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Record W4394601987 · doi:10.1016/j.cjco.2024.03.014

Monitoring Cardiovascular Disease in Métis Citizens Across Ontario, 2012-2020

2024· article· en· W4394601987 on OpenAlexafffundabout
Sabastian Koprich, Shelley Cripps, Abigail Simms, Noel Tsui, Sarah Edwards, Stephanie W. Tobin

Bibliographic record

VenueCJC Open · 2024
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Health and Risk Factors
Canadian institutionsTrent UniversityMétis National CouncilPublic Health OntarioUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaGovernment of CanadaPublic Health AgencyPublic Health Agency of Canada
KeywordsDiseaseMedicineInternal medicine

Abstract

fetched live from OpenAlex

Background: Population-based analyses of Métis-specific health outcomes in Canada are limited. This study aimed to address this gap and examine cardiovascular disease outcomes in citizens of the Métis Nation of Ontario (MNO) over a 9-year period. Methods: Under a data governance and sharing agreement between the MNO and ICES, registered MNO citizens aged ≥ 20 years were linked to administrative health data in Ontario. Existing algorithms were used to determine the burden of heart failure and hypertension. In the most recent year, prevalence rates were compared for income quintiles, age, and sex. Results: Age-adjusted prevalence rates of hypertension decreased, and age-adjusted prevalence rates of heart failure increased in MNO citizens from 2012 to 2020. A larger decrease in prevalence of hypertension was observed for female citizens, by 12% from 28.9 per 100 (confidence interval [CI]: 27.6-30.2) in 2012 to 25.4 per 100 (CI: 24.5-26.3) in 2020. As for heart failure, the age-adjusted prevalence rates for male citizens had the largest increase, by 47% from 2.6 per 100 (CI: 2.1-3.1) in 2012 to 3.8 per 100 (CI: 3.3-4.2) in 2020. Hypertension and heart failure were more prevalent in male citizens, those of advanced age, and those living in areas within the lowest income quintile. Conclusions: This study is the first in nearly 10 years to investigate trends in cardiovascular outcomes among MNO citizens. Understanding this burden is critical to the MNO's ability to guide program and policy planning, as well as to advocate within and beyond the health system for Métis-specific needs.

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)0.001
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 score0.397
Threshold uncertainty score0.944

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.028
GPT teacher head0.331
Teacher spread0.304 · 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

Citations3
Published2024
Admission routes3
Has abstractyes

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