Effect of Liraglutide, a Glucagon-Like Peptide-1 Analogue, on Left Ventricular Function in Stable Chronic Heart Failure Patients with and Without Diabetes (LIVE)—a Multicentre, Double-Blind, Randomised, Placebo-Controlled Trial
Bibliographic record
Abstract
AIMS: To determine the effect of the glucagon-like peptide-1 analogue liraglutide on left ventricular function in chronic heart failure patients with and without type 2 diabetes. METHODS AND RESULTS: LIVE was an investigator-initiated, randomised, double-blinded, placebo-controlled multicentre trial. Patients (n = 241) with reduced left ventricular ejection fraction (LVEF ≤45%) were recruited (February 2012 to August 2015). Patients were clinically stable and on optimal heart failure treatment. Intervention was liraglutide 1.8 mg once daily or matching placebo for 24 weeks. The LVEF was similar at baseline in the liraglutide and the placebo group (33.7 ± 7.6% vs. 35.4 ± 9.4%). Change in LVEF did not differ between the liraglutide and the placebo group; mean difference (95% confidence interval) was -0.8% (-2.1, 0.5; P = 0.24). Heart rate increased with liraglutide [mean difference: 7 b.p.m. (5, 9), P < 0.0001]. Serious cardiac events were seen in 12 (10%) patients treated with liraglutide compared with 3 (3%) patients in the placebo group (P = 0.04). CONCLUSION: Liraglutide did not affect left ventricular systolic function compared with placebo in stable chronic heart failure patients with and without diabetes. Treatment with liraglutide was associated with an increase in heart rate and more serious cardiac adverse events, and this raises some concern with respect to the use of liraglutide in patients with chronic heart failure and reduced left ventricular function. More data on the safety of liraglutide in different subgroups of heart failure patients are needed.
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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) | 0.003 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".