A phase 3 multicenter, open-label, prospective study designed to evaluate the effectiveness and ease of use of nasal glucagon in the treatment of moderate and severe hypoglycemia in children and adolescents with type 1 diabetes in the home or school setti
Bibliographic record
Abstract
OBJECTIVE: This multicenter, open-label study was designed to evaluate real-world effectiveness and ease of use of nasal glucagon (NG) in treating moderate or severe hypoglycemic events in children and adolescents with type 1 diabetes (T1D). METHODS: Caregivers were trained to administer NG (3 mg) to the child/adolescent with T1D during spontaneous, symptomatic moderate or severe hypoglycemic events, observe treatment response (defined as awakening or returning to normal status within 30 minutes), and measure blood glucose (BG) levels every 15 minutes. Data regarding adverse events and ease of use were solicited using questionnaires. RESULTS: The analysis population included 14 patients who experienced 33 moderate hypoglycemic events with neuroglycopenic symptoms and BG level ≤70 mg/dL. Patients returned to normal status within 30 minutes of NG administration in all 33 events. Mean BG levels increased from 55.5 mg/dL (range 42-70 mg/dL) at baseline to 113.7 mg/dL (range 79-173 mg/dL) within 15 minutes of NG administration. In most hypoglycemic events (93.9%), caregivers reported that NG administration was easy or very easy; they could administer NG within 30 seconds in 60.6% of events. There were no serious adverse events. CONCLUSIONS: A single 3-mg dose of NG was effective in treating moderate, symptomatic, hypoglycemic events in children and adolescents with T1D in a real-world setting. It was easy-to-use and reasonably well tolerated. NG shows promise as an effective, needle-free, and user-friendly alternative to injectable glucagon.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".