Thoracoscopic Lung Biopsies in Heaves-Affected Horses Using a Bipolar Tissue Sealing System
Bibliographic record
Abstract
OBJECTIVE: To validate the use of the LigaSure™ Vessel Sealing System (LVSS) to perform thoracoscopic lung tissue biopsies in heaves-affected horses. STUDY DESIGN: Prospective clinical study. ANIMALS: Heaves-affected horses (n=12). METHODS: Lung biopsies (n=34) were collected with the LVSS (2-4 biopsies/horse) in horses with and without clinical signs of heaves. Thoracoscope (13th intercostal space [ICS]) and 2 instruments (between the 12-15th ICS) portals were used. Selected clinical and arterial blood gas variables were monitored. Postoperative pneumothorax was evaluated. Depth of thermal injury to the surrounding tissue and representativeness of the biopsies were determined. RESULTS: Mean surgical time was 22.9±8.0 minutes. The complication rate was 5.6%, and primarily related to a focal inadequate sealing of the biopsy margin. Five horses in exacerbation required intraoperative intranasal O(2) . Mean PaO(2) was significantly lower in heaves-affected horses with clinical signs compared with those without clinical signs. Postoperative pneumothorax was detected radiographically after 20 of the 34 procedures. One horse with clinical signs of heaves developed a fatal tension pneumothorax 5 days postoperatively despite close radiographic monitoring. CONCLUSION: Thoracoscopic lung biopsy using LVSS is a rapid and effective technique to harvest peripheral lung tissues from heaves-affected horses. Although the complication rate was tolerable, tension pneumothorax was a potential life-threatening complication because of incomplete lung sealing. CLINICAL RELEVANCE: LVSS can be used with relative safety to perform thoracoscopic lung biopsy, but close postoperative monitoring is necessary to avoid tension pneumothorax.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".