ArticleInternational journal of Alzheimer's disease2011
Does EEG montage influence Alzheimer's disease electroclinic diagnosis?
Article in International journal of Alzheimer's disease, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Systematic Review on Resting-State EEG for Alzheimer's Disease Diagnosis and Progression Assessment.Disease markers · 2018Pooled it
- The effects of automated artifact removal algorithms on electroencephalography-based Alzheimer's disease diagnosis.Frontiers in aging neuroscience · 2014Article
- Characterizing Alzheimer's disease severity via resting-awake EEG amplitude modulation analysis.PloS one · 2013Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
There is not a specific Alzheimer's disease (AD) diagnostic test. AD diagnosis relies on clinical history, neuropsychological, and laboratory tests, neuroimaging and electroencephalography. Therefore, new approaches are necessary to enable earlier and more accurate diagnosis and to measure treatment results. Quantitative EEG (qEEG) can be used as a diagnostic tool in selected cases. The aim of this study was to answer if distinct electrode montages have different sensitivity when differentiating controls from AD patients. We analyzed EEG spectral peaks (delta, theta, alpha, beta, and gamma bands), and we compared references (Biauricular, Longitudinal bipolar, Crossed bipolar, Counterpart bipolar, and Cz reference). Support Vector Machines and Logistic Regression classifiers showed Counterpart bipolar montage as the most sensitive electrode combination. Our results suggest that Counterpart bipolar montage is the best choice to study EEG spectral peaks of controls versus AD.
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Registered trials
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