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This protocol will collect real world EHR data to support the product development life cycle activities associated with developing the Major Adverse Cardiac Events (MACE) Clinical Decision Support (CDS) software.
The data will also be utilized in subsequent clinical validation to support an FDA application and/or applications to other regulatory agencies as needed.
Full description
The primary objective is to develop a machine learning tool which predicts risk of 30-day MACE (major adverse cardiac event) risk stratification among patients visiting ED with suspicion of ACS (Acute Coronary Syndrome).
The data will also be utilized in subsequent clinical validation. In addition to retrospective Electronic Health Record (EHR) data, Health Information Exchange (HIE) data and patient reported outcomes will be collected to capture 30-day MACE outcomes, as applicable.
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0 participants in 1 patient group
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Central trial contact
Kalyan Deepthi Akula; Alicia Drain
Data sourced from clinicaltrials.gov
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