Abstract 12562: To Call ‘911’ or Not: What Influences Decision Making in Patients With St-Elevation Myocardial Infarction (STEMI)?
Bibliographic record
Abstract
Introduction: It is well-established that total ischemic time (TT) is related to mortality of STEMI patients treated with primary percutaneous coronary intervention (PPCI). TT is composed of the time from symptom onset (Sx) to first medical contact (FMC) and FMC to device. Shortest times are achieved when patients decide to call ‘911’, have a pre-hospital electrocardiogram and are transported directly for PPCI. Efforts have primarily focused on improvement of FMC-Device time. SxFMC time is less understood, collected and studied. Our goal was to identify factors that influence STEMI patients’ decision making to employ emergency medical services (EMS) vs self-presenting to an emergency department (ED). Methods: Between 1/1/2013- 12/31/2014, we collected data on 481 consecutive low risk STEMI patients, excluding cardiogenic shock, cardiac arrest and unsuccessful PPCI. Results: The median SxFMC was 53 minutes (interquartile range (IQR) 23-120) in EMS cohort versus 139 minutes (IQR 72-297) in ED group (p<0.001). EMS patients were more often older (median age 64, IQR 56-74 vs 60 IQR 52-68) vs ED, p<0.001. Presenting features such as sex, anterior STEMI, and Killip Class were not statistically different between EMS and ED. Risk factors (RF) for coronary disease including hypertension, dyslipidemia, diabetes, smoking, previous diagnosis of myocardial infarction (MI), previous PCI or coronary artery bypass grafting (CABG) were not statistically different between the groups. There was no difference in time of the day of symptoms onset between the groups. Conclusions: Accordingly, demographic, cardiac risk factors, time of onset of symptoms, location and severity of infarction are not associated with patient decisions to employ EMS. However, older patients were more likely to employ EMS. Further research is required to understand these decision-making processes to develop targeted public awareness interventions that are directed to improve SxFMC in STEMI patients.
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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 | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".