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.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".