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Cited by 731

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Cerebrospinal fluid analysis: disease-related data patterns and evaluation programs

Open access
Reiber, Hansotto, Peter, James B.·2001·Journal of the Neurological Sciences

Abstract

Cerebrospinal fluid (CSF) analysis is a basic tool for diagnosis of neurological diseases. Knowledge regarding blood-CSF barrier function (molecular flux/CSF flow theory) and neuroimmunology is reviewed to aid understanding and evaluation of CSF data. Disease-related immunoglobulin patterns (IgG, IgA, IgM with reference to albumin) are described in CSF/serum quotient diagrams with the hyperbolic reference range for blood-derived protein fractions in CSF. Clinical relevance of complementary analyses (cytology, PCR, oligoclonal IgG, antibody detection and brain-derived proteins) is briefly discussed. Integrated CSF data reports are shown with numerical and graphical data representation, reference range-related interpretation and diagnosis-related comments. The principles and rationale of general CSF analysis reported in this review should enable the reader to accurately interpret CSF data profiles, and to plan a proper evaluation of new brain- or blood-derived analytes in CSF.

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Metadata

Authors
Reiber, H., & Peter, J. B.
Venue
Journal of the Neurological Sciences
Publisher
Elsevier BV
Published
2001-03
Volume
184
Issue
2
Pages
101-122
ISSN
0022-510X (ISSN-L)
OpenAlex
W1967138600
Cited by
731
References
1
FWCI
5.45
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Cerebrospinal fluid analysis: disease-related data patterns and evaluation programs. https://app.cochat.ai/papers/10.1016/s0022-510x(00)00501-3
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Reiber, H., & Peter, J. B. (2001). Cerebrospinal fluid analysis: disease-related data patterns and evaluation programs. Journal of the Neurological Sciences. https://doi.org/10.1016/s0022-510x(00)00501-3

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.