Split Phenomenon of Fasciculation between Antagonistic Muscles in Amyotrophic Lateral Sclerosis: An Ultrasound Study
Bibliographic record
Abstract
ABSTRACT: Objective: Paresis of muscle groups in patients with amyotrophic lateral sclerosis (ALS) tends to present split phenomena. We explored the split phenomenon of fasciculation in multiple antagonistic muscle groups in ALS patients. Methods: One hundred and forty ALS patients and 66 non-ALS patients were included from a single ALS center. Muscle ultrasonography (MUS) was performed to detect fasciculation in elbow flexor-extensor, wrist flexor-extensor, knee flexor-extensor, and ankle flexor-extensor. Split phenomena of fasciculation between different antagonistic muscle groups were summarized, and the possible influence factors were analyzed through stratified analysis. Results: The frequency of split phenomenon of fasciculation intensity was significantly higher than those of muscle strength (26.1% vs. 7.1% for elbow flexor-extensor, 38.3% vs. 5.7% for wrist flexor-extensor, 37.9% vs. 3.0% for knee extensor-flexor, and 33.6% vs. 14.4% for ankle flexor-extensor) (P < 0.01). For muscles with 0–1 level of muscle strength (the Medical Research Council, MRC, score), significance difference in mean fasciculation intensity was observed only in ankle flexor-extensor. For muscles with 2–5 level of muscle strength, significant dissociation of fasciculation grade was common, especially among patients with slow rapid progression rate and both upper and lower motor neuron (UMN and LMN) involvement. As for non-ALS patients, no significant difference was observed in fasciculation intensity between antagonistic muscles. Conclusion: Split phenomenon of fasciculation between antagonistic muscles was common and relatively specific in ALS patients. Muscle strength, progression rate, and UMN involvement were influence factors of the split phenomenon of fasciculation intensity.
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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) | 0.000 | 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) | 0.002 | 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".