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

<i>Background</i>: 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...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Ming-Hsien Tsai, Hung-Hsiang Liou, Yen-Chun Huang, Tian-Shyug Lee, Mingchih Chen, Yu-Wei Fang
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	chronic kidney disease real-world evidence machine learning aspirin nonsteroidal anti-inflammatory drugs dialysis Medicine R
Acceso en línea:	https://doaj.org/article/32b7f629c96148328af6c502461415dd
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:32b7f629c96148328af6c502461415dd
record_format	dspace
spelling	oai:doaj.org-article:32b7f629c96148328af6c502461415dd2021-11-25T17:44:37ZHazardous Effect of Low-Dose Aspirin in Patients with Predialysis Advanced Chronic Kidney Disease Assessed by Machine Learning Method Feature Selection10.3390/healthcare91114842227-9032https://doaj.org/article/32b7f629c96148328af6c502461415dd2021-10-01T00:00:00Zhttps://www.mdpi.com/2227-9032/9/11/1484https://doaj.org/toc/2227-9032<i>Background</i>: 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. <i>Methods</i>: 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 (<i>n</i> = 3021) and a control group without aspirin use (<i>n</i> = 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. <i>Results</i>: 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]). <i>Conclusions</i>: 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.Ming-Hsien TsaiHung-Hsiang LiouYen-Chun HuangTian-Shyug LeeMingchih ChenYu-Wei FangMDPI AGarticlechronic kidney diseasereal-world evidencemachine learningaspirinnonsteroidal anti-inflammatory drugsdialysisMedicineRENHealthcare, Vol 9, Iss 1484, p 1484 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	chronic kidney disease real-world evidence machine learning aspirin nonsteroidal anti-inflammatory drugs dialysis Medicine R
spellingShingle	chronic kidney disease real-world evidence machine learning aspirin nonsteroidal anti-inflammatory drugs dialysis Medicine R Ming-Hsien Tsai Hung-Hsiang Liou Yen-Chun Huang Tian-Shyug Lee Mingchih Chen Yu-Wei Fang Hazardous Effect of Low-Dose Aspirin in Patients with Predialysis Advanced Chronic Kidney Disease Assessed by Machine Learning Method Feature Selection
description	<i>Background</i>: 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. <i>Methods</i>: 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 (<i>n</i> = 3021) and a control group without aspirin use (<i>n</i> = 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. <i>Results</i>: 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]). <i>Conclusions</i>: 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.
format	article
author	Ming-Hsien Tsai Hung-Hsiang Liou Yen-Chun Huang Tian-Shyug Lee Mingchih Chen Yu-Wei Fang
author_facet	Ming-Hsien Tsai Hung-Hsiang Liou Yen-Chun Huang Tian-Shyug Lee Mingchih Chen Yu-Wei Fang
author_sort	Ming-Hsien Tsai
title	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_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_sort	hazardous effect of low-dose aspirin in patients with predialysis advanced chronic kidney disease assessed by machine learning method feature selection
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/32b7f629c96148328af6c502461415dd
work_keys_str_mv	AT minghsientsai hazardouseffectoflowdoseaspirininpatientswithpredialysisadvancedchronickidneydiseaseassessedbymachinelearningmethodfeatureselection AT hunghsiangliou hazardouseffectoflowdoseaspirininpatientswithpredialysisadvancedchronickidneydiseaseassessedbymachinelearningmethodfeatureselection AT yenchunhuang hazardouseffectoflowdoseaspirininpatientswithpredialysisadvancedchronickidneydiseaseassessedbymachinelearningmethodfeatureselection AT tianshyuglee hazardouseffectoflowdoseaspirininpatientswithpredialysisadvancedchronickidneydiseaseassessedbymachinelearningmethodfeatureselection AT mingchihchen hazardouseffectoflowdoseaspirininpatientswithpredialysisadvancedchronickidneydiseaseassessedbymachinelearningmethodfeatureselection AT yuweifang hazardouseffectoflowdoseaspirininpatientswithpredialysisadvancedchronickidneydiseaseassessedbymachinelearningmethodfeatureselection
_version_	1718412035520200704

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

Ejemplares similares