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Record W1972343395 · doi:10.1159/000137671

Neuropsychiatric Correlates of Cerebrospinal Fluid Biomarkers in Alzheimer’s Disease

2008· article· en· W1972343395 on OpenAlexaff
Ragnhild Eide Skogseth, Ezra Mulugeta, Clive Ballard, Arvid Rongve, Sabine Nore, Guido Alves, Dag Aarsland

Bibliographic record

VenueDementia and Geriatric Cognitive Disorders · 2008
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsCentre for Movement Disorders
Fundersnot available
KeywordsApathyCerebrospinal fluidPsychosisDepression (economics)Alzheimer's diseaseDementiaPsychologyInternal medicineDiseaseDegenerative diseasePsychiatryPathologyMedicine

Abstract

fetched live from OpenAlex

BACKGROUND: The aim of this study was to explore the relationship between cerebrospinal fluid biomarkers and neuropsychiatric symptoms in people with Alzheimer's disease. Psychosis, agitation, apathy and depression were assessed using standardised measures in 32 patients with mild Alzheimer's disease. METHODS: The levels of the 42-amino-acid form of beta-amyloid (A beta(1-42)), tau and p-tau (phosphorylated at threonine 181) were quantified using the conventional enzyme-linked immunosorbent assay method. RESULTS: Our result shows that apathy is significantly correlated with tau and p-tau but not with A beta(1-42). There were no significant correlations between indices of psychosis/agitation,or depression and cerebrospinal fluid A beta(1-42), tau or p-tau concentrations. CONCLUSION: Our finding suggests that apathy is associated with the level of neurofibrillary tangles in people with mild Alzheimer's disease. In contrast, the overall levels of neurofibrillary tangles or amyloid plaques do not seem to be associated with depression or psychosis, indicating that other brain changes contribute to these symptoms.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.273
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations75
Published2008
Admission routes1
Has abstractyes

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