Effects of heliox and non-invasive neurally adjusted ventilatory assist (NIV-NAVA) in preterm infants
Bibliographic record
Abstract
Due to its unique properties, helium-oxygen (heliox) mixtures may provide benefits during non-invasive ventilation, however, knowledge regarding the effects of such therapy in premature infants is limited. This is the first report of heliox non-invasive neurally adjusted ventilatory assist (NIV-NAVA) ventilation applied in neonates born ≤ 32 weeks gestational age. After baseline NIV-NAVA ventilation with a standard mixture of air and oxygen, heliox was introduced for 3 h, followed by 3 h of air-oxygen. Heart rate, peripheral capillary oxygen saturation, cerebral oxygenation, electrical activity of the diaphragm (Edi) and selected ventilatory parameters (e.g., respiratory rate, peak inspiratory pressure) were continuously monitored. We found that application of heliox NIV-NAVA in preterm infants was feasible and associated with a prompt and significant decrease of Edi suggesting reduced respiratory effort, while all other parameters were stable throughout the study, and had similar values during heliox and air-oxygen ventilation. This therapy may potentially enhance the efficacy of non-invasive respiratory support in preterm neonates and reduce the number of infants progressing to ventilatory failure.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 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".