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Record W2786816727

Clinical Research Epidemiology of Hypertension in Canada: An Update

2016· article· en· W2786816727 on OpenAlexaboutno aff
Raj Padwal, Asako Bienek, Finlay A. McAlister

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicBlood Pressure and Hypertension Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineEpidemiologyBlood pressurePopulationPopulation healthEnvironmental healthDiseasePublic healthGerontologyDiabetes mellitusDemographyInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

Background: High blood pressure (BP) is the leading cause of death and disability in the world. The objective of this analysis was to perform a detailed update of the epidemiology of hypertension in Canada. Methods: Five population-based data sources were analyzed. We used the Canadian Health Measures Survey to determine the latest directly measured prevalence, awareness, and control estimates (2012-2013); the National Population Health Survey, and Canadian Community Health Survey to assess crude and age-standardized self-reported prevalence (1994-2013); the Canadian Chronic Disease Surveillance System to assess administrative dataeascertained prevalence and mortality trends (1998-2010); and Intercontinental Medical Statistics Health data to examine antihypertensive drugeprescribing trends and costs (2007-2014). Results: In 2012-2013, the prevalence of hypertension (defined as drug treatment for high BP or BP � 140/90 mm Hg) in Canadian adults was 22.6%, and the proportion of disease controlled was 68.1%. In Canadians with diabetes, the prevalence (defined as drug treatment

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)0.013
metaresearch head score (Gemma)0.021
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.047
Threshold uncertainty score0.342

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.021
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0250.051
Science and technology studies0.0020.002
Scholarly communication0.0050.002
Open science0.0030.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.402
GPT teacher head0.453
Teacher spread0.051 · 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
GenreReview

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
Published2016
Admission routes1
Has abstractyes

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