White matter abnormalities in children with idiopathic developmental delay
Bibliographic record
Abstract
BACKGROUND: The underlying cause of developmental delay (DD) often remains unclear despite extensive clinical examination and investigations. Interference in normal development of the brain may result in DD. PURPOSE: To identify the prevalence of abnormalities on magnetic resonance (MR) imaging in idiopathic developmental delay. MATERIAL AND METHODS: Of the 124 children referred for MR imaging with DD, 34 were excluded due to known history of progressive neurodevelopmental disorders, birth asphyxia, congenital CNS infections, metabolic disorder, chromosomal anomalies, and severe epileptic syndromes. The following structures were systematically reviewed: ventricles, corpus callosum, gray and white matter, limbic system, basal ganglia, brainstem, and cerebellum. RESULTS: Ten out of 90 (11%) were referred with DD only, whilst 80/90 (89%) were referred with DD and additional clinical findings, such as seizures, neurological deficit, and abnormal head size. Of the 90 patients, 14 (16%) had normal MR and 76 (84%) had abnormal MR findings. Abnormal ventricles were seen in 43/90 (48%); abnormal corpus callosum was identified in 40/90 (44%). Other MR findings included abnormalities in the white matter (23/90, 26%), hippocampi (5/90, 6%), cerebellum (5/90, 6%), and brainstem (4/90, 4%). CONCLUSION: Abnormalities of the ventricles and corpus callosum were identified in a large proportion of patients with idiopathic DD, indicative of changes in the white matter. Further studies using quantitative methods and diffusion tensor imaging are required to evaluate the white matter in these children.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| 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 teacher head, 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".