Hyperglycemia associated with acute brain injury in neonatal encephalopathy
Bibliographic record
Abstract
OBJECTIVE: To identify how alterations in glucose levels are associated with regional brain injury in neonatal encephalopathy. METHODS: This was a prospective cohort study of 102 newborns with neonatal encephalopathy, with continuous glucose monitoring for 72 h. 97 (95%) completed 72 h of therapeutic hypothermia. Brain imaging around day 5 of life included diffusion tensor imaging and MR spectroscopy. Regions of interest were placed for both DTI and MR spectroscopy, and tractography of the optic radiation and corticospinal tract were evaluated. Linear regression models related each MR metric with minimum and maximum glucose values during each day of life, adjusting for 5-minute Apgar scores and umbilical artery pH. RESULTS: Higher maximum glucose levels on the first day of life were associated with widespread changes in mean diffusivity in the anterior and posterior white matter, splenium of the corpus callosum, lentiform nucleus, pulvinar nucleus of the thalamus, posterior limb of the internal capsule, and optic radiations, thus including regions traditionally associated with hypoxia-ischemia or hypoglycemia. No associations were found between lower minimum glucose levels and DTI changes in any regions tested, or between glucose levels and MR spectroscopy. CONCLUSIONS: In this cohort of neonatal encephalopathy with therapeutic hypothermia, higher maximal glucose on the first day of life was associated with widespread microstructural changes, but lower minimum glucose levels were not associated with changes in any of the regions tested. Long-term follow-up will determine if imaging findings translate to long-term outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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 | 0.000 | 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".