Benign External Hydrocephalus in a Subgroup of Autistic Children Prior to Autism Diagnosis
Bibliographic record
Abstract
ABSTRACT Benign external hydrocephalus (BEH) is evident in < 0.6% of births. It is defined by abnormally large cerebrospinal fluid (CSF) volumes in the subarachnoid space (SAS) and otherwise normal neuroimaging findings before 2 years of age. BEH has not been associated with specific developmental disorders and is not treated because it usually resolves spontaneously. However, quantitative MRI studies have reported that some toddlers with autism exhibit enlarged extra‐axial CSF (EA‐CSF) volumes. Our objective was to determine whether a subgroup of children with autism exhibits both qualitative BEH and quantitative EA‐CSF volume enlargements. We analyzed clinical brain MRI scans in a retrospective sample of 136 children, 5–99 months old, 83 with autism, who were assessed for BEH by neuroradiologists. EA‐CSF volume and total cerebral volume (TCV) were quantified in T2‐weighted scans by manual labeling. Measures were compared across groups while stratifying participants by age. Neuroradiologists reported BEH findings in 33% of autistic children scanned before the age of 2 years old (i.e., before autism diagnosis). Quantitative MRI analyses demonstrated that autistic children in this age group exhibited significantly larger EA‐CSF volumes relative to controls ( t (49) = 2.89, p = 0.006, Cohen's d = 0.82) with 30% of autistic children and 9.5% of the controls exhibiting EA‐CSF/TCV ratios > 0.14, a previously suggested threshold of potential clinical relevance. EA‐CSF differences were not apparent in older children. The prevalence of BEH associated with quantifiable EA‐CSF enlargements was remarkably high in toddlers who later developed autism, suggesting a specific autism etiology involving early transient CSF circulation problems with potentially long‐lasting neurodevelopmental impact.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".