Description

The aim of this study is to explore in-hospital patient management and predict clinical outcomes in AMI patients receiving primary PCI through wearable technology (e.g., smart watches and wristband devices). The investigators expect to involve patients diagnosed with AMI, including ST-elevation myocardial infarction (STEMI) and non-ST-elevation myocardial infarction (NSTEMI), who are admitted to the cardiac Cardiac Intensive Care Unit (CICU) after primary PCI.

With written consent, eligible participants will be consistently monitored by a wearable device during the CICU stay, in addition to a conventional monitoring system. Vital signs including heart rate (beats/minute), oxygen saturation (%) blood pressure (mmHg), and other crucial parameters such as sleep patterns will be recorded. The collected data will be analyzed using AI-assisted and machine learning techniques, integrated with other clinical data to construct models that support risk stratification, guide clinical decision-making, improve the quality of nursing care, and predict long-term prognosis for these patients. Serial follow-ups (6-month, annual, and long-term) will be performed, and important information such as cardiac function assessed by echocardiography, the incidence of major adverse cardiovascular events, and life qualities will be collected for each follow-up.