Pediatric Cohort of Charcot-Marie-Tooth Disease
Bibliographic record
Abstract
Background and Objectives: Charcot-Marie-Tooth (CMT) disease is a heterogeneous group of hereditary peripheral neuropathies. While pediatric-onset CMT exhibits unique clinical and genetic characteristics, data on this subset remain sparse. This study investigates the clinical and genetic features of a pediatric CMT cohort in a single center in ON, Canada. Methods: A retrospective cross-sectional study reviewed data from patients diagnosed with CMT disease at The Hospital for Sick Children between 2013 and 2022. Genetic testing targeted up to 87 genes linked to CMT, with patient demographics, clinical features, electrodiagnostic findings, and orthopaedic complications analyzed using descriptive and inferential statistics. Results: Sixty-one patients from 14 genetically confirmed subtypes were included (29 female patients, 32 male patients). The median age at diagnosis was 7.7 years (range 1-17). Overall, foot deformities were present in 84% of patients, Achilles contractures in 42%, hammertoes in 28%, hip dislocation in 10%, and scoliosis in 23%. Discussion: This study provides a description of pediatric CMT disease in a Canadian cohort. We show that while genetic distributions mirror international data, family-based genetic screening can identify children even before clinical onset, and that orthopaedic complications are already common in early childhood. These findings reinforce the importance of early genetic confirmation, orthopaedic surveillance, and expanded sequencing strategies to improve care and refine genotype-phenotype correlations in pediatric CMT disease.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".