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Record W2897188104 · doi:10.1016/j.jalz.2018.07.098

P4‐276: CEREBROCHOLESTEROL, A MARKER OF AGITATION SEVERITY IN PATIENTS WITH MODERATE‐TO‐SEVERE ALZHEIMER'S DISEASE

2018· article· en· W2897188104 on OpenAlexaff
Myuri Ruthirakuhan, Nathan Herrmann, Damien Gallagher, Nicolaas Paul L.G. Verhoeff, Sandra E. Black, Krista L. Lanctôt

Bibliographic record

VenueAlzheimer s & Dementia · 2018
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsBaycrest HospitalSunnybrook HospitalOccupational Cancer Research CentreHealth Sciences CentreSunnybrook Health Science CentreUniversity of Toronto
Fundersnot available
KeywordsInternal medicinePlaceboMedicineCannabinoidRandomized controlled trialEndocrinologyPsychologyReceptorPathology

Abstract

fetched live from OpenAlex

Alzheimer's disease (AD) progression is associated with reduced brain cholesterol metabolism, which increases free cholesterol and reduces membrane fluidity. This may attenuate endocannabinoid system signalling, which has been implicated in agitation, and may also interfere with receptor binding of cannabinoid pharmacotherapies for agitation, such as nabilone. We assessed whether cerebrocholesterol (Cchol), the only brain cholesterol metabolite able to cross the blood brain barrier, was associated with agitation and treatment response to nabilone. Serum Cchol was collected from moderate-to-severe AD patients participating in a 14-week, double-blind cross-over trial comparing 6 weeks of nabilone to placebo with a 1-week washout between phases. Samples were collected at the start and end of each treatment phase. We assessed (1) the relationship between Cchol and Neuropsychiatric Inventory-Agitation/Aggression subscore (NPI-A/A), at baseline (BL); (2) the relationship between BL levels of Cchol and change in NPI-A/A, following nabilone treatment; and (3) the longitudinal relationship between changes in Cchol levels and changes in NPI-A/A, following nabilone treatment, in all patients, and in patients who demonstrated improvement on the Clinicians’ Global Impression of Change (CGIC). Thirty-nine patients (mean±SD age=86.7±10, 77% male, NPI-A/A=7.1±3.3, Mini-Mental Status Exam=6.3±6.3, Cchol=14.3±5.2 ng/mL) were randomized. There was no significant association between Cchol and NPI-A/A at BL (OR=0.098, 95% CI 0.002 to 5.423, p=0.257). However, in those with severe agitation/aggression (NPI-A/A≥6) (N=27), lower Cchol levels were significantly associated with greater NPI-A/A at BL (OR=0.005, 95% CI 0.00003 to 0.63, p=0.03). Lower BL Cchol levels had an associative trend with improvements in NPI-A/A with nabilone compared to placebo (b=-5.3, 95% -11.02 to 0.35, p=0.065). Increases in Cchol levels from BL had an associative trend with a reduction in NPI-A/A with nabilone compared to placebo (b=-4.0, 95% -8.24 to 0.27, p=0.067). In those with minimal to marked improvement on the CGIC during nabilone (N=17), increases in Cchol levels from BL were significantly associated with a reduction in NPI-A/A in nabilone compared to placebo (b=-8.1, 95% CI -12.7 to -3.5, p=0.001). These findings suggest that serum Cchol may be a marker of agitation severity in AD, and a marker of treatment response to nabilone.

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)0.001
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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.019
GPT teacher head0.276
Teacher spread0.257 · 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

Citations2
Published2018
Admission routes1
Has abstractyes

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