Fast-Acting Insulin Aspart Improves Glycemic Control in Basal-Bolus Treatment for Type 1 Diabetes: Results of a 26-Week Multicenter, Active-Controlled, Treat-to-Target, Randomized, Parallel-Group Trial (onset 1)
Bibliographic record
Abstract
OBJECTIVE This multicenter, treat-to-target, phase 3 trial evaluated the efficacy and safety of fast-acting insulin aspart (faster aspart) versus conventional insulin aspart (IAsp) in adults with type 1 diabetes. RESEARCH DESIGN AND METHODS The primary end point was change from baseline in HbA1c after 26 weeks. After an 8-week run-in, subjects were randomized (1:1:1) to double-blind mealtime faster aspart (n = 381), IAsp (n = 380), or open-label postmeal faster aspart (n = 382)—each with insulin detemir. RESULTS HbA1c was reduced in both treatment groups, and noninferiority to IAsp was confirmed for both mealtime and postmeal faster aspart (estimated treatment difference [ETD] faster aspart–IAsp, mealtime, –0.15% [95% CI –0.23; –0.07], and postmeal, 0.04% [–0.04; 0.12]); mealtime faster aspart statistically significantly reduced HbA1c versus IAsp (P = 0.0003). Postprandial plasma glucose (PPG) increments were statistically significantly lower with mealtime faster aspart at 1 h (ETD –1.18 mmol/L [95% CI –1.65; –0.71], –21.21 mg/dL [–29.65; –12.77]; P < 0.0001) and 2 h (–0.67 mmol/L [–1.29; –0.04], –12.01 mg/dL [–23.33; –0.70]; P = 0.0375) after the meal test; superiority to IAsp for the 2-h PPG increment was confirmed. The overall rate of severe or blood glucose–confirmed (plasma glucose <3.1 mmol/L [56 mg/dL]) hypoglycemic episodes and safety profiles were similar between treatments. CONCLUSIONS Faster aspart effectively improved HbA1c, and noninferiority to IAsp was confirmed, with superior PPG control for mealtime faster aspart versus IAsp. Subjects randomized to postmeal faster aspart for all meals maintained HbA1c noninferior to that obtained with mealtime IAsp.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| 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 | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".