Neonatal Watershed Brain Injury on Magnetic Resonance Imaging Correlates With Verbal IQ at 4 Years
Bibliographic record
Abstract
OBJECTIVE: We have previously described patterns of neonatal brain injury that correlate with global cognitive and motor outcomes. We now examine, in survivors of neonatal encephalopathy (presumed secondary to hypoxia-ischemia) without functional motor deficits, whether the severity and neuroanatomical involvement on neonatal MRI are associated with domain-specific cognitive outcomes, verbal and performance IQ, at 4 years of age. METHODS: In this prospective study, neonatal MRIs of 81 term infants with neonatal encephalopathy were scored for degree of injury in 2 common patterns: watershed distribution and basal ganglia distribution. Follow-up evaluation at 4 years of age by examiners blinded to clinical history and MRIs included a 5-point neuromotor score and the Wechsler Preschool and Primary Scale of Intelligence-Revised. In 64 subjects with no functional motor impairment, test of trend was used to examine the association of ordered watershed-distribution and basal ganglia-distribution MRI scores with mean verbal and performance IQ. RESULTS: Lower verbal and performance IQs were seen with increasing degree of injury on both watershed-distribution and basal ganglia-distribution scales in univariate analyses. When each MRI pattern score was adjusted for the other, only the association of decreasing verbal IQ with increasing watershed-distribution injury remained significant. A suggestion of decreasing verbal IQ with increasing basal ganglia-distribution injury was also seen in the multivariate model, whereas no association was seen between performance IQ and severity of injury in either MRI pattern. CONCLUSIONS: In survivors of neonatal encephalopathy without functional motor deficits at 4 years of age, an increasing severity of watershed-distribution injury is associated with more impaired language-related abilities.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".