Improving the Timeliness of Care for Patients with Acute ST-Elevation Myocardial Infarction: Implications of "Self-Transport" versus Use of EMS
Bibliographic record
Abstract
Background Coronary heart disease affects millions of people in North America each year and is a leading cause of death worldwide ( Jollis et al ). In many patients coronary Early reperfusion of the myocardium is crucial in treating patients with acute ST segment elevation myocardial infarction (STEMI). Emergency medical services (EMS) plays an important role in minimizing delays to reperfusion. This study demonstrates that a large proportion of patients presenting with STEMI do not use EMS. Thus, such patients cannot benefit from many mechanisms designed to minimize time delays. Healthcare providers are challenged with both implementing strategies for improving care (minimizing delays to reperfusion) for patients not using EMS, and encouraging patients to access care via EMS in the event of acute chest pain.
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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 | 0.000 | 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 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".