The risk of pancreatitis with sitagliptin therapy in older adults: a population-based cohort study
Bibliographic record
Abstract
BACKGROUND: The risk of pancreatitis with sitagliptin use in routine care remains to be established in older patients. We aimed to determine this risk in older adults who were newly prescribed sitagliptin versus an alternative hypoglycemic agent in the outpatient setting. METHODS: In a population-based retrospective cohort study in Ontario from 2010 until 2012 involving adults aged 66 years and older, we studied those who were newly prescribed sitagliptin or an alternative hypoglycemic agent. Our primary outcome of interest was a hospital encounter (emergency department visit or hospital admission) with acute pancreatitis within 90 days. We used inverse probability of treatment weighting to balance the 2 groups and logistic regression with a robust variance estimate to calculate odds ratios (ORs) and 95% confidence intervals (CIs). RESULTS: A total of 57 689 patients (mean age 74 yr) were newly prescribed sitagliptin, and 83 405 patients (mean age 75 yr) were given an alternative hypoglycemic agent (metformin, glyburide, gliclazide or insulin) during the study period. After weighting, there were no significant differences in measured baseline characteristics between groups. In the weighted sample, sitagliptin was not associated with an increased risk of a hospital encounter with pancreatitis compared with alternative hypoglycemic agents (weighted total 46 of 57 689 patients taking sitagliptin [0.08%] v. 48 of 55 705 patients taking alternative hypoglycemic agents [0.09%], absolute risk difference -0.01% [95% CI -0.05% to 0.02%], OR 0.92 [95% CI 0.55 to 1.55]). INTERPRETATION: Older adults newly prescribed sitagliptin in routine care were not at a substantially higher risk of pancreatitis than those prescribed alternative hypoglycemic agents. These findings are reassuring for those who use or prescribe sitagliptin in the management of type 2 diabetes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".