Ethnic Disparities in ST-Segment Elevation Myocardial Infarction Outcomes and Processes of Care in Patients With and Without Standard Modifiable Cardiovascular Risk Factors: A Nationwide Cohort Study
Bibliographic record
Abstract
Background: There is growing interest in patients with ST-elevation myocardial infarction (STEMI) without ‘standard modifiable cardiovascular risk factors’(SMuRFs), including smoking, hypertension, diabetes and hypercholesterolaemia. Trials suggest ‘SMuRFless’ patients have poorer outcomes than those with SMuRFs but have not investigated ethnicity’s contribution. Methods & Results: We analysed 118,177 STEMI patients using the Myocardial Infarction National Audit Project registry. Clinical characteristics and outcomes were analysed using hierarchical logistic regression models, patients with ≥1 SMuRF (88,055) were compared to ‘SMuRFless’ patients (30,122), with subgroup analysis comparing outcomes of white and ethnic minority patients (Black, Asian, Mixed and other). Primary outcomes were in-hospital mortality and major adverse cardiovascular events (MACE). Secondary outcomes were in-hospital cardiacmortality and major bleeding. SMuRFless patients had higher incidence of MACE (OR 1.09, CI 1.02-1.16), in-hospital mortality (OR 1.09, CI 1.01-1.18), and cardiac-mortality (OR 1.08, CI 1.00-1.17) after adjusting for demographics, haemodynamics, Killip classification, cardiac arrest, and comorbidities. When additionally adjusting for invasive angiography and revascularisation (PCI or CABG), results for in-hospital mortality were not statistically significant (OR 1.05, CI 0.97-1.13). There were no significant differences in outcomes between white and ethnic minority patients. Ethnic minority patients were more likely to undergo revascularisation with ≥1 SMuRF (88% vs. 80%) or SMuRFless (87% vs. 77%). Conclusion: SMuRFless patients have a higher incidence of MACE, in-hospital mortality, and cardiac- mortality than those with SMuRFs, persisting after adjusting for demographics, haemodynamics, Killip classification, cardiac arrest, and comorbidities. Ethnic minority patients were more likely undergo ICA and revascularisation regardless of SMuRF status.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".