Primary splenic torsion in dogs: 102 cases (1992–2014)
Bibliographic record
Abstract
OBJECTIVE: To determine the percentage of dogs surviving to hospital discharge and identify factors associated with death prior to hospital discharge among dogs undergoing surgery because of primary splenic torsion (PST). DESIGN: Retrospective case series. ANIMALS: 102 client-owned dogs. PROCEDURES: Medical records of dogs with a confirmed diagnosis of PST that underwent surgery between August 1992 and May 2014 were reviewed. History, signalment, results of physical examination and preoperative bloodwork, method of splenectomy, concurrent surgical procedures, perioperative complications, duration of hospital stay, splenic histopathologic findings, and details of follow-up were recorded. Best-fit multivariate logistic regression was performed to identify perioperative factors associated with survival to hospital discharge. RESULTS: 93 of the 102 (91.2%) dogs survived to hospital discharge. German Shepherd Dogs (24/102 [23.5%]), Great Danes (15/102 [14.7%]), and English Bulldogs (12/102 [11.8%]) accounted for 50% of cases. Risk factors significantly associated with death prior to hospital discharge included septic peritonitis at initial examination (OR, 32.4; 95% confidence interval [CI], 2.1 to 502.0), intraoperative hemorrhage (OR, 22.6; 95% CI, 1.8 to 289.8), and postoperative development of respiratory distress (OR, 35.7; 95% CI, 2.7 to 466.0). Histopathologic evidence of splenic neoplasia was not found in any case. CONCLUSIONS AND CLINICAL RELEVANCE: Results suggested that the prognosis for dogs undergoing splenectomy because of PST was favorable. Several risk factors for death prior to discharge were identified, including preexisting septic peritonitis, intraoperative hemorrhage, and postoperative development of respiratory distress.
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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 | 0.002 | 0.002 |
| 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 | 0.001 | 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".