Continuous glucose monitoring in insulin-experienced individuals with type 2 diabetes switched to once-weekly insulin icodec versus once-daily comparators in ONWARDS 2 and 4: post-hoc analysis
Bibliographic record
Abstract
Background and aims Insulin icodec (icodec) is a once-weekly basal insulin under clinical development. Here, we investigated time in, above, and below range (TIR, TAR, TBR) using continuous glucose monitoring (CGM) data during the switch period (weeks 0–4) and steady state (weeks 22–26) from two phase 3, randomized, treat-to-target trials in type 2 diabetes (T2D). Methods Insulin-experienced individuals with T2D received once-weekly icodec or once-daily degludec (ONWARDS 2), or icodec or once-daily glargine U100 with mealtime insulin aspart (ONWARDS 4). When switching, a one-time additional 50% dose of icodec was administered at first dose; basal insulins were titrated weekly (target: 80–130 mg/dL). TIR (70–180 mg/dL), TAR (> 180 mg/dL), and TBR (< 70 and<54 mg/dL) were calculated using double-blinded Dexcom G6® CGM data. Results Immediately after switch, TIR, TAR and TBR were not significantly different between once-weekly icodec and comparators. At steady state, there was no significant difference between arms in TIR or TAR. Except for ONWARDS 2, where TBR<70mg/dL was significant longer with icodec (ERR=1.59; 95% CI 1.21; 2.08; P=0.001), all other TBR comparisons in both trials were not statistically different. From switch to steady state, overall observed mean TIR increased, TAR decreased and TBR remained below internationally recommended targets in all groups. Conclusion In insulin-experienced participants with T2D, TIR and TAR were not significantly different versus once-daily degludec or glargine U100. TBR remained within the international targets in all groups. Publication History Article published online: 02 May 2023 © 2023. Thieme. All rights reserved. Georg Thieme Verlag Rüdigerstraße 14, 70469 Stuttgart, Germany
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".