High Flow Nasal Cannula for Weaning Nasal Continuous Positive Airway Pressure in Preterm Infants: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
INTRODUCTION: The aim of this study was to systematically review the benefits and harms of using a high-flow nasal cannula (HFNC) for weaning continuous positive airway pressure (CPAP) support in preterm infants. METHODS: Cochrane Central, EMBASE, Medline, and Web of Science were searched from inception to July 15, 2023. Randomised clinical trials (RCTs) comparing weaning CPAP using HFNC versus weaning CPAP alone and evaluating predefined outcomes were included. Two authors independently performed data extraction and methodological quality assessment. Meta-analysis was conducted using a random-effects model, and the certainty of evidence was assessed using Cochrane GRADE. RESULTS: Among 843 identified records, seven RCTs involving 781 preterm infants were eligible for analysis. The meta-analysis found no statistically significant difference in duration of respiratory support when using HFNC for weaning compared to weaning CPAP alone (mean difference (95% confidence interval) 3.52 (-0.02, 7.05); 5 RCTs; participants = 488; I2 = 29%). The evidence certainty was downgraded to low due to study limitations and imprecision. There were no significant differences in secondary outcomes, except for a lower occurrence of nasal trauma with HFNC for weaning CPAP compared to weaning CPAP alone (relative risk (95% confidence interval) 0.61 (0.38, 0.99); 4 RCTs; participants = 335; I2 = 0%). The evidence certainty for the secondary outcomes was low to very low. CONCLUSION: Low certainty of evidence suggests using HFNC for weaning CPAP in preterm infants may not impact the duration of respiratory support. Caution is advised when considering HFNC for weaning CPAP, especially in extremely preterm infants, until additional supportive evidence on its safety becomes available.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".