Hypothermia for Neonatal Hypoxic Ischemic Encephalopathy
Bibliographic record
Abstract
OBJECTIVE: To establish the evidence of therapeutic hypothermia for newborns with hypoxic ischemic encephalopathy(HIE). DATA SOURCES: Cochrane Central Register of Controlled Trials, Oxford Database of Perinatal Trials, MEDLINE, EMBASE, and previous reviews. STUDY SELECTION: Randomized controlled trials that compared therapeutic hypothermia to normothermia for newborns with HIE. INTERVENTION: Therapeutic hypothermia. MAIN OUTCOME MEASURES: Death or major neurodevelopmental disability at 18 months. RESULTS: Seven trials including 1214 newborns were identified. Therapeutic hypothermia resulted in a reduction in the risk of death or major neurodevelopmental disability(risk ratio [RR], 0.76; 95% CI, 0.69-0.84) and increase in the rate of survival with normal neurological function (1.63; 1.36-1.95) at age 18 months. Hypothermia reduced the risk of death or major neurodevelopmental disability at age 18 months in newborns with moderate HIE (RR, 0.67; 95% CI, 0.56-0.81) and in newborns with severe HIE (0.83; 0.74-0.92). Both total body cooling and selective head cooling resulted in reduction in the risk of death or major neurodevelopmental disability(RR, 0.75; 95% CI, 0.66-0.85 and 0.77; 0.65-0.93,respectively). CONCLUSION: Hypothermia improves survival and neurodevelopment in newborns with moderate to severe HIE.Total body cooling and selective head cooling are effective methods in treating newborns with HIE. Clinicians should consider offering therapeutic hypothermia as part of routine clinical care to these newborns.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".