Mealtime fast‐acting insulin aspart versus insulin aspart for controlling postprandial hyperglycaemia in people with insulin‐resistant Type 2 diabetes
Bibliographic record
Abstract
Abstract Aim This post hoc analysis explored whether mealtime fast‐acting insulin aspart treatment provided an advantage in postprandial plasma glucose ( PPG ) control vs. insulin aspart in people with Type 2 diabetes receiving high doses of bolus insulin. Methods A post hoc , post‐randomization, subgroup analysis of a 26‐week, randomized, double‐blind, treat‐to‐target trial (onset 2) that compared mealtime fast‐acting insulin aspart vs. mealtime insulin aspart, both in a basal–bolus regimen, in people with Type 2 diabetes uncontrolled on basal insulin therapy and metformin. At the end of trial, the impact of fast‐acting insulin aspart and insulin aspart on PPG control was assessed with a standard liquid meal test and participants were grouped into three post‐randomization subgroups: meal test bolus insulin dose ≤ 10 units per dose ( n = 171), > 10–20 units per dose ( n = 289) and > 20 units per dose ( n = 146). Results A statistically significant treatment difference in favour of fast‐acting insulin aspart vs. insulin aspart was observed for the change in PPG increment at all post‐meal time points (from 1 to 4 h) for those in the > 20 units bolus insulin subgroup. There was no difference in the magnitude of change from baseline in HbA 1c level between fast‐acting insulin aspart and insulin aspart in any of the bolus insulin dose subgroups (data herein). Conclusion Fast‐acting insulin aspart may hold promise as a more effective treatment compared with insulin aspart for controlling PPG in people with insulin‐resistant Type 2 diabetes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".