Achieving a clinically relevant composite outcome of an HbA1c of <7% without weight gain or hypoglycaemia in type 2 diabetes: a meta‐analysis of the liraglutide clinical trial programme
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
AIM: Effective type 2 diabetes management requires a multifactorial approach extending beyond glycaemic control. Clinical practice guidelines suggest targets for HbA1c, blood pressure and lipids, and emphasize weight reduction and avoiding hypoglycaemia. The phase 3 clinical trial programme for liraglutide, a human glucagon-like peptide 1 analogue, showed significant improvements in HbA1c and weight with a low risk of hypoglycaemia compared to other diabetes therapies. In this context, we performed a meta-analysis of data from these trials evaluating the proportion of patients achieving a clinically relevant composite measure of diabetes control consisting of an HbA1c <7% without weight gain or hypoglycaemia. METHODS: A prespecified meta-analysis was performed on 26-week patient-level data from seven trials (N = 4625) evaluating liraglutide with commonly used therapies for type 2 diabetes: glimepiride, rosiglitazone, glargine, exenatide, sitagliptin or placebo, adjusting for baseline HbA1c and weight, for a composite outcome of HbA1c <7.0%, no weight gain and no hypoglycaemic events. RESULTS: At 26 weeks, 40% of the liraglutide 1.8 mg group, 32% of the liraglutide 1.2 mg group and 6-25% of comparators (6% rosiglitazone, 8% glimepiride, 15% glargine, 25% exenatide, 11% sitagliptin, 8% placebo) achieved this composite outcome. Odds ratios favoured liraglutide 1.8 mg by 2.0- to 10.5-fold over comparators. CONCLUSIONS: As assessed by the composite outcome of HbA1c <7%, no hypoglycaemia and no weight gain, liraglutide was clearly superior to the other commonly used therapies. However, the long-term clinical impact of this observation remains to be shown.
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.
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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.013 | 0.005 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 it