Assisted Ventilation in Patients with Acute Respiratory Distress Syndrome
Bibliographic record
Abstract
AbstractAbstract Twelve patients with mild-to-moderate acute respiratory distress syndrome were ventilated in a randomized order with three ventilation modes: pressure control ventilation, pressure support ventilation, and neurally adjusted ventilatory assist. Lung-protective ventilation was maintained to a similar degree in all study arms; the results are hypothesis generating for using assisted ventilation in patients with acute respiratory distress syndrome after the first 48 h of therapy, which might include paralysis. Supplemental Digital Content is available in the text. Background: In patients with acute respiratory distress syndrome (ARDS), the use of assisted mechanical ventilation is a subject of debate. Assisted ventilation has benefits over controlled ventilation, such as preserved diaphragm function and improved oxygenation. Therefore, higher level of “patient control” of ventilator assist may be preferable in ARDS. However, assisted modes may also increase the risk of high tidal volumes and lung-distending pressures. The current study aims to quantify how differences in freedom to control the ventilator affect lung-protective ventilation, breathing pattern variability, and patient–ventilator interaction. Methods: Twelve patients with ARDS were ventilated in a randomized order with assist pressure control ventilation (PCV), pressure support ventilation (PSV), and neurally adjusted ventilatory assist (NAVA). Transpulmonary pressure, tidal volume, diaphragm electrical activity, and patient–ventilator interaction were measured. Respiratory variability was assessed using the coefficient of variation of tidal volume. Results: During inspiration, transpulmonary pressure was slightly lower with NAVA (10.3 ± 0.7, 11.2 ± 0.7, and 9.4 ± 0.7 cm H 2 O for PCV, PSV, and NAVA, respectively; P < 0.01). Tidal volume was similar between modes (6.6 [5.7 to 7.0], 6.4 [5.8 to 7.0], and 6.0 [5.6 to 7.3] ml/kg for PCV, PSV, and NAVA, respectively), but respiratory variability was higher with NAVA (8.0 [6.4 to 10.0], 7.1 [5.9 to 9.0], and 17.0 [12.0 to 36.1] % for PCV, PSV, and NAVA, respectively; P < 0.001). Patient–ventilator interaction improved with NAVA (6 [5 to 8] % error) compared with PCV (29 [14 to 52] % error) and PSV (12 [9 to 27] % error); P < 0.0001. Conclusion: In patients with mild-to-moderate ARDS, increasing freedom to control the ventilator maintains lung-protective ventilation in terms of tidal volume and lung-distending pressure, but it improves patient–ventilator interaction and preserves respiratory variability.
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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) | 0.000 | 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 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".