Constant rate infusion of glucagon as an emergency treatment for hypoglycemia in a domestic ferret (Mustela putorius furo)
Bibliographic record
Abstract
CASE DESCRIPTION: A 3-year-old female domestic ferret (Mustela putorius furo) with an insulinoma was treated because of a hypoglycemic crisis prior to scheduled pancreatectomy with concurrent nodulectomy. CLINICAL FINDINGS: Previously, the ferret had clinical signs of lethargy and hind limb weakness; at that time, blood glucose concentration was low, and a tentative diagnosis (subsequently confirmed) of insulinoma was made. Prednisolone treatment (0.3 mg/kg [0.14 mg/lb], PO, q 12 h) did not improve clinical signs; the dosage was gradually increased over a 1-month course (1.8 mg/kg [0.82 mg/lb], PO, q 12 h) and maintained for 10 days. Overall, the treatment was ineffective, and the ferret remained lethargic and developed inappetence. At a reevaluation, the ferret had severe weakness and nonresponsiveness nearing a comatose state. Standard treatment with dextrose (1 mL of 50% solution, IV), and dexamethasone (1 mg/kg [0.45 mg/lb], SC) was administered with resultant improvement in mentation. The ferret was discharged from the hospital and then returned 3 days later for stabilization prior to pancreatectomy with concurrent nodulectomy. TREATMENT AND OUTCOME: The day before surgery, the ferret was administered a glucagon constant rate infusion at a rate of 15 ng/kg/min (6.8 ng/lb/min), which resulted in an increase in blood glucose concentration to a euglycemic state and resolution of clinical signs of hypoglycemia. CLINICAL RELEVANCE: As illustrated by the case described in this report, a glucagon constant rate infusion can be used successfully for the emergency treatment of hyperinsulinemic-hypoglycemic crisis in insulinomic ferrets.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".