Musculocutaneous neuropathy
Bibliographic record
Abstract
INTRODUCTION: Isolated musculocutaneous neuropathy is uncommon. In this study we aimed to determine its causes and clinical presentation and interpret the electrodiagnostic findings associated with this condition. METHODS: Our investigation was a retrospective review of patients diagnosed with musculocutaneous neuropathy at the Mayo Clinic (Rochester, Minnesota) electromyography (EMG) laboratory between 1997 and 2015. RESULTS: Thirty-two patients with musculocutaneous neuropathy and 5 patients with lateral antebrachial cutaneous neuropathy were identified. The most common cause was acute trauma or surgery (65%). Fourteen percent of the cases were idiopathic and 14% were inflammatory. Pain and sensory disturbance were more common presentations than weakness. Weakness from nerve injury was not noted in 2 patients, suggesting that other muscles may provide adequate elbow flexion/supination. The bilateral absence of lateral antebrachial cutaneous nerve sensory responses suggests an inflammatory cause. DISCUSSION: Musculocutaneous neuropathy usually results from trauma or iatrogenic injury. Nerve conduction studies alone are insufficient to confirm neuropathy, and needle EMG examination should be a routine part of the diagnostic evaluation. Muscle Nerve 58: 726-729, 2018.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.013 | 0.002 |
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".