Early Prediction of Hypoxic‐Ischemic Brain Injury by a New Panel of Biomarkers in a Population of Term Newborns
Bibliographic record
Abstract
This research paper is aimed at evaluating the predictive role of a default panel of oxidative stress (OS) biomarkers for the early identification of infants at high risk of HIE and their validation through the correlation with MRI findings. A multicenter prospective observational study was performed between March 2012 and April 2015 in two European tertiary NICUs. Eighty‐four term infants at risk for HIE (pH < 7, BE < −13 mmol/L, and 5 ′ Apgar < 5) were enrolled. Three were excluded for chromosomal abnormalities and one due to lack of blood samples. The final population was divided according to the severity of perinatal hypoxia into 2 groups: mild/moderate HIE and severe HIE. Advanced oxidation protein products (AOPP), non‐protein‐bound iron (NPBI), and F2‐isoprostanes (F2‐IsoPs) were measured in blood samples at P1 (4–6 hours), P2 (24–72 hours), and P3 (5 days), in both groups. MRIs were scored for the severity of brain injury, using a modified Barkovich score. The mean GA was 39.8 weeks (SD 1.4) and the mean birth weight 3538 grams (SD 660); 37 were females and 43 males. Significantly lower 5 ′ Apgar score, pH, and BE and higher Thompson score were found in group II compared to group I at birth. Group II showed significantly higher AOPP and NPBI levels than group I (mean (SD) AOPP: 15.7 (15.5) versus 34.1 (39.2), p = 0.033; NPBI 1.1 (2.5) versus 3.9 (4.4), p = 0.013) soon after birth (P1). No differences were observed in OS biomarker levels between the two groups at P2 and P3. A regression model, including adjustment for hypothermia treatment, gender, and time after birth, showed that AOPP levels and male gender were both risk factors for higher brain damage scores (AOPP: OR 3.6, 95% CI (1.1–12.2) and gender: OR 5.6, 95% CI (1.2–25.7), resp.). Newborns with severe asphyxia showed higher OS than those with mild asphyxia at birth. AOPP are significantly associated with the severity of brain injury assessed by MRI, especially in males.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 teacher head, 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".