Persistent pulmonary hypertension and short-term neurological outcomes in infants with moderate to severe hypoxic ischemic encephalopathy
Bibliographic record
Abstract
BACKGROUND: Our aim was to investigate the relationship between persistent pulmonary hypertension of the newborn (PPHN), short-term brain injury or death, and clinical parameters in infants with moderate to severe hypoxic ischemic encephalopathy (HIE). METHODS: Retrospective single-center cohort study of 274 HIE infants, 230 underwent Therapeutic Hypothermia (TH). Primary outcome was severe HIE brain injury on MRI and/or death within the first month of life in relation to presence and severity of PPHN (clinical or echocardiographic). Secondary outcomes were HIE brain injury pattern, abnormal electroencephalogram (EEG), seizures, clinical, and laboratory differences. A logistic regression model was performed to evaluate PPHN presence and severity as risk factor for brain injury or death. RESULTS: The combined outcome of severe brain injury or death was higher in the clinical PPHN group vs non-PPHN (32.6 vs 22.8%, p = 0.014). There was no difference in brain injury, seizure burden or EEG abnormalities associated with PPHN, despite those with PPHN being sicker with higher ventilation needs and worse laboratory values than those without. Mortality had a strong correlation with echocardiographic PPHN with the highest incidence in severe (36%) vs moderate (7.7%) vs mild PPHN (10%, p = 0.002). Highest mortality had those with 'early exit' who did not complete 72 hours of TH (71.4%). CONCLUSIONS: In infants with HIE, PPHN was not associated with increased risk of brain injury as evident on MRI, nor seizure burden, despite being sicker with worse laboratory values. However, mortality rates were higher the worse the PPHN, especially with early exit from TH.
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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 | 0.002 |
| 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 | 0.000 |
| 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".