Admission Systolic Blood Pressure and Outcomes in Preterm Infants of ≤ 26 Weeks' Gestation
Bibliographic record
Abstract
Objective To examine the relationship between admission systolic blood pressure (SBP) and adverse neonatal outcomes. Specifically, we aimed to identify the optimal SBP that is associated with the lowest rates of adverse outcomes in extremely preterm infants of ≤ 26 weeks' gestation. Methods In this retrospective study, inborn neonates born at ≤ 26 weeks' gestational age and admitted to tertiary neonatal units participating in the Canadian Neonatal Network between 2003 and 2009 were included. The primary outcome was early mortality (≤ 7 days). Secondary outcomes included severe brain injury, late mortality, and a composite outcome defined as early mortality or severe brain injury. Nonlinear multivariable logistic regression models examined the relationship between admission SBP and outcomes. Results Admission SBP demonstrated a U-shaped relationship with early mortality, severe brain injury, and composite outcome after adjustment for confounders (p < 0.01). The lowest risks of early mortality, severe brain injury, and composite outcome occurred at admission SBPs of 51, 55, and 54 mm Hg, respectively. Conclusion In extremely preterm infants of ≤ 26 weeks' gestational age, the relationship between admission SBP, and early mortality and severe brain injury was “U-shaped.” The optimal admission SBP associated with lowest rates of adverse outcome was between 51 and 55 mm Hg.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".