Incretin based drugs and risk of acute pancreatitis in patients with type 2 diabetes: cohort study
Bibliographic record
Abstract
OBJECTIVES: To determine whether the use of incretin based drugs, compared with sulfonylureas, is associated with an increased risk of acute pancreatitis. DESIGN: Population based cohort study. SETTING: 680 general practices in the United Kingdom contributing to the Clinical Practice Research Datalink. PARTICIPANTS: From 1 January 2007 to 31 March 2012, 20 748 new users of incretin based drugs were compared with 51 712 users of sulfonylureas and followed up until 31 March 2013. MAIN OUTCOME MEASURES: Cox proportional hazards models were used to estimate hazard ratios and 95% confidence intervals for acute pancreatitis in users of incretin based drugs compared with users of sulfonylureas. Models were adjusted for tenths of high dimensional propensity score (hdPS). RESULTS: The crude incidence rate for acute pancreatitis was 1.45 per 1000 patients per year (95% confidence interval 0.99 to 2.11) for incretin based drug users and 1.47 (1.23 to 1.76) for sulfonylurea users. The rate of acute pancreatitis associated with the use of incretin based drugs was not increased (hdPS adjusted hazard ratio: 1.00, 95% confidence interval 0.59 to 1.70) relative to sulfonylurea use. CONCLUSIONS: Compared with use of sulfonylureas, the use of incretin based drugs is not associated with an increased risk of acute pancreatitis. While this study is reassuring, it does not preclude a modest increased risk, and thus additional studies are needed to confirm these findings.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".