Magnetic resonance imaging of the anterior compartment of the lower leg is a biomarker for weakness, disability, and impaired gait in childhood Charcot–Marie–Tooth disease
Bibliographic record
Abstract
INTRODUCTION: Biomarkers of disease severity in Charcot-Marie-Tooth disease (CMT) are required to evaluate early responses to treatment. In this study we used magnetic resonance imaging (MRI) to evaluate the relationship between muscle volume and intramuscular fat accumulation with weakness, disability, and impaired gait in affected children and adolescents. METHODS: Fifty-five participants underwent MRI of the anterior compartment of the lower leg. Muscle and fat volumes were calculated. Strength was measured using hand-held dynamometry, disability using the CMT Pediatric Scale, and 3-dimensional gait analysis using an 8-camera Vicon Nexus motion capture system. RESULTS: Lower muscle volume was significantly associated with reduced dorsiflexion strength, increased disability, impaired gait profile score, and foot drop. Intramuscular fat accumulation was associated with reduced dorsiflexion strength and impaired gait profile score. DISCUSSION: The MRI protocol described was feasible, reliable, and sensitive to the magnitude of weakness, disability, and walking difficulties in children with CMT. Muscle Nerve 59:213-217, 2019.
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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 | 0.001 | 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) | 0.001 | 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".