ArticleScientific reports2025
Clinical validation of new alzheimer disease diagnosis tools based on plasma p-Tau217.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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.
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Who cites it
1 citing paper in PubMed.
- Knowledge-Guided Deep Learning with Clinical EEG Biomarkers for Automated Dementia Detection and Staging.Diagnostics (Basel, Switzerland) · 2026Article
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Authors and funding
10 authors.
Funding
Abstract
Nowadays, there is an unmet need for reliable and minimally-invasive diagnosis tools capable of detecting Alzheimer's disease at early stages. Such tools could significantly reduce the reliance on confirmatory tests that are invasive and costly, such as cerebrospinal fluid (CSF) biomarkers and neuroimaging. The aim of this study is to validate previously developed diagnosis tools (multivariate models and plasma p-Tau217 levels) in three independents cohorts. For this, a cohort was obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) including some variables (age, Apolipoprotein E (ApoE) genotype, plasma p-Tau217, CSF biomarkers) (n = 113); and two cohorts from cognitive disorders units (Hospital Universitari i Politècnic La Fe (HUiPLaFe, n = 163), Hospital Doctor Peset (n = 31)), whose plasma samples were analysed to determine plasma p-Tau217, and to evaluate the previous diagnosis tools performance. For the cohort from HUiPLaFe, the multivariate model (plasma p-Tau217, age, ApoE genotype) showed a sensitivity of 94.9% and a specificity of 88.2%; for the cohort from Hospital Doctor Peset, the sensitivity was 100% and specificity 80%; for the ADNI cohort, sensitivity was 89.5% and specificity 39.5%. Regarding the plasma p-Tau217 levels, the results were satisfactory for the cognitive disorders units; while ADNI cohort showed very low specificity. In conclusion, the multivariate model was clinically validated in independent cohorts from clinical units, representing its first step for implementation.
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