Risk Prediction Model of MACE in Patients With AMI Based on Multi-modal Machine Learning

the Risk Prediction Model of MACE After PCI in Patients With AMI Based on Multimodal Machine Learning and the Effect of Digital Therapeutics for Cardiac Rehabilitation

A prospective, multicenter, observational study is adopted, with Jiangsu Provincial People's Hospital as the leading unit, and the other 13 Hospitals as cooperative units.

The deployment of an integrated cardiac rehabilitation management platform from the hospital to the outside of the hospital is uniformly arranged, and based on this platform, a study on the construction of a MACE prediction model and disease risk stratification for patients with acute myocardial infarction after PCI is carried out. It is planned to include 655 inpatients after PCI for acute myocardial infarction. Among them, the leading unit completes the enrollment and follow-up of 44 patients, and each cooperative unit completes the enrollment and follow-up of 47 patients, and competitive enrollment is allowed.

Inclusion Criteria:

• Meeting the diagnostic criteria of AMI;

  • Ages 18 - 75 years old;

    • Meeting the indications for emergency PCI surgery, with informed consent and voluntarily undergoing PCI treatment; ④ Accurate and complete clinical relevant data; ⑤ First diagnosis and treatment; ⑥ All patients were given unified antiplatelet therapy after the operation; ⑦ All patients were followed up for 12 months after the operation.

Exclusion Criteria:

• With malignant tumors, infections and other diseases;

  • Blood diseases, immune system diseases, severe liver and kidney function disorders; ③ With other heart diseases such as heart failure; ④ Patients undergoing surgical treatment.