Thoracotomy for esophageal foreign body removal in a dog
Bibliographic record
Abstract
In the clinical routine of small animals, the occurrence of foreign bodies (FB) in the digestive tract is routine, especially in dogs and cats with uncontrolled eating habits and puppies. In dogs, the main occurrence is bones, and in cats, linear materials. Surgical removal is usually the effective method in the treatment of esophageal FB, and endoscopy is the technique of choice, however, in some cases, it is recommended to perform thoracotomy with esophagotomy, as it presents the best results in surgical resolution. The objective of this study is to report the case of a two-year-old Labrador canine who was treated by the Ophthalmology and Surgery Sector of the University Veterinary Hospital of the Federal University of Santa Maria (HVU-UFSM) and who presented esophageal obstruction by the body and tranche. After the diagnosis and with the results of the complementary comb exams, the patient was submitted to thoracotomy with esophagotomy for the removal of the FB. In the intraoperative period, analgesic, anti-inflammatory, and antibiotic medications were used, as follows: dipyrone 25 mg/kg, TID, tramadol hydrochloride 4 mg/kg, TID, meloxicam 0.1 mg/kg SID and ceftaroline 30 mg/kg BID, all intravenous lines. On the third day after surgery, the patient was discharged without complications. The same medications were prescribed for home administration, replacing the route of administration for the oral route and the antibiotic for cefalexin 30mg/kg. The surgical approach chosen for the treatment was indicated by the size and location of the FB in the esophagus. Thus, it is concluded that the use of this technique provides the removal with the visualization of the viability of the layers and sofic and demonstrates excellent results with a return to routine activities.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".