ResearchBib Share Your Research, Maximize Your Social Impacts
Sign for Notice Everyday Sign up >> Login

P-SELECTIN AND INTEGRIN-β3 LEVELS IN BLOOD PLASMA IN PATIENTS WITH CORONARY ARTERY DISEASE AFTER PERCUTANEOUS CORONARY INTERVENTION

Journal: Journal of the Grodno State Medical University (Vol.22, No. 5)

Publication Date:

Authors : ;

Page : 451-457

Keywords : coronary artery disease; restenosis; percutaneous coronary intervention; P-selectin; integrin-β3; biochemical markers; predictors;

Source : Downloadexternal Find it from : Google Scholarexternal

Abstract

Background. Coronary artery disease (CAD) is a leading cause of mortality and disability worldwide. Modern treatment methods, such as percutaneous coronary intervention (PCI), have significantly improved patients' outcomes. However, the risk of stent restenosis remains a significant problem. Objective. To determine the levels of biochemical markers (P-selectin and integrin-β3) in the plasma of patients with coronary artery disease (CAD) after percutaneous coronary intervention (PCI), and to evaluate the effectiveness of various models for predicting in-stent restenosis. Material and methods. The study included 209 CAD patients divided into four groups: healthy individuals, patients with chronic CAD without indications for invasive coronary angiography, patients with CAD who underwent elective PCI, and patients with in-stent restenosis. Plasma levels of P-selectin and integrin-β3 were measured using enzymelinked immunosorbent assay (ELISA). Results. In-stent restenosis occurred in 12 patients (8.05%) after elective PCI. Analysis showed that P-selectin and integrin-β3 levels did not have statistically significant differences between patient groups. The predictive model including BMI, ventricular extrasystole, number of stents, diabetes mellitus, and multifocal atherosclerotic coronary artery disease showed the best key metrics efficiency. Conclusion. P-selectin and integrin-β3 levels did not show significant differences in patients with in-stent restenosis. The model including BMI, VE, number of stents, DM, and MFCAD is the most effective for predicting restenosis recurrence.

Last modified: 2024-11-14 15:50:21