ABSTRACT
Background: Delayed intervention for ST-segment elevation myocardial infarction (STEMI) is associated with higher mortality. The association of door-to-ECG (D2E) with clinical outcomes has not been directly explored in a contemporary US-based population. Methods: This was a three-year, 10-center, retrospective cohort study of ED-diagnosed patients with STEMI comparing mortality between those who received timely (<10 min) vs. untimely (>10 min) diagnostic ECG. Among survivors, we explored left ventricular ejection fraction (LVEF) dysfunction during the STEMI encounter and recovery upon post-discharge follow-up. Results: Mortality was lower among those who received a timely ECG where one-week mortality was 5% (21/420) vs. 10.2% (26/256) among those with untimely ECGs (p = 0.016), and in-hospital mortality was 6.0% (25/420) vs. 10.9% (28/256) (p = 0.028). Data to compare change in LVEF metrics were available in only 24% of patients during the STEMI encounter and 46.5% on discharge follow-up. Conclusions: D2E within 10 min may be associated with a 50% reduction in mortality among ED STEMI patients. LVEF dysfunction is the primary resultant morbidity among STEMI survivors but was infrequently assessed despite low LVEF being an indication for survival-improving therapy. It will be difficult to assess the impact of STEMI care interventions without more consistent LVEF assessment.
ABSTRACT
We compared four methods to screen emergency department (ED) patients for an early electrocardiogram (ECG) to diagnose ST-elevation myocardial infarction (STEMI) in a 5-year retrospective cohort through observed practice, objective application of screening protocol criteria, a predictive model, and a model augmenting human practice. We measured screening performance by sensitivity, missed acute coronary syndrome (ACS) and STEMI, and the number of ECGs required. Our cohort of 279,132 ED visits included 1397 patients who had a diagnosis of ACS. We found that screening by observed practice augmented with the model delivered the highest sensitivity for detecting ACS (92.9%, 95%CI: 91.4-94.2%) and showed little variation across sex, race, ethnicity, language, and age, demonstrating equity. Although it missed a few cases of ACS (7.6%) and STEMI (4.4%), it did require ECGs on an additional 11.1% of patients compared to current practice. Screening by protocol performed the worst, underdiagnosing young, Black, Native American, Alaskan or Hawaiian/Pacific Islander, and Hispanic patients. Thus, adding a predictive model to augment human practice improved the detection of ACS and STEMI and did so most equitably across the groups. Hence, combining human and model screening--rather than relying on either alone--may maximize ACS screening performance and equity.
ABSTRACT
Background: The Society for Academic Emergency Medicine (SAEM) has a core value to promote a diverse workforce for patients, providers, and learners. Understanding the organization's membership demographics and how that compares to the academic emergency medicine (EM) workforce is prerequisite to the success of this core value. Methods: We obtained 2020 faculty membership data sets from the Association of American Medical Colleges (AAMC) and SAEM; data included self-reported sex, race and ethnicity, and academic rank (professor, associate professor, assistant professor, and instructor). We employed standardized mean difference (SMD) to quantify difference in proportions between data sets. Results: We identified 5874 (AAMC) and 2785 (SAEM) faculty. The AAMC (38.3%) and the SAEM (41.3%) had similar proportions of overall female faculty (SMD 0.063) although SAEM (compared to AAMC) had a higher proportion of female full (25.5% vs. 20.5%, SMD 0.121) and assistant (46.5% vs. 41.2%, SMD 0.106) professors. With the exception of Hispanic instructors, SAEM (compared to AAMC) also had higher proportions of Black and Hispanic female faculty at all ranks (SMD ranging from 0.109 to 0.777). Conclusion: SAEM faculty demographics generally reflect that of the academic EM workforce demographics reported in the AAMC database and that overall, the proportions of female, Black, and Hispanic faculty in SAEM are slightly larger than those in the AAMC database. However, faculty who identify as Black or Hispanic in both the AAMC and the SAEM databases (compared to the overall U.S. population) are dramatically underrepresented.
