MétaCan
Menu
Back to cohort
Record W4319791650 · doi:10.1002/mdc3.13666

Demographics and Clinical Characteristics of Autosomal Dominant Spinocerebellar Ataxia in Canada

2023· article· en· W4319791650 on OpenAlex
Sohaila Alshimemeri, Danah Abo Alsamh, Lily Zhou, Sarah Furtado, Scott Kraft, Verónica Bruno, Antoine Duquette, Bernard Brais, Oksana Suchowersky, Renato P. Munhoz, Elizabeth Slow

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueMovement Disorders Clinical Practice · 2023
Typearticle
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsUniversity of AlbertaUniversity of CalgaryMcGill UniversityCentre Hospitalier de l’Université de MontréalUniversity of British ColumbiaUniversity Health NetworkUniversity of Toronto
FundersActelion PharmaceuticalsIpsenFriedreich's Ataxia Research AlliancePfizerPTC TherapeuticsCHDI FoundationAllerganNational Ataxia Foundation
KeywordsSpinocerebellar ataxiaDemographicsDemographyMedicineEthnic groupPopulationEpidemiologyPediatricsDiseasePathologyEnvironmental health

Abstract

fetched live from OpenAlex

Background: Autosomal dominant (AD) spinocerebellar ataxias (SCAs) encompass a large group of rare disorders, which occurs in individuals of different ethnic backgrounds. To date, demographics, and clinical descriptions of AD SCA in Canada are lacking. Methods: A retrospective chart review of patients with a genetically confirmed diagnosis of AD SCAs was performed at five tertiary centers across Canada in the provinces of Quebec, Alberta, and Ontario. Demographic, genetic, and clinical information were collected and analyzed. Results: A total of 203 patients with AD SCA were identified. Weighted estimated prevalence of AD SCA in three large Canadian provinces was calculated (2.25 cases per 100.000) which is in keeping with the figures documented worldwide. We found that the distribution of the most common SCA differed when comparing provinces. The most prevalent SCA diagnosis in Ontario was SCA3 (49%), while the most prevalent SCA diagnosis in Alberta and Quebec was SCA2 in 26% and 47%, respectively. SCA6 was the third most prevalent SCA subtype in Quebec (14%), which was not seen as commonly in other provinces. SCA1 was uncommonly seen in both Alberta and Quebec, despite being common in Ontario. Conclusions: In this largest Canadian study, we describe the prevalence, distribution, and clinical characteristics of AD SCA. We found that the distribution of the most common SCA differed in the three provinces studied. This finding reflects the heterogenous nature of the Canadian 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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.022
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.101
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.045
GPT teacher head0.351
Teacher spread0.306 · 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