Abstract 9234: Evaluating the Association Between Perceived Discrimination and Health Status Outcomes Among Young Adults Hospitalized for Acute Myocardial Infarction
Bibliographic record
Abstract
Background: Perceived discrimination is associated with several risk factors for acute myocardial infarction (AMI), but little is known about the association between discrimination and health status outcomes post-AMI. Methods: We analyzed the 1- and 12-month health status of 2,670 young (≤ 55 years) adults recovering from an AMI enrolled in the VIRGO study (Variation in Recovery: Role of Gender on Outcomes of Young AMI Patients). Perceived discrimination was assessed using the Everyday Discrimination Scale (EDS). General health status was measured using the Short Form 12 Physical and Mental Component Scores (PCS and MCS). Disease-specific health status was measured using the following domains of the Seattle Angina Questionnaire (SAQ): treatment satisfaction (TS), quality of life (QL) and dichotomous forms of the physical limitation and angina frequency domain scores (score < 100). Lower scores indicate worse health status. Multivariable linear regression of the PCS, MCS, TS, and QL scores and multivariable logistic regression of the dichotomous forms of physical limitation and angina frequency were used to assess their adjusted associations with perceived discrimination. Results: Nearly 35.0% of the cohort reported discrimination (EDS > 0). At 1-month post-AMI, increased EDS score was significantly associated with lower MCS, TS, and QL scores and higher odds of physical limitation and angina after adjustment (Figure) . At 12-months post-AMI, increased EDS score retained its significant associations with lower MCS and QL scores and higher odds of physical limitation and angina, but not its association with TS (Figure) . The EDS score was not associated with PCS at either 1- or 12-months post-AMI. Conclusions: Perceived discrimination was associated with worse mental health and disease-specific health status one year after AMI after adjusting important confounders. Further work to understand the source and how to mitigate perceived discrimination is needed.
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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 | 0.002 | 0.004 |
| 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 | 0.001 |
| 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".