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Prevalence and risk factors of angina pectoris and its association with coronary atherosclerosis in a general population, a cross-sectional study

2022· article· en· W4306251413 on OpenAlexaboutno aff
Kerstin Welén-Schef, Emil Hagström, Annica Ravn‐Fischer, Stefan Söderberg, Troels Yndigegn, Per Tornvall, Tomas Jernberg

Bibliographic record

VenueEuropean Heart Journal · 2022
Typearticle
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAnginaCoronary artery diseasePopulationCross-sectional studyInternal medicineEpidemiologyCohortCanadian Cardiovascular SocietyCohort studyRisk factorCardiologyMyocardial infarctionEnvironmental healthPathology

Abstract

fetched live from OpenAlex

Abstract Background Angina pectoris (AP) is a common clinical presentation with low association to significant coronary artery disease (CAD) in selected cohorts, though yet associated with an elevated risk of major cardiovascular adverse events. Current knowledge on AP prevalence is not up to date since contemporary cross-sectional population-based studies using symptom evaluation are sparse and epidemiological studies often use administrative data from routine health care. Also, there is a lack of studies in the general population examining the association between AP and presence of coronary atherosclerosis. Purpose To assess the prevalence of AP, the relationship to CAD, and risk factors associated to the conditions in a population-based, middle-aged Swedish cohort. Methods Data were based on the Swedish CArdioPulmonary bioImage Study (SCAPIS), in which 30,154 men and women aged 50–64 years were recruited from the general population between 2013 and 2018. Exposure variables included information from blood sampling, physiological examinations, coronary computed tomographic angiography (CCTA) and an extensive questionnaire, including WHO Rose questionnaire on AP. Participants that completed the Rose questionnaire were included and categorized as having Rose angina or No angina. Subjects with a valid CCTA were further assessed regarding correlation between having Rose angina and degree of CAD, categorized as obstructive (>50% occlusion, O-CAD), non-obstructive (<50% occlusion, NO-CAD) or normal coronary angiography (Normal CA). Associations between risk factor exposures and outcomes were analysed in both cohorts using bivariate logistic regression. Results The main cohort consisted of N=28,974 individuals, of which n=1025 fulfilled the criteria of Rose angina, giving a prevalence of 3.5%. Out of these, N=24,602 subjects constituted the CCTA-cohort. Coronary atherosclerosis was significantly more common in individuals having Rose angina compared with those with No angina, (p≤0.001; O-CAD 11.8% vs 5.4%, NO-CAD 38.9% vs 37.0%, Normal CA 49.4% vs 57.7%). Factors associated with Rose angina were birthplace outside of Sweden, low educational level, unemployment, poor economic status, symptoms of depression, and high degree of general stress (Table). Physical inactivity, and current or previous cardiopulmonary diseases only marginally attenuated the associations. These findings were consistent in the sub-population of Rose angina with NO-CAD or Normal CA. Conclusion Rose Questionnaire AP was common in a Swedish general population, with a greater association to coronary atherosclerosis at CCTA compared with asymptomatic individuals. O-CAD was though uncommon. Risk factors associated with AP were sociodemographic and psychological, irrespective of degree of CAD. Funding Acknowledgement Type of funding sources: Foundation. Main funding source(s): SCAPIS has been funded mainly from the Swedish Heart- and Lung foundation and Knut och Alice Wallenberg foundation.

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)0.002
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 score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.029
GPT teacher head0.293
Teacher spread0.264 · 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".

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Citations5
Published2022
Admission routes1
Has abstractyes

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