Management of Hypotension in Preterm Infants (The HIP Trial): A Randomised Controlled Trial of Hypotension Management in Extremely Low Gestational Age Newborns
Bibliographic record
Abstract
BACKGROUND: Extremely preterm babies (delivered at <28 completed weeks of gestation) are frequently diagnosed with hypotension and treated with inotropic and pressor drugs in the immediate postnatal period. Dopamine is the most commonly used first-line drug. Babies who are treated for hypotension more frequently sustain brain injury, have long-term disability or die compared to those who are not. Despite the widespread use of drugs to treat hypotension in such infants, evidence for efficacy is lacking, and the effect of these agents on long-term outcomes is unknown. HYPOTHESIS: In extremely preterm babies, restricting the use of dopamine when mean blood pressure (BP) values fall below a nominal threshold and using clinical criteria to determine escalation of support ('restricted' approach) will result in improved neonatal and longer-term developmental outcomes. RESEARCH PLAN: In an international multi-centre randomised trial, 830 infants born at <28 weeks of gestation, and within 72 h of birth, will be allocated to 1 of 2 alternative treatment options (dopamine vs. restricted approach) to determine the better strategy for the management of BP, using a conventional threshold to commence treatment. The first co-primary outcome of survival without brain injury will be determined at 36 weeks' postmenstrual age and the second co-primary outcome (survival without neurodevelopmental disability) will be assessed at 2 years of age, corrected for prematurity. DISCUSSION: It is essential that appropriately designed trials be performed to define the most appropriate management strategies for managing low BP in extremely preterm babies.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".