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A risk score model of contrast-induced acute kidney injury in patients with emergency percutaneous coronary interventions
BACKGROUND: The previously built score models of contrast-induced acute kidney injury (CI-AKI) were principally founded on selective percutaneous coronary intervention (PCI) cases. Our study was to form a risk score model of CI-AKI and make a temporal validation in a population who underwent emergen...
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/PMC9606750/ https://www.ncbi.nlm.nih.gov/pubmed/36312242 http://dx.doi.org/10.3389/fcvm.2022.989243 |
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author | Yuan, Ying Qiu, Hong Hu, Xiaoying Zhang, Jun Wu, Yuan Qiao, Shubin Yang, Yuejin Gao, Runlin |
author_facet | Yuan, Ying Qiu, Hong Hu, Xiaoying Zhang, Jun Wu, Yuan Qiao, Shubin Yang, Yuejin Gao, Runlin |
author_sort | Yuan, Ying |
collection | PubMed |
description | BACKGROUND: The previously built score models of contrast-induced acute kidney injury (CI-AKI) were principally founded on selective percutaneous coronary intervention (PCI) cases. Our study was to form a risk score model of CI-AKI and make a temporal validation in a population who underwent emergency PCIs. METHODS: We included patients who underwent emergency PCIs from 2013 to 2018 and divided them into the derivation and validation cohorts. Logistic regression analysis was harnessed to create the risk model. In this research, we defined CI-AKI as an increase in serum creatinine (SCr) ≥0.5 mg/dL (44.2 μmol/L) above baseline within seven days following exposure to contrast medium. RESULTS: A total of 3564 patients who underwent emergency PCIs were enrolled and divided into the derivation (2376 cases) and validation cohorts (1188 cases), with CI-AKI incidence of 6.61 and 5.39%, respectively. By logistic analysis, the CI-AKI risk score model was constituted by 8 variables: female (1 point), history of transient ischemic attack (TIA)/stroke (1 point), left ventricular ejection fraction (LVEF) classification (1 point per class), big endothelin-1 (ET-1) classification (1 point per class), estimated glomerular filtration rate (eGFR) classification (1 point per class), intra-aortic balloon pump (IABP) application (1 point), left anterior descending (LAD) stented (1 point), and administration of diuretic (2 points). The patients could be further divided into three groups: low-risk, moderate-risk, and high-risk groups, in accordance with the risk scores of 3–6, 7–10, and ≥11 points, and to the CI-AKI rates of 1.4, 11.9, and 42.6%. The CI-AKI risk score model performed well in discrimination (C statistic = 0.787, 95% CI: 0.731–0.844) and calibration ability, and showed a superior clinical utility. CONCLUSION: We developed a simple CI-AKI risk score model which performs well as a tool for CI-AKI prediction in patients who underwent emergency PCIs. |
format | Online Article Text |
id | pubmed-9606750 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-96067502022-10-28 A risk score model of contrast-induced acute kidney injury in patients with emergency percutaneous coronary interventions Yuan, Ying Qiu, Hong Hu, Xiaoying Zhang, Jun Wu, Yuan Qiao, Shubin Yang, Yuejin Gao, Runlin Front Cardiovasc Med Cardiovascular Medicine BACKGROUND: The previously built score models of contrast-induced acute kidney injury (CI-AKI) were principally founded on selective percutaneous coronary intervention (PCI) cases. Our study was to form a risk score model of CI-AKI and make a temporal validation in a population who underwent emergency PCIs. METHODS: We included patients who underwent emergency PCIs from 2013 to 2018 and divided them into the derivation and validation cohorts. Logistic regression analysis was harnessed to create the risk model. In this research, we defined CI-AKI as an increase in serum creatinine (SCr) ≥0.5 mg/dL (44.2 μmol/L) above baseline within seven days following exposure to contrast medium. RESULTS: A total of 3564 patients who underwent emergency PCIs were enrolled and divided into the derivation (2376 cases) and validation cohorts (1188 cases), with CI-AKI incidence of 6.61 and 5.39%, respectively. By logistic analysis, the CI-AKI risk score model was constituted by 8 variables: female (1 point), history of transient ischemic attack (TIA)/stroke (1 point), left ventricular ejection fraction (LVEF) classification (1 point per class), big endothelin-1 (ET-1) classification (1 point per class), estimated glomerular filtration rate (eGFR) classification (1 point per class), intra-aortic balloon pump (IABP) application (1 point), left anterior descending (LAD) stented (1 point), and administration of diuretic (2 points). The patients could be further divided into three groups: low-risk, moderate-risk, and high-risk groups, in accordance with the risk scores of 3–6, 7–10, and ≥11 points, and to the CI-AKI rates of 1.4, 11.9, and 42.6%. The CI-AKI risk score model performed well in discrimination (C statistic = 0.787, 95% CI: 0.731–0.844) and calibration ability, and showed a superior clinical utility. CONCLUSION: We developed a simple CI-AKI risk score model which performs well as a tool for CI-AKI prediction in patients who underwent emergency PCIs. Frontiers Media S.A. 2022-10-13 /pmc/articles/PMC9606750/ /pubmed/36312242 http://dx.doi.org/10.3389/fcvm.2022.989243 Text en Copyright © 2022 Yuan, Qiu, Hu, Zhang, Wu, Qiao, Yang and Gao. 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 Yuan, Ying Qiu, Hong Hu, Xiaoying Zhang, Jun Wu, Yuan Qiao, Shubin Yang, Yuejin Gao, Runlin A risk score model of contrast-induced acute kidney injury in patients with emergency percutaneous coronary interventions |
title | A risk score model of contrast-induced acute kidney injury in patients with emergency percutaneous coronary interventions |
title_full | A risk score model of contrast-induced acute kidney injury in patients with emergency percutaneous coronary interventions |
title_fullStr | A risk score model of contrast-induced acute kidney injury in patients with emergency percutaneous coronary interventions |
title_full_unstemmed | A risk score model of contrast-induced acute kidney injury in patients with emergency percutaneous coronary interventions |
title_short | A risk score model of contrast-induced acute kidney injury in patients with emergency percutaneous coronary interventions |
title_sort | risk score model of contrast-induced acute kidney injury in patients with emergency percutaneous coronary interventions |
topic | Cardiovascular Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9606750/ https://www.ncbi.nlm.nih.gov/pubmed/36312242 http://dx.doi.org/10.3389/fcvm.2022.989243 |
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