Gait Adaptations to Walking Speeds in Individuals with Myotonic Dystrophy Type 1
Bibliographic record
Abstract
Abstract Background Myotonic dystrophy type 1 (DM1) is a prevalent inherited muscular dystrophy in adults, affecting distal muscles such as the gastrocnemius, soleus, and tibialis anterior. This leads to significant gait deviations and reduced walking speed, impacting overall well-being and increasing fall risk. Objective This study aimed to assess how walking speed affects gait kinematics in individuals with DM1. Method Eighteen individuals with genetically confirmed DM1 (4 women, age: 41.0 [35.5; 47.8] years, mass: 76.8 [67.1; 94.6] kg, height: 166.0 [156.7; 173.3] cm) participated in this study. Each participant walked barefoot along a 13-meter walkway at comfortable and fast speeds. Subsequently, spatiotemporal parameters and joint kinematics were assessed. Results The step length (p < 0.001), cycle speed (p < 0.001), and cadence (p < 0.001) increased significantly, leading to a higher walking speed. Moreover, the vertical amplitude of the center of mass (CoM) increased significantly (p = 0.015), while the mediolateral amplitude decreased (p = 0.001) at fast walking condition. In addition, significant kinematic changes included increased trunk tilt (p < 0.001), greater anterior pelvic tilt (p < 0.001), increased hip flexion at initial contact, and enhanced knee flexion during both stance and swing phases. Ankle dorsiflexion showed a trend towards increase during stance phase (p = 0.055) at fast walking condition. Conclusions Fast walking speed in individuals with DM1 lead to significant gait adaptations. These adaptations reflect compensatory mechanisms to manage muscle weakness. The present study revealed significant changes in spatiotemporal parameters related to walking speed. Fast walking also highlighted kinematic adaptations in trunk, pelvis and lower limb joints. These findings enhance our understanding of gait deviation in individuals with DM1 and suggest the potential benefits of targeted fast walking training in this population.
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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 | 0.000 | 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".