Cardiorespiratory effects of NIV‐NAVA, NIPPV, and NCPAP shortly after extubation in extremely preterm infants: A randomized crossover trial
Bibliographic record
Abstract
Abstract Objective Investigate the cardiorespiratory effects of noninvasive neurally adjusted ventilatory assist (NIV‐NAVA), nonsynchronized nasal intermittent positive pressure ventilation (NIPPV), and nasal continuous positive airway pressure (NCPAP) shortly after extubation. Hypothesis Types of noninvasive pressure support and the presence of synchronization may affect cardiorespiratory parameters. Study Design Randomized crossover trial. Patient–Subject Selection Infants with birth weight (BW) 1250 g or under, undergoing their first planned extubation were randomly assigned to all three modes using a computer‐generated sequence. Methodology Electrocardiogram and electrical activity of the diaphragm (Edi) were recorded for 30 min on each mode. Analysis of heart rate variability (HRV), diaphragmatic activity (Edi area, breath area, amplitude, inspiratory and expiratory times), and respiratory variability were compared between modes. Results Twenty‐three infants had full data recordings and analysis: Median (IQR) gestational age = 25.9 weeks (25.2–26.4), BW = 760 g (595–900), and postnatal age 7 (4–19) days. There were no differences in HRV between modes. A significantly reduced Edi area and breath amplitude, and increased coefficient of variation (CV) of breath amplitude were observed during NIV‐NAVA and NIPPV compared to NCPAP. A higher proportion of assisted breaths (99% vs. 51%; p < .001) provided a higher mean airway pressure (MAP; 9.4 vs. 8.2 cmH 2 O; p = .002) with lower peak inflation pressures (PIPs; 14 vs. 16 cmH 2 O; p < .001) during NIV‐NAVA compared to NIPPV. Conclusions NIV‐NAVA and NIPPV applied shortly after extubation were associated with lower respiratory efforts and higher respiratory variability. These effects were more evident for NIV‐NAVA where optimal patient–ventilator synchronization provided a higher MAP with lower PIPs.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".