Neuropathy in ARSACS is demyelinating but without typical nerve enlargement in nerve ultrasound
Bibliographic record
Abstract
BACKGROUND: To specify peripheral nerve affection in autosomal recessive spastic ataxia of Charlevoix-Saguenay (ARSACS) by correlating high-resolution nerve ultrasound and nerve conduction studies. METHODS: We assessed a cohort of 11 ARSACS patients with standardized nerve conduction studies and high-resolution ultrasound of peripheral nerves and compared nerve ultrasound findings to a healthy control group matched for age, sex, size and weight. RESULTS: Mean age of patients was 39.0 (± 14.1) years and disease duration at assessment 30.6 (± 12.5) years. All patients presented with a spasticity, ataxia and peripheral neuropathy. Neuropathy appeared to be primarily demyelinating in 9/11 cases and was not classifiable in 2/11 cases due to not evocable potentials. Nerve ultrasound revealed a normal ultrasound pattern sum score (UPSS) in each ARSACS patient and no significant nerve enlargement compared to the control group. CONCLUSIONS: Peripheral neuropathy in ARSACS showed primarily demyelinating rather than axonal characteristics and presented without nerve enlargement. As demyelinating neuropathies do commonly present enlarged nerves we recommend further genetic testing of the SACS gene in patients who present with this combination of demyelinating neuropathy without nerve enlargement. ARSACS cases that initially presented only with neuropathy without spasticity or ataxia and therefore were misdiagnosed as Charcot-Marie-Tooth disease are supporting this suggestion.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".