The goal of this observational study is to investigate the structural composition and metabolic characteristics of OxPLs in STEMI patients. Explore OxPLs characteristic fingerprint biomarkers from different populations and analyze OxPLs fingerprint spectra. Based on the OxPLs fingerprint of STEMI patients, a machine learning classifier is used to establish an artificial intelligence assisted post PCI MACE risk prediction system, achieving the transformation of basic research into clinical application.
Study Type
OBSERVATIONAL
Enrollment
240
First Affiliated Hospital of Ningbo University
Ningbo, Zhejiang, China
Number of Participants with Treatment-Related Adverse Events as Assessed by CTCAE v5.0
Time frame: 12 months
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