Preoperative Cerebral and Renal Saturations in Neonates with Congenital Heart Defects: A Prospective Cohort Study
Bibliographic record
Abstract
Introduction: Congenital heart disease (CHD) is one of the most common birth defects. Cerebral (cStO2) and renal (rStO2) saturations measured by near-infrared spectroscopy (NIRS) and the corresponding fractional tissue oxygen extraction (FTOE) during the first week of life in neonates with CHD are described comparing those with and without diastolic steal. Methods: Single-center prospective cohort study (Montreal Children’s Hospital, Montreal, QC, Canada) was conducted, including neonates >34 weeks with CHD without chromosomal anomalies. CStO2/rStO2 was monitored from enrollment until day 7 of life. FTOE was calculated using systemic saturation (SpO2) as [SpO2 − (cStO2 or rStO2)]/SpO2. Daily echocardiography was performed during the monitoring period. Random mixed-effects models were constructed to assess the association between NIRS/FTOE and the presence of retrograde postductal aortic flow on last available echocardiography. Results: Among 49 included neonates, 27 (55%) exhibited retrograde flow in the postductal aorta on the last day of monitoring. Prostaglandin exposure was 100% in the retrograde group vs. 27% in the non-retrograde group. CStO2/rStO2 progressively declined in neonates with CHD over the first week of life. Retrograde aortic flow was associated with negative cStO2 (β = −9.1%, 95% CI [−14.3; −3.8]) and rStO2 (β = −8.4%, 95% CI [−14.5; −2.3]). Cerebral FTOE was lower in the non-retrograde group, while renal FTOE was similar between groups. Conclusion: During the first week of life, neonates with CHD who displayed retrograde aortic flow exhibited lower cStO2 and rStO2 as well as higher cerebral FTOE. Future studies should evaluate whether these markers in neonates with CHD are modifiable factors that could influence cerebral or renal injury when addressed.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".