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Record W2785165670

Clinical Research Sex- and Gender-Related Risk Factor Burden in Patients With Premature Acute Coronary Syndrome

2014· article· en· W2785165670 on OpenAlexaboutno aff
Jin Choi, Stella S. Daskalopoulou, George Thanassoulis, Igor Karp, Roxanne Pelletier, Hassan Behlouli, Louise Pilote

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineInterquartile rangeDyslipidemiaAcute coronary syndromeFamily historyRisk factorPopulationDepression (economics)Framingham Risk ScoreObesityCoronary artery diseasePediatricsDemographyInternal medicineDiseaseMyocardial infarctionEnvironmental health
DOInot available

Abstract

fetched live from OpenAlex

Background: Few contemporary data exist on traditional (TRF) and non-TRF (NTRF) burden in patients with premature acute coronary syndrome (ACS). Methods: Prevalence of TRFs and NTRFs were measured in 1015 young (55 years old or younger) ACS patients recruited from 26 centres in Canada, the United States, and Switzerland. Risk factors were compared across sex and family history categories, and against a sample of the general Canadian population based on the 2000-2001 Canadian Community Health Survey. The 10- and 30-year risks of cardiovascular disease (CVD) were estimated using Framingham Risk Scores. Results: Risk factors were more prevalent in premature ACS patients compared with the general population. Young women with a family history of coronary artery disease showed the greatest risk factor burden including TRFs of hypertension (67%), dyslipidemia (67%), obesity (53%), smoking (42%), and diabetes (33%), and NTRFs of anxiety (55%), low household income (44%), and depression (37%). The estimated median 10-year risk of CVD was 7% (interquartile range [IQR], 3%-9%) in women and 13% (IQR, 7%-17%) in men, whereas the

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)0.003
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 score0.006
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.052
GPT teacher head0.409
Teacher spread0.357 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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