Switching to Once-Weekly Insulin Icodec Versus Once-Daily Insulin Glargine U100 in Type 2 Diabetes Inadequately Controlled on Daily Basal Insulin: A Phase 2 Randomized Controlled Trial
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE Insulin icodec (icodec) is a novel once-weekly basal insulin analog. This trial investigated two approaches for switching to icodec versus once-daily insulin glargine 100 units/mL (IGlar U100) in people with type 2 diabetes receiving daily basal insulin and one or more oral glucose-lowering medications. RESEARCH DESIGN AND METHODS This multicenter, open-label, treat-to-target phase 2 trial randomized (1:1:1) eligible basal insulin–treated (total daily dose 10–50 units) people with type 2 diabetes (HbA1c 7.0–10.0% [53.0–85.8 mmol/mol]) to icodec with an initial 100% loading dose (in which only the first dose was doubled [icodec LD]), icodec with no loading dose (icodec NLD), or IGlar U100 for 16 weeks. Primary end point was percent time in range (TIR; 3.9–10.0 mmol/L [70–180 mg/dL]) during weeks 15 and 16, measured using continuous glucose monitoring. Key secondary end points included HbA1c, adverse events (AEs), and hypoglycemia. RESULTS Estimated mean TIR during weeks 15 and 16 was 72.9% (icodec LD; n = 54), 66.0% (icodec NLD; n = 50), and 65.0% (IGlar U100; n = 50), with a statistically significant difference favoring icodec LD versus IGlar U100 (7.9%-points [95% CI 1.8–13.9]). Mean HbA1c reduced from 7.9% (62.8 mmol/mol) at baseline to 7.1% (54.4 mmol/mol icodec LD) and 7.4% (57.6 mmol/mol icodec NLD and IGlar U100); incidences and rates of AEs and hypoglycemic episodes were comparable. CONCLUSIONS Switching from daily basal insulin to once-weekly icodec was well tolerated and provided effective glycemic control. Loading dose use when switching to once-weekly icodec significantly increased percent TIR during weeks 15 and 16 versus once-daily IGlar U100, without increasing hypoglycemia risk.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it