Literature DB >> 31279603

Development and Validation of an Evidence-Based Algorithm for Diagnosing Periprosthetic Joint Infection.

Noam Shohat1, Timothy L Tan2, Craig J Della Valle3, Tyler E Calkins3, Jaiben George4, Carlos Higuera4, Javad Parvizi2.   

Abstract

BACKGROUND: The 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.
METHODS: This 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.
RESULTS: The 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%).
CONCLUSION: This 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.
Copyright © 2019 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  algorithm; diagnosis; evidence-based; periprosthetic joint infection; total joint arthroplasty; validated

Year:  2019        PMID: 31279603     DOI: 10.1016/j.arth.2019.06.016

Source DB:  PubMed          Journal:  J Arthroplasty        ISSN: 0883-5403            Impact factor:   4.757


  8 in total

Review 1.  The Expanding Role of Biomarkers in Diagnosing Infection in Total Joint Arthroplasty: A Review of Current Literature.

Authors:  Ardalan Sayan; Adam Kopiec; Alisina Shahi; Madhav Chowdhry; Matthew Bullock; Ali Oliashirazi
Journal:  Arch Bone Jt Surg       Date:  2021-01

Review 2.  Diagnostic Value of Next-Generation Sequencing in Periprosthetic Joint Infection: A Systematic Review.

Authors:  Yuchen Tang; Dacheng Zhao; Shenghong Wang; Qiong Yi; Yayi Xia; Bin Geng
Journal:  Orthop Surg       Date:  2021-12-21       Impact factor: 2.071

3.  The quality of diagnostic studies used for the diagnostic criteria of periprosthetic joint infections.

Authors:  Mansi Patel; Aaron Gazendam; Thomas J Wood; Daniel Tushinski; Kamal Bali
Journal:  Eur J Orthop Surg Traumatol       Date:  2022-09-19

4.  CORR Insights®: What Is the Optimal Timing for Reading the Leukocyte Esterase Strip for the Diagnosis of Periprosthetic Joint Infection?

Authors:  Timothy L Tan
Journal:  Clin Orthop Relat Res       Date:  2021-06-01       Impact factor: 4.755

5.  What's New in Musculoskeletal Infection.

Authors:  Thomas K Fehring; Keith A Fehring; Angela Hewlett; Carlos A Higuera; Jesse E Otero; Aaron J Tande
Journal:  J Bone Joint Surg Am       Date:  2020-07-15       Impact factor: 6.558

6.  Assessment of a Multiplex Serological Test for the Diagnosis of Prosthetic Joint Infection: a Prospective Multicentre Study.

Authors:  Pascale Bémer; Céline Bourigault; Anne Jolivet-Gougeon; Chloé Plouzeau-Jayle; Carole Lemarie; Rachel Chenouard; Anne-Sophie Valentin; Sandra Bourdon; Anne-Gaëlle Leroy; Stéphane Corvec
Journal:  J Bone Jt Infect       Date:  2020-03-30

7.  Prosthetic joint infection diagnosis applying the three-level European Bone and Joint Infection Society (EBJIS) approach.

Authors:  Chiara Papalini; Giacomo Pucci; Giulia Cenci; Antonella Mencacci; Daniela Francisci; Auro Caraffa; Pierluigi Antinolfi; Maria Bruna Pasticci
Journal:  Eur J Clin Microbiol Infect Dis       Date:  2022-03-22       Impact factor: 5.103

8.  Synovial bone sialoprotein indicates aseptic failure in total joint arthroplasty.

Authors:  André Busch; Marcus Jäger; Florian Dittrich; Alexander Wegner; Stefan Landgraeber; Marcel Haversath
Journal:  J Orthop Surg Res       Date:  2020-05-27       Impact factor: 2.359

  8 in total

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