CLOSTRIDIUM TETANUS INFECTION IN 13 DOGS AND ONE CAT
Bibliographic record
Abstract
Clostridium tetani infection is uncommon in dogs and cats. Up to this point in time just single case reports have been published in veterinary medicine. The goal of this retrospective study was to describe the clinical features and outcome of 13 dogs and one cat affected with Clostridium tetani. The medical records of the last ten year were reviewed. Dogs and cats that were identified as being infected with Clostridium tetani on the basis of characteristic clinical signs and/or bacterial culture from infected wounds were eligible for study inclusion. Thirteen dogs and one cat met the criteria for study inclusion. Six different breeds and mix‐breed dogs were affected, German Shepherd dogs (n=4, 29%) and Labrador retriever (n=3, 21%) were the most frequently affected breeds. Observed clinical complications were ventricular aspiration pneumonia (n=7), laryngeal spasm (n=6), hypersalivation (n=4), ventricular tachycardia (n=3), and third degree AV block (n=1). Median days from onset of clinical signs until first signs of improvement were 10 days (range: 9–12 days). Median hospitalisation time was 18 days (range: 14–22 days). Six animals showed full recovery and 8 animals died or were euthanized. Death was associated with acute onset of ventricular tachycardia in 2 dogs, 1 dog died with non‐responsive third degree AV‐block, 3 dogs died after developing aspiration pneumonia, and 1 dog died of unknown 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".