Neurally adjusted ventilatory assist in patients with acute respiratory failure: study protocol for a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Patient-ventilator asynchrony is a common problem in mechanically ventilated patients with acute respiratory failure. It is assumed that asynchronies worsen lung function and prolong the duration of mechanical ventilation (MV). Neurally Adjusted Ventilatory Assist (NAVA) is a novel approach to MV based on neural respiratory center output that is able to trigger, cycle, and regulate the ventilatory cycle. We hypothesized that the use of NAVA compared to conventional lung-protective MV will result in a reduction of the duration of MV. It is further hypothesized that NAVA compared to conventional lung-protective MV will result in a decrease in the length of ICU and hospital stay, and mortality. METHODS/DESIGN: This is a prospective, multicenter, randomized controlled trial in 306 mechanically ventilated patients with acute respiratory failure from several etiologies. Only patients ventilated for less than 5 days, and who are expected to require prolonged MV for an additional 72 h or more and are able to breathe spontaneously, will be considered for enrollment. Eligible patients will be randomly allocated to two ventilatory arms: (1) conventional lung-protective MV (n = 153) and conventional lung-protective MV with NAVA (n = 153). Primary outcome is the number of ventilator-free days, defined as days alive and free from MV at day 28 after endotracheal intubation. Secondary outcomes are total length of MV, and ICU and hospital mortality. DISCUSSION: This is the first randomized clinical trial examining, on a multicenter scale, the beneficial effects of NAVA in reducing the dependency on MV of patients with acute respiratory failure. TRIAL REGISTRATION: ClinicalTrials.gov website ( NCT01730794 ). Registered on 15 November 2012.
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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 | 0.017 | 0.022 |
| Meta-epidemiology (narrow) | 0.006 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.005 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.050 | 0.007 |
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".