicine, Pittsburgh, PA;2. Division of Infectious Disease, Department of Internal Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA;3. Division of General Internal Medicine, Center for Research on Health Care Data Center, University of Pittsburgh School of Medicine, Pittsburgh, PA;4. Department of Orthopaedic Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA;5. Arthritis and Arthroplasty Design Group, The Bone and Joint Center, Magee Womens Hospital of the University of Pittsburgh Medical Center, Pittsburgh, PA;6. Department of Orthopaedic Surgery, University of Pittsburgh, Pittsburgh, PA;7. Department of Bioengineering, Clinical and Translational Science Institute, University of Pittsburgh, Pittsburgh, PA;8. Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA;1. Rothman Orthopaedic Institute at Thomas Jefferson University, Philadelphia, PA;2. Department of Orthopaedic Surgery, Shanghai Jiaotong University Affiliated Shanghai Sixth People''s Hospital, Shanghai, China;3. Department of Orthopaedic Surgery, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan;4. Department of Orthopaedic Surgery, General Hospital of People''s Liberation Army, Beijing, China |
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| Abstract: | BackgroundThe guidelines for diagnosis of periprosthetic joint infection (PJI) introduced by the American Academy of Orthopaedic Surgeons served the orthopedic community well. However, they have never been validated and do not account for newer diagnostic modalities. Our aim was to update current guidelines and develop an evidence-based and validated diagnostic algorithm.MethodsThis multi-institutional study examined total joint arthroplasty patients from 3 institutions. Patients fulfilling major criteria for infection as defined by Musculoskeletal Infection Society were considered infected (n = 684). Patients undergoing aseptic revision for a noninfective indication and did not show evidence of PJI or undergo reoperation within 2 years served as a noninfected control group (n = 820). The algorithm was validated on a separate cohort of 422 cases.ResultsThe first step in evaluating PJI should include a physical examination, followed by serum C-reactive protein, erythrocyte sedimentation rate, and D-dimer. If at least one of these tests are elevated, or if high clinical suspicion exists, joint aspiration should be performed, sending the fluid for a white blood cell count, leukocyte esterase, polymorphonuclear percentage, and culture. Alpha defensin did not show added benefit as a routine diagnostic test. In inconclusive cases, intraoperative findings including gross purulence, histology, and next-generation sequencing or a single positive culture can aid in making the diagnosis. The proposed algorithm demonstrated a high sensitivity (96.9%) and specificity (99.5%).ConclusionThis validated, evidence-based algorithm for diagnosing PJI should guide clinicians in the workup of patients undergoing revision arthroplasty and improve clinical practice. It also has the potential to reduce cost. |
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| Keywords: | periprosthetic joint infection diagnosis algorithm total joint arthroplasty evidence-based validated |
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