Changes to insulin requirements over time with semaglutide in adults with type 1 diabetes on insulin pump therapy: A post‐hoc analysis of a double‐blinded, randomised, crossover trial
Bibliographic record
Abstract
BACKGROUND: There is little data on how semaglutide affects basal versus bolus insulin and dosing parameters in adults with type 1 diabetes on insulin pump therapy. METHODS: This is a post-hoc analysis of a double-blinded, randomised, crossover trial assessing semaglutide (up to 1 mg) versus placebo during automated insulin delivery (AID). This analysis focuses on the first 11 of 15 weeks where participants used their routine pump therapy with continuous glucose monitoring (CGM), where remote follow-ups were performed on days 7, 21, 32, 56, 63, and 77 (± 4 days). Changes in insulin requirements, carbohydrate input, and pump parameters over time compared to baseline were assessed, as well as the frequency of parameter adjustments. RESULTS: Twenty-six participants were included; 100% were using CGM and 81% using AID at baseline. Daily total and bolus insulin, along with carbohydrate input, were significantly reduced by day 7 and remained so, while basal was significantly reduced by day 32. By day 77, there was a median increase in carbohydrate ratios by 4.1% [-1.8, 7.7] and in correction factors by 11.2% [0.0, 20.8], and a reduction in pre-programmed basal rates by 7.9% [-12.7, -4.2]. The median time spent in hypoglycemia was rarely >4% during these follow-ups. CONCLUSIONS: Insulin needs decrease rapidly upon initiation of semaglutide use in type 1 diabetes on pump therapy, predominantly due to bolus changes from less carbohydrate consumption. While diabetes technology helps to reduce hypoglycemia, adjustments to pump dosing are still required.
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 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 | 0.011 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| 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 | 0.002 |
| 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".