Gender Difference in Prognosis of Patients with Heart Failure: A Propensity Score Matching Analysis

Xue Zhou, Xin Zhu, Keijiro Nakamura, Ming Huang
{"title":"Gender Difference in Prognosis of Patients with Heart Failure: A Propensity Score Matching Analysis","authors":"Xue Zhou, Xin Zhu, Keijiro Nakamura, Ming Huang","doi":"10.1109/BHI56158.2022.9926861","DOIUrl":null,"url":null,"abstract":"Heart failure (HF) has been a global health concern with high prevalence, mortality and costs. A reliable prognostic prediction for HF was essential. Despite advances in predicting adverse outcomes in patients with HF, limited studies considered or specifically explored the effect of gender differences on prognosis. In this study, we estimated the gender differences in prognosis of patients with HF based on a propensity score matched cohort. Missing data were handled by a multiple imputation method using regression with predictive mean matching. Thereafter, propensity score matching (PSM) was performed with a single hidden layer neural network in a 1:1 matching (male vs. female). Totally, 730 patients with HF were enrolled in this study, (male: 399; female: 331). After PSM analysis, 364 patients were matched (male: 182; female: 182) and important prognostic factors including age, echocardiographic variables, and variables related to kidney function were balanced between female and male groups. This study demonstrated that female gender had better overall survival than that of male (hazard ratio of allcause mortality between female and male: 0.593; 95% confidence interval(CI), 0.353-0.996, p = 0.048) but prognosis conditions involving cardiovascular survival and HF-related readmission had no significant difference between male and female patients (cardiovascular mortality: hazard ratio: 0.669; 95%CI, 0.3111.443, p = 0.306; HF-related readmission: hazard ratio:0.828; 95%CI, 0.549-1.250, p = 0.370).","PeriodicalId":347210,"journal":{"name":"2022 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)","volume":"93 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BHI56158.2022.9926861","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Heart failure (HF) has been a global health concern with high prevalence, mortality and costs. A reliable prognostic prediction for HF was essential. Despite advances in predicting adverse outcomes in patients with HF, limited studies considered or specifically explored the effect of gender differences on prognosis. In this study, we estimated the gender differences in prognosis of patients with HF based on a propensity score matched cohort. Missing data were handled by a multiple imputation method using regression with predictive mean matching. Thereafter, propensity score matching (PSM) was performed with a single hidden layer neural network in a 1:1 matching (male vs. female). Totally, 730 patients with HF were enrolled in this study, (male: 399; female: 331). After PSM analysis, 364 patients were matched (male: 182; female: 182) and important prognostic factors including age, echocardiographic variables, and variables related to kidney function were balanced between female and male groups. This study demonstrated that female gender had better overall survival than that of male (hazard ratio of allcause mortality between female and male: 0.593; 95% confidence interval(CI), 0.353-0.996, p = 0.048) but prognosis conditions involving cardiovascular survival and HF-related readmission had no significant difference between male and female patients (cardiovascular mortality: hazard ratio: 0.669; 95%CI, 0.3111.443, p = 0.306; HF-related readmission: hazard ratio:0.828; 95%CI, 0.549-1.250, p = 0.370).
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
心力衰竭患者预后的性别差异:倾向评分匹配分析
心力衰竭(HF)一直是全球关注的健康问题,其发病率、死亡率和成本都很高。可靠的心衰预后预测至关重要。尽管在预测心衰患者不良结局方面取得了进展,但有限的研究考虑或专门探讨了性别差异对预后的影响。在这项研究中,我们基于倾向性评分匹配队列估计了心衰患者预后的性别差异。缺失数据采用回归预测均值匹配的多重插值方法进行处理。然后,采用单隐层神经网络进行倾向评分匹配(PSM),匹配比例为1:1(男女)。共有730例心衰患者纳入本研究,(男性399例;女:331)。经PSM分析,匹配364例患者(男性182例;女性:182),重要的预后因素包括年龄、超声心动图变量和肾功能相关变量在男女组之间是平衡的。本研究表明,女性的总生存率高于男性(男女全因死亡率危险比:0.593;95%可信区间(CI) 0.353-0.996, p = 0.048),但涉及心血管生存和hf相关再入院的预后条件在男性和女性患者之间无显著差异(心血管死亡率:危险比:0.669;95%CI, 0.3111.443, p = 0.306;hf相关再入院:风险比:0.828;95%CI, 0.549-1.250, p = 0.370)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
BEBOP: Bidirectional dEep Brain cOnnectivity maPping Stabilizing Skeletal Pose Estimation using mmWave Radar via Dynamic Model and Filtering Behavioral Data Categorization for Transformers-based Models in Digital Health Gender Difference in Prognosis of Patients with Heart Failure: A Propensity Score Matching Analysis Influence of Sensor Position and Body Movements on Radar-Based Heart Rate Monitoring
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1