Brain Perfusion in Asphyxiated Newborns Treated with Therapeutic Hypothermia
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Induced hypothermia is thought to work partly by mitigating reperfusion injury in asphyxiated term neonates. The purpose of this study was to assess brain perfusion in the first week of life in these neonates. MATERIALS AND METHODS: In this prospective cohort study, MR imaging and ASL-PI were used to assess brain perfusion in these neonates. We measured regional CBF values on 1-2 MR images obtained during the first week of life and compared these with values obtained in control term neonates. The same or later MR imaging scans were obtained to define the extent of brain injury. RESULTS: Eighteen asphyxiated and 4 control term neonates were enrolled; 11 asphyxiated neonates were treated with hypothermia. Those developing brain injury despite being treated with induced hypothermia usually displayed hypoperfusion on DOL 1 and then hyperperfusion on DOL 2-3 in brain areas subsequently exhibiting injury. Asphyxiated neonates not treated with hypothermia who developed brain injury also displayed hyperperfusion on DOL 1-6 in brain areas displaying injury. CONCLUSIONS: Our data show that ASL-PI may be useful for identifying asphyxiated neonates at risk of developing brain injury, whether or not hypothermia is administered. Because hypothermia for 72 hours may not prevent brain injury when hyperperfusion is found early in the course of neonatal hypoxic-ischemic encephalopathy, such neonates may be candidates for adjustments in their hypothermia therapy or for adjunctive neuroprotective therapies.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".