Outcome in dogs undergoing adrenalectomy for small adrenal gland tumours without vascular invasion
Bibliographic record
Abstract
Veterinary studies have reported the outcome of adrenalectomies in dogs; however, these studies typically include a wide variety of adrenal tumour sizes, including cases with or without vascular invasion. The purpose of this study was to report outcome in a cohort of dogs with histologically confirmed small adrenal tumours without vascular invasion treated with adrenalectomy. This retrospective study was conducted using data from the University of Florida and University of California-Davis databases between 2010 and 2017. Dogs were included if they underwent excision of an adrenal gland tumour with a maximal diameter ≤ 3 cm, without evidence of vascular invasion to any location as assessed via computed tomography. Fifty-one dogs met the inclusion criteria. The short-term survival rate of dogs undergoing adrenalectomy was 92.2%, and one-year disease-specific survival was 83.3%. Twenty-eight of 51 (54.9%) dogs were diagnosed with a malignancy. Minor complications were observed commonly intra-operatively and post-operatively. Major complications were observed in six dogs, and included sudden death, respiratory arrest, acute kidney injury, haemorrhage, hypotension and aspiration pneumonia. Short-term mortality occurred in four dogs. Sudden death and haemorrhage were the most common major complications leading to death. While adrenalectomy is sometimes controversial because of the high perioperative mortality rates previously reported, the results of this study support that adrenalectomy for small tumours with no vascular invasion can be performed with low risk.
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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 | 0.001 | 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".