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Record W7132913541

Investigating Nutritional Status in Moderate to Severe Alzheimer's Disease Patients Enrolled in a Randomized Controlled Trial with Nabilone

2018· dissertation· W7132913541 on OpenAlexaff
Chelsea Sherman

Bibliographic record

VenueTSpace · 2018
Typedissertation
Language
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMalnutritionRandomized controlled trialQuality of life (healthcare)DiseaseClinical trial
DOInot available

Abstract

fetched live from OpenAlex

Nutritional status is of great clinical significance in Alzheimer’s disease (AD) patients as malnutrition can increase risk of morbidity, mortality and severity of neuropsychiatric symptoms. Due to a lack of pharmacological treatments for malnutrition, we investigate the use of nabilone, a synthetic cannabinoid, for the improvement of nutritional status. Patients were recruited from a clinical trial in AD patients with clinically significant agitation. Patients treated with nabilone did not have improved nutritional status over time as assessed by the Mini Nutritional Assessment-Short Form (b=-0.020 (95%CI -0.27 to 0.23), p=0.87) and body mass index (b=0.020 (95%CI -0.13 to 0.17), p=0.79). Safety outcomes did not significantly differ with respect to nutrition for patients receiving nabilone treatment. By identifying efficacious interventions to manage nutrition in an at-risk population, there may be potential to improve quality of life for AD patients.

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)0.002
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: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.027
GPT teacher head0.364
Teacher spread0.337 · 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 designRandomized trial
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

Citations0
Published2018
Admission routes1
Has abstractyes

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