Surfactant delivery via thin catheter in preterm infants: A systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVE: Surfactant administration via a thin catheter (STC) is an alternative to surfactant administration post endotracheal intubation in preterm infants with respiratory distress syndrome (RDS); however, the benefits particularly in infants <29 weeks' gestation and the neurodevelopmental outcomes remain unclear. Thus, our objective was to systematically review and meta-analyze the efficacy and safety of STC compared to intubation for surfactant or nasal continuous positive airway pressure (nCPAP) in preterm infants with RDS. METHODS: Medical databases were searched until December 2022 for randomized controlled trials (RCTs) assessing STC compared to controls that included intubation for surfactant or nCPAP in preterm infants with RDS. The primary outcome was bronchopulmonary dysplasia (BPD) at 36 weeks gestation in survivors. Subgroup analysis was conducted comparing STC to controls in infants < 29 weeks' gestation. The Cochrane risk of bias (ROB) tool was used and certainty of evidence (CoE) was rated according to GRADE. RESULTS: Twenty-six RCTs of 3349 preterm infants, in which half of the studies had low risk of bias, were included. STC decreased the risk of BPD in survivors compared to controls (17 RCTs; N = 2408; relative risk (RR) = 0.66; 95% confidence interval (CI) 0.51 to 0.85; number needed to treat for an additional beneficial outcome (NNTB) = 13; CoE: moderate). In infants < 29 weeks' gestation, STC significantly reduced the risk of BPD compared to controls (6 RCTs, N = 980; RR 0.63; 95% CI 0.47 to 0.85; NNTB = 8; CoE: moderate). CONCLUSIONS: Compared to controls, STC may be a more efficacious and safe method of surfactant delivery in preterm infants with RDS, including infants < 29 weeks' gestation.
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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 | 0.009 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.028 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".