52: Does Intratracheal Administration of Surfactant Using Thin Catheter Compared with Insure Technique Reduce the Outcome of Death or BPD
Bibliographic record
Abstract
Traditionally, preterm infants with respiratory distress syndrome (RDS) were intubated to receive surfactant, and many of them were left on mechanical ventilation for some time. With the advent and benefits of non-invasive respiratory support has come the need of using less invasive methods for administering surfactant. InSurE (Intubation, Surfactant administration, and Extubation) technique is widely used for surfactant delivery in preterm infants with RDS, however it still implies intubation and positive pressure ventilation. Less invasive surfactant administration (LISA) into trachea using a thin catheter in spontaneous breathing infants while on CPAP has been described as an alternative method to provide surfactant without the need of intubation. To conduct a systematic review of randomized trials (RCTs) comparing LISA with InSurE in preterm infants with RDS for clinical outcomes. We searched MEDLINE, CENTRAL and EMBASE (until September 17, 2014). Additional citations were identified from trial registries, conference proceedings and bibliography of selected articles. Included studies were RCTs, comparing LISA with InSurE, in preterm infants with RDS, and reporting any of the prespecified clinical outcomes during primary hospitalization. No language restrictions were applied. Data was extracted independently by two reviewers. Four RCTs, enrolling 767 infants, were included. LISA resulted in a significant reduction in the composite outcome of death or BPD at 36 weeks (RR 0.74 [95% CI 0.58–095], P=0.02) (Figure 1), mechanical ventilation within first 72 h after birth (RR 0.71 [95% CI 0.51–0.98], P=0.04) Results of the other outcomes are presented in Table 1. LISA, compared with InSurE, resulted in a reduction in the composite outcome of death or BPD at 36 weeks and less mechanical ventilation in first 72 h after birth.
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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 | 0.006 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.012 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".