Application of artificial intelligence to optimize the diagnosis and treatment of acute coronary syndrome: a real experience

Abstract Funding Acknowledgements Type of funding sources: None. Background/Introduction cardiovascular disease (CVD) is the leading cause of death in the world, with acute myocardial infarction (AMI) being the main responsible for this leadership. One of the determining factors in the outcome of Acute Coronary Syndrome (ACS) is the time to start treatment. An extremely promising path for obtaining earlier diagnosis and treatment has been the use of technological innovations in emergency care units. Prupose this study was carried out to assess the impact of applying a technology hub in the chest pain scenario in the emergency room, regarding the feasibility and potential reduction of time for diagnosis and treatment of ACS. Methods data obtained from 10 hospitals in the public health system in Brazil, which implemented the technology hub in the last 7 months (May to October 2021), were analyzed. This technology hub uses Artificial Intelligence (AI) to identify electrocardiograms (ECGs) with a high probability of alterations, which must be reported within 5 minutes by the cardiologist on shift (24/7) on the platform. Results 5,506 ECGs were entered into the platform, of which 53.77% (2,961) were considered abnormal; of these, 9.92% (294) had alterations compatible with ischemic events (currents of injury or myocardial ischemia). The median time for the ECG report made by the specialist was 2 minutes and 51 seconds. Conclusion the implementation of a technology hub in the chest pain scenario in the emergency room proved to be feasible and has great potential for reducing the distance between symptoms and the treatment of patients with ACS.