Ionized hypocalcemia as a prognostic indicator in dogs following trauma
Bibliographic record
Abstract
OBJECTIVE: To determine the incidence of ionized hypocalcemia (iHCa) in dogs with blunt and penetrating traumatic injuries upon presentation to a hospital, and to determine the association of iHCa with mortality, duration of hospitalization, and requirement for intensive care therapies. DESIGN: Retrospective study (January 2007-December 2008). SETTING: University veterinary teaching hospital. ANIMALS: Eighty-eight dogs admitted to the ICU within 24 hours of a traumatic event and with assessment of a venous blood gas sample, including ionized calcium, at hospital admission. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Most dogs (72%) sustained injuries as a result of a motor vehicle accident. iHCa (<1.25 mmol/L [<2.50 mEq/L]) was present in 14 of 88 dogs (16%). Dogs with abdominal trauma were significantly more likely to have iHCa (P = 0.020) than dogs with other injuries. Dogs with iHCa spent significantly longer time in the hospital (P = 0.036) and ICU (P = 0.005), and were more likely to require oxygen supplementation (P = 0.048), synthetic colloids (P = 0.020), vasopressors (P = 0.0043), and blood transfusions (P < 0.0001). Six of 14 dogs (43%) with iHCa demonstrated clinical signs consistent with hypocalcemia during the course of hospitalization, and calcium gluconate was administered intravenously to one dog. Overall mortality was 16% (14/88) and dogs with iHCa were significantly less likely to survive (P < 0.001). CONCLUSIONS: The incidence of iHCa upon hospital admission in this group of dogs with blunt and penetrating trauma is similar to the incidence of iHCa in critically ill dogs. Findings further suggest that dogs with iHCa are more severely injured and subsequently require increased intensive care therapies and have a lower likelihood of survival compared to dogs with normocalcemia. Ionized calcium concentration may therefore be a useful prognostic indicator in dogs with blunt and penetrating traumatic injuries.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".