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Record W2001976096 · doi:10.1159/000221835

Long-Term Statin Therapy and CSF Cholesterol Levels: Implications for Alzheimer’s Disease

2009· article· en· W2001976096 on OpenAlexafffund
Barbara Evans, Stephen P. Baker, Kevin Kane, Joan M. Swearer, Douglas Hinerfeld, Richard J. Caselli, Ekaterina Rogaeva, Peter St George‐Hyslop, Majaz Moonis, Daniel A. Pollen

Bibliographic record

VenueDementia and Geriatric Cognitive Disorders · 2009
Typearticle
Languageen
FieldMedicine
TopicLipoproteins and Cardiovascular Health
Canadian institutionsToronto Western HospitalUniversity of Toronto
FundersCanadian Institutes of Health ResearchWellcome Trust
KeywordsLathosterolInternal medicineCholesterolEndocrinologyMedicineSimvastatinAtorvastatinCerebrospinal fluidApolipoprotein BAsymptomaticApolipoprotein EStatinGastroenterologyDisease

Abstract

fetched live from OpenAlex

BACKGROUND/AIMS: It is not yet established whether statins (lipophilic or hydrophilic) reduce the risk of Alzheimer's disease and, if so, by differentially modifying brain lipid levels. Our aim was to assess changes in brain cholesterol metabolism as reflected in the cerebrospinal fluid (CSF) before and after treatment with either atorvastatin or simvastatin. METHODS: We carried out a longitudinal analysis of CSF cholesterol, lathosterol and 24(S)-hydroxycholesterol before and after treatment with maximum doses of statins in 10 asymptomatic subjects, 8 of whom were heterozygous for apolipoprotein E epsilon4, and in 6 presymptomatic PS1 subjects. RESULTS: Statins initially reduced CSF lathosterol cholesterol and 24(S)-hydroxycholesterol in both PS1 and non-PS1 subjects reaching a nadir at 6-7 months, followed by a return to baseline at 15 months with an overshoot at 2 years, tending to return to baseline thereafter. CONCLUSIONS: Possible long-term protective effects of statins are not likely largely related to the temporally-dependent biphasic effects of statin therapy upon the magnitude and direction of changes in CSF lipid levels and their subsequent return to baseline levels.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.854
Threshold uncertainty score0.581

Codex and Gemma teacher scores by category

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

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 head0.033
GPT teacher head0.316
Teacher spread0.283 · 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 teacher head, 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

Citations31
Published2009
Admission routes2
Has abstractyes

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