Neighborhood Socioeconomic Disadvantage and Care After Myocardial Infarction in the National Cardiovascular Data Registry
Bibliographic record
Abstract
Background: Patients living in disadvantaged neighborhoods are at high risk for adverse outcomes after acute myocardial infarction (MI). Whether residential socioeconomic status (SES) is associated with quality of in-hospital care among patients presenting with MI is unclear. Methods and Results: Multivariable logistic regression was used to examine the relationship between SES, quality of care, and in-hospital cardiovascular outcomes among patients with MI from diverse SES neighborhoods from July 2008 to December 2013, at 586 participating hospitals in the Acute Coronary Treatment and Intervention Outcomes Network Registry–Get With The Guidelines quality improvement program. Patients were categorized according to which SES summary measure group they resided in through linkage with US census block data. Outcomes were in-hospital mortality and major adverse cardiovascular events. Quality of MI care was assessed with the defect-free care measure that delineates the proportion of eligible patients who received all acute and discharge guideline-recommended therapies. Among 390 692 patients, there was a substantially longer median arrival-to-angiography time in lower SES neighborhoods (lowest 8.0 hours, low 5.5 hours, medium 4.8 hours, high 4.5 hours, highest 3.4 hours; P <0.0001), and a higher proportion of ST-segment–elevation myocardial infarction patients treated with fibrinolysis (lowest 23.1%, low 20.2%, medium 18.0%, high 14.2%, highest 5.9%; P <0.0001). However, after adjustment for clinical risk factors, insurance status, and hospital characteristics, socioeconomic disadvantage was not associated with lower rates of guideline-recommended defect-free acute care. Patients presenting from more disadvantaged neighborhoods had a progressively higher independent risk of in-hospital mortality ( P global =0.03) and major bleeding ( P global <0.001), along with lower quality of discharge care. Conclusions: In this national registry of MI, patients living in the most disadvantaged neighborhoods received equitable in-hospital care compared with advantaged neighborhoods. However, they experienced substantial delays in receiving angiography. Furthermore, patients living in disadvantaged neighborhoods remain at higher risk of adverse in-hospital outcomes after MI, including mortality. These observations suggest there are further opportunities for improvement in acute and discharge MI care.
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How this classification was reachedexpand
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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".