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Record W4407947558 · doi:10.1136/bmj-2024-080679

Glucagon-like peptide-1 receptor agonists and risk of suicidality among patients with type 2 diabetes: active comparator, new user cohort study

2025· article· en· W4407947558 on OpenAlexafffund
Samantha B. Shapiro, Hui Yin, Oriana Hoi Yun Yu, Soham Rej, Samy Suissa, Laurent Azoulay

Bibliographic record

VenueBMJ · 2025
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsMcGill UniversityJewish General Hospital
FundersCanadian Institutes of Health Research
KeywordsMedicineHazard ratioCohortType 2 diabetesInternal medicineGlucagon-like peptide 1 receptorCohort studyDipeptidyl peptidase-4Proportional hazards modelSuicidal ideationDiabetes mellitusConfidence intervalEndocrinologyPoison controlEmergency medicineAgonistReceptorInjury prevention

Abstract

fetched live from OpenAlex

Abstract Objective To determine whether the use of glucagon-like peptide-1 (GLP-1) receptor agonists is associated with an increased risk of suicidal ideation, self-harm, and suicide among patients with type 2 diabetes compared with the use of dipeptidyl peptidase-4 (DPP-4) inhibitors or sodium-glucose cotransporter-2 (SGLT-2) inhibitors. Design Active comparator, new user cohort study. Setting Primary care practices contributing data to the UK Clinical Practice Research Datalink linked to the Hospital Episodes Statistics Admitted Patient Care and Office for National Statistics Death Registration databases. Participants Patients with type 2 diabetes. Exposures Two cohorts were assembled, with the first composed of patients who started and continued on GLP-1 receptor agonists or DPP-4 inhibitors between 1 January 2007 and 31 December 2020 and the second composed of patients who started and continued on GLP-1 receptor agonists or SGLT-2 inhibitors between 1 January 1 2013 and 31 December 2020. Both cohorts were followed until 29 March 2021. Main outcome measures The primary outcome was suicidality, defined as a composite of suicidal ideation, self-harm, and suicide. Secondary outcomes were each of these events considered separately. Propensity score fine stratification weighted Cox proportional hazards models were fitted to estimate hazard ratios and 95% confidence intervals (CIs) to estimate the average treatment effect among the treated patients. Results The first cohort included 36 082 GLP-1 receptor agonist users (median follow-up 1.3 years) and 234 028 DPP-4 inhibitor users (median follow-up 1.7 years). In crude analyses, GLP-1 receptor agonist use was associated with an increased incidence of suicidality compared with DPP-4 inhibitors (crude incidence rates 3.9 v 1.8 per 1000 person years, respectively; hazard ratio 2.08, 95% CI 1.83 to 2.36). This estimate decreased to a null value after confounding factors were accounted for (hazard ratio 1.02, 95% CI 0.85 to 1.23). The second cohort included 32 336 GLP-1 receptor agonist users (median follow-up 1.2 years) and 96 212 SGLT-2 inhibitor users (median follow-up 1.2 years). Similarly, GLP-1 receptor agonist use was associated with an increased risk of suicidality compared with SGLT-2 inhibitors in crude analyses (crude incidence rates 4.3 v 2.7 per 1000 person years; hazard ratio 1.60, 95% CI 1.37 to 1.87) but not after confounding factors were accounted for (0.91, 0.73 to 1.12). Similar findings were observed when suicidal ideation, self-harm, and suicide were analysed separately in both cohorts. Conclusions In this large cohort study, the use of GLP-1 receptor agonists was not associated with an increased risk of suicidality compared with the use of DPP-4 inhibitors or SGLT-2 inhibitors in patients with type 2 diabetes.

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)0.005
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.274
Teacher spread0.264 · 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".

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Citations37
Published2025
Admission routes2
Has abstractyes

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