International journal of cardiology. Heart & vasculature · 2025
Observational study of sudden cardiac arrest risk (OSCAR): Rationale and design of an electronic health records cohort.
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Reinier Kyndaron, Chugh Harpriya S, Uy-Evanado Audrey, Heckard Elizabeth, Mathias Marco, Bosson Nichole, Calsavara Vinicius F, Slomka Piotr J, Elashoff David A, Bui Alex A T, Chugh Sumeet S
Аннотация
BACKGROUND: Out-of-hospital sudden cardiac arrest (SCA) is a major cause of mortality and improved risk prediction is needed. The Observational Study of Sudden Cardiac Arrest Risk (OSCAR) is an electronic health records (EHR)-based cohort study of patients receiving routine medical care in the Cedars-Sinai Health System (CSHS) in Los Angeles County, CA designed to evaluate predictors of SCA. This paper describes the rationale, objectives, and study design for the OSCAR cohort.
METHODS AND RESULTS: The OSCAR cohort includes 379,833 Los Angeles County residents with at least one patient encounter at CSHS in each of two consecutive calendar years from 2016 to 2020. We obtained baseline cohort characteristics from the EHR from 2012 until the start of follow-up, including demographics, vital signs, clinical diagnoses, cardiac tests and imaging, procedures, laboratory results, and medications. Follow-up will continue until Dec. 31, 2025, with an expected median follow-up time of ∼ 7 years. The primary outcome is out-of-hospital SCA of likely cardiac etiology attended by Los Angeles County Emergency Medical Services (LAC-EMS). The secondary outcome is total mortality identified using California Department of Public Health - Vital Records death certificates. We will use conventional approaches (diagnosis code algorithms) and artificial intelligence (natural language processing, deep learning) to define patient phenotypes and biostatistical and machine learning approaches for analysis.
CONCLUSIONS: The OSCAR cohort will provide a large, diverse dataset and adjudicated SCA outcomes to facilitate the derivation and testing of risk prediction models for incident SCA.
METHODS AND RESULTS: The OSCAR cohort includes 379,833 Los Angeles County residents with at least one patient encounter at CSHS in each of two consecutive calendar years from 2016 to 2020. We obtained baseline cohort characteristics from the EHR from 2012 until the start of follow-up, including demographics, vital signs, clinical diagnoses, cardiac tests and imaging, procedures, laboratory results, and medications. Follow-up will continue until Dec. 31, 2025, with an expected median follow-up time of ∼ 7 years. The primary outcome is out-of-hospital SCA of likely cardiac etiology attended by Los Angeles County Emergency Medical Services (LAC-EMS). The secondary outcome is total mortality identified using California Department of Public Health - Vital Records death certificates. We will use conventional approaches (diagnosis code algorithms) and artificial intelligence (natural language processing, deep learning) to define patient phenotypes and biostatistical and machine learning approaches for analysis.
CONCLUSIONS: The OSCAR cohort will provide a large, diverse dataset and adjudicated SCA outcomes to facilitate the derivation and testing of risk prediction models for incident SCA.