Validation of a 2‐mm videoendoscope for the evaluation of the paranasal sinuses with a minimally invasive technique
Bibliographic record
Abstract
OBJECTIVE: To describe the technique, experience, and limitations of using a 2-mm flexible endoscope to perform standing minimally invasive sinoscopy. STUDY DESIGN: In phases 1 and 2, we used cadaveric heads (ex vivo). In phase 3, we used unaffected horses (in vivo). ANIMALS: Five cadaveric equine skulls in phase 1 and 10 cadaveric equine skulls in phase 2. Six horses older than 5 years in phase 3. METHODS: In phase 1, the specimens were used to determine the suitability of the endoscope for sinoscopy and the ideal landmarks to approach the paranasal sinuses through minisinusotomies performed with a 14 gauge needle. In phase 2, a nonblinded evaluation of the visualization of the different sinus compartments was performed, and a score was attributed to each structure. Procedures were video recorded and compared with direct visualization of the sinuses after performing frontal and maxillary flaps. In phase 3, the technique was validated in healthy horses under sedation. RESULTS: The landmarks determined in phase 1 allowed a thorough exploration of the sinuses in phases 2 and 3. Sinoscopy findings were confirmed after direct visualization of the sinuses via frontal and maxillary bone flaps in phase 2. The procedure was well tolerated by all horses. CONCLUSION: Minimally invasive sinoscopy was readily performed without relevant complications in standing horses. A thorough evaluation of most sinus structures was obtained only using the frontal and the rostral maxillary portals. CLINICAL SIGNIFICANCE: Minimally invasive sinoscopy offers an alternative diagnostic tool to veterinarians. A specialized endoscope and appropriate training are required to perform this minimally invasive procedure.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 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".