Illness Severity Predicts Death and Brain Injury in Asphyxiated Newborns Treated with Hypothermia
Bibliographic record
Abstract
Objective To determine if illness severity during the first days of life predicts adverse outcome in asphyxiated newborns treated with hypothermia. Study Design We conducted a retrospective cohort study of asphyxiated newborns treated with hypothermia. Illness severity was calculated daily during the first 4 days of life using the Score for Neonatal Acute Physiology II (SNAP-II score). Adverse outcome (death and/or brain injury) was recorded. Differences in SNAP-II scores between the newborns with and without adverse outcome were assessed. Result 214 newborns were treated with hypothermia. The average SNAP-II score over the first 4 days of life was significantly worse in newborns developing adverse outcome. The average SNAP-II score was an excellent predictor of death (area under the curve [AUC]: 0.93; p < 0.001) and a fair predictor of adverse outcome (AUC: 0.73; p < 0.001). The average SNAP-II score remained a significant predictor of adverse outcome (odds ratio [95% confidence interval]: 1.08 [1.04–1.12]; p < 0.001), after adjusting for baseline characteristics, degree of initial asphyxial event, and initial severity of encephalopathy. Conclusion In asphyxiated newborns treated with hypothermia, not only the initial asphyxial event but also the illness severity during the first days of life was a significant predictor of death or brain injury.
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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".