Efficacy and Safety of the Human Glucagon-Like Peptide-1 Analog Liraglutide in Combination With Metformin and Thiazolidinedione in Patients With Type 2 Diabetes (LEAD-4 Met+TZD)
Bibliographic record
Abstract
OBJECTIVE: To determine the efficacy and safety of liraglutide (a glucagon-like peptide-1 receptor agonist) when added to metformin and rosiglitazone in type 2 diabetes. RESEARCH DESIGN AND METHODS: This 26-week, double-blind, placebo-controlled, parallel-group trial randomized 533 subjects (1:1:1) to once-daily liraglutide (1.2 or 1.8 mg) or liraglutide placebo in combination with metformin (1 g twice daily) and rosiglitazone (4 mg twice daily). Subjects had type 2 diabetes, A1C 7-11% (previous oral antidiabetes drug [OAD] monotherapy >or=3 months) or 7-10% (previous OAD combination therapy >or=3 months), and BMI <or=45 kg/m(2). RESULTS: Mean A1C values decreased significantly more in the liraglutide groups versus placebo (mean +/- SE -1.5 +/- 0.1% for both 1.2 and 1.8 mg liraglutide and -0.5 +/- 0.1% for placebo). Fasting plasma glucose decreased by 40, 44, and 8 mg/dl for 1.2 and 1.8 mg and placebo, respectively, and 90-min postprandial glucose decreased by 47, 49, and 14 mg/dl, respectively (P < 0.001 for all liraglutide groups vs. placebo). Dose-dependent weight loss occurred with 1.2 and 1.8 mg liraglutide (1.0 +/- 0.3 and 2.0 +/- 0.3 kg, respectively) (P < 0.0001) compared with weight gain with placebo (0.6 +/- 0.3 kg). Systolic blood pressure decreased by 6.7, 5.6, and 1.1 mmHg with 1.2 and 1.8 mg liraglutide and placebo, respectively. Significant increases in C-peptide and homeostasis model assessment of beta-cell function and significant decreases in the proinsulin-to-insulin ratio occurred with liraglutide versus placebo. Minor hypoglycemia occurred more frequently with liraglutide, but there was no major hypoglycemia. Gastrointestinal adverse events were more common with liraglutide, but most occurred early and were transient. CONCLUSIONS: Liraglutide combined with metformin and a thiazolidinedione is a well-tolerated combination therapy for type 2 diabetes, providing significant improvements in glycemic control.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".