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Record W4417498343 · doi:10.1016/j.xcrm.2025.102511

Glucagon-like peptide-1 medicines in neurological and psychiatric disorders

2025· article· en· W4417498343 on OpenAlexafffund
Susanna Fang, Daniel J. Drucker

Bibliographic record

VenueCell Reports Medicine · 2025
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsLunenfeld-Tanenbaum Research InstituteUniversity of Toronto
FundersCanadian Institutes of Health ResearchCanadian Cancer Society
KeywordsMigraineClinical trialHeadache DisordersDiabetes mellitusSafety profileAlternative medicine

Abstract

fetched live from OpenAlex

Glucagon-like peptide-1 (GLP-1) medicines are used for the treatment of type 2 diabetes (T2D) and obesity and reduce rates of cardiovascular disease, including stroke, in people with T2D. Substantial evidence from real-world data and clinical trials highlights the therapeutic potential of GLP-1 medicines for the treatment of neurodegenerative disorders such as Parkinson's and Alzheimer's diseases. Similarly, there is growing evidence for the potential utility of using GLP-1 medicines to reduce rates of smoking, or use of alcohol, tobacco, cannabis, or cocaine in individuals with substance use disorders. More limited clinical data suggest utility for GLP-1 medicines in patients with migraine or intracranial hypertension. The available data suggest that the use of GLP-1 medicines exhibits an acceptable safety profile in most individuals with neuropsychiatric disorders. Here, we review recent clinical evidence and ongoing trials exploring the efficacy and safety of GLP-1 medicines across a broad range of neurological conditions.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.221
Threshold uncertainty score0.650

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.007
GPT teacher head0.250
Teacher spread0.244 · 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

Citations4
Published2025
Admission routes2
Has abstractyes

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