Successful Management of Follicular Cyst-induced Dermatoses in a Labrador Retriever Dog
Bibliographic record
Abstract
Background: Sex hormone dermatoses are uncommon in dog and causes overproduction of one or more of the sex hormones or exogenous administration. Ovarian cyst-induced hyperestrogenemia increased cortisol, hypertestosteronemia, and skin lesions mostly underwent undiagnosed and untreated. This case was documented as clinical pathological changes, diagnosis, and treatment of sex hormone imbalance-induced dermatosis due to an ovarian follicular cyst in a Labrador Retriever bitch. Methods: This clinical investigation was carried out in the month of April’2022 at Veterinary Clinical Complex, Veterinary College and Research Institute, Tirunelveli with a history of prolonged proestrus bleeding, perineal pruritus with reddening, swelling, and enlargement of the vulva. Vaginal exfoliative cytology, hormonal assay, ultrasonography, histopathology of skin, and haemato-biochemistry were performed. Result: Physical examination revealed hyperpigmentation and hyperkeratinization of the skin. Vaginal exfoliative cytology and progesterone assay revealed cytological estrus. Ultrasonography revealed greater than 10 mm-sized anechoic structures in both ovaries along with uterine endometrial hyperplasia. Hormonal analysis revealed hyperestrogenemia and increased cortisol and testosterone. A biopsy of the perineal skin revealed hyperplasia and hyperkeratosis. The case was confirmed as sex hormone imbalance-induced dermatosis due to an ovarian follicular cyst. The animal was treated with two shots of Inj. hCG 500IU in 48 hrs interval followed by OHE after three months.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".