Equity Gaps in the Diagnosis and Treatment of Occlusion Myocardial Infarction
Bibliographic record
Abstract
Background Patients with occlusion myocardial infarction (OMI) who meet the ST-elevation myocardial infarction (STEMI) criteria experience inequitable delays in care, because of sociodemographic factors, such as age and sex. OMI patients who do not meet STEMI criteria and are admitted to the hospital as non-STEMI patients, experience further delays. However, whether equity gaps exist in OMI care remains unknown. Methods A retrospective chart review included patients with acute coronary syndrome admitted to the hospital through 2 academic emergency departments, in the period from January 1, 2021 to December 31, 2022. Patients were categorized as having one of the following: OMI (acute culprit with Thrombolysis In Myocardial Infarction [TIMI] 0-2 flow, or acute culprit with TIMI 3 flow, and a troponin I level > 10,000 ng/L; or if they had no angiogram, a troponin I level > 10,000 ng/L plus new regional wall-motion abnormality on echocardiogram); non-OMI (MI that did not meet the OMI threshold); or MI ruled out. Results Among 662 charts, 260 were OMI patients, 296 were non-OMI patients, and 106 were patients with MI ruled out. Of the 260 OMI patients, 116 were admitted to the hospital as STEMI patients (true-positive), and 144 (55.4%) were admitted as non-STEMI patients (false-negative). In bivariate analyses, true-positive STEMI patients with atypical symptoms had a longer door-to-electrocardiogram (ECG) time ( P < 0.0001) and a longer ECG-to-catheterization time ( P < 0.001). False-negative STEMI patients had a longer door-to-ECG time for atypical symptoms ( P < 0.0001), a longer ECG-to-catheterization time for atypical symptoms ( P = 0.003), and were aged ≥75 years ( P = 0.006). Conclusions True-positive STEMI patients had delayed ECGs and catheterization for those presenting with atypical symptoms. More than half of those with OMI were admitted as non-STEMI patients, with further reperfusion delays for older patients and those presenting with atypical symptoms. Shifting to the OMI paradigm highlights reperfusion delays and equity gaps in the management of ACS.
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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 | 0.004 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".