Abstract 16866: Sex Differences in Access to Care Before Acute Myocardial Infarction: Does the Health Care System Matter?
Bibliographic record
Abstract
Introduction: Access to high-quality health care for young women with acute myocardial infarction (AMI) lags behind that of men. Whether access to care varies based on the health care system remains unknown. We evaluated sex differences in pre-AMI access to care in young patients with AMI across countries. Methods: We utilized data from the GENESIS-PRAXY and VIRGO cohorts, which included young ( < 55 yrs) AMI patients hospitalized in countries with public (Canada, Spain, Australia) or private (United States [US], Switzerland) health care systems (2009-13). We collected data on demographics, CV risk, and psychosocial factors. Pre-AMI access to care was defined as: having a primary health care provider, difficulties in access to primary/specialist care, primary health care visits/diagnostic tests for cardiac symptoms (12 months prior to AMI). Sex-stratified analysis by health care system was performed. Results: Among 4,689 AMI patients (58% women, mean age 47±6 yrs), 64% were from the US and 22% from Canada. Compared with men, women had more CV risk factors, higher rates of depression/stress and lower socioeconomic status (SES) (Table); more strikingly in the US. Across countries, 70% of patients had a primary health care provider. However, women experienced more difficulties accessing primary (21% vs. 15%) or specialist care (27% vs. 20%, all p<.001) versus men. Women in the US reported cost barriers (47% vs. 5%), whereas women from other countries had difficulties in contacting primary health care providers (91% vs. 46%, all p<.001). Nevertheless, compared with men, women reported more primary health care provider visits (46% vs. 37%) and tests for cardiac symptoms (66% vs. 50%), regardless of health care system. Conclusions: In both public and privately funded health care systems, one-fifth of young AMI patients had poor pre-AMI access to care, despite a high-risk factor burden - especially among women in the US. Young women of low SES should be targeted for primary prevention.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".