Inhaled Nitric Oxide: In Vitro Analysis of Continuous Flow Noninvasive Delivery via Nasal Cannula
Bibliographic record
Abstract
BACKGROUND: Inhaled nitric oxide (NO) is most frequently delivered to mechanically ventilated patients in critical care, but it can also be administered noninvasively. The delivered dose and efficiency of continuous flow NO supplied through a nasal cannula has yet to be established. This study aimed to determine the influence of nasal cannula type, supply flow, and breathing pattern on delivered NO using a realistic adult airway replica and lung simulator. METHODS: Simulated breathing patterns were selected to represent rest, sleep, and light exercise, and were varied to investigate the effects of tidal volume and breathing frequency independently. Supplied gas flows targeted tracheal concentrations at rest of 5 or 20 ppm NO and were supplied with 2 L/min O 2 . Three different cannulas were tested. Tracheal NO concentrations and NO mass flow past the trachea were evaluated. RESULTS: Cannula type had a minor influence on delivered dose. Tracheal NO concentrations differed significantly based on breathing pattern ( P < 0.01); for a target NO concentration of 20 ppm at rest, average inhaled NO concentrations were 23.3 ± 0.5 ppm, 36.5 ± 1.4 ppm, and 17.2 ± 0.3 ppm for the rest, sleep, and light exercise breathing patterns, respectively. For the same test conditions, mass flow of NO past the trachea was less sensitive to breathing pattern: 20.3 ± 0.5 mg/h, 19.9 ± 0.8 mg/h, and 24.3 ± 0.4 mg/h for the rest, sleep, and light exercise breathing patterns, respectively. Mass flow and delivery efficiency increased when minute volume increased. CONCLUSIONS: These results indicate that inhaled NO concentration is strongly influenced by breathing pattern, whereas inhaled NO mass flow is not. NO mass flow may therefore be a useful dose metric for continuous flow delivery via nasal cannula.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".