Laparoscopic adrenalectomy for resection of unilateral noninvasive adrenal masses in dogs is associated with excellent outcomes in experienced centers
Bibliographic record
Abstract
OBJECTIVE: To report the short- and long-term outcomes of laparoscopic adrenalectomy (LA) for resection of unilateral adrenal masses and to document risk factors for conversion and peri- and postoperative morbidity. ANIMALS: 255 client-owned dogs. METHODS: Dogs were included if LA was attempted for resection of a unilateral adrenal mass. Medical records were evaluated and relevant data were reported, including complications, conversion, perioperative death, and long-term outcomes. Signalment, clinicopathological data, and surgical experience were factors statistically evaluated for possible associations with capsular penetration during surgery, conversion, surgical time, duration of hospital stay, death prior to discharge, mass recurrence, and survival time. RESULTS: 155 dogs had left-sided tumors, and 100 had right-sided tumors. Conversion to an open approach was performed in 9.4% of cases. Capsular penetration (19.2%) and major hemorrhage (5.4%) were the most prevalent intraoperative complications. Of the dogs operated on, 94.9% were discharged from the hospital. Lesion side, portion of the gland affected, and surgeon experience influenced surgical time. Conversion rate increased with increasing body condition score and lesion size. Risk of death prior to discharge increased with increasing lesion size. Risk of conversion and death prior to discharge were lower when performed by more experienced surgeons. Capsular penetration during LA increased the risk of tumor recurrence. CLINICAL RELEVANCE: LA for resection of unilateral adrenal masses is associated with excellent outcomes in experienced centers. Surgeons with greater experience with LA have lower surgical times, conversion rates, and risk of death prior to discharge.
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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 | 0.001 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".