Less Invasive Surfactant Administration in Extremely Preterm Infants: Impact on Mortality and Morbidity
Bibliographic record
Abstract
BACKGROUND: A new mode of surfactant administration without intubation - less invasive surfactant administration (LISA) - has recently been described for premature infants. OBJECTIVE: We report single-center outcome data of extremely premature infants who have been managed by LISA in our department. Mortality and morbidity rates of the cohort were compared to historical controls from our own center and to data of the Vermont-Oxford Neonatal Network (VONN). PATIENTS AND METHODS: All infants born at 23-27 weeks' gestational age during 01/2009 and 06/2011 (n = 224) were managed by LISA and included in the study group. RESULTS: LISA was tolerated by 94% of all infants. 68% of infants stayed on continuous positive airway pressure on day 3. The rate of mechanical ventilation was 35% within the first week and 59% during the entire hospital stay. Compared to historical controls, we found significantly higher survival rates (75.8 vs. 64.1%) and significantly less intraventricular hemorrhage (IVH) (28.1 vs. 45.9%), severe IVH (13.1 vs. 23.9%) and cystic periventricular leukomalacia (1.2 vs. 5.6%); only persistent ductus arteriousus (PDA) (74.7 vs. 52.6%) and retinopathy of prematurity (ROP) (40.5 vs. 21.1%) occurred significantly more often. Compared to VONN data, we found significantly less chronic lung disease (20.6 vs. 46.4%), severe cerebral lesions (IVH 3/4 + cystic PVL; 9.4 vs. 16.1%) and ROP (all grades) (40.5 vs. 56.5%); only PDA (74.7 vs. 63.1%) and severe ROP (> grade 2) (24.1 vs. 14.1%) occurred significantly more often in our cohort. CONCLUSION: Surfactant can be effectively and safely delivered via LISA and this is associated with low rates of mechanical ventilation and various adverse outcomes in extremely premature infants.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".