Machine-learning-based prediction of fractional flow reserve after percutaneous coronary intervention

Integrative bioinformatics analysis identifies APOB as a critical biomarker in coronary in-stent restenosis

Aim: Coronary artery disease (CAD) is a major contributor to the worldwide prevalence of cardiovascular disease. In-stent restenosis (ISR) is a common complication which can lead to stent implantation failure, necessitating repeated intervention and presenting a significant obstacle for CAD management. Methods: To accurately assess and determine the hub genes associated with ISR, CAD databases from the Gene Expression Omnibus were utilized and weighted gene coexpression network analysis was employed to identify key genes in blood samples. Results: APOB was identified as a risk gene for ISR occurrence. Subsequent correlation analysis of APOB demonstrated a positive association with ISR. Clinical validation further confirmed the predictive value of APOB in ISR detection. Conclusion: We have identified APOB as a critical predictive biomarker for ISR in CAD patients.