Changes in Respiratory Management and the Impact on Bronchopulmonary Dysplasia
Bibliographic record
Abstract
Objective: Non-invasive respiratory support has reduced the need for mechanical ventilation and surfactant administration in very premature neonates. We sought to determine how the increased use of non-invasive ventilation and less surfactant instillation has impacted the development of bronchopulmonary dysplasia (BPD) and compared BPD outcome applying four currently used definitions. Study Design: This is a retrospective, single center cohort study of neonates born at less than 28 weeks gestation between 2010 and 2018. A respiratory practice change (less surfactant and more non-invasive ventilation) occurred in 2014 following participation in the SUPPORT trial. Therefore, patients were divided into 2 epochs to compare postnatal respiratory and clinical course and BPD outcomes across four currently relevant definitions (VON, NICHD, Canadian, NRN). Results: Clinical and demographic variables were similar between epochs. Despite significant differences in maternal and infant characteristics and clinical course, the incidence of BPD was not significantly different between the 2 epochs regardless of the BPD definition utilized. There was a wide range in the incidence of BPD depending on the definition used. Conclusions: Despite decreased use of invasive mechanical ventilation and surfactant administration between the two epochs, the incidence of BPD did not change and there was wide variation depending on the definition used. A better understanding of the risk factors associated with BPD and a consensus definition is urgently needed in order to facilitate the conduct of clinical trials and the development of novel therapeutic interventions to improve outcome.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".