Application of Neonatologist Performed Echocardiography in the assessment and management of persistent pulmonary hypertension of the newborn
Bibliographic record
Abstract
Pulmonary hypertension contributes to morbidity and mortality in both the term newborn infant, referred to as persistent pulmonary hypertension of the newborn (PPHN), and the premature infant, in the setting of abnormal pulmonary vasculature development and arrested growth. In the term infant, PPHN is characterized by the failure of the physiological postnatal decrease in pulmonary vascular resistance that results in impaired oxygenation, right ventricular failure, and pulmonary-to-systemic shunting. The pulmonary vasculature is either maladapted, maldeveloped, or underdeveloped. In the premature infant, the mechanisms are similar in that the early onset pulmonary hypertension (PH) is due to pulmonary vascular immaturity and its underdevelopment, while late onset PH is due to the maladaptation of the pulmonary circulation that is seen with severe bronchopulmonary dysplasia. This may lead to cor-pulmonale if left undiagnosed and untreated. Neonatologist performed echocardiography (NPE) should be considered in any preterm or term neonate that presents with risk factors suggesting PPHN. In this review, we discuss the risk factors for PPHN in term and preterm infants, the etiologies, and the pathophysiological mechanisms as they relate to growth and development of the pulmonary vasculature. We explore the applications of NPE techniques that aid in the correct diagnostic and pathophysiological assessment of the most common neonatal etiologies of PPHN and provide guidelines for using these techniques to optimize the management of the neonate with PPHN.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".