Bibliographic record
Abstract
Lhermitte's sign (LS) is strongly linked to multiple sclerosis (MS). Our aim is to reassess its frequency, natural history, various characteristics and neuroradiological correlation in a cohort of MS patients attending our specialized MS clinic and to propose a working definition. Consecutive patients with CDMS and normal controls were interviewed using a structured questionnaire. Cervical MRIs were reviewed when available. There were 300 MS patients and 100 normal controls. Forty-one per cent of the patients and none of the controls reported having LS during the course of their illness. In 53% of those who reported LS, it started in the first three years of the illness and began as an isolated symptom in 64% and was polysymptomatic in 36%. In all patients LS was a short-lasting sensation in all patient who experienced it and was mostly stereotyped in individual patients. Characteristics varied widely between patients. Forty-three patients had cervical MRIs; 17 out of 18 patients who reported LS had abnormalities, whereas only 13 out of the 25 with no LS had abnormalities. The results indicate that LS is highly prevalent in MS, is commonly stereotyped in individual patients, has a variable natural course and correlates significantly with cervical MRI abnormalities. A working definition is proposed.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".