Accuracy of delivered airway pressure and work of breathing estimation during proportional assist ventilation: a bench study
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Proportional assist ventilation+ (PAV+) delivers airway pressure (P aw) in proportion to patient effort (P mus) by using the equation of motion of the respiratory system. PAV+ calculates automatically respiratory mechanics (elastance and resistance); the work of breathing (WOB) is estimated by the ventilator. The accuracy of P mus estimation and hence accuracy of the delivered P aw and WOB calculation have not been assessed. This study aimed at assessing the accuracy of delivered P aw and calculated WOB by PAV+ and examining the factors influencing this accuracy. METHODS: Using an active lung model with different respiratory mechanics, we compared (1) the actual delivered P aw by the ventilator to the theoretical P aw as defined by the equation of motion and (2) the WOB value displayed by the ventilator to the WOB measured from a Campbell diagram. RESULTS: Irrespective of respiratory mechanics and gain, the ventilator provided a P aw approximately 25 % lower than expected. This underassistance was greatest at the beginning of the inspiration. Intrinsic PEEP (PEEPi), associated with an increase in trigger delay, was a major factor affecting PAV+ accuracy. The absolute value of total WOB displayed by the ventilator was underestimated, but the changes in WOB were accurately detected by the ventilator. CONCLUSION: The assistance provided by PAV+ well follows P mus but with a constant underassistance. This is associated with an underestimation by the ventilator of the WOB. PEEPi can be a major factor contributing to PAV+ inaccuracy. Clinical recommendations should include using a high trigger sensitivity and a careful PEEP titration.
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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 | 0.002 |
| 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 | 0.000 |
| 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 it