Vildagliptin add‐on to metformin produces similar efficacy and reduced hypoglycaemic risk compared with glimepiride, with no weight gain: results from a 2‐year study
Bibliographic record
Abstract
AIM: To show that vildagliptin added to metformin is non-inferior to glimepiride in reducing HbA1c levels from baseline over 2 years. METHODS: A randomized, double-blind, active-comparator study of patients with type 2 diabetes mellitus inadequately controlled (HbA1c 6.5-8.5%) by metformin monotherapy. Patients received vildagliptin (50 mg twice daily) or glimepiride (up to 6 mg/day) added to metformin. RESULTS: In all, 3118 patients were randomized (vildagliptin, n = 1562; glimepiride, n = 1556). From similar baseline values (7.3%), after 2 years adjusted mean (s.e.) change in HbA1c was comparable between vildagliptin and glimepiride treatment: -0.1% (0.0%) and -0.1% (0.0%), respectively. The primary objective of non-inferiority was met. A similar proportion of patients reached HbA1c <7% (36.9 and 38.3%, respectively), but with vildagliptin more patients reached this target without hypoglycaemia (36.0% vs. 28.8%; p = 0.004). The initial response (IR) was sustained for a mean (s.d.) of 309 (244) days with vildagliptin versus 270 (223) days for glimepiride (p < 0.001) (IR = nadir HbA1c where change from baseline > or =0.5% or HbA1c < or =6.5% within the first six months of treatment. After IR was detected, sustained response = time between nadir and an increase of >0.3% above IR). Independent of disease duration, age was a predictor of effect sustainability. Fewer patients experienced hypoglycaemia with vildagliptin (2.3% vs. 18.2% with glimepiride) with a 14-fold difference in the number of hypoglycaemic events (59 vs. 838). Vildagliptin had a beneficial effect on body weight [mean (s.e.) change from baseline -0.3 (0.1) kg; between-group difference -1.5 kg; p < 0.001]. Overall, both treatments were well tolerated and displayed similar safety profiles. CONCLUSIONS: Vildagliptin add-on has similar efficacy to glimepiride after 2 years' treatment, with markedly reduced hypoglycaemia risk and no weight gain.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".