Thoracoscopic removal of cranial mediastinal masses in dogs is associated with a low conversion rate, excellent survival to discharge, and good long-term outcome
Bibliographic record
Abstract
OBJECTIVE: To report the complications and outcomes associated with thoracoscopic cranial mediastinal mass resection in dogs. ANIMALS: 49 client-owned dogs that underwent thoracoscopic cranial mediastinal mass removal. METHODS: This was a retrospective cohort study (January 1, 2014, to July 31, 2023), and the medical records of 49 client-owned dogs that underwent thoracoscopic cranial mediastinal mass removal were reviewed. The signalment, history, clinicopathologic features, perioperative complications, and long-term outcome were recorded. RESULTS: Preoperative myasthenia gravis (MG) and megaesophagus (ME) were identified in 17 of 49 (35%) dogs and 11 of 49 (22%) dogs, respectively. The median maximal tumor diameter on CT images was 4.7 cm (range, 2.7 to 8.5 cm). Nonemergent conversion to an open procedure was necessary in 4 of 49 (8%) dogs, and dogs with conversion to an open procedure had a significantly larger median maximal CT tumor diameter than dogs without conversion (P = .03). The most common tumor type was thymoma (37/49 [76%]). The overall median survival time for dogs with thymoma was 1,102 days (95% CI, 482 to upper bound not reached). The median survival time for dogs with thymoma and concurrent presurgical MG was 182 days (95% CI, 14 to upper bound not reached). Presurgical diagnosis of MG (P = .44) or ME (P = .69) was not associated with survival time. CLINICAL RELEVANCE: Thoracoscopic removal of cranial mediastinal masses was associated with low conversion and complication rates. Long-term survival is possible, and thoracoscopic removal should be considered for select cases.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".