Adding Once-Daily Lixisenatide for Type 2 Diabetes Inadequately Controlled by Established Basal Insulin
Bibliographic record
Abstract
OBJECTIVE: To examine the efficacy and safety of adding the once-daily glucagon-like peptide-1 receptor agonist (GLP-1RA) lixisenatide to established basal insulin therapy alone or together with metformin, in people with type 2 diabetes and elevated glycated hemoglobin (HbA1c). RESEARCH DESIGN AND METHODS: We conducted a double-blind, parallel-group, placebo-controlled trial. Patients (n = 495) with established basal insulin therapy but inadequate glycemic control were randomized to add lixisenatide 20 μg or placebo for 24 weeks. Basal insulin dosage was unchanged except to limit hypoglycemia. HbA1c reduction from baseline was the primary end point. RESULTS: Mean duration of diabetes was 12.5 years, duration of insulin use was 3.1 years, insulin dosage was 55 units/day, and baseline HbA1c was 8.4%. With lixisenatide, the placebo-corrected change of HbA1c from baseline was -0.4% (95% CI -0.6 to -0.2; P = 0.0002), and mean HbA1c at end point was 7.8%. HbA1c <7.0% (53 mmol/mol) was attained by more lixisenatide (28%) than placebo (12%; P < 0.0001) participants. Lixisenatide reduced plasma glucose levels after a standardized breakfast (placebo-corrected reduction, -3.8 mmol/L; P < 0.0001); seven-point glucose profiles showed a reduction persisting through the day. Reductions in body weight (placebo corrected, -1.3 kg; P < 0.0001) and insulin dosage (-3.7 units/day; P = 0.012) were greater with lixisenatide. Main adverse events (AEs) with lixisenatide were gastrointestinal. Symptomatic hypoglycemia was 28% for lixisenatide and 22% for placebo; 4 of 328 subjects (1.2%) had severe hypoglycemia with lixisenatide vs. 0 of 167 with placebo. CONCLUSIONS: By improving HbA1c and postprandial hyperglycemia without weight gain in type 2 diabetes with inadequate glycemic control despite stable basal insulin, lixisenatide may provide an alternative to rapid-acting insulin or other treatment options.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".