Continuous Glucose Monitoring–Based Metrics and Hypoglycemia Duration in Insulin-Experienced Individuals With Long-standing Type 2 Diabetes Switched From a Daily Basal Insulin to Once-Weekly Insulin Icodec: Post Hoc Analysis of ONWARDS 2 and ONWARDS 4
Bibliographic record
Abstract
OBJECTIVE: This post hoc analysis assessed continuous glucose monitoring (CGM)-based metrics and hypoglycemia duration with once-weekly insulin icodec versus once-daily basal insulin analogs in insulin-experienced individuals with long-standing type 2 diabetes from two 26-week phase 3a trials (ONWARDS 2 and ONWARDS 4). RESEARCH DESIGN AND METHODS: Time in range (TIR) (3.9-10.0 mmol/L), time above range (TAR) (>10.0 mmol/L), and time below range (TBR) (<3.9 mmol/L and <3.0 mmol/L) were assessed during three CGM time periods (switch [weeks 0-4], end of treatment [weeks 22-26], and follow-up [weeks 27-31]) for icodec versus comparators (ONWARDS 2, insulin degludec [basal regimen]; ONWARDS 4, insulin glargine U100 [basal-bolus regimen]) using double-blind CGM data. CGM-derived hypoglycemic episode duration (<3.9 mmol/L) was assessed. RESULTS: In both trials, there were no statistically significant differences in TIR, TAR, or TBR (<3.0 mmol/L) for icodec versus comparators across all time periods. In the end-of-treatment period, mean TIR was 63.1% (icodec) vs. 59.5% (degludec) in ONWARDS 2 and 66.9% (icodec) vs. 66.4% (glargine U100) in ONWARDS 4. Mean TBR <3.9 mmol/L and <3.0 mmol/L remained within recommended targets (<4% and <1%, respectively) across time periods and treatment arms. Hypoglycemic episode duration (<3.9 mmol/L) was comparable across time periods and treatment arms (median duration ≤40 min). CONCLUSIONS: In insulin-experienced participants with long-standing type 2 diabetes, CGM-based TIR, TAR, and CGM-derived hypoglycemia duration (<3.9 mmol/L) were comparable for icodec and once-daily basal insulin analogs during all time periods. TBR remained within recommended targets.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| 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".