DOES THE TIMING OF INITIATION OF THERAPEUTIC HYPOTHERMIA INFLUENCE MRI FINDINGS AND OUTCOMES IN ENCEPHALOPATHIC BABIES?
Bibliographic record
Abstract
Abstract BACKGROUND Therapeutic hypothermia (TH), initiated < 6h of life, is the standard treatment for infants with moderate to severe hypoxic ischemic encephalopathy (HIE). While preclinical studies show that TH is more effective when started early, little clinical data exists. OBJECTIVES The objectives of our study are to examine the effect of early vs. late TH on the severity and pattern of brain injury on MRI and on the neurodevelopmental outcomes. DESIGN/METHODS This retrospective cohort included infants with HIE treated with TH at a level three neonatal intensive care unit between 2009 and 2016. Babies were grouped into: early cooling (TH started ≤ 180 minutes of life) or late cooling (TH started > 180 minutes of life). Two radiologists evaluated the severity and pattern of brain injury on MRI using both NICHD and Barkovich scoring system. Neurodevelopmental outcomes were evaluated at 4, 10, 18 and 48 months. RESULTS Ninety-four patients (median gestational age 39 weeks; median birth weight 3.3 kg) were included in the study, 55 in the early cooling and 39 in the late cooling group. The early cooling group included more patients with severe HIE (32.7% vs 10.3%, p=0.01). No difference was observed between the 2 groups in regard to the pattern and severity of brain injury. In the late cooling group, there was a trend toward more severe watershed (WS) injury (WS score ≥3) (30.6% vs 17%, p=0.19) and more moderate to severe brain injury (33.3% vs 23.4%, p=0.33). There was no difference in the neurodevelopmental outcomes between the 2 groups. CONCLUSION TH initiated early (before 180 minutes of life) was neither associated with a difference in brain injury on MRI nor better neurodevelopmental outcomes. Despite having more infants with severe HIE in the early cooling group, there was a trend toward less significant brain injury in this group.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".