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A predictive model involving serum uric acid, C-reactive protein, diabetes, hypercholesteremia, multiple lesions for restenosis risk in everolimus-eluting stent-treated coronary heart disease patients
PURPOSE: As a second-generation drug-eluting stent, the restenosis risk factors of the everolimus-eluting stent (EES) lack sufficient evidence. Therefore, the study investigated the in-stent restenosis occurrence and its predictive factors among patients with coronary heart disease (CHD) who underwe...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9403046/ https://www.ncbi.nlm.nih.gov/pubmed/36035940 http://dx.doi.org/10.3389/fcvm.2022.857922 |
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author | Feng, Qiang Zhao, Ying Wang, Haiyan Zhao, Jiayu Wang, Xun Shi, Jianping |
author_facet | Feng, Qiang Zhao, Ying Wang, Haiyan Zhao, Jiayu Wang, Xun Shi, Jianping |
author_sort | Feng, Qiang |
collection | PubMed |
description | PURPOSE: As a second-generation drug-eluting stent, the restenosis risk factors of the everolimus-eluting stent (EES) lack sufficient evidence. Therefore, the study investigated the in-stent restenosis occurrence and its predictive factors among patients with coronary heart disease (CHD) who underwent percutaneous coronary intervention (PCI) with EES. MATERIALS AND METHODS: Totally, 235 patients with CHD who underwent PCI with EES were included. At 1 year post PCI with EES (or earlier if clinically indicated), coronary angiography was performed to evaluate the in-stent restenosis status. RESULTS: Within 1 year post-operation, 20 patients developed in-stent restenosis while 215 patients did not develop in-stent restenosis, resulting in a 1-year in-stent restenosis rate of 8.5%. Diabetes mellitus, hypercholesteremia, hyperuricemia, fasting blood glucose, serum uric acid (SUA), high-sensitivity C-reactive protein (HsCRP), target lesions in the left circumflex artery, patients with two target lesions, length of target lesions and length of stent positively correlated with in-stent restenosis risk, while high-density lipoprotein cholesterol negatively associated with in-stent restenosis risk. Notably, diabetes mellitus, hypercholesteremia, SUA, HsCRP levels, and patients with two target lesions were independent predictive factors for in-stent restenosis risk by multivariate logistic regression analysis. Then, the in-stent restenosis risk prediction model was established based on these independent predictive factors, which exhibited an excellent value in predicting in-stent restenosis risk (area under the curve: 0.863; 95% CI: 0.779–0.848) by receiver operating characteristic analysis. CONCLUSION: In-stent restenosis risk prediction model, consisting of diabetes mellitus, hypercholesteremia, SUA, HsCRP, and patients with two target lesions, may predict in-stent restenosis risk in patients with CHD who underwent post-PCI with EES. |
format | Online Article Text |
id | pubmed-9403046 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-94030462022-08-26 A predictive model involving serum uric acid, C-reactive protein, diabetes, hypercholesteremia, multiple lesions for restenosis risk in everolimus-eluting stent-treated coronary heart disease patients Feng, Qiang Zhao, Ying Wang, Haiyan Zhao, Jiayu Wang, Xun Shi, Jianping Front Cardiovasc Med Cardiovascular Medicine PURPOSE: As a second-generation drug-eluting stent, the restenosis risk factors of the everolimus-eluting stent (EES) lack sufficient evidence. Therefore, the study investigated the in-stent restenosis occurrence and its predictive factors among patients with coronary heart disease (CHD) who underwent percutaneous coronary intervention (PCI) with EES. MATERIALS AND METHODS: Totally, 235 patients with CHD who underwent PCI with EES were included. At 1 year post PCI with EES (or earlier if clinically indicated), coronary angiography was performed to evaluate the in-stent restenosis status. RESULTS: Within 1 year post-operation, 20 patients developed in-stent restenosis while 215 patients did not develop in-stent restenosis, resulting in a 1-year in-stent restenosis rate of 8.5%. Diabetes mellitus, hypercholesteremia, hyperuricemia, fasting blood glucose, serum uric acid (SUA), high-sensitivity C-reactive protein (HsCRP), target lesions in the left circumflex artery, patients with two target lesions, length of target lesions and length of stent positively correlated with in-stent restenosis risk, while high-density lipoprotein cholesterol negatively associated with in-stent restenosis risk. Notably, diabetes mellitus, hypercholesteremia, SUA, HsCRP levels, and patients with two target lesions were independent predictive factors for in-stent restenosis risk by multivariate logistic regression analysis. Then, the in-stent restenosis risk prediction model was established based on these independent predictive factors, which exhibited an excellent value in predicting in-stent restenosis risk (area under the curve: 0.863; 95% CI: 0.779–0.848) by receiver operating characteristic analysis. CONCLUSION: In-stent restenosis risk prediction model, consisting of diabetes mellitus, hypercholesteremia, SUA, HsCRP, and patients with two target lesions, may predict in-stent restenosis risk in patients with CHD who underwent post-PCI with EES. Frontiers Media S.A. 2022-08-11 /pmc/articles/PMC9403046/ /pubmed/36035940 http://dx.doi.org/10.3389/fcvm.2022.857922 Text en Copyright © 2022 Feng, Zhao, Wang, Zhao, Wang and Shi. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Cardiovascular Medicine Feng, Qiang Zhao, Ying Wang, Haiyan Zhao, Jiayu Wang, Xun Shi, Jianping A predictive model involving serum uric acid, C-reactive protein, diabetes, hypercholesteremia, multiple lesions for restenosis risk in everolimus-eluting stent-treated coronary heart disease patients |
title | A predictive model involving serum uric acid, C-reactive protein, diabetes, hypercholesteremia, multiple lesions for restenosis risk in everolimus-eluting stent-treated coronary heart disease patients |
title_full | A predictive model involving serum uric acid, C-reactive protein, diabetes, hypercholesteremia, multiple lesions for restenosis risk in everolimus-eluting stent-treated coronary heart disease patients |
title_fullStr | A predictive model involving serum uric acid, C-reactive protein, diabetes, hypercholesteremia, multiple lesions for restenosis risk in everolimus-eluting stent-treated coronary heart disease patients |
title_full_unstemmed | A predictive model involving serum uric acid, C-reactive protein, diabetes, hypercholesteremia, multiple lesions for restenosis risk in everolimus-eluting stent-treated coronary heart disease patients |
title_short | A predictive model involving serum uric acid, C-reactive protein, diabetes, hypercholesteremia, multiple lesions for restenosis risk in everolimus-eluting stent-treated coronary heart disease patients |
title_sort | predictive model involving serum uric acid, c-reactive protein, diabetes, hypercholesteremia, multiple lesions for restenosis risk in everolimus-eluting stent-treated coronary heart disease patients |
topic | Cardiovascular Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9403046/ https://www.ncbi.nlm.nih.gov/pubmed/36035940 http://dx.doi.org/10.3389/fcvm.2022.857922 |
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