Corticospinal Tract Pre-Wallerian Degeneration
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: In neonatal arterial ischemic stroke, pre-Wallerian degeneration in descending corticospinal tracts (DCST) on diffusion MRI (DWI) predicts poor outcome. This signal has not been studied in older children. METHODS: A consecutive arterial ischemic stroke cohort (1 month to 18 years) with acute DWI and >12 months of follow-up were enrolled (SickKids Children's Stroke Program). DCST-DWI variables were quantified with a validated software technique and correlations to the Pediatric Stroke Outcome Measure were sought. RESULTS: Abnormal DCST-DWI signal was detected in 20 of 29 children (69%), with 85% having motor deficits on Pediatric Stroke Outcome Measure. DCST variables correlated with hemiparesis included: (1) any abnormal signal within the course of the DCST; (2) midbrain location; (3) percentage of peduncle; (4) vertical length; and (5) relative volume affected (all P<0.003). Unexpectedly, abnormal DWI signal was detected in the contralesional DCST in 7 children, all with severe hemiparesis. DCST signal abnormality increased over time, outlasted infarct DWI changes, and was difficult to appreciate on visual inspection. CONCLUSIONS: DCST-DWI signal is an acute predictor of motor outcome in childhood stroke and can help guide management. Previously unrecognized contralesional DCST signal predicts severe hemiparesis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".