Flexible laryngeal mask airway for head and neck oncoplastic surgery?
Bibliographic record
Abstract
EDITOR: We read with interest Drs Martin-Castro and Montero's report on the use of the flexible laryngeal mask (FLMA) as an alternative to reinforced tracheal tube for upper chest, head and neck oncoplastic surgery [1]. We seek some clarifications from them with regard to the operations concerned. How many of the patients whose airways were managed with the FLMA had oro-pharyngeal malignancies? What reconstructions were performed? Were there any postoperative tracheal intubations? The term ‘head and neck oncoplastic surgery' conventionally refers to resection of head, face and neck (or oral, pharyngeal and laryngeal) tumours followed by reconstruction using local, regional or microvascular free tissue flaps [2]. These tumours often result in anticipated difficult airways and additionally may require nasotracheal and/or fibreoptic intubation or preoperative tracheotomy [3-5]. Airway management decisions are also based on the complexity of the planned reconstruction or the need for postoperative ventilation [6]. In our opinion, the airway management in head and neck oncoplastic surgery differs from upper chest (specifically breast oncoplastic) surgery. In the former, the laryngeal mask airway device can be used to temporarily secure the airway, as a conduit for fibreoptic intubation or offer a rescue technique before or after surgery. Therefore, while the FLMA, as these authors have reported, would be useful for breast oncoplastic surgery, it may have a limited role in the perioperative airway management for head and neck oncoplastic surgery.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".