Cranial Vena Cava Syndrome in a Retriever Dog Receiving CPN through Central Venous Catheter
Bibliographic record
Abstract
A 5-year-old castrated male Golden Retriever dog weighing 15 kg presented with evidence of intestinal intussusception. The patient had cachexia and severe dehydration before being referred to our department. Ultrasound imaging revealed a target sign indicative of intestinal intussusception. Emergency surgery was performed shortly after diagnosis. After a successful surgery, the patient was hospitalised for postoperative care. Initial treatment was aimed at the reversion of dehydration and the provision of adequate nutrition. Fluid therapy and central parenteral nutrition were administered via the peripheral and central venous catheters, respectively. Ten days postoperatively, swelling and edema were observed in the head and neck. Ultrasound and computed tomography confirmed complete blockage of the cranial vena cava due to thrombosis, which consequently obstructed both the left and right jugular veins. For treatment, dalteparin and tissue plasminogen activator were administered. However, the patient lost all of its vital function on the daybreak of postoperative day 11. Venous thrombus formation secondary to central parenteral nutrition application via the central line is a rare but possible complication. Veterinarians who are concerned about taking care of patients receiving CPN through the central line should keep the possibility of venous thrombus formation in mind.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| 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".