Effect of perioperative desmopressin in cats with mammary carcinoma treated with bilateral mastectomy
Bibliographic record
Abstract
Perioperative administration of desmopressin has shown to significantly decrease rates of local recurrence and metastasis, and increase survival times in dogs with grade II and III mammary carcinomas. The objective of this study was to compare the oncologic outcome of cats with mammary carcinoma treated with bilateral mastectomy with or without perioperative administration of desmopressin. Medical records from nine veterinary institutions were searched to identify cats diagnosed with mammary carcinoma treated with bilateral mastectomy. Sixty cats treated with single-session or staged bilateral mastectomy were included. There were no significant differences in oncologic outcomes found between cats treated and not treated with desmopressin. No adverse effects were seen in any of the cats treated with perioperative desmopressin. Postoperative complications occurred in 18 cats (38.3%) treated with single-session bilateral mastectomy and in three cats (23.1%) treated with staged bilateral mastectomy (P = .48). Histologic grade and a modification of a proposed five-stage histologic staging system were both prognostic for disease-free interval. Incomplete histologic excision was associated with significantly increased rates of metastasis and tumour progression, and a shorter median survival time (MST). Cats that developed local recurrence also had a significantly shorter MST. The results of this study do not support the use of perioperative desmopressin to improve outcome when performing bilateral mastectomy for the treatment of mammary carcinoma in cats.
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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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".