Muscle thickness measured by ultrasound is reduced in neuromuscular disorders and correlates with clinical and electrophysiological findings
Bibliographic record
Abstract
Abstract Introduction Nerve imaging has a limited role in axonal and muscle fiber loss. In this study, we sought to explore the utility of standardized muscle ultrasound (US) assessment in these clinical scenarios. Methods We performed a prospective study from March to August 2018 of patients attending the neuromuscular clinic. All patients underwent clinical evaluation and standardized muscle thickness measurement by US in seven muscles. Results The study cohort consisted of 114 participants, including patients with polyneuropathy, motor neuron disease, and myopathy. The smallest distal muscle thickness was found in patients with polyneuropathy, while the smallest proximal muscle thickness was found in patients with myopathy. Muscle thickness was strongly correlated with muscle strength ( r 2 = 0.62), electrophysiological findings ( r 2 : 0.44‐0.55), and disability score ( r 2 = 0.53). Discussion Standardized muscle thickness measured by US shows diagnostic usefulness in a spectrum of neuromuscular disorders and correlates with clinical and electrophysiological findings.
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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) | 0.001 | 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 | 0.001 |
| 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".