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Record W2147917322 · doi:10.1161/strokeaha.115.009616

Prevalence of Individuals Experiencing the Effects of Stroke in Canada

2015· article· en· W2147917322 on OpenAlexaffabout
Hans Krueger, Jacqueline Koot, Ruth Hall, Christina O’Callaghan, Mark Bayley, Dale Corbett

Bibliographic record

VenueStroke · 2015
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsUniversity of British ColumbiaInstitute for Clinical Evaluative SciencesUniversity of TorontoOntario Stroke NetworkToronto Rehabilitation InstituteHeart and Stroke FoundationCanadian Institute for Advanced ResearchUniversity of OttawaInstitute for Work & HealthGolder Associates (Canada)
Fundersnot available
KeywordsMedicineStroke (engine)DemographyPopulationEpidemiologyGerontologyEnvironmental healthInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: Previous estimates of the number and prevalence of individuals experiencing the effects of stroke in Canada are out of date and exclude critical population groups. It is essential to have complete data that report on stroke disability for monitoring and planning purposes. The objective was to provide an updated estimate of the number of individuals experiencing the effects of stroke in Canada (and its regions), trending since 2000 and forecasted prevalence to 2038. METHODS: The prevalence, trends, and projected number of individuals experiencing the effects of stroke were estimated using region-specific survey data and adjusted to account for children aged <12 years and individuals living in homes for the aged. RESULTS: In 2013, we estimate that there were 405 000 individuals experiencing the effects of stroke in Canada, yielding a prevalence of 1.15%. This value is expected to increase to between 654 000 and 726 000 by 2038. Trends in stroke data between 2000 and 2012 suggest a nonsignificant decrease in stroke prevalence, but a substantial and rising increase in the number of individuals experiencing the effects of stroke. Stroke prevalence varied considerably between regions. CONCLUSIONS: Previous estimates of stroke prevalence have underestimated the true number of individuals experiencing the effects of stroke in Canada. Furthermore, the projected increases that will result from population growth and demographic changes highlight the importance of maintaining up-to-date estimates.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.448
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

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

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 head0.013
GPT teacher head0.248
Teacher spread0.235 · 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 teacher head, 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

Citations201
Published2015
Admission routes2
Has abstractyes

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