Experience With Intravenous Glucagon Infusions as a Treatment for Resistant Neonatal Hypoglycemia
Bibliographic record
Abstract
BACKGROUND: Based on limited anecdotal evidence, glucagon is used for the management of intractable neonatal hypoglycemia persisting in the face of high glucose administration rates. OBJECTIVE: To evaluate the short-term response of blood glucose levels to an intravenous infusion of glucagon. DESIGN: A retrospective observational study in which all newborns who received glucagon infusions (usual dose, 0.5-1 mg/d) during a 5-year period were identified (N = 55). The common causes of hypoglycemia were perinatal stress, intrauterine growth restriction, prematurity, and maternal diabetes mellitus. Laboratory blood glucose measurements made between 24 hours before and 72 hours after the start of the glucagon infusion and the rates of glucose administration during the same period were analyzed. The effects of glucagon on sodium and platelet levels were also examined. SETTING: University referral hospital. RESULTS: A statistically and clinically significant rise in blood glucose concentration, from a mean of 36.3 to 93.0 mg/dL (2.02-5.17 mmol/L), was observed within 4 hours of starting glucagon administration. The change was unrelated to the cause of the hypoglycemia. The frequency of hypoglycemic episodes was significantly reduced, and no further episodes of severe hypoglycemia (glucose level, <20 mg/dL [<1.1 mmol/L]) occurred. Five patients, 4 of whom were preterm newborns with intrauterine growth restriction, required additional glycemic treatment. Seventy-five percent of newborns were thrombocytopenic before starting glucagon infusion, and in 9 newborns platelet counts decreased following glucagon infusion. There was no hyponatremia attributable to glucagon. CONCLUSION: Glucagon infusions appear to be beneficial for problematic neonatal hypoglycemia of different causes.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".