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Validation of the Erlangen Score Algorithm for Differential Dementia Diagnosis in Autopsy-Confirmed Subjects.
- Source :
-
Journal of Alzheimer's disease : JAD [J Alzheimers Dis] 2019; Vol. 68 (3), pp. 1151-1159. - Publication Year :
- 2019
-
Abstract
- Background: Despite decades of research on the optimization of the diagnosis of Alzheimer's disease (AD), its biomarker-based diagnosis is being hampered by the lack of comparability of raw biomarker data. In order to overcome this limitation, the Erlangen Score (ES), among other approaches, was set up as a diagnostic-relevant interpretation algorithm.<br />Objective: To validate the ES algorithm in a cohort of neuropathologically confirmed cases with AD (n = 106) and non-AD dementia (n = 57).<br />Methods: Cerebrospinal fluid (CSF) biomarker concentrations of Aβ1-42, T-tau, and P-tau181 were measured with commercially available single analyte ELISA kits. Based on these biomarkers, ES was calculated as previously reported.<br />Results: This algorithm proved to categorize AD in different degrees of likelihood, ranging from neurochemically "normal", "improbably having AD", "possibly having AD", to "probably having AD", with a diagnostic accuracy of 74% using the neuropathology as a reference.<br />Conclusion: The ability of the ES to overcome the high variability of raw CSF biomarker data may provide a useful diagnostic tool for comparing neurochemical diagnoses between different labs or methods used.
- Subjects :
- Aged
Aged, 80 and over
Algorithms
Alzheimer Disease cerebrospinal fluid
Alzheimer Disease diagnosis
Alzheimer Disease pathology
Amyloid beta-Peptides cerebrospinal fluid
Autopsy
Biomarkers cerebrospinal fluid
Brain pathology
Dementia cerebrospinal fluid
Dementia pathology
Diagnosis, Differential
Female
Humans
Male
Middle Aged
Peptide Fragments cerebrospinal fluid
ROC Curve
Reproducibility of Results
tau Proteins cerebrospinal fluid
Dementia diagnosis
Subjects
Details
- Language :
- English
- ISSN :
- 1875-8908
- Volume :
- 68
- Issue :
- 3
- Database :
- MEDLINE
- Journal :
- Journal of Alzheimer's disease : JAD
- Publication Type :
- Academic Journal
- Accession number :
- 30883344
- Full Text :
- https://doi.org/10.3233/JAD-180563