Decremental responses in patients with motor neuron disease
Bibliographic record
Abstract
Objective: Involvement of the neuromuscular junction (NMJ) in amyotrophic lateral sclerosis (ALS) has been reported and is increasingly recognized as an important pathophysiological aspect. The relationship between decrement and clinical measures for possible application as a biomarker has not been comprehensively explored. Methods: We performed routine repetitive nerve stimulation (RNS) of three nerves on patients with ALS. We captured measures of muscle strength, grip strength, fatigability, and calculated slow vital capacity (SVC) rates of change assessing for associations. Results: In 42 subjects, 210 muscles were studied. Negative correlation was found between the percentage of decrement and compound muscle action potential (CMAP) amplitude. Approximately half of the patients with hand weakness did not have decrement. There was no significant correlation between decrement and handgrip fatigue, SVC < 80% predicted, or more rapid worsening of SVC over time. Conclusions: Abnormal decremental responses are well described in ALS. We report that the degree of decremental response does not correlate with the degree of weakness. Abnormal decrement is only rarely present in nerve-muscle pairs with normal motor power. Our findings did not support a correlation between abnormal decrement and clinical measures suggesting that RNS may not be useful as a biomarker to monitor ALS 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 | 0.000 | 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".