Equal improvement in glycaemia with lixisenatide given before breakfast or the main meal of the day
Bibliographic record
Abstract
AIMS: The aim of this study is to explore whether administration timing affects glycaemic control by lixisenatide once-daily in type 2 diabetes mellitus (T2DM). METHODS: A phase IIIb, open-label, 1:1 randomized, active-controlled, 24-week multicentre study of T2DM patients inadequately controlled on metformin was conducted. Patients were administered lixisenatide before breakfast or the main meal. The primary endpoint was change from baseline at week 24 in glycated haemoglobin (HbA1c). Other endpoints: changes in body weight, fasting plasma glucose (FPG), 7-point self-monitored plasma glucose (SMPG) and Diabetes Treatment Satisfaction Questionnaire status (DTSQs) score. Adverse events (AEs) were monitored. RESULTS: Mean change in HbA1c from baseline at week 24 was -0.65% (-7.1mmol/mol; main meal) and -0.74% (-8.1mmol/mol; breakfast). Mean changes in FPG, body weight and DTSQs score were comparable between groups. The mean change in body weight (kg) was -2.60 (main meal) and -2.80 (breakfast group). The 7-point SMPG profiles showed greatest reductions in postprandial glucose after the meal at which lixisenatide was administered, with a residual effect seen on the subsequent meal. AE rates were similar between groups, including gastrointestinal AEs. CONCLUSIONS: Lixisenatide before the main meal was noninferior to lixisenatide before breakfast in patients insufficiently controlled on metformin. Lixisenatide treatment allows flexibility in administration timing.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".