Video‐assisted thoracic surgery for the management of pyothorax in dogs: 14 cases
Bibliographic record
Abstract
OBJECTIVE: To report the perioperative findings and outcome of dogs undergoing video-assisted thoracic surgery (VATS) for the management of pyothorax. DESIGN: Multi-institutional, retrospective study. ANIMALS: Client-owned dogs (n = 14). METHODS: Medical records of dogs with pyothorax managed via VATS were reviewed for signalment, history, clinical signs, clinicopathological findings, diagnostic imaging results, surgical variables, bacterial culture and sensitivity results, post-operative management and outcome. VATS was performed after placing a paraxyphoid endoscopic portal and 2-3 intercostal instrument portals. VATS exploration was followed by one or more of the following: mediastinal debridement, tissue sampling, pleural lavage, and placement of a thoracostomy tube. RESULTS: Two dogs (14%) required conversion from VATS to an open thoracotomy to completely resect proliferative mediastinal tissue. These dogs had severe pleural effusion on preoperative thoracic radiographs and one had severely thickened contrast-enhancing mediastinum on preoperative computed tomography (CT). The cause of pyothorax was identified as a penetrating gastric foreign body (n = 2), migrating plant material (n = 2), and idiopathic (n = 10). The median follow-up time was 143 days (range, 14-2402 days). All dogs were discharged from the hospital and their clinical signs resolved. One patient had recurrence of a pyothorax requiring revision surgery 17 months postoperatively. CONCLUSION: VATS allows minimally invasive treatment of uncomplicated canine pyothorax. Preoperative thoracic CT may help identify candidates for VATS among dogs with pyothorax.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 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 | 0.000 |
| 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".