Fecal microbiota transplantation in puppies with canine parvovirus infection
Bibliographic record
Abstract
BACKGROUND: Diarrhea associated with parvovirus infection is common in dogs. Supportive care is the mainstay of treatment, but recovery may be prolonged and mortality rate can be high. Modification of the intestinal bacterial microbiota has been promising in human and veterinary medicine as an adjunctive treatment of various enteric diseases. OBJECTIVES: To investigate the safety and efficacy of fecal microbiota transplantation (FMT) on the clinical recovery of puppies with acute hemorrhagic diarrhea syndrome. ANIMALS: Sixty-six puppies with parvovirus infection were evaluated at 2 veterinary hospitals. METHODS: Randomized clinical trial. Puppies were randomly distributed into 2 groups: standard treatment (STD) and standard treatment + FMT (STD + FMT). The STD puppies (n = 33) received only treatment with IV fluids and antimicrobials and the STD + FMT puppies (n = 33) received FMT in addition to standard treatment. For FMT, 10 g of feces from a healthy dog diluted in 10 mL of saline were administered rectally 6-12 hours post-admission. RESULTS: Among survivors, treatment with FMT was associated with faster resolution of diarrhea (P < .001) and shorter hospitalization time (P = .001; median, 3 days in STD + FMT; median, 6 days in STD) compared to standard treatment. Mortality in STD was 36.4% (12/33) as compared to 21.2% (7/33) in puppies treated with FMT, but there was no statistical difference between groups (P = .174). Polymerase chain reaction indicated that all animals carried canine parvovirus, strain CPV-2b. CONCLUSIONS: Fecal microbiota transplantation in parvovirus-infected puppies was associated with faster resolution of diarrhea.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".