Airway opening pressure maneuver to detect airway closure in mechanically ventilated pediatric patients
Bibliographic record
Abstract
Background: Airway closure, which refers to the complete collapse of the airway, has been described under mechanical ventilation during anesthesia and more recently in adult patients with acute respiratory distress syndrome (ARDS). A ventilator maneuver can be used to identify airway closure and measure the pressure required for the airway to reopen, known as the airway opening pressure (AOP). Without that maneuver, AOP is unknown to clinicians. Objective: This study aims to demonstrate the technical adaptation of the adult maneuver for children and illustrate its application in two cases of pediatric ARDS (p-ARDS). Methods: A bench study was performed to adapt the maneuver for 3-50 kg patients. Four maneuvers were performed for each simulated patient, with 1, 2, 3, and 4 s of insufflation time to deliver a tidal volume (Vt) of 6 ml/kg by a continuous flow. Results: O with a clear inflection point, except for the 3 kg simulated patient. Regarding insufflation time, a 4 s maneuver exhibited a better performance in 30 and 50 kg simulated patients since shorter insufflation times had excessive flowrates (>10 L/min). Below 20 kg, the difference in resistive pressure between a 3 s and a 4 sec maneuver was negligible; therefore, prolonging the maneuver beyond 3 s was not useful. Airway closure was identified in two p-ARDS patients, with the pediatric maneuver being employed in the 28 kg patient. Conclusions: We propose a pediatric AOP maneuver delivering 6 ml/kg of Vt at a continuous low-flow inflation for 3 s for patients weighing up to 20 kg and for 4 s for patients weighing beyond 20 kg.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".