Evaluation of freshwater submersion in small animals: 28 cases (1996–2006)
Bibliographic record
Abstract
OBJECTIVE: To determine clinical characteristics, treatments, and outcome in dogs and cats evaluated after submersion in freshwater. DESIGN: Retrospective case series. ANIMALS: 25 dogs and 3 cats. PROCEDURES: Medical records were reviewed for signalment; causes, location, and month of submersion; physical examination findings at admission; results of blood gas analysis; treatments administered; duration of hospitalization; and outcome, including evidence of organ failure or compromise. RESULTS: All submersions involved bodies of freshwater. Fourteen animals were submerged in man-made water sources, 13 were submerged in natural water sources, and the body of water was not recorded in 1 case. Twenty (71%) submersions occurred from May through September. Cause was identified in 16 animals and included extraordinary circumstances (n = 6), falling into water (5), breaking through ice (3), and intentional submersion (2). Twelve animals were found submerged in water with unclear surrounding circumstances. Treatment included administration of supplemental oxygen, antimicrobials, furosemide, corticosteroids, and aminophylline and assisted ventilation. Respiratory dysfunction was detected in 21 animals. Neurologic dysfunction was detected in 12 animals, hepatocellular compromise was detected in 6 animals, and cardiovascular dysfunction was detected in 4 animals. Three dogs had hematologic dysfunction, and 2 dogs had acute renal dysfunction. Eighteen (64%) animals survived to hospital discharge, but all of the cats died. In 9 of 10 nonsurvivors, respiratory tract failure was the cause of death or reason for euthanasia. CONCLUSIONS AND CLINICAL RELEVANCE: Results suggest that submersion is an uncommon reason for veterinary evaluation but is associated with a good prognosis in dogs in the absence of respiratory tract failure.
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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 | 0.001 |
| 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".