Ultrasound in Multifocal Motor Neuropathy: Clinical and Electrophysiological Correlations
Bibliographic record
Abstract
OBJECTIVES: Multifocal motor neuropathy (MMN) is a treatable autoimmune polyneuropathy, which may prove challenging diagnostically in the setting of absent conduction blocks or advanced axonal loss. Relatively few studies have examined the role of ultrasound (US) in MMN. METHODS: Retrospective, cross-sectional study of patients with MMN who underwent peripheral nerve US. Charts were reviewed to extract clinical, sonographic, and electrophysiological data. RESULTS: Eleven patients with MMN underwent US between 2013 and 2015; of these 11 patients, 7 had ≥3 abnormal nerve segments, and 6 had ≥5 sites of increased cross-sectional area (CSA). There was moderate correlation between the degree of amplitude drop observed in the median and ulnar motor nerves, and CSA. Significant correlation between CSA and limb strength was only observed for the median nerve. CONCLUSIONS: Peripheral nerve US shows promise as a diagnostic tool in MMN and may be helpful to distinguish MMN from motor neuron disease.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".