Abstract 334: Impact of Sex, Gender and Healthcare System on the Quality of Care in Young Adults With Acute Myocardial Infarction
Bibliographic record
Abstract
Background: The quality of care among young adults with acute myocardial infarction (AMI) may be related to biological (sex) or psycho-socio-cultural (gender) determinants or healthcare system-level factors. Objectives: To examine whether sex, gender, and the type of healthcare system influence the quality of AMI care among young adults. Methods: A total of 4,564 AMI young adults (<55 years) (59% women, 47 years, 66% US) were analyzed from the VIRGO and GENESIS-PRAXY studies consisting of single-payer (Canada, Spain) versus multipayer (US) systems. For each patient treated in each system, we calculated a quality of care score (QCS) for pre-AMI (1-year pre-admission), in-hospital, and post-AMI (1-year post-discharge) phases of care (the number of quality indicators received divided by the total number [range=0-100%], with higher scores indicating better quality). The standard quality of care indicators were selected on the basis of being the standard of care to which young adults with AMI should have access to, based on European and North American Guidelines. Ordinal logistic or linear regression models and 2-way interactions between sex, gender and healthcare system were tested. Results: Women in the multipayer system had the highest risk factor burden. Across the phases of care for AMI, 20% of quality indicators were missed in both sexes. High stress, earner status, and social support were associated with a higher QCS in the pre-AMI phase, whereas only employment and earner status were associated with QCS in all other phases. In the pre-AMI phase, women had higher QCS than men, mainly in the single-payer system (adjusted-OR=1.85, 95%CI 1.46,2.35 vs. 1.07, 95%CI 0.84,1.36, P-interaction=0.002). Regardless of sex, only employment status had a greater effect in the multipayer system (adjusted-OR=0.59, 95%CI 0.44,0.78 vs 1.13, 95%CI 0.89,1.44, P-interaction<0.001). In the in-hospital phase, women had a lower QCS than men, especially in the multipayer system (adjusted-mean-difference: -2.48, 95%CI-3.87,-1.08). Employment was associated with a higher QCS (2.0, 95%CI 0.9-3.17, P interaction >0.05). Finally, in the post-AMI phase, men and women had a lower QCS, predominantly in the multipayer system. However, primary earners had higher QCS regardless of the healthcare system. Conclusion: Sex, gender, and the healthcare system affected the quality of care after AMI. Women had a poorer in-hospital than men and young adults had suboptimal post-discharge care. Being unemployed lowered the quality of care, more so in the multipayer healthcare system.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.004 | 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".