Cadaveric evaluation of fluoroscopy‐assisted placement of one‐lung ventilation devices for video‐assisted thoracoscopic surgery in dogs
Bibliographic record
Abstract
OBJECTIVE: To evaluate the feasibility of fluoroscopy-assisted placement of one-lung ventilation (OLV) devices in dogs. STUDY DESIGN: Experimental study. SAMPLE POPULATION: Canine cadavers (n = 8) weighing between 20.2 and 37.4 kg. METHODS: Thoracoscopic access with a two-port approach was established to evaluate bilateral lung ventilation patterns. Advancement of a left-sided Robertshaw double-lumen endobronchial tube (DLT) and the EZ-blocker (EZ) were evaluated under direct fluoroscopic guidance. Each dog also underwent bronchoscopy-assisted placement of an Arndt endobronchial blocker (EBB). Time to initial placement, success of creating complete OLV (after initial placement attempt and after up to two repositionings), and ease of placement score were recorded. Device position was evaluated bronchoscopically after each fluoroscopy-assisted placement attempt. RESULTS: Time to initial placement was significantly shorter for EZ than for DLT and EBB. The rate of successful placement after up to two repositioning attempts was 87.5%, 87.5%, and 100.0% on the right and 87.5%, 100.0%, 100.0% on the left for DLT, EZ, and EBB, respectively, and was not different between devices. Ease of placement scores were significantly higher for DLT compared with EZ and EBB on both the left and the right sides. CONCLUSION: Fluoroscopy-assisted placement of DLT and EZ appears feasible in canine cadavers. EZ-blocker placement was efficient and technically easier than DLT, but positioning must be adapted for dogs. Bronchoscopy-assisted placement of EBB remains highly successful. CLINICAL SIGNIFICANCE: Fluoroscopy-assisted placement of EZ and DLT is a useful alternative to bronchoscopy-assisted placement of these OLV devices.
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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".