Foot orthosis design for children with Charcot-Marie-Tooth and impact on gait
Bibliographic record
Abstract
BACKGROUND: Charcot-Marie-Tooth (CMT) is a progressive disease resulting in distal sensory deficit and muscular weakness. As the disease progresses, most children develop a cavovarus foot deformity. Foot orthoses (FO) are widely prescribed in CMT to support the foot and improve gait, but there is a lack of guidelines for their conception. The aim of this pilot study was to report the methodology used for the design of FO (FOmax) based on an evaluation of foot deformities and to assess its effects on gait in children with CMT. METHODS: This study included 11 children with CMT. Participants were provided with a classic pair of FO (FOclass) and a pair of FOmax. A full evaluation of foot deformities was performed, and a decision-making algorithm was used for the FOmax design. A gait analysis was performed with both FO after 3 months of wear. RESULTS: Wearing FOmax compared with FOclass increased walking speed, step length, and single stance time. Hip flexion/extension range of motion during stance also increased. The pressure-time integral decreased on the lateral midfoot with FOmax. CONCLUSIONS: These results suggest that the FOmax, based on the algorithm, offers benefits for walking in children with CMT. The increased step length could be related to the increase of hip range of motion. The increase in walking speed and single support times could result from a better distribution of the plantar pressure that optimizes stability during walking. The present results need to be confirmed with a larger sample.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".