Frequency and Topographic Distribution of Brain Lesions in Pediatric Cerebral Venous Thrombosis
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Cerebral sinovenous thrombosis (CSVT) is increasingly encountered in children, including neonates. The purpose of this study was to assess the frequency and topographic distribution of parenchymal brain lesions associated with CSVT in children and to compare these with the known anatomic venous drainage pathways. MATERIALS AND METHODS: Brain CT/CT venograms and/or MR imaging/MR venograms of 71 consecutive patients with CSVT were reviewed retrospectively. The patients were grouped into neonates, infants, and older children. The site of CSVT, the location and size of the brain lesions, and the presence of hemorrhage were documented. The frequency of the brain lesions was calculated. RESULTS: There were 34 neonates, 10 infants, and 27 older children with CSVT who were included. The most common sites of CSVT were the transverse sinuses, the superior sagittal sinus, and the straight sinus. Overall, 37 of 71 children with CSVT had parenchymal brain lesions. There were 21 of 34 neonates, 4 of 10 infants, and 12 of 27 older children who had brain lesions. The most common locations were in the frontal and parietal lobes. The topographic distribution of lesions correlated with the corresponding venous drainage territory in 16 of 21 neonates, all infants, and all older children. The neonates had smaller-sized lesions. Brain lesions were hemorrhagic in 76% of neonates, 75% of infants, and 33% of older children. CONCLUSION: The topographic distribution of brain lesions associated with CSVT correlates with the known drainage territories of the dural venous sinus in children.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".