Magnetic resonance imaging findings and neurodevelopmental outcomes in neonates with urea-cycle defects
Bibliographic record
Abstract
The urea-cycle functions to facilitate ammonia excretion, a disruption of which results in the accumulation of toxic metabolites. The neurological outcome of neonatal-onset urea-cycle defects (UCDs) is poor, and there are no good predictors of prognosis beyond ammonia levels at presentation. The role of neuroimaging in the prognosis of neonatal-onset UCDs is unclear. We describe the magnetic resonance imaging (MRI) findings of two patients with neonatal-onset UCDs (argininosuccinic aciduria and citrullinemia) at presentation and at 2-year follow-up, and present a review of the literature on neuroimaging in this age-group. We observed two potentially significant distinct patterns of cerebral involvement on MRI: (1) a central and focal pattern of involvement limited to the basal ganglia, perirolandic regions, and internal capsule; and (2) diffuse involvement of the cerebral cortex, internal capsule, basal ganglia, and variably thalami and brain stem. Patients with more diffuse findings tended to have higher serum glutamine peaks and worse neurological outcomes, while those with central involvement, aggressive acute management, and early liver transplantation tended to have better outcomes. We propose that MRI imaging of the brain may have prognostic value following presentation with neonatal UCDs, particularly in identifying patients at risk for poor outcome. The role and timing of follow-up neuroimaging is currently unclear. Further collaborative studies are necessary to evaluate whether patterns of MRI findings vary with specific UCD subtypes, and are predictive of clinical outcomes in neonatal UCDs.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".