Liraglutide and Glycaemic Outcomes in the LEADER Trial
Bibliographic record
Abstract
The LEADER trial was a cardiovascular (CV) outcomes trial in patients with type 2 diabetes at high CV risk that compared liraglutide ( n = 4668) with placebo ( n = 4672) using a primary composite endpoint of 3-point major adverse CV events. The objective of this post hoc analysis was to investigate glycaemic outcomes across both treatment groups. Glycated haemoglobin (HbA 1c ) was measured at randomisation, month 3, month 6 and every 6 months thereafter. Cox regression was used to analyse time to a composite endpoint of glycaemic deterioration, defined as a specified change in HbA 1c or a substantial intensification of insulin or oral antihyperglycaemic drug (OAD). The individual components of the composite were also analysed. Baseline characteristics, including insulin and OAD use, were balanced between treatment groups. HbA 1c decreased from baseline in both groups, but the reduction was greater with liraglutide [estimated treatment difference at month 36: − 0.40%; 95% confidence interval (CI) − 0.45, − 0.34] despite the addition of more OADs and higher insulin use in the placebo group. Fewer of the patients treated with liraglutide ( n = 3202, 68.6%) experienced glycaemic deterioration compared with those administered the placebo ( n = 3988, 85.4%; average hazard ratio: 0.50; 95% CI 0.48, 0.53; p < 0.001). Analysis of the individual components showed similar results (both p < 0.001). Type 2 diabetes patients at high risk of CV events who were treated with liraglutide achieved greater reductions in HbA 1c , had a lower risk of hypoglycaemia and presented less glycaemic deterioration than similar patients who received the placebo. Nonetheless, progressive loss of glycaemic control occurred in both groups. ClinicalTrials.gov, NCT01179048. Novo Nordisk. Plain language summary available for this article.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".