Fetal Tracheal Occlusion for the Treatment of Congenital Diaphragmatic Hernia
Bibliographic record
Abstract
BACKGROUND: Congenital diaphragmatic hernia (CDH) continues to be associated with significant mortality and morbidity rates despite advances in neonatal care. Fetal intervention for CDH has been studied for 25 years. After initial difficulties encountered with open fetal repair, attention has turned to tracheal occlusion (TO) as a method to correct pulmonary hypoplasia before birth. This article reviews our contribution to this field of research and outlines the current status of this treatment modality. MATERIALS AND METHODS: Using the fetal lamb model, we have studied the effects of fetal TO on tracheal fluid pressure, lung growth and type II pneumocyte maturation, and surfactant production. We developed a minimally invasive and reversible technique of TO, using a detachable balloon placed using single-port tracheoscopy. We examined differential lung growth, structural maturation, pulmonary artery remodeling, and lung function during an 8-h resuscitation period in lambs, comparing normal controls, lambs with a surgically created CDH, those with CDH+TO, and those with CDH+TO and release of TO 1 week before delivery. We also studied the potential benefits of maternal betamethasone administration and the administration of surfactant at birth. Using a neonatal piglet model, we examined the effect of postnatal pulmonary distension with perfluorocarbon on lung growth. More recently, we turned to the rat nitrofen-induced CDH model to study the effects of TO on bronchial branching and some molecular markers of lung growth (Shh and LGL1). CONCLUSIONS: Fetal TO is being used to treat human CDH, but its application remains limited by the absence of reliable and widely reproducible prenatal prognostic criteria. A better understanding of the molecular events guiding the lung growth seen with TO may help to refine its use in humans.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 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".