Clinical Features of Lewis–Sumner Syndrome: Can Trauma Precipitate Symptoms?
Bibliographic record
Abstract
INTRODUCTION: Lewis-Sumner syndrome (LSS) is a demyelinating peripheral neuropathy described in 1982. METHODS: We reviewed the charts of nine LSS patients in neurological care for their symptoms, response to different treatment regimens, and pattern of nerve involvement. RESULTS: One patient had an Adie's pupil. Every patient studied had median nerve involvement. Seven of nine patients required intravenous immunoglobulin (IVIg) therapy and all showed improvement with IVIg. Four of nine patients received oral steroid therapy and had some improvement. Two of nine patients received azathioprine to little effect. Two of nine patients experienced significant trauma while receiving neurological follow-up and their symptoms worsened to a clinically significant degree afterward. DISCUSSION: We noticed a possible association between trauma and symptom severity in cases of LSS with preexisting neurological follow-up. We hypothesize that physical trauma exacerbates LSS. To our knowledge, this is an unreported phenomenon.
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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 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".