Minimally invasive splenectomy is associated with a low perioperative complication rate and short operative time in cats
Bibliographic record
Abstract
OBJECTIVE: To report the perioperative outcome and complications in cats undergoing minimally invasive splenectomy. ANIMALS: 17 client-owned cats. METHODS: Perioperative data were collected from cats undergoing minimally invasive splenectomy from September 2010 to June 2023. Data included history, signalment, preoperative examination and diagnostic testing results, operative technique and time, perioperative outcomes, complications, hospitalization duration, histopathological diagnosis, and outcome. RESULTS: 13 spayed females and 4 neutered males were included, with a median age of 144 months (48 to 196 months). Seven cats underwent total laparoscopic splenectomy (TLS), with 1 cat requiring conversion from TLS to laparoscopic-assisted splenectomy (LAS) due to splenomegaly and an additional cat requiring conversion from TLS to open splenectomy due to uncontrollable splenic capsular hemorrhage. Ten cats underwent LAS, with 1 cat requiring conversion to open splenectomy due to splenomegaly. Additional procedures were performed in 13 cats, with the most common being liver biopsy in 10 cats. Median operative times were 50 minutes (45 to 90 minutes) for TLS and 35 minutes (25 to 80 minutes) for LAS. An intraoperative complication occurred in 1 cat. All but 1 cat survived to discharge. Median follow-up time was 234 days (18 to 1,761 days), with 15 of 16 cats confirmed alive at 30 days and 9 of 16 cats alive at 180 days postoperatively. CLINICAL RELEVANCE: Minimally invasive splenectomy in this cohort of cats was associated with short operative times and a low perioperative complication rate. Veterinary surgeons may consider minimally invasive splenectomy as an efficient and feasible technique in the treatment of splenomegaly or modestly sized splenic masses for diagnostic and therapeutic purposes in cats.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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 teacher head, 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".