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Record W7011805263

New clinical features of Autosomal Recessive Spastic Ataxia of Charlevoix-Saguenay

2019· article· en· W7011805263 on OpenAlexaboutno aff

Bibliographic record

VenueOpen Repository and Bibliography (University of Liège) · 2019
Typearticle
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsCohortAtaxiaDiseaseCerebellar ataxiaSpasticCohort studySpinocerebellar ataxiaDystoniaClinical diagnosis
DOInot available

Abstract

fetched live from OpenAlex

Background and purpose: Autosomal recessive spastic ataxia of Charlevoix-Saguenay ARSACS) diagnosis is based on the presence of three main clinical features: 1) ataxia, 2) pyramidal involvement, and 3) axonal neuropathy. This study aimed to explore, among a cohort of adults with ARSACS, the prevalence of other signs and symptoms than those commonly describe in this disease and compare their prevalence between younger (< 40 years) and older (≥40 years) participants. Methods: A clinical interview based on a standardized questionnaire was conducted. It included the following items: memory and concentration problems, hearing impairment, epilepsy, spasms, choreathetosis, neuropathic pain, cramps and fecal incontinence. Results: A total of 43 participants were interviewed, with a mean age of 38.9 years and 51.2% were men. Spasms (55.8%), cramps (53.5%), and concentration problems (39.5%) were the most frequent manifestations. Except for choreathetosis, which was present in only one participant, all other signs and symptoms were present in 9.3% to 29.3% of participants. Conclusions: People with ARSACS may experience many other clinical manifestations than the most commonly described. This study is a preliminary step toward the development of a comprehensive evidence-based clinical care guideline for this population.

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)0.001
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 score0.996
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.028
GPT teacher head0.272
Teacher spread0.244 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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