The primary design of this study is an ambispective cohort study. We plan to integrate coronary imaging features (including parameters derived from Coronary Computed Tomography Angiography(CCTA) and coronary angiography(CAG)), coronary functional indices (e.g., FFR, QFR), and metabolic biomarkers (e.g., LDL-C, Lp(a), hs-CRP). First, we will develop a multimodal risk prediction model for coronary artery disease using a retrospective cohort; subsequently, we will validate the model in a prospective cohort to assess its performance in discriminating high- versus low-risk individuals and to explore its potential clinical utility for risk stratification and decision-making.
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The composite endpoint of major adverse cardiovascular events (MACE)
Timeframe: At 12, 24, 36, 48, and 60 months after discharge
Frequency of occurrence of high-risk plaques
Timeframe: baseline, pre-intervention
CT Fractional Flow Reserve gradient
Timeframe: baseline, pre-intervention
Perivascular Fat Attenuation Index
Timeframe: baseline, pre-intervention
PPG derived by follow up CCTA
Timeframe: baseline, pre-intervention
SYNTAX score
Timeframe: immediately after the intervention
Coronary Angiography-derived FFR and Coronary Angiography-derived Index of Microcirculatory Resistance
Timeframe: baseline, pre-intervention
Radial Wall Strain
Timeframe: immediately after the intervention
IVUS-related parameters
Timeframe: immediately after the intervention
OCT-related parameters
Timeframe: immediately after the intervention