Literature DB >> 34126362

Big Data Analysis of the Risk of Intracranial Hemorrhage in Korean Populations Taking Low-Dose Aspirin.

Tae Gon Kim1, Soyoung Yu2.   

Abstract

OBJECTIVES: Aspirin has traditionally been used as an analgesic and anti-inflammatory drug; however, low-dose aspirin is known to increase the risk of gastrointestinal and intracranial hemorrhage. In this study, the risk of intracranial hemorrhage in patients taking low-dose aspirin was assessed.
MATERIALS AND METHODS: We used the Standard Sample Cohort DB dataset from the National Health Insurance Sharing Service of Korea. This dataset includes details of medical care and prescriptions for patients who used hospital services during a 14-year period throughout Korea. Of approximately 1 million total patients, data from 746,703 adults over the age of 30 years were included for analysis. An Χ2 test was performed to assess the effect of low-dose aspirin on intracranial hemorrhage. In addition, the relationship between use of low-dose aspirin and intracranial hemorrhage was analyzed using multiple logistic regression with consideration of all confounding variables.
RESULTS: The results revealed no significant positive correlations between the use of low-dose aspirin and intracranial hemorrhage requiring hospitalization.
CONCLUSIONS: Big data analysis of 746,703 patients in Korea over a period of 14 years showed that serious intracranial hemorrhage requiring hospitalization was unrelated to low-dose aspirin use. Moreover, low-dose aspirin use reduced the risk of intracranial hemorrhage in Korean populations.
Copyright © 2021 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Aspirin; Big data; Intracranial hemorrhage; Statistics

Year:  2021        PMID: 34126362     DOI: 10.1016/j.jstrokecerebrovasdis.2021.105917

Source DB:  PubMed          Journal:  J Stroke Cerebrovasc Dis        ISSN: 1052-3057            Impact factor:   2.136


  1 in total

1.  Big Data Analysis and Application of Liver Cancer Gene Sequence Based on Second-Generation Sequencing Technology.

Authors:  Chaohui Xiao; Fuchuan Wang; Tianye Jia; Liru Pan; Zhaohai Wang
Journal:  Comput Math Methods Med       Date:  2022-08-16       Impact factor: 2.809

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.