Synovial Fluid d-Lactate-A Novel Pathogen-Specific Biomarker for the Diagnosis of Periprosthetic Joint Infection.


Journal

The Journal of arthroplasty
ISSN: 1532-8406
Titre abrégé: J Arthroplasty
Pays: United States
ID NLM: 8703515

Informations de publication

Date de publication:
08 2020
Historique:
received: 09 02 2020
revised: 02 03 2020
accepted: 08 03 2020
pubmed: 10 4 2020
medline: 20 3 2021
entrez: 10 4 2020
Statut: ppublish

Résumé

Synovial fluid d-lactate may be useful for diagnosing periprosthetic joint infection (PJI) as this biomarker is exclusively produced by bacteria. We evaluated the performance of synovial fluid d-lactate using 2 definition criteria and determined its optimal cutoff value for diagnosing PJI. Consecutive patients undergoing joint aspiration before prosthesis revision were prospectively included. Synovial fluid was collected for culture, leukocyte count, and d-lactate concentration (by spectrophotometry). Youden's J statistic was used for determining optimal d-lactate cutoff value on the receiver operating characteristic curve by maximizing sensitivity and specificity. A total of 224 patients were included. Using Musculoskeletal Infection Society criteria, 71 patients (32%) were diagnosed with PJI and 153 (68%) with aseptic failure (AF), whereas using institutional criteria, 92 patients (41%) were diagnosed with PJI and 132 (59%) with AF. The optimal cutoff of synovial fluid d-lactate to differentiate PJI from AF was 1.3 mmol/L, independent of the used definition criteria. Synovial fluid d-lactate had a sensitivity of 94.3% (95% confidence interval [95% CI], 86.2-98.4) and specificity of 78.4% (95% CI, 66.8-81.2) using Musculoskeletal Infection Society criteria, whereas its sensitivity was 92.4% (95% CI, 84.9-96.9) and specificity 88.6% (95% CI, 81.9-93.5) using institutional criteria. The concentration of d-lactate was higher in infections caused by Staphylococcus aureus (P < .001) and streptococci (P = .016) than by coagulase-negative staphylococci or in culture-negative PJI. The synovial fluid d-lactate showed high sensitivity (>90%) for diagnosis of PJI using both definition criteria and correlated with the pathogen virulence. The high sensitivity makes this biomarker useful as a point-of-care screening test for PJI. Diagnostic level I.

Sections du résumé

BACKGROUND
Synovial fluid d-lactate may be useful for diagnosing periprosthetic joint infection (PJI) as this biomarker is exclusively produced by bacteria. We evaluated the performance of synovial fluid d-lactate using 2 definition criteria and determined its optimal cutoff value for diagnosing PJI.
METHODS
Consecutive patients undergoing joint aspiration before prosthesis revision were prospectively included. Synovial fluid was collected for culture, leukocyte count, and d-lactate concentration (by spectrophotometry). Youden's J statistic was used for determining optimal d-lactate cutoff value on the receiver operating characteristic curve by maximizing sensitivity and specificity.
RESULTS
A total of 224 patients were included. Using Musculoskeletal Infection Society criteria, 71 patients (32%) were diagnosed with PJI and 153 (68%) with aseptic failure (AF), whereas using institutional criteria, 92 patients (41%) were diagnosed with PJI and 132 (59%) with AF. The optimal cutoff of synovial fluid d-lactate to differentiate PJI from AF was 1.3 mmol/L, independent of the used definition criteria. Synovial fluid d-lactate had a sensitivity of 94.3% (95% confidence interval [95% CI], 86.2-98.4) and specificity of 78.4% (95% CI, 66.8-81.2) using Musculoskeletal Infection Society criteria, whereas its sensitivity was 92.4% (95% CI, 84.9-96.9) and specificity 88.6% (95% CI, 81.9-93.5) using institutional criteria. The concentration of d-lactate was higher in infections caused by Staphylococcus aureus (P < .001) and streptococci (P = .016) than by coagulase-negative staphylococci or in culture-negative PJI.
CONCLUSION
The synovial fluid d-lactate showed high sensitivity (>90%) for diagnosis of PJI using both definition criteria and correlated with the pathogen virulence. The high sensitivity makes this biomarker useful as a point-of-care screening test for PJI.
LEVEL OF EVIDENCE
Diagnostic level I.

Identifiants

pubmed: 32269008
pii: S0883-5403(20)30264-3
doi: 10.1016/j.arth.2020.03.016
pii:
doi:

Substances chimiques

Biomarkers 0
Lactic Acid 33X04XA5AT
C-Reactive Protein 9007-41-4

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

2223-2229.e2

Informations de copyright

Copyright © 2020 Elsevier Inc. All rights reserved.

Auteurs

Svetlana Karbysheva (S)

Charité - Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Center for Musculoskeletal Surgery (CMSC), Berlin, Germany; Federal Center of Traumatology, Orthopedics and Arthroplasty, Barnaul, Russia; Berlin-Brandenburg School for Regenerative Therapies (BSRT), Charité - Universitätsmedizin Berlin, Berlin, Germany.

Katsiaryna Yermak (K)

Charité - Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Center for Musculoskeletal Surgery (CMSC), Berlin, Germany.

Ludmila Grigoricheva (L)

Federal Center of Traumatology, Orthopedics and Arthroplasty, Barnaul, Russia.

Nora Renz (N)

Charité - Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Center for Musculoskeletal Surgery (CMSC), Berlin, Germany.

Carsten Perka (C)

Charité - Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Center for Musculoskeletal Surgery (CMSC), Berlin, Germany.

Andrej Trampuz (A)

Charité - Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Center for Musculoskeletal Surgery (CMSC), Berlin, Germany; Berlin-Brandenburg School for Regenerative Therapies (BSRT), Charité - Universitätsmedizin Berlin, Berlin, Germany.

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Classifications MeSH