Association of GLP‐1 Receptor Agonists With Risk of Suicidal Ideation and Behaviour: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
ABSTRACT Background and Objective Glucagon‐like peptide‐1 receptor agonists (GLP‐1RAs) are widely used to treat type 2 diabetes and obesity, providing metabolic and cardiovascular benefits. However, concerns have emerged about potential neuropsychiatric side effects, including suicidal ideation and behaviour, prompting investigations by regulatory bodies such as the FDA and EMA. This systematic review and meta‐analysis aimed to assess the association between GLP‐1RA use and the risk of suicidal ideation or behaviour. Methods A systematic literature search was conducted in PubMed, Embase, and Web of Science through September 2024, adhering to PRISMA guidelines. Observational cohort and case‐control studies reporting suicidal ideation or behaviour in adults using GLP‐1RAs were included. The Modified Newcastle‐Ottawa Scale assessed risk of bias, and random‐effect models calculated risk ratios (RR) with 95% confidence intervals (CIs). Heterogeneity was assessed using the I 2 statistic. Results Of 126 studies, 11 were included from multiple countries with diverse designs. The meta‐analysis of four studies showed no statistically significant difference in suicidal outcomes between GLP‐1RA users and users of other anti‐hyperglycaemic drugs (RR: 0.568, 95% CI: 0.077–4.205). Substantial heterogeneity was observed (I 2 = 98%). Pharmacovigilance studies indicated no disproportionate increase in suicidality, while some observational studies suggested a lower risk. Conclusion This review found no significant link between GLP‐1RA use and increased suicidal ideation or behaviour. However, the high heterogeneity and reliance on pharmacovigilance data suggest caution. Clinicians should monitor patients, particularly those with psychiatric conditions, and further research is needed to assess long‐term neuropsychiatric safety.
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 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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.013 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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".