Diagnostic Approach to Macrocephaly in Children
Why this work is in the frame
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Bibliographic record
Abstract
Macrocephaly affects up to 5% of the pediatric population and is defined as an abnormally large head with an occipitofrontal circumference (OFC) >2 standard deviations (SD) above the mean for a given age and sex. Taking into account that about 2-3% of the healthy population has an OFC between 2 and 3 SD, macrocephaly is considered as "clinically relevant" when OFC is above 3 SD. This implies the urgent need for a diagnostic workflow to use in the clinical setting to dissect the several causes of increased OFC, from the benign form of familial macrocephaly and the Benign enlargement of subarachnoid spaces (BESS) to many pathological conditions, including genetic disorders. Moreover, macrocephaly should be differentiated by megalencephaly (MEG), which refers exclusively to brain overgrowth, exceeding twice the SD (3SD-"clinically relevant" megalencephaly). While macrocephaly can be isolated and benign or may be the first indication of an underlying congenital, genetic, or acquired disorder, megalencephaly is most likely due to a genetic cause. Apart from the head size evaluation, a detailed family and personal history, neuroimaging, and a careful clinical evaluation are crucial to reach the correct diagnosis. In this review, we seek to underline the clinical aspects of macrocephaly and megalencephaly, emphasizing the main differential diagnosis with a major focus on common genetic disorders. We thus provide a clinico-radiological algorithm to guide pediatricians in the assessment of children with macrocephaly.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it