Relationship between cerebral oxygenation, cardiac output, and blood pressure during transitional period in extremely low gestational age neonates
Bibliographic record
Abstract
Objective To describe the relationship between cerebral oxygenation, cardiac output, arterial blood pressure (BP), and cerebral blood flow velocity in extremely low gestational age neonates (ELGANs) during transition. Methods This study comprises secondary analyses from a prospective observational study conducted at a tertiary Neonatal Intensive Care Unit. Recruited ELGANs underwent cerebral saturation (CrSO2) monitoring and serial echocardiography during 72 h from birth. Correlative analyses of CrSO2 and cerebral fractional tissue oxygen extraction (CFTOE) with left (LVO) and right ventricular output (RVO), superior vena cava (SVC) flow, middle cerebral artery blood flow mean velocity (MCA.MV), systolic (SBP), diastolic (DBP), and mean (MBP) BP were conducted. Results Fifty ELGANs with median (range) gestational age of 25.9 (23.1–27.9) weeks were recruited. Echocardiography was performed sequentially at a median (range) age 5.0 (3.8–6.6), 17.3 (15.4–19.4), 31.0 (27.0–34.1), and 53.7 (49.3–58.3) hours. RVO, LVO, CrSO2, and SBP increased over time but no changes in MBP, DBP, CFTOE, MCA.MV or SVC flow were noted. A weak correlation was identified between CrSO2 and SBP (r2 = 0.11, p = 0.047) and MBP (r2 = 0.12, p = 0.04) at 17.3 (15.4–19.4) hours. No correlation of either CrSO2 or CFTOE with any measures of blood flow was identified. Conclusion There is a weak correlation between measures of cardiac output, BP, and MCA.MV with both CrSO2 and CFTOE in ELGANs during transition. Whether this finding suggests intact cerebral autoregulation requires prospective evaluation in a cohort of sick ELGANs.
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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 | 0.000 | 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) | 0.000 | 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".