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Hazardous Effect of Low-Dose Aspirin in Patients with Predialysis Advanced Chronic Kidney Disease Assessed by Machine Learning Method Feature Selection

Background: Low-dose aspirin (100 mg) is widely used in preventing cardiovascular disease in chronic kidney disease (CKD) because its benefits outweighs the harm, however, its effect on clinical outcomes in patients with predialysis advanced CKD is still unclear. This study aimed to assess the effec...

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Autores principales: Tsai, Ming-Hsien, Liou, Hung-Hsiang, Huang, Yen-Chun, Lee, Tian-Shyug, Chen, Mingchih, Fang, Yu-Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8625790/
https://www.ncbi.nlm.nih.gov/pubmed/34828530
http://dx.doi.org/10.3390/healthcare9111484
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author Tsai, Ming-Hsien
Liou, Hung-Hsiang
Huang, Yen-Chun
Lee, Tian-Shyug
Chen, Mingchih
Fang, Yu-Wei
author_facet Tsai, Ming-Hsien
Liou, Hung-Hsiang
Huang, Yen-Chun
Lee, Tian-Shyug
Chen, Mingchih
Fang, Yu-Wei
author_sort Tsai, Ming-Hsien
collection PubMed
description Background: Low-dose aspirin (100 mg) is widely used in preventing cardiovascular disease in chronic kidney disease (CKD) because its benefits outweighs the harm, however, its effect on clinical outcomes in patients with predialysis advanced CKD is still unclear. This study aimed to assess the effect of aspirin use on clinical outcomes in such group. Methods: Patients were selected from a nationwide diabetes database from January 2009 to June 2017, and divided into two groups, a case group with aspirin use (n = 3021) and a control group without aspirin use (n = 9063), by propensity score matching with a 1:3 ratio. The Cox regression model was used to estimate the hazard ratio (HR). Moreover, machine learning method feature selection was used to assess the importance of parameters in the clinical outcomes. Results: In a mean follow-up of 1.54 years, aspirin use was associated with higher risk for entering dialysis (HR, 1.15 [95%CI, 1.10–1.21]) and death before entering dialysis (1.46 [1.25–1.71]), which were also supported by feature selection. The renal effect of aspirin use was consistent across patient subgroups. Nonusers and aspirin users did not show a significant difference, except for gastrointestinal bleeding (1.05 [0.96–1.15]), intracranial hemorrhage events (1.23 [0.98–1.55]), or ischemic stroke (1.15 [0.98–1.55]). Conclusions: Patients with predialysis advanced CKD and anemia who received aspirin exhibited higher risk of entering dialysis and death before entering dialysis by 15% and 46%, respectively.
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spelling pubmed-86257902021-11-27 Hazardous Effect of Low-Dose Aspirin in Patients with Predialysis Advanced Chronic Kidney Disease Assessed by Machine Learning Method Feature Selection Tsai, Ming-Hsien Liou, Hung-Hsiang Huang, Yen-Chun Lee, Tian-Shyug Chen, Mingchih Fang, Yu-Wei Healthcare (Basel) Article Background: Low-dose aspirin (100 mg) is widely used in preventing cardiovascular disease in chronic kidney disease (CKD) because its benefits outweighs the harm, however, its effect on clinical outcomes in patients with predialysis advanced CKD is still unclear. This study aimed to assess the effect of aspirin use on clinical outcomes in such group. Methods: Patients were selected from a nationwide diabetes database from January 2009 to June 2017, and divided into two groups, a case group with aspirin use (n = 3021) and a control group without aspirin use (n = 9063), by propensity score matching with a 1:3 ratio. The Cox regression model was used to estimate the hazard ratio (HR). Moreover, machine learning method feature selection was used to assess the importance of parameters in the clinical outcomes. Results: In a mean follow-up of 1.54 years, aspirin use was associated with higher risk for entering dialysis (HR, 1.15 [95%CI, 1.10–1.21]) and death before entering dialysis (1.46 [1.25–1.71]), which were also supported by feature selection. The renal effect of aspirin use was consistent across patient subgroups. Nonusers and aspirin users did not show a significant difference, except for gastrointestinal bleeding (1.05 [0.96–1.15]), intracranial hemorrhage events (1.23 [0.98–1.55]), or ischemic stroke (1.15 [0.98–1.55]). Conclusions: Patients with predialysis advanced CKD and anemia who received aspirin exhibited higher risk of entering dialysis and death before entering dialysis by 15% and 46%, respectively. MDPI 2021-10-31 /pmc/articles/PMC8625790/ /pubmed/34828530 http://dx.doi.org/10.3390/healthcare9111484 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Tsai, Ming-Hsien
Liou, Hung-Hsiang
Huang, Yen-Chun
Lee, Tian-Shyug
Chen, Mingchih
Fang, Yu-Wei
Hazardous Effect of Low-Dose Aspirin in Patients with Predialysis Advanced Chronic Kidney Disease Assessed by Machine Learning Method Feature Selection
title Hazardous Effect of Low-Dose Aspirin in Patients with Predialysis Advanced Chronic Kidney Disease Assessed by Machine Learning Method Feature Selection
title_full Hazardous Effect of Low-Dose Aspirin in Patients with Predialysis Advanced Chronic Kidney Disease Assessed by Machine Learning Method Feature Selection
title_fullStr Hazardous Effect of Low-Dose Aspirin in Patients with Predialysis Advanced Chronic Kidney Disease Assessed by Machine Learning Method Feature Selection
title_full_unstemmed Hazardous Effect of Low-Dose Aspirin in Patients with Predialysis Advanced Chronic Kidney Disease Assessed by Machine Learning Method Feature Selection
title_short Hazardous Effect of Low-Dose Aspirin in Patients with Predialysis Advanced Chronic Kidney Disease Assessed by Machine Learning Method Feature Selection
title_sort hazardous effect of low-dose aspirin in patients with predialysis advanced chronic kidney disease assessed by machine learning method feature selection
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8625790/
https://www.ncbi.nlm.nih.gov/pubmed/34828530
http://dx.doi.org/10.3390/healthcare9111484
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