Isolated musculocutaneous neuropathy: a case report.
Bibliographic record
Abstract
OBJECTIVE: To present the diagnostic and clinical features of musculocutaneous neuropathy, propose possible conservative management strategies, and create awareness of this rare condition. CASE PRESENTATION: We present the case of a 24-year old competitive soccer athlete, who sought care for an unrelated lower extremity complaint. Upon examination, significant wasting of the right biceps was noted. The patient reported right arm pain and weakness that began six months prior, following a long sleep with his arm beneath him. Neurological examination revealed an absent deep tendon reflex of C5 on the right, diminished sensation on the right anterolateral forearm, and significant weakness in muscle testing of the biceps brachii on the right. The patient was referred to a neurologist to confirm suspicion of a musculocutaneous nerve injury. Electromyography and magnetic resonance imaging confirmed the diagnosis of musculocutaneous neuropathy and ruled out other differential diagnoses. The patient is currently awaiting confirmation to determine if he is a surgical candidate for a nerve transfer. SUMMARY: Musculocutaneous neuropathy is a rare condition. Recognition of the clinical presentation of this condition is important for early diagnosis and prompt intervention.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".