Case report: Radiography and computed tomography of tension pneumoperitoneum caused by gastric perforation in a dog
Bibliographic record
Abstract
Tension pneumoperitoneum is characterized by excessive accumulation of gas in the peritoneal cavity, which leads to cardiorespiratory distress. We present the case of a 4-year-old female Labrador retriever who presented with a severe abdominal distension and panting. Radiography revealed a large volume of free gas in the peritoneal cavity with decreased serosal detail. After emergency needle decompression, ultrasound-guided aspiration of the peritoneal effusion helped confirm septic peritonitis. Computed tomography revealed a gastric mass measuring approximately 3.7 × 5.0 × 5.5 cm, which was suspected to have caused the gastric perforation. A large volume of free gas was present in the peritoneal cavity, causing compression and centralization of the abdominal organs. A low-attenuating cleft suggestive of perforation site near the gastric mass was also observed. Exploratory laparotomy confirmed gastric perforation of approximately 2.2 cm adjacent to the gastric mass. The patient was finally diagnosed with tension pneumoperitoneum caused by gastric perforation. The mass was resected with a 1-2-cm surgical margin, and imprinting cytology indicated gastric carcinoma. The patient was aggressively treated with fluid, analgesic, antithrombotic, and antibacterial therapy. However, the patient's condition continued to deteriorate, and euthanasia was performed at the owner's request. Our report is the first to describe the multimodal imaging features of a dog with tension pneumoperitoneum secondary to gastric perforation caused by gastric neoplasm.
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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) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.008 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".