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Record W1893679037 · doi:10.1002/mds.25604

Clinical presentation and early evolution of spastic ataxia of Charlevoix‐Saguenay

2013· article· en· W1893679037 on OpenAlexaffabout
Antoine Duquette, Bernard Brais, Jean‐Pierre Bouchard, Jean Mathieu

Bibliographic record

VenueMovement Disorders · 2013
Typearticle
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsUniversité de SherbrookeHôpital de l'Enfant-JésusUniversité LavalMontreal Neurological Institute and HospitalMcGill UniversityCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsSpasticityMedicinePresentation (obstetrics)AtaxiaPediatricsCohortSpasticDifferential diagnosisSpinocerebellar ataxiaPhysical medicine and rehabilitationSurgeryCerebral palsyPathologyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Autosomal recessive spastic ataxia of Charlevoix-Saguenay (ARSACS) is an increasingly recognized form of spastic ataxia worldwide, but early diagnosis remains a challenge. METHODS: We reviewed the initial presentation (n = 40) and early clinical evolution (n = 50) of a large ARSACS cohort that was followed at the Saguenay Neuromuscular clinic. RESULTS: The average age at presentation was 3.41 ± 1.55 years. Increased deep tendon reflexes were more common than spasticity initially, and the neuropathy only became apparent clinically in the second decade. Despite a homogeneous genetic background, some patients showed no signs of neuropathy or spasticity by the age of 18 years. CONCLUSIONS: At presentation, ARSACS lacks certain features that are considered typical in adults after years of evolution. Considering that ARSACS is probably under-diagnosed, it should be included in the differential diagnosis of early onset ataxias with or without pyramidal features and is worthwhile to consider in older patients, even when some features are absent.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.024
GPT teacher head0.286
Teacher spread0.262 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations64
Published2013
Admission routes2
Has abstractyes

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