Airway opening pressure in mechanically ventilated patients: regional distribution and impact of body position
Bibliographic record
Abstract
BACKGROUND: Airway Opening Pressure (AOP) refers to the pressure level needed to reopen previously collapsed airways. Its underlying mechanisms remain debated. This study aimed to assess its regional distribution and the effect of body position. METHODS: Global AOP (AOPGLOBAL) was assessed by the low-flow inflation maneuver. Electrical impedance tomography allowed to assess regional AOP (ventral and dorsal). Measurements were performed in the semi-recumbent position (SR30°) in all patients and repeated in supine position (SP0°) in a subgroup of patients to explore the effect of body position. As a proof of concept, AOP was also evaluated in four Thiel cadavers in both SR30° and SP0°, with and without the adjunction of a 3 kg saline bag on the abdomen. RESULTS: 46 mechanically ventilated patients were analyzed. In SR30°, AOPGLOBAL was detected in 10 patients (22%) (median level 8.4 [6.3–12.0] cmH2O), while AOPVENTRAL and AOPDORSAL occurred in 11 (24%) and 16 (35%) patients, respectively. The lowest regional AOP correlated with the AOPGLOBAL (r2 = 0.993, p < 0.001). In the subgroup of 23 patients with position analysis, the highest regional AOP increased from SR30° to SP0°. Cadavers’ experiments showed that the increase in end-expiratory esophageal pressure associated with SP0° or increased abdominal pressure correlated with the increase in AOPGLOBAL (r2 = 0.908, p < 0.001). CONCLUSION: Bedside AOP detection based on the low-flow insufflation method may miss regional AOP, leading to an underestimation of the minimal positive end-expiratory pressure which may be required to avoid tidal opening and closing in some lung regions. The level of regional AOP increases in SP0° compared to SR30° position.
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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".