Comparative safety and effectiveness of sitagliptin in patients with type 2 diabetes: retrospective population based cohort study
Bibliographic record
Abstract
OBJECTIVE: To determine if the use of sitagliptin in newly treated patients with type 2 diabetes is associated with any changes in clinical outcomes. DESIGN: Retrospective population based cohort study. SETTING: Large national commercially insured US claims and integrated laboratory database. PARTICIPANTS: Inception cohort of new users of oral antidiabetic drugs between 2004 and 2009 followed until death, termination of medical insurance, or December 31 2010. MAIN OUTCOME MEASURE: Composite endpoint of all cause hospital admission and all cause mortality, assessed with time varying Cox proportional hazards regression after adjustment for demographics, clinical and laboratory data, pharmacy claims data, healthcare use, and time varying propensity scores. RESULTS: The cohort included 72,738 new users of oral antidiabetic drugs (8032 (11%) used sitagliptin; 7293 (91%) were taking it in combination with other agents) followed for a total of 182,409 patient years. The mean age was 52 (SD 9) years, 54% (39,573) were men, 11% (8111) had ischemic heart disease, and 9% (6378) had diabetes related complications at the time their first antidiabetic drug was prescribed. 14,215 (20%) patients met the combined endpoint. Sitagliptin users showed similar rates of all cause hospital admission or mortality to patients not using sitagliptin (adjusted hazard ratio 0.98, 95% confidence interval 0.91 to 1.06), including patients with a history of ischemic heart disease (adjusted hazard ratio 1.10, 0.94 to 1.28) and those with estimated glomerular filtration rate below 60 mL/min (1.11, 0.88 to 1.41). CONCLUSIONS: Sitagliptin use was not associated with an excess risk of all cause hospital admission or death compared with other glucose lowering agents among newly treated patients with type 2 diabetes. Most patients prescribed sitagliptin in this cohort were concordant with clinical practice guidelines, in that it was used as add-on treatment.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".