Neonatal hypertension: concerns within and beyond the neonatal intensive care unit
Bibliographic record
Abstract
Neonatal hypertension occurs in 1%-2% of neonates in the neonatal intensive care unit (NICU) although may be underdiagnosed. Blood pressure values in premature neonates change rapidly in the first days and weeks of life which may make it more difficult to recognize abnormal blood pressure values. In addition, the proper blood pressure measurement technique must be used to ensure the accuracy of the measured values as most blood pressure devices are not manufactured specifically for this population. In premature neonates, the cause of the hypertension is most commonly related to prematurity-associated complications or management while in term neonates is more likely to be due to an underlying condition. Both oral and intravenous antihypertensive medications can be used in neonates to treat high blood pressure although none are approved for use in this population by regulatory agencies. The natural history of most neonatal hypertension is that it resolves over the first year or two of life. Of concern are the various neonatal risk factors for later cardiovascular and kidney disease that are present in most NICU graduates. Prematurity increases the risk of adulthood hypertension while intrauterine growth restriction may even lead to hypertension during childhood. From neonates through to adulthood NICU graduates, this review will cover each of these topics in more detail and highlight the aspects of blood pressure management that are established while also highlighting where knowledge gaps exist.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".