Medizinische Universität Graz Austria/Österreich - Forschungsportal - Medical University of Graz

Logo MUG-Forschungsportal

Gewählte Publikation:

SHR Neuro Krebs Kardio Lipid Stoffw Microb

Reyes-Coronel, C; Waser, M; Garn, H; Deistler, M; Dal-Bianco, P; Benke, T; Ransmayr, G; Grossegger, D; Schmidt, R.
Predicting rapid cognitive decline in Alzheimer's disease patients using quantitative EEG markers and neuropsychological test scores.
Conf Proc IEEE Eng Med Biol Soc. 2016; 2016(2):6078-6081 Doi: 10.1109/EMBC.2016.7592115
PubMed FullText FullText_MUG


Co-Autor*innen der Med Uni Graz
Schmidt Reinhold

Dimensions Citations:

Plum Analytics:

Scite (citation analytics):

Alzheimer's Disease (AD) can take different courses: some patients remain relatively stable while others decline rapidly within a given period of time. Losing more than 3 Mini-Mental State Examination (MMSE) points in one year is classified as rapid cognitive decline (RCD). This study used neuropsychological test scores and quantitative EEG (QEEG) markers obtained at a baseline examination to identify if an AD patient will be suffering from RCD. Data from 68 AD patients of the multi-centric cohort study PRODEM-Austria were applied. 15 of the patients were classified into the RCD group. RCD versus non-RCD support vector machine (SVM) classifiers using QEEG markers as predictors obtained 72.1% and 77.9% accuracy ratings based on leave-one-out validation. Adding neuropsychological test scores of Boston Naming Test improved the classifier to 80.9% accuracy, 80% sensitivity, and 81.1% specificity. These results indicate that QEEG markers together with neuropsychological test scores can be used as RCD predictors.
Find related publications in this database (using NLM MeSH Indexing)
Alzheimer Disease - diagnosis
Biomarkers - analysis
Cognitive Dysfunction - diagnosis
Cohort Studies -
Electroencephalography -
Humans -
Neuropsychological Tests -
Sensitivity and Specificity -

© Med Uni Graz Impressum