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Record W2054008298 · doi:10.1080/02770900701752391

The Relationship between Age of Asthma Onset and Cardiovascular Disease in Canadians

2007· article· en· W2054008298 on OpenAlexaffabout
Shilpa Dogra, Chris I. Ardern, Joseph Baker

Bibliographic record

VenueJournal of Asthma · 2007
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsYork University
Fundersnot available
KeywordsMedicineAsthmaDiseaseBlood pressureLogistic regressionOdds ratioStroke (engine)Internal medicinePopulationHeart diseaseAge of onsetPediatricsEnvironmental health

Abstract

fetched live from OpenAlex

PURPOSE: To quantify the association between cardiovascular disease (CVD) and asthma in Canadian adults and to determine whether age of asthma onset is a moderator of this association. METHODS: We used a sample of 74 342 participants with a mean age of 56.4 +/- 12.5 from cycle 1.1 of the Canadian Community Health Survey. Asthma age of onset was categorized into early-onset (0-20 years) and adult-onset (21-54 years). Three major outcomes were used to estimate the relationship between asthma and CVD, namely: high blood pressure, heart disease, and stroke. RESULTS: Multiple logistic regression models revealed that asthmatics were 43% (OR = 1.43, CI = 1.19-1.72) more likely to have heart disease, and 36% (OR = 1.36, CI = 1.21-1.53) more likely to have high blood pressure than non-asthmatics. There were no consistent results for age of onset with high blood pressure, heart disease, or stroke. CONCLUSION: Using a population-based dataset we confirmed that asthmatics are at increased odds of cardiovascular disease compared to non-asthmatics; furthermore, age of asthma onset did not appear to moderate this relationship. Future research should focus on determining whether asthma severity or allergic/non-allergic phenotypes have a differential effect on the asthma-CVD relationship.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.024
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.022
GPT teacher head0.276
Teacher spread0.254 · 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

Citations64
Published2007
Admission routes2
Has abstractyes

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