Hypernatremia in neonatal elk calves: 30 cases (1988–1998)
Bibliographic record
Abstract
OBJECTIVE: To characterize hypernatremia in neonatal elk calves, including clinical signs, incidence, physical examination findings, and possible causes. DESIGN: Retrospective case series. ANIMALS: 26 neonatal elk calves were examined; 4 calves were evaluated twice, for a total of 30 examinations. PROCEDURE: Medical records were reviewed for signalment, history, physical examination findings, results of diagnostic tests, and response to treatment. Hypernatremia was defined as serum sodium concentration > 153 mEq/L. RESULTS: Hypernatremia was diagnosed in 14 calves and was significantly associated with diarrhea, high WBC count, high anion gap, and high serum concentrations of albumin, chloride, creatinine, and urea. Hypernatremia was not significantly associated with survival, but high serum albumin concentration and rectal temperature were significantly associated with survival of calves. Animals given antibiotics and electrolyte solutions orally prior to evaluation were significantly more likely to die than those untreated. Dehydration was a common reason for evaluation but was not significantly associated with survival. CONCLUSIONS AND CLINICAL RELEVANCE: Hypernatremia was significantly associated with diarrhea. Treatment of diarrheic elk calves is often the same as that used in bovine calves with diarrhea; however, bovine calves are commonly hypo- or normonatremic. Our experience suggests that treatment protocols used in bovine calves are unsatisfactory for elk calves. The rate at which serum sodium concentration is reduced should be < 1.7 mEq Na/L/h to avoid development of neurologic signs associated with iatrogenically induced cerebral edema.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".