Trial design and baseline data for LIRA‐PRIME: A randomized trial investigating the efficacy of liraglutide in controlling glycaemia in type 2 diabetes in a primary care setting
Bibliographic record
Abstract
AIMS: Using a pragmatic approach, the LIRA-PRIME trial aims to address a knowledge gap by comparing efficacy in controlling glycaemia with glucagon-like peptide-1 analog liraglutide vs oral antidiabetic drugs (OADs) in patients with type 2 diabetes (T2D) uncontrolled with metformin monotherapy in primary care practice. We report the study design and patient baseline characteristics. MATERIALS AND METHODS: This 104-week, two-arm, open-label, active-controlled trial is active in 219 primary care practices across nine countries. At screening, eligible patients with T2D were at least 18 years of age, had been using a stable daily dose of metformin ≥1500 mg or the maximum tolerated dose for ≥60 days, and had a glycated haemoglobin (HbA1c) of 7.5% to 9.0%, measured ≤90 days before screening. Patients were randomized (1:1) to liraglutide or OAD, both in addition to pre-trial metformin. Individual OADs were chosen by the treating physician based on local guidelines. The primary endpoint is time to inadequate glycaemic control, defined as HbA1c above 7.0% at two scheduled consecutive visits after the first 26 weeks of treatment. RESULTS: The trial randomized 1997 patients with a mean (standard deviation) age of 56.9 (10.8) years, T2D duration of 7.2 (5.9) years (range, <1-47 years), and HbA1c of 8.2%. One-fifth of patients had a history of diabetes complications, and most were overweight (24.8%) or had obesity (65.3%). CONCLUSIONS: This pragmatically designed, large-scale, multinational, randomized clinical trial will help guide treatment decisions for patients with T2D who are inadequately controlled with metformin monotherapy and treated in primary care.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.011 | 0.013 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".