Socioeconomic Status, Mortality, and Access to Cardiac Services After Acute Myocardial Infarction in Canada: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
BACKGROUND: Low socioeconomic status (SES) is an important prognosticator for those with acute myocardial infarction (AMI), having previously been described to be associated with increased short-term mortality. Whether this effect persists over time, and whether access to cardiac interventions is equitable within Canada's universal health care system, remains unknown. METHODS: We conducted a systematic review to determine the associations of SES with mortality and access to a spectrum of interventions including cardiac catheterization, revascularization, and cardiac rehabilitation. Electronic databases (EMBASE and MEDLINE) were searched in March 2019 and December 2019. Original studies from Canada examining associations between SES and any of the above outcomes in AMI patients were included. Meta-analyses were conducted using random effects models. RESULTS: Nineteen studies were included, 11 of which could be meta-analyzed. Low SES was associated with a 48% and 34% increase in short-term and intermediate-term mortality, respectively. There was a trend toward increased long-term mortality more than 1-year post-event (pooled odds ratio [OR] 1.34 [95% confidence interval {CI} 0.95-1.88]). Low SES was also associated with lower rates of cardiac catheterization (pooled OR 0.80 [95% CI 0.65-0.99]) and revascularization (pooled OR 0.76 [95% CI 0.63-0.90]) post-AMI. Studies on cardiac rehabilitation showed reduced access and participation in low-SES groups. CONCLUSIONS: Low SES is associated with not only increased mortality post-AMI, but also reduced access to cardiac interventions that have demonstrated benefits for mortality and morbidity. Interventions that improve access to catheterization, revascularization, and cardiac rehabilitation for low-SES populations are needed if true equitable care in Canada is desired.
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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 | 0.008 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.026 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".