Efficacy and safety of switching from sitagliptin to liraglutide in subjects with type 2 diabetes ( <scp>LIRA‐SWITCH</scp> ): a randomized, double‐blind, double‐dummy, active‐controlled 26‐week trial
Bibliographic record
Abstract
AIMS: To confirm superiority on glycaemic control by switching from sitagliptin to liraglutide 1.8 mg/d versus continued sitagliptin. MATERIALS AND METHODS: A randomized, multicentre, double-blind, double-dummy, active-controlled trial across 86 office- or hospital-based sites in North America, Europe and Asia. Subjects with type 2 diabetes who had inadequate glycaemic control (glycated haemoglobin [HbA1c] 7.5-9.5% on sitagliptin (100 mg/d) and metformin (≥1500 mg daily) for ≥90 days were randomized to either switch to liraglutide (n = 203) or continue sitagliptin (n = 204), both with metformin. The primary endpoint was change in HbA1c from baseline to week 26. Change in body weight was a confirmatory secondary endpoint. RESULTS: Greater reduction in mean HbA1c was achieved with liraglutide than with continued sitagliptin [-1.14% vs. -0.54%; estimated mean treatment difference (ETD): -0.61% (95% CI -0.82 to -0.40; p < 0.0001)], confirming superiority of switching to liraglutide. Body weight was reduced more with liraglutide [-3.31 kg vs. -1.64 kg; ETD: -1.67 kg (95% CI -2.34 to -0.99; p < 0.0001)]. Nausea was more common with liraglutide [44 subjects (21.8%)] than with continued sitagliptin [16 (7.8%)]. Three subjects (1.5%) taking sitagliptin reported a confirmed hypoglycaemic episode. CONCLUSIONS: Subjects insufficiently controlled with sitagliptin who switch to liraglutide can obtain clinically relevant reductions in glycaemia and body weight, without compromising safety. A switch from sitagliptin to liraglutide provides an option for improved management of type 2 diabetes while still allowing patients to remain on dual therapy.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| 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".