Crossed Cerebellar Atrophy in Perinatal Stroke
Bibliographic record
Abstract
Background and Purpose— Perinatal stroke causes most hemiparetic cerebral palsy and lifelong disability. Crossed cerebellar atrophy (CCA) is chronic cerebellar volume loss following contralateral motor pathway injury. We hypothesized that CCA is quantifiable in perinatal stroke and associated with poor motor outcome. Methods— Term-born children with perinatal stroke, magnetic resonance imaging beyond 6 months of age, and no additional neurological disorders were recruited. Blinded scorers measured cerebellar volumes expressed as ratios (contralesional/ipsilesional), with values <1 suggesting CCA. Motor outcomes including perinatal stroke outcome measure (PSOM) motor and cognitive scores (good/poor), Assisting Hand Assessment, and Melbourne Assessment were compared with cerebellar volume measures. Results— Seventy-three children met criteria (53% male). Mean cerebellar ratios were <1.0 (0.975±0.04; range, 0.885–1.079; P <0.001) suggesting occurrence of CCA. Cerebellar ratios did not differ between stroke types or across PSOM motor outcomes. Larger ipsilesional cerebellar volume was associated with poor PSOM cognitive outcome ( P =0.042), possibly with poor PSOM motor outcome ( P =0.063), and overall PSOM score ( P =0.034). Conclusions— CCA occurs in perinatal stroke but is not strongly associated with motor outcome. However, ipsilesional cerebellar volume is associated with poor cognitive and overall outcomes.
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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 | 0.003 |
| 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 | 0.001 |
| 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".