Optimizing management of chronic pulmonary hypertension in preterm infants: strategies for a complex population
Bibliographic record
Abstract
PURPOSE OF REVIEW: Pulmonary hypertension (PH) is commonly observed in premature infants with bronchopulmonary dysplasia (BPD) and is associated with poor outcomes and increased mortality. This review explores the management of this intricate condition of the pulmonary vasculature, which exhibits heterogeneous effects and may involve both arterial and postcapillary components. RECENT FINDINGS: Current management of BPD-PH should focus on optimizing ventilatory support, which involves treatment of underlying lung disease, transitioning to a chronic phase ventilation strategy and evaluation of the airway. Data on management is limited to observational studies. Diuretics are considered a part of the initial management, particularly in infants with right ventricular dilation. In many cases, pulmonary vasodilator therapy is required to induce pulmonary arterial vasodilation, reduce right ventricular strain, and prevent coronary ischemia and heart failure. Echocardiography plays a pivotal role in guiding treatment decisions and monitoring disease progression. SUMMARY: BPD-PH confers a heightened risk of mortality and long-term cardio-respiratory adverse outcomes. Echocardiography has been advocated for screening, while catheterization allows for confirmation in select more complex cases. Successful management of BPD-PH requires a multidisciplinary approach, focusing on optimizing BPD treatment and addressing underlying pathologies.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".