Psychiatric adverse events linked to glucagon-like peptide 1 analogues: a disproportionality analysis in American, Canadian and Australian adverse event databases
Bibliographic record
Abstract
BACKGROUND: Glucagon-like peptide 1 (GLP-1) analogues are a class of medications that stimulate glucose-dependent insulin release and slow gastric emptying. With the increasing use of GLP-1 analogues, concerns about potential psychiatric adverse events (AEs) remain under-explored. AIM: This pharmacovigilance study aimed to investigate the prevalence of psychiatric AEs associated with currently available GLP-1 analogues by analysing publicly available national datasets from the US (FAERS), Canada (CVAROD) and Australia (DAEN). METHOD: Psychiatric AE reports were extracted from all three databases for all approved GLP-1 analogues. A disproportionality analysis was conducted to calculate reporting odds ratios (RORs) and 95% confidence intervals (CIs) for psychiatric AEs of interest. RESULTS: Significant associations were identified when multiple databases reported elevated RORs. Semaglutide was associated with depressive symptoms (FAERS, ROR = 6.24 CI 4.49-8.69), panic attacks (FAERS, ROR = 1.46 CI 1.16-1.82) and suicidal ideation (FAERS, ROR = 2.58 CI 2.31-2.88). Liraglutide was linked to depression (CVAROD, ROR = 1.68 CI 1.12-2.51), while dulaglutide showed positive associations with eating disorders (FAERS, ROR = 1.47 CI 1.26-1.71) and insomnia (FAERS, ROR = 2.93 CI 2.35-3.66). CONCLUSION: GLP-1 analogues, particularly semaglutide and liraglutide, are associated with significant psychiatric AEs, especially depression and suicidal ideation. Further studies are required to understand the mechanisms underlying these associations, particularly in patients with pre-existing psychiatric conditions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".