Quantitative Motor Assessment in Myotonic Dystrophy
Bibliographic record
Abstract
OBJECTIVE: To establish baseline data, using a quantitative motor evaluation protocol, prior to a prospective longitudinal study of the natural history of muscular involvement in myotonic dystrophy (DM). DESIGN/METHODS: We conducted a cross-sectional study using a protocol consisting of manual muscle testing (MMT), quantitative muscle testing (QMT), and timed functional testing (TFT) on 50 definite DM patients (27 men, 23 women), aged 16 to 67 years. The relationships between MMT, QMT and TFT scores and disease duration were examined using linear regression analysis. RESULTS: The muscle weakness was symmetric and the neck flexors and the distal muscles of upper and lower extremities were weaker than proximal muscles. Using MMT scores, the average strength decline was 0.95% per year and was similar for men and women. The strength decline was significantly more rapid for distal muscles than for proximal muscles. Quantitative muscle testing scores documented a strength decline per year of disease duration of 1.2-1.6% for the hip flexors and of 2.0-3.0% for the hand grip flexors. CONCLUSIONS: We observed significant linear relationships between the scores generated by this protocol and disease duration. These data illustrate the distal to proximal progression of muscular involvement in DM, a pattern of progression well-recognized by the clinicians. The follow-up assessment of a large DM cohort in a longitudinal study will establish whether this quantitative protocol provides sensitive measures of the disease progression.
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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 | 0.009 | 0.012 |
| 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".