CXCL13 as a biomarker in the diagnostics of European lyme Neuroborreliosis - A prospective multicentre study in Austria.

CXCL13 cut-off neuroborreliosis prospective multicentre study

Journal

Journal of central nervous system disease
ISSN: 1179-5735
Titre abrégé: J Cent Nerv Syst Dis
Pays: United States
ID NLM: 101595026

Informations de publication

Date de publication:
2024
Historique:
received: 27 10 2023
accepted: 27 03 2024
medline: 6 5 2024
pubmed: 6 5 2024
entrez: 6 5 2024
Statut: epublish

Résumé

'Definite Neuroborreliosis (NB)' is diagnosed with the presence of NB-specific symptoms, cerebrospinal fluid (CSF) pleocytosis and an elevated Definition of a CSF CXCL13 cut-off for the diagnosis of acute and untreated NB in a prospective study setting. This multicentre prospective study involved 6 neurological departments treating patients in the Lower Austria district (1.7 million inhabitants). The controls were patients scheduled for a spinal tap but not clinically diagnosed with NB. Demographic data, clinical characteristics and blood counts, as well as inflammatory CSF values and CSF CXCL13-concentration were analysed. We recruited 440 adult patients, of whom 42 have been diagnosed as having an acute and untreated 'definite NB'. Three hundred ninety-eight patients were assigned to the control group. The median intrathecal CXCL13 concentration was 2384 pg/ml for patients with NB and 0 pg/ml for controls. The difference was highly statistically significant ( Based on our results, we propose a CSF CXCL13 cut-off of 271 pg/ml with Euroimmun-Elisa for the diagnosis of acute and untreated NB. Due to its high sensitivity and specificity, CXCL13 is a strong candidate biomarker for routine NB assessment, especially in clinically unclear cases.

Sections du résumé

Background UNASSIGNED
'Definite Neuroborreliosis (NB)' is diagnosed with the presence of NB-specific symptoms, cerebrospinal fluid (CSF) pleocytosis and an elevated
Objective UNASSIGNED
Definition of a CSF CXCL13 cut-off for the diagnosis of acute and untreated NB in a prospective study setting.
Design and methods UNASSIGNED
This multicentre prospective study involved 6 neurological departments treating patients in the Lower Austria district (1.7 million inhabitants). The controls were patients scheduled for a spinal tap but not clinically diagnosed with NB. Demographic data, clinical characteristics and blood counts, as well as inflammatory CSF values and CSF CXCL13-concentration were analysed.
Results UNASSIGNED
We recruited 440 adult patients, of whom 42 have been diagnosed as having an acute and untreated 'definite NB'. Three hundred ninety-eight patients were assigned to the control group. The median intrathecal CXCL13 concentration was 2384 pg/ml for patients with NB and 0 pg/ml for controls. The difference was highly statistically significant (
Conclusion UNASSIGNED
Based on our results, we propose a CSF CXCL13 cut-off of 271 pg/ml with Euroimmun-Elisa for the diagnosis of acute and untreated NB. Due to its high sensitivity and specificity, CXCL13 is a strong candidate biomarker for routine NB assessment, especially in clinically unclear cases.

Identifiants

pubmed: 38706882
doi: 10.1177/11795735241247026
pii: 10.1177_11795735241247026
pmc: PMC11067428
doi:

Types de publication

Journal Article

Langues

eng

Pagination

11795735241247026

Informations de copyright

© The Author(s) 2024.

Déclaration de conflit d'intérêts

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Auteurs

Christoph Waiß (C)

Department of Neurology, Karl-Landsteiner-Private University of Health Sciences (KLPU), University Hospital St. Poelten, St Polten, Austria.

Barbara Ströbele (B)

Institute of Hygiene and Microbiology, Karl-Landsteiner-Private University of Health Sciences (KLPU), University Hospital St. Poelten, St Polten, Austria.

Uwe Graichen (U)

Department for Health Sciences, Biostatistics and Data Science, Karl-Landsteiner-Private University of Health Sciences (KLPU), Krems an der Donau, Austria.

Sascha Klee (S)

Department for Health Sciences, Biostatistics and Data Science, Karl-Landsteiner-Private University of Health Sciences (KLPU), Krems an der Donau, Austria.

Joshua Gartlehner (J)

Department of Neurology, Karl-Landsteiner-Private University of Health Sciences (KLPU), University Hospital St. Poelten, St Polten, Austria.

Estelle Sonntagbauer (E)

Department of Neurology, Karl-Landsteiner-Private University of Health Sciences (KLPU), University Hospital St. Poelten, St Polten, Austria.

Stephanie Hirschbichler (S)

Department of Neurology, Karl-Landsteiner-Private University of Health Sciences (KLPU), University Hospital St. Poelten, St Polten, Austria.

Alexander Tinchon (A)

Department of Neurology, Karl-Landsteiner-Private University of Health Sciences (KLPU), University Hospital St. Poelten, St Polten, Austria.

Emrah Kacar (E)

Department of Neurology, Karl-Landsteiner-Private University of Health Sciences (KLPU), University Hospital Tulln, Tulln, Austria.

Bianca Wuchty (B)

Department of Neurology, Hospital Mistelbach, Mistelbach, Austria.

Bianka Novotna (B)

Department of Neurology, Hospital Mistelbach, Mistelbach, Austria.

Zofia Kühn (Z)

Department of Neurology, Hospital Wr. Neustadt, Wiener Neustadt, Austria.

Johann Sellner (J)

Department of Neurology, Hospital Mistelbach, Mistelbach, Austria.

Walter Struhal (W)

Department of Neurology, Karl-Landsteiner-Private University of Health Sciences (KLPU), University Hospital Tulln, Tulln, Austria.

Christian Bancher (C)

Department of Neurology, Hospital Horn, Horn, Austria.

Peter Schnider (P)

Department of Neurology, Hospital Wr. Neustadt, Wiener Neustadt, Austria.

Susanne Asenbaum-Nan (S)

Department of Neurology, Hospital Amstetten, Amstetten, Austria.

Stefan Oberndorfer (S)

Department of Neurology, Karl-Landsteiner-Private University of Health Sciences (KLPU), University Hospital St. Poelten, St Polten, Austria.
Karl Landsteiner Institute for Neurology and Neuropsychology St. Poelten, Krems an der Donau, Austria.

Classifications MeSH