Decomposition‐based quantitative electromyography in the evaluation of muscular dystrophy severity
Bibliographic record
Abstract
INTRODUCTION: Electromyography is useful in the diagnosis of myopathies, but its utility in determining disease severity requires further investigation. In this study we aimed to determine whether decomposition-based quantitative electromyography (DQEMG) could indicate the severity of involvement in a cohort of patients with muscular dystrophies (MDs). METHODS: Fifteen patients with facioscapulohumeral (FSHD), limb-girdle (LGMD), and Becker (BMD) muscular dystrophy, and 7 healthy controls, participated in this investigation. Knee extensor isometric strength differentiated the "more severe" and "less severe" MD groups. The vastus lateralis (VL), biceps brachii (BB), and tibialis anterior (TA) muscle groups were investigated using DQEMG. RESULTS: All muscles from the MD group showed changes in mean MUP (motor unit potential) AAR (area-to-amplitude ratio), and turns, compared with controls (P < 0.05). More severely affected muscles (VL and BB) also had shortened mean MUP durations compared with controls (P < 0.01). CONCLUSIONS: DQEMG was capable of indicating the severity of MD involvement, as changes in MUP morphology reflected the progressive nature of the disease.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".