58 Relationship Between Early Laboratory Measures and Neurological Injury in Neonates Undergoing Therapeutic Hypothermia
Bibliographic record
Abstract
Abstract Primary Subject area Neonatal-Perinatal Medicine Background Hypoxic-ischemic encephalopathy (HIE) is a major contributor to morbidity and mortality. Therapeutic hypothermia (TH) is the standard of care for neonates with moderate to severe HIE. Brain magnetic resonance imaging (MRI) is the imaging modality of choice for confirmation of HIE, assessment of injury severity, and prognostication. Reliable, inexpensive and widely available laboratory measures for early identification of risk for neurological injury can play a critical role in the optimal management of neonatal HIE, especially in the resource-limited setting. Our study examined whether derangements in early routine laboratory measures (acid-base, haematological, metabolic) were worse in neonates with MRI findings of neurological injury. Objectives Primary objective: To evaluate the role of early laboratory measures in predicting neurological injury as detected by MRI at 72 hours. Secondary objective: To evaluate the role of early laboratory measures in predicting survival to NICU discharge in patients with HIE. Design/Methods This single-centre, retrospective cohort study included neonates ≥ 35 weeks gestation with moderate to severe HIE, who had undergone therapeutic hypothermia. Based on findings of brain MRI completed within 72 hours of life, our cohort was divided into 2 groups: neonates with, and without, evidence of neurological injury consistent with HIE. Baseline characteristics, as well as laboratory measures, were compared between groups, and a receiver operating characteristic (ROC) curve analysis was conducted to determine the cut-off for prediction of neurological injury based on the highest sensitivity and specificity values. Results 104 neonates were analyzed. Baseline characteristics (Table 1) were similar between both groups, except for cord venous pH and base excess (BE), which were significantly lower in the abnormal MRI group (p = 0.02). In bivariate analysis, pH (at 1 h of age, p = 0.027), BE (at 1 h, p = 0.001, and 6 h of age, p = 0.004), ionized calcium (at 6 h of age, p = 0.02), and platelets (at 1 h of age, p = 0.004) were significantly different in neonates with abnormal MRI. In ROC curve analysis, BE at 1 h of life was the best predictor of abnormal MRI (AUC = 0.71, p = 0.002), with a cut-off value of ≤ -14.95, sensitivity of 67% and specificity of 66% (Figure 1). Conclusion Among neonates with HIE undergoing TH, early laboratory measures such as acid-base status, ionized calcium, and platelet count were worse in neonates with abnormal MRI, in comparison to neonates with normal MRI. Base excess at 1 h of life is a good predictor of abnormal MRI. Future prospective studies to validate these findings are needed
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".