Sitagliptin and Acute Pancreatitis: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
Background and Objectives: Sitagliptin is a dipepidyl peptidase inhibitor (DPP-4i) with gentle antidiabetic effects with a lower risk of hypoglycemia. The association with acute pancreatitis is controversial. The current meta-analysis aimed to assess the relationship of sitagliptin and acute pancreatitis. Methods: The literature in PubMed and Google Scholar was searched for relevant articles published in the last ten years up to September 2021. The keywords sitagliptins, DPP-4i, acute pancreatitis were used with the protean AND or OR. Among the 204 articles retrieved, 24 full-texts were assessed for eligibility and only five studies (Three from the USA, one from Asia, and one from Canada) met the inclusion criteria for the systematic review. The author name, year of publication, country, type of study, number of patients, and the duration of the study were reported. Results: There were five studies. The total number of patients were 729808 with 6459 events. The studies showed no increased rate of acute pancreatitis following sitagliptin use, odd ratio, 0.79, 95% CI, 0.29-2.15, a significant heterogeneity was observer, I2 for heterogeneity=98%, P-value, <001, the P-value for overall effect was 0.65 and the chi-square, 160.15. Interpretation and Conclusion: Sitagliptin use is not associated with acute pancreatitis.
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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 | 0.015 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.036 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".