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Combining Pulse Wave Velocity With Galectin-3 to Predict Mortality and Cerebrovascular and Cardiovascular Events in Hemodialysis Patients
Background: Cerebrovascular and cardiovascular diseases contribute substantially to the mortality of end-stage renal disease patients. We sought to combine pulse wave velocity (PWV) with galectin-3 to predict the mortality and cerebrovascular and cardiovascular events in hemodialysis patients. Metho...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7606274/ https://www.ncbi.nlm.nih.gov/pubmed/33195327 http://dx.doi.org/10.3389/fmed.2020.579021 |
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author | Zhang, Qi Yin, Kanhua Zhu, Mingli Lin, Xinghui Fang, Yan Lu, Jiayue Li, Zhenyuan Ni, Zhaohui |
author_facet | Zhang, Qi Yin, Kanhua Zhu, Mingli Lin, Xinghui Fang, Yan Lu, Jiayue Li, Zhenyuan Ni, Zhaohui |
author_sort | Zhang, Qi |
collection | PubMed |
description | Background: Cerebrovascular and cardiovascular diseases contribute substantially to the mortality of end-stage renal disease patients. We sought to combine pulse wave velocity (PWV) with galectin-3 to predict the mortality and cerebrovascular and cardiovascular events in hemodialysis patients. Methods and Results: End-stage renal disease patients who underwent stable hemodialysis were screened for inclusion. Patients with preexisting cardiovascular and cerebrovascular diseases were excluded. The primary endpoint was a composite of all-cause mortality and major adverse cerebrovascular and cardiovascular events. Receiver operating characteristic curve analysis was used to determine the optimal cutoffs to dichotomize PWV and galectin-3. The study population was then stratified into four groups based on these cutoffs. Both univariable and multivariable Cox regression analyses were performed to estimate the hazard ratio and 95% confidence interval (CI) for clinical factors. Model performance was compared among models with or without PWV and galectin-3. A total of 284 patients were enrolled. During a median follow-up of 31 months, 57 patients (20.1%) reached the primary endpoint. The optimal cutoffs for PWV and galectin-3 were 7.9 m/s and 30.5 ng/ml, respectively. In the multivariable regression analysis, the high PWV–high galectin-3 group was associated with a 3-fold increased risk of all-cause mortality and major adverse cerebrovascular and cardiovascular events (hazard ratio = 3.19, 95% CI: 1.05–9.66, p = 0.04) compared with the low PWV–low galectin-3 group. The combination of PWV and galectin-3 was associated with improved model discrimination, calibration, and reclassification. Conclusions: The combination of PWV and galectin-3 can be used to predict mortality and cerebral and cardiovascular complications in hemodialysis patients. |
format | Online Article Text |
id | pubmed-7606274 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-76062742020-11-13 Combining Pulse Wave Velocity With Galectin-3 to Predict Mortality and Cerebrovascular and Cardiovascular Events in Hemodialysis Patients Zhang, Qi Yin, Kanhua Zhu, Mingli Lin, Xinghui Fang, Yan Lu, Jiayue Li, Zhenyuan Ni, Zhaohui Front Med (Lausanne) Medicine Background: Cerebrovascular and cardiovascular diseases contribute substantially to the mortality of end-stage renal disease patients. We sought to combine pulse wave velocity (PWV) with galectin-3 to predict the mortality and cerebrovascular and cardiovascular events in hemodialysis patients. Methods and Results: End-stage renal disease patients who underwent stable hemodialysis were screened for inclusion. Patients with preexisting cardiovascular and cerebrovascular diseases were excluded. The primary endpoint was a composite of all-cause mortality and major adverse cerebrovascular and cardiovascular events. Receiver operating characteristic curve analysis was used to determine the optimal cutoffs to dichotomize PWV and galectin-3. The study population was then stratified into four groups based on these cutoffs. Both univariable and multivariable Cox regression analyses were performed to estimate the hazard ratio and 95% confidence interval (CI) for clinical factors. Model performance was compared among models with or without PWV and galectin-3. A total of 284 patients were enrolled. During a median follow-up of 31 months, 57 patients (20.1%) reached the primary endpoint. The optimal cutoffs for PWV and galectin-3 were 7.9 m/s and 30.5 ng/ml, respectively. In the multivariable regression analysis, the high PWV–high galectin-3 group was associated with a 3-fold increased risk of all-cause mortality and major adverse cerebrovascular and cardiovascular events (hazard ratio = 3.19, 95% CI: 1.05–9.66, p = 0.04) compared with the low PWV–low galectin-3 group. The combination of PWV and galectin-3 was associated with improved model discrimination, calibration, and reclassification. Conclusions: The combination of PWV and galectin-3 can be used to predict mortality and cerebral and cardiovascular complications in hemodialysis patients. Frontiers Media S.A. 2020-10-20 /pmc/articles/PMC7606274/ /pubmed/33195327 http://dx.doi.org/10.3389/fmed.2020.579021 Text en Copyright © 2020 Zhang, Yin, Zhu, Lin, Fang, Lu, Li and Ni. http://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 | Medicine Zhang, Qi Yin, Kanhua Zhu, Mingli Lin, Xinghui Fang, Yan Lu, Jiayue Li, Zhenyuan Ni, Zhaohui Combining Pulse Wave Velocity With Galectin-3 to Predict Mortality and Cerebrovascular and Cardiovascular Events in Hemodialysis Patients |
title | Combining Pulse Wave Velocity With Galectin-3 to Predict Mortality and Cerebrovascular and Cardiovascular Events in Hemodialysis Patients |
title_full | Combining Pulse Wave Velocity With Galectin-3 to Predict Mortality and Cerebrovascular and Cardiovascular Events in Hemodialysis Patients |
title_fullStr | Combining Pulse Wave Velocity With Galectin-3 to Predict Mortality and Cerebrovascular and Cardiovascular Events in Hemodialysis Patients |
title_full_unstemmed | Combining Pulse Wave Velocity With Galectin-3 to Predict Mortality and Cerebrovascular and Cardiovascular Events in Hemodialysis Patients |
title_short | Combining Pulse Wave Velocity With Galectin-3 to Predict Mortality and Cerebrovascular and Cardiovascular Events in Hemodialysis Patients |
title_sort | combining pulse wave velocity with galectin-3 to predict mortality and cerebrovascular and cardiovascular events in hemodialysis patients |
topic | Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7606274/ https://www.ncbi.nlm.nih.gov/pubmed/33195327 http://dx.doi.org/10.3389/fmed.2020.579021 |
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