Racial Variations in Treatment and Outcomes of Black and White Patients With High-Risk Non–ST-Elevation Acute Coronary Syndromes
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Bibliographic record
Abstract
BACKGROUND: Black patients with acute myocardial infarction are less likely than whites to receive coronary interventions. It is unknown whether racial disparities exist for other treatments for non-ST-segment elevation acute coronary syndromes (NSTE ACS) and how different treatments affect outcomes. METHODS AND RESULTS: Using data from 400 US hospitals participating in the CRUSADE (Can Rapid Risk Stratification of Unstable Angina Patients Suppress Adverse Outcomes with Early Implementation of the ACC/AHA Guidelines?) National Quality Improvement Initiative, we identified black and white patients with high-risk NSTE ACS (positive cardiac markers and/or ischemic ST-segment changes). After adjustment for demographics and medical comorbidity, we compared the use of therapies recommended by the American College of Cardiology/American Heart Association guidelines for NSTE ACS and outcomes by race. Our study included 37,813 (87.3%) white and 5504 (12.7%) black patients. Black patients were younger; were more likely to have hypertension, diabetes, heart failure, and renal insufficiency; and were less likely to have insurance coverage or primary cardiology care. Black patients had a similar or higher likelihood than whites of receiving older ACS treatments such as aspirin, beta-blockers, or ACE inhibitors but were significantly less likely to receive newer ACS therapies, including acute glycoprotein IIb/IIIa inhibitors, acute and discharge clopidogrel, and statin therapy at discharge. Blacks were also less likely to receive cardiac catheterization, revascularization procedures, or smoking cessation counseling. Acute risk-adjusted outcomes were similar between black and white patients. CONCLUSIONS: Black patients with NSTE ACS were less likely than whites to receive many evidence-based treatments, particularly those that are costly or newer. Longitudinal studies are needed to assess the long-term impact of these treatment disparities on clinical outcomes.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it