Fertility following successful treatment of canine pyometra
Bibliographic record
Abstract
Canine pyometra is a potentially life-threatening condition characterized by pus accumulation in the uterus, often triggered by hormonal changes during the estrous cycle. It commonly affects intact female dogs over five years old due to prolonged progesterone exposure post-estrus during each estrous cycle. The present study discusses the fertility outcome of a six-year-old female Labrador Retriever treated for open cervix pyometra. The dog was presented to the Veterinary Clinical Complex, RIVER, Puducherry, with foul-smelling mucopurulent vulvar discharge for a week. The dog had whelped four times, with the last pregnancy ending in abortion, and had shown proestral bleeding two and a half months earlier. Clinical examination revealed a distended abdomen, inappetence, dullness and purulent discharge from vulva. Ultrasonography showed anechoic sacculations in the uterus, and haematology indicated severe leucocytosis, monocytosis, thrombocytopenia, and elevated creatinine. Based on the clinical, haematological and ultrasonographic examinations, the case was diagnosed as open cervix pyometra. The dog was treated with Tab. Mifepristone (5 mg/kg for 3 days) orally and per-vaginal misoprostol (3 mcg/kg) until uterine evacuation, alongside intravenous ceftriaxone-tazobactam (30 mg/kg) for 14 days and supportive fluids for 7 days. Probiotics (Tab. Renodis- One tablet a day PO) was prescribed for 10 days. Seven days after the treatment, ultrasonography revealed a significant reduction in uterine size, the animal regained feed intake indicating full recovery. The dog was followed another 6 months. It showed proestral bleeding 4 months after treatment, became pregnant and delivered 5 healthy puppies.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".