Measurement of airway pressure during high‐flow nasal therapy in apnoeic oxygenation: a randomised controlled crossover trial <sup>*</sup>
Bibliographic record
Abstract
Summary It is recognised that high‐flow nasal therapy can prevent desaturation during airway management. Studies in spontaneously breathing patients show an almost linear relationship between flow rate and positive airway pressure in the nasopharynx. Positive airway pressure has been suggested as one of the possible mechanisms explaining how high‐flow nasal therapy works. However, data on pressures generated by high‐flow nasal therapy in apnoeic adults under general anaesthesia are absent. This randomised controlled crossover trial investigated airway pressures generated by different flow rates during high‐flow nasal therapy in anaesthetised and paralysed apnoeic patients, comparing pressures with closed and open mouths. Following induction of anaesthesia and neuromuscular blockade, a continuous jaw thrust was used to enable airway patency. Airway pressure was measured in the right main bronchus, the middle of the trachea and the pharynx, using a fibreoptically‐placed catheter connected to a pressure transducer. Each measurement was randomised with respect to closed or open mouth and different flow rates. Twenty patients undergoing elective surgery were included (mean (SD) age 38 (18) years, BMI 25.0 (3.3) kg.m ‐2 , nine women, ASA physical status 1 (35%), 2 (55%), 3 (10%). While closed mouths and increasing flow rates demonstrated non‐linear increases in pressure, the pressure increase was negligible with an open mouth. Airway pressures remained below 10 cmH 2 O even with closed mouths and flow rates up to 80 l.min −1 ; they were not influenced by catheter position. This study shows an increase in airway pressures with closed mouths that depends on flow rate. The generated pressure is negligible with an open mouth. These data question positive airway pressure as an important mechanism for maintenance of oxygenation during apnoea.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".