Literature DB >> 25320195

The host response: Toll-like receptor expression in periprosthetic tissues as a biomarker for deep joint infection.

Cara Cipriano1, Aparna Maiti1, Gregory Hale1, William Jiranek1.   

Abstract

BACKGROUND: Toll-like receptors (TLRs) 1 and 6 are consistent molecular indicators of the host inflammatory response against bacterial infection. Our aims were to determine whether TLR elevation could be detected in infected periprosthetic tissues and to assess the utility of these biomarkers as tests for detecting a periprosthetic joint infection.
METHODS: Fifty-nine patients undergoing revision total joint arthroplasty (twenty-seven hips and thirty-two knees) were prospectively evaluated for periprosthetic joint infection according to currently recommended diagnostic criteria. Nine patients were excluded because of insufficient work-up, leaving fifty available for study. Of these, twenty-one were categorized as infected and twenty-nine as noninfected. Periprosthetic tissues were collected intraoperatively, and total RNA was extracted by standard techniques. Expression of TLR messenger RNAs was assessed by first-strand complementary DNA synthesis from 1 μg of total RNA followed by real-time PCR (polymerase chain reaction). Results were normalized relative to the housekeeping gene GAPDH (glyceraldehyde 3-phosphate dehydrogenase). Expression of TLRs 1, 6, and 10 in the infected and noninfected groups was compared with use of the Student t test. The receiver operating characteristic curve, area under the curve (AUC), sensitivity, specificity, positive likelihood ratio (LR+), and negative likelihood ratio (LR-) were calculated to determine the accuracy of each TLR for predicting periprosthetic joint infection at its optimal diagnostic threshold.
RESULTS: Mean TLR1 mRNA expression was significantly elevated in infected compared with noninfected samples (0.600 compared with 0.005, p = 0.0003); the same was true of TLR6 (0.208 compared with 0.0165, p = 0.0059) but not of TLR10 (0.00019 compared with 0.00014, p = 0.6238). The AUC was 0.995 for TLR1, 0.883 for TLR6, and 0.546 for TLR10. The optimal threshold for diagnosing periprosthetic joint infection was 0.0924 for TLR1 (sensitivity = 95.2%, specificity = 100%, LR+ = 13.80, LR- = 0.91) and 0.0215 for TLR6 (sensitivity = 85.7%, specificity = 82.8%, LR+ = 4.98, LR- = 0.83).
CONCLUSIONS: In our pilot study, TLR1 expression in periprosthetic tissues most accurately predicted periprosthetic joint infection. This measure of the host response may be particularly helpful in detecting culture-negative infections and avoiding false positives resulting from contamination. LEVEL OF EVIDENCE: Diagnostic Level III. See Instructions for Authors for a complete description of levels of evidence.
Copyright © 2014 by The Journal of Bone and Joint Surgery, Incorporated.

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Year:  2014        PMID: 25320195     DOI: 10.2106/JBJS.M.01295

Source DB:  PubMed          Journal:  J Bone Joint Surg Am        ISSN: 0021-9355            Impact factor:   5.284


  9 in total

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Review 2.  The Expanding Role of Biomarkers in Diagnosing Infection in Total Joint Arthroplasty: A Review of Current Literature.

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Review 4.  Diagnosis of peripheral bone and prosthetic joint infections: overview on the consensus documents by the EANM, EBJIS, and ESR (with ESCMID endorsement).

Authors:  Luca Maria Sconfienza; Alberto Signore; Victor Cassar-Pullicino; Maria Adriana Cataldo; Olivier Gheysens; Olivier Borens; Andrej Trampuz; Klaus Wörtler; Nicola Petrosillo; Heinz Winkler; Filip M H M Vanhoenacker; Paul C Jutte; Andor W J M Glaudemans
Journal:  Eur Radiol       Date:  2019-06-27       Impact factor: 5.315

Review 5.  Advancements in Diagnosing Periprosthetic Joint Infections after Total Hip and Knee Arthroplasty.

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Journal:  Open Orthop J       Date:  2016-11-30

6.  Peri-prosthetic tissue cells show osteogenic capacity to differentiate into the osteoblastic lineage.

Authors:  Monique A E Schoeman; Angela E Oostlander; Karien Ede Rooij; Edward R Valstar; Rob G H H Nelissen
Journal:  J Orthop Res       Date:  2017-04-13       Impact factor: 3.494

7.  Excellent Diagnostic Characteristics for Ultrafast Gene Profiling of DEFA1-IL1B-LTF in Detection of Prosthetic Joint Infections.

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Journal:  J Clin Microbiol       Date:  2017-06-21       Impact factor: 5.948

Review 8.  Histopathology in Periprosthetic Joint Infection: When Will the Morphomolecular Diagnosis Be a Reality?

Authors:  G Bori; M A McNally; N Athanasou
Journal:  Biomed Res Int       Date:  2018-05-13       Impact factor: 3.411

9.  Consensus document for the diagnosis of prosthetic joint infections: a joint paper by the EANM, EBJIS, and ESR (with ESCMID endorsement).

Authors:  Alberto Signore; Luca Maria Sconfienza; Olivier Borens; Andor W J M Glaudemans; Victor Cassar-Pullicino; Andrej Trampuz; Heinz Winkler; Olivier Gheysens; Filip M H M Vanhoenacker; Nicola Petrosillo; Paul C Jutte
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  9 in total

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