five

Urinary Incontinence as a Predictor of Death: A Systematic Review and Meta-Analysis

收藏
Figshare2016-09-28 更新2026-04-29 收录
下载链接:
https://figshare.com/articles/dataset/Urinary_Incontinence_as_a_Predictor_of_Death_A_Systematic_Review_and_Meta-Analysis/3901887
下载链接
链接失效反馈
官方服务:
资源简介:
BackgroundThe association between urinary incontinence (UI) and increased mortality remains controversial. The objective of our study was to evaluate if this association exists.MethodsWe performed a systematic review and meta-analysis of observational studies comparing death rates among patients suffering from UI to those without incontinence. We searched in Medline, Embase and the Cochrane library using specific keywords. Studies exploring the post-stroke period were excluded. Hazard ratios (HR) were pooled using models with random effects. We stratified UI by gender and by UI severity and pooled all models with adjustment for confounding variables.ResultsThirty-eight studies were retrieved. When compared to non-urinary incontinent participants, UI was associated with an increase in mortality with pooled non adjusted HR of 2.22 (95%CI 1.77–2.78). The risk increased with UI severity: 1.24 (95%CI: 0.79–1.97) for light, 1.71 (95%CI: 1.26–2.31) for moderate, and 2.72 (95%CI: 1.90–3.87) for severe UI respectively. When pooling adjusted measures of association, the resulting HR was 1.27 (95%CI: 1.13–1.42) and increased progressively for light, moderate and severe UI: 1.07 (95%CI: 0.79–1.44), 1.25 (95%CI: 0.99–1.58), and 1.47 (95%CI: 1.03–2.10) respectively. There was no difference between genders.ConclusionUI is a predictor of higher mortality in the general and particularly in the geriatric population. The association increases with the severity of UI and persists when pooling models adjusted for confounders. It is unclear if this association is causative or just reflects an impaired general health condition. As in most meta-analyses of observational studies, methodological issues should be considered when interpreting results.
创建时间:
2016-09-28
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作