Sex and Gender Discrepancies in Health-Related Quality of Life Outcomes Among Patients With Established Coronary Artery Disease
Bibliographic record
Abstract
BACKGROUND: Although eradicating discrepancies in health is of unquestioned importance, there are few studies examining health-related quality of life (HRQOL) among men and women with coronary artery disease (CAD), a highly prevalent and morbid condition among industrialized nations. This study compares the HRQOL outcomes of men and women in Alberta, Canada, 1 year after the documentation of coronary artery disease by cardiac catheterization. METHOD AND RESULTS: Patients' disease-specific HRQOL was assessed 1 year after angiography using the Seattle Angina Questionnaire, whereas their generic health status, burden of depressive symptoms, and social support were respectively quantified with the EuroQol EQ-5D, the Center for Epidemiological Studies Depression Scale (short form), and the Medical Outcomes Study social support scale. The latter 2 instruments were used to adjust Seattle Angina Questionnaire outcomes for potential confounding characteristics hypothesized to be associated with sex and gender. General linear modeling and a change in Seattle Angina Questionnaire scores from baseline to 1 year were used to compare the HRQOL outcomes of men and women, after adjusting for demographics, clinical factors, depressive symptoms, and social support differences between groups. A total of 2394 (60% of those eligible) patients responded to the baseline and the 1-year follow-up survey. The adjusted mean 1-year Seattle Angina Questionnaire scores were significantly higher in men when compared with women, even after adjustment for all clinical factors, social support, depressive symptoms, and baseline HRQOL scales. Not only were women noted to have worse health status at the time of angiography, but despite adjusting for these differences, residual discrepancies in 1-year health status persisted. CONCLUSIONS: Women with coronary artery disease report worse HRQOL 1 year after coronary angiography when compared with men, and the discrepancies observed are only partially accounted for by sex differences in depression and social support. As a result, the measurement of gender roles and perceptions may be the best place to persist on the quest to identifying and understanding the noted discrepancies in cardiac recovery and HRQOL outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".