Dasiglucagon—A Next-Generation Glucagon Analog for Rapid and Effective Treatment of Severe Hypoglycemia: Results of Phase 3 Randomized Double-Blind Clinical Trial
Bibliographic record
Abstract
OBJECTIVE: To evaluate the efficacy and safety of dasiglucagon, a ready-to-use, next-generation glucagon analog in aqueous formulation for subcutaneous dosing, for treatment of severe hypoglycemia in adults with type 1 diabetes. RESEARCH DESIGN AND METHODS: This randomized, double-blind trial included 170 adult participants with type 1 diabetes, each randomly assigned to receive a single subcutaneous dose of 0.6 mg dasiglucagon, placebo, or 1 mg reconstituted glucagon (2:1:1 randomization) during controlled insulin-induced hypoglycemia. The primary end point was time to plasma glucose recovery, defined as an increase of ≥20 mg/dL from baseline without rescue intravenous glucose. The primary comparison was dasiglucagon versus placebo; reconstituted lyophilized glucagon was included as reference. RESULTS: Median (95% CI) time to recovery was 10 (10, 10) minutes for dasiglucagon compared with 40 (30, 40) minutes for placebo (P < 0.001); the corresponding result for reconstituted glucagon was 12 (10, 12) minutes. In the dasiglucagon group, plasma glucose recovery was achieved within 15 min in all but one participant (99%), superior to placebo (2%; P < 0.001) and similar to glucagon (95%). Similar outcomes were observed for the other investigated time points at 10, 20, and 30 min after dosing. The most frequent adverse effects were nausea and vomiting, as expected with glucagon treatment. CONCLUSIONS: Dasiglucagon provided rapid and effective reversal of hypoglycemia in adults with type 1 diabetes, with safety and tolerability similar to those reported for reconstituted glucagon injection. The ready-to-use, aqueous formulation of dasiglucagon offers the potential to provide rapid and reliable treatment of severe hypoglycemia.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".