High-flow nasal oxygen for laryngeal tumor debulking: case report and current challenges
Bibliographic record
Abstract
High-flow nasal oxygen (HFNO) has brought new opportunities in shared airway surgery. Contemporary challenges with its use in severely obstructive conditions such as laryngeal tumors still need to be addressed as there is discrepancy in its use and access among centres. We reported a case in which the use of HFNO allowed laryngeal tumor debulking while avoiding tracheotomy in a stridulous patient. The patient described was a 70 year old patient with stridor at rest secondary to a laryngeal tumor diagnosed five days before surgery. Tumor debulking could be safely initiated under general anaesthesia, which would not have been possible without HFNO. This report served as an example of an alternative to awake tracheotomy in the management of severely obstructive laryngeal pathology We wish to discuss through this case management of severely obstructive laryngeal pathology in the era of HFNO, while encouraging discussion on its potential benefits and limits.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.008 | 0.005 |
| 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".