The <scp>LMA</scp>‐<scp>Supreme<sup>TM</sup></scp> as an intubation conduit in patients with known difficult airways: a prospective evaluation study
Bibliographic record
Abstract
BACKGROUND: Many extraglottic airway devices allow the direct passage of an adult-sized tracheal tube, but this is not possible with the LMA-Supreme(TM) . We evaluated the feasibility of using the LMA-Supreme(TM) as a conduit for intubation in patients with known difficult airways. METHODS: Sixty-eight adult patients, with preoperative predictors of difficult intubation, were scheduled for elective surgery under general anaesthesia. After assessing the direct laryngoscopy view, 23 patients with Cormack-Lehane III/IV were included in the study. An LMA-Supreme(TM) was inserted, followed by the passage of a flexible bronchoscope loaded with an Aintree Intubation Catheter into the trachea. The bronchoscope and LMA-Supreme(TM) were removed, and a tracheal tube was railroaded over the Aintree Intubation Catheter into the trachea. RESULTS: Tracheal intubation was successful in all patients using the above technique. SpO(2) was >95% during the intubation procedure. CONCLUSIONS: We conclude that the LMA-Supreme(TM) is a successful conduit for bronchoscopic/Aintree Intubation Catheter-guided intubation in patients with known difficult airway.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".