Race-Based Differences in ST-Segment-Elevation Myocardial Infarction Process Metrics and Mortality From 2015 Through 2021: An Analysis of 178 062 Patients From the American Heart Association Get With The Guidelines-Coronary Artery Disease Registry.

BACKGROUND: Systems of care have been developed across the United States to standardize care processes and improve outcomes in patients with ST-segment-elevation myocardial infarction (STEMI). The effect of contemporary STEMI systems of care on racial and ethnic disparities in achievement of time-to-treatment goals and mortality in STEMI is uncertain. METHODS: We analyzed 178 062 patients with STEMI (52 293 women and 125 769 men) enrolled in the American Heart Association Get With The Guidelines-Coronary Artery Disease registry between January 1, 2015, and December 31, 2021. Patients were stratified into and outcomes compared among 3 racial and ethnic groups: non-Hispanic White, Hispanic White, and Black. The primary outcomes were the proportions of patients achieving the following STEMI process metrics: prehospital ECG obtained by emergency medical services; hospital arrival to ECG obtained within 10 minutes for patients not transported by emergency medical services; arrival-to-percutaneous coronary intervention time within 90 minutes; and first medical contact-to-device time within 90 minutes. A secondary outcome was in-hospital mortality. Analyses were performed separately in women and men, and all outcomes were adjusted for age, comorbidities, acuity of presentation, insurance status, and socioeconomic status measured by social vulnerability index based on patients' county of residence. RESULTS: Compared with non-Hispanic White patients with STEMI, Hispanic White patients and Black patients had lower odds of receiving a prehospital ECG and achieving targets for door-to-ECG, door-to-device, and first medical contact-to-device times. These racial disparities in treatment goals were observed in both women and men, and persisted in most cases after multivariable adjustment. Compared with non-Hispanic White women, Hispanic White women had higher adjusted in-hospital mortality (odds ratio, 1.39 [95% CI, 1.12-1.72]), whereas Black women did not (odds ratio, 0.88 [95% CI, 0.74-1.03]). Compared with non-Hispanic White men, adjusted in-hospital mortality was similar in Hispanic White men (odds ratio, 0.99 [95% CI, 0.82-1.18]) and Black men (odds ratio, 0.96 [95% CI, 0.85-1.09]). CONCLUSIONS: Race- or ethnicity-based disparities persist in STEMI process metrics in both women and men, and mortality differences are observed in Hispanic White compared with non-Hispanic White women. Further research is essential to evolve systems of care to mitigate racial differences in STEMI outcomes.

Empowering Research With the American Heart Association Get With The Guidelines Registries Through Integration of a Database and Research Tools.

BACKGROUND: The American Heart Association's Get With The Guidelines (GWTG) has emerged as a vital resource in advancing the standards and practices of inpatient care across stroke, heart failure, coronary artery disease, atrial fibrillation, and resuscitation focus areas. The GWTG registry data have also created new opportunities for secondary use of real-world clinical data in biomedical research. Our goal was to implement a scalable database with an integrated user interface (UI) to improve GWTG data management and accessibility. METHODS: The curation of registry data begins by going through a data processing and quality control pipeline programmed in Python. This pipeline includes data cleaning and record exclusion, variable derivation and unit harmonization, limited data set preparation, and documentation generation of the registry data. The database was built using PostgreSQL, and integrations between the database and the UI were built using the Django Web Framework in Python. Smaller subsets of data were created using SQLite database files for distribution purposes. Use cases of these tools are provided in the article. RESULTS: We implemented an automated data curation pipeline, centralized database, and UI application for the American Heart Association GWTG registry data. The database and the UI are accessible through a Precision Medicine Platform workspace. As of March 2024, the database contains over 13.2 million cleaned GWTG patient records. The SQLite subsets benefit researchers by optimizing data extraction and manipulation using Structured Query Language. The UI improves accessibility for nontechnical researchers by presenting data in a user-friendly tabular format with intuitive filtering options. CONCLUSIONS: With the implementation of the GWTG database and UI application, we addressed data management and accessibility concerns despite its growing scale. We have launched tools to provide streamlined access and accessibility of GWTG registry data to all researchers, regardless of familiarity or experience in coding.