Outcomes for dogs with functional thyroid tumors treated by surgical excision alone
Bibliographic record
Abstract
OBJECTIVE: To describe clinical findings and survival times for dogs with functional thyroid tumors treated with surgery alone and investigate potential prognostic factors for outcome in these patients. ANIMALS: 27 client-owned dogs. PROCEDURES: Medical records of 9 institutions were reviewed to identify dogs with hyperthyroidism secondary to thyroid neoplasia that were treated with surgery alone between 2005 and 2015. Data collected included signalment, hematologic and physical examination findings, tumor staging results, time from diagnosis to treatment, surgical procedure performed, histologic findings, evidence of recurrence or metastatic disease, and date of death or last follow-up. Median survival time and 1-, 2-, and 3-year survival rates were assessed by Kaplan-Meier analysis. Associations between variables of interest and the outcome of death were assessed with Cox proportional hazards models. RESULTS: Dogs from 8 institutions met inclusion criteria. Median age at diagnosis was 10 years (range, 8 to 13 years). Golden Retrievers and Labrador Retrievers were commonly represented (5 dogs each). Polyuria with polydipsia (15/27 [56%]) and weight loss (12 [44%]) were the most common clinical signs; 2 dogs without clinical signs had hyperthyroidism identified by routine hematologic analysis. One dog had metastatic disease at the time of diagnosis. Most tumors (23/27 [85%]) were malignant. Estimated median survival time was 1,072 days. No significant prognostic factors were identified. CONCLUSIONS AND CLINICAL RELEVANCE: Dogs with resectable functional thyroid tumors had a good prognosis with surgical excision alone. Survival times for these dogs were similar to those in previous studies that included dogs with nonfunctional thyroid tumors.
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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) | 0.001 | 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".