Effectiveness and safety of nasal mask versus binasal prongs for providing continuous positive airway pressure in preterm infants—A systematic review and meta‐analysis
Bibliographic record
Abstract
Continuous positive airway pressure (CPAP) delivered via binasal prongs has been the cornerstone of respiratory management in preterm infants. Though effective, the use of binasal prongs is associated with nasal trauma, and CPAP failure. To overcome these issues, nasal masks are increasingly used to deliver CPAP in preterm infants. The aim was to conduct a systematic review of randomized controlled trials (RCTs) comparing nasal mask versus binasal prongs to deliver CPAP in preterm infants. Medline, Embase, Cochrane Central Register of Controlled Trials, Cumulative Index of Nursing, and Allied Health Literature, and E-abstracts from the Pediatric Academic Society meetings were searched in May 2017. All RCTs comparing nasal mask versus binasal prongs for delivering CPAP in preterm infants were included. Primary outcome was CPAP failure (need for mechanical ventilation within 72 h of initiating CPAP). Secondary outcomes included duration of CPAP, moderate to severe nasal trauma, any nasal trauma, pneumothorax, severe IVH, bronchopulmonary dysplasia at 36 weeks postmenstrual age, and mortality. Five RCTs with low risk of bias were included. Nasal mask significantly decreased the risk of CPAP failure (4 RCTs [N = 459]; relative risk [RR]: 0.63; 95% confidence interval [CI]: 0.45-0.88; P=.007; I2 = 0%, NNT: 9), and the incidence of moderate to severe nasal trauma (3 RCTs [N = 275], RR: 0.41; 95%CI, 0.24-0.72; P = 0.002; I2 = 74%, NNT: 6). Other outcomes did not differ significantly between the groups. Compared to binasal prongs, nasal mask may provide a safe and effective alternative by minimizing the risk of CPAP failure in preterm infants needing CPAP support.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.035 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".