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Record W4413114409 · doi:10.1155/ijpe/8045343

Tiny Lungs, Big Decisions: A Meta‐Analysis Comparing Minimally Invasive Surfactant Therapy Versus Intubation–Surfactant–Extubation in Preterm Neonates With Respiratory Distress Syndrome

2025· article· en· W4413114409 on OpenAlexaboutno aff
Flavio Veintemilla‐Burgos, Geovanna Minchalo-Ochoa, Sebastian Balda, Ivo Diaz-Djevoich, Rodolfo Kronfle, Matias Panchana‐Lascano, Thomas Leone-Berry

Bibliographic record

VenueInternational Journal of Pediatrics · 2025
Typearticle
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineSurfactant therapyPulmonary surfactantIntubationRespiratory distressAnesthesiaTracheal intubationMeta-analysisAcute respiratory distressIntensive care medicineNeonatal respiratory distress syndromeRespiratory systemLungInternal medicineGestational agePregnancy

Abstract

fetched live from OpenAlex

Background: Neonatal respiratory distress syndrome (NRDS) is a leading cause of morbidity and mortality in preterm infants. Minimally invasive surfactant therapy (MIST) has emerged as a promising alternative to traditional approaches, aiming to reduce mechanical ventilation while maintaining spontaneous breathing. This meta‐analysis compares the efficacy and safety of MIST versus the intubation–surfactant–extubation (INSURE) method in preterm neonates with NRDS. Methods: We searched PubMed, Scopus, and Embase for eligible studies. Two independent reviewers screened studies via the Rayyan platform. We included randomized controlled trials and observational cohorts of preterm neonates (< 37 weeks) with NRDS requiring surfactant therapy, comparing MIST and INSURE. Data extraction included study characteristics, demographics, and clinical outcomes. Risk of bias was assessed using the Newcastle–Ottawa Scale and Cochrane tools. Risk ratios (RRs) and mean differences (MDs) with 95% confidence intervals (CIs) were calculated using a random‐effects model. Heterogeneity was evaluated via I 2 statistics. Results: Then, 17 studies ( n = 1931 neonates; MIST: 913, INSURE: 932) were included. Baseline characteristics were similar between groups. Mortality did not differ significantly (RR 0.62; 95% CI 0.38–1.01; p = 0.05). MIST was associated with reduced risks of bronchopulmonary dysplasia (RR 0.59; 95% CI 0.45–0.76), intraventricular hemorrhage (RR 0.66; 95% CI 0.48–0.92), patent ductus arteriosus (RR 0.75; 95% CI 0.61–0.93), and pneumothorax (RR 0.54; 95% CI 0.34–0.87). Rates of pulmonary hemorrhage and surfactant reflux were comparable. MIST also resulted in shorter oxygen day requirements (MD −2.45; p = 0.04) and need for mechanical ventilation (RR 0.54; p = 0.002). Duration of ventilation and NICU showed no significant differences. Conclusion: MIST proved to be a safer and more effective alternative to INSURE in preterm infants with NRDS, reducing several complications and mechanical ventilation needs. These findings highlight MIST’s potential as a preferred approach, warranting further research to support broader implementation.

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 imitation

Not 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.

metaresearch head score (Codex)0.020
metaresearch head score (Gemma)0.041
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.041
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0180.056
Bibliometrics0.0040.004
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.109
GPT teacher head0.390
Teacher spread0.281 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2025
Admission routes1
Has abstractyes

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