Non-Invasive High Frequency Oscillatory Ventilation Versus Nasal Continuous Positive Airway Pressure in Transient Tachypnea of the Newborn: A Randomized Controlled Trial
Bibliographic record
Abstract
Introduction: Nasal continuous positive airway pressure (nCPAP) is one of the most commonly used non-invasive ventilation modes in neonates with transient tachypnea of the newborn (TTN). Non-invasive high frequency oscillatory ventilation (nHFOV) is an non-invasive ventilation mode that has been increasingly used in neonatal respiratory disorders. Based on the unique physiologic advantages that nHFOV offers, we hypothesized that nHFOV might result in a decrease in the duration of non-invasive positive pressure ventilation in neonates with TTN. Methods: Late preterm and term infants > 34 weeks’ gestation were included in the study. Infants were randomized into nHFOV or nCPAP groups. Treatment was started with standard settings in both groups. Infants who met treatment failure criteria were switched to nasal intermittent mandatory ventilation for further positive-pressure support. Results: Total of 60 infants were included in the study. Thirty of these infants were included in the nHFOV group and 30 were included in the nCPAP group. There was no difference between the groups in terms of duration of positive-pressure ventilation; however, it showed a decreasing trend in the nHFOV group (21 hours, IQR [16-68] vs 15 hours, IQR [11-33]; p=0.09). After adjusting for confounders, the nHFOV group had a shorter duration of positive-pressure ventilation compared with the nCPAP group (mean difference: 16.3 hours; 95% confidence interval [CI], 0.7 to 31.9; p=0.04). Conclusion: Non-invasive high frequency oscillatory ventilation can shorten the duration of positive-pressure ventilation and supplemental oxygen in TTN.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".