Risk Factors for 1-Year Mortality and Hospital Utilization Patterns in Critical Care Survivors: A Retrospective, Observational, Population-Based Data Linkage Study

重症监护幸存者一年死亡率和住院模式的风险因素:一项回顾性、观察性、基于人群的数据链接研究

阅读:2

Abstract

OBJECTIVES: Clear understanding of the long-term consequences of critical care survivorship is essential. We investigated the care process and individual factors associated with long-term mortality among ICU survivors and explored hospital use in this group. DESIGN: Population-based data linkage study using the Secure Anonymised Information Linkage databank. SETTING: All ICUs between 2006 and 2013 in Wales, United Kingdom. PATIENTS: We identified 40,631 patients discharged alive from Welsh adult ICUs. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Primary outcome was 365-day survival. The secondary outcomes were 30- and 90-day survival and hospital utilization in the 365 days following ICU discharge. Kaplan-Meier curves were plotted to compare survival rates. Cox proportional hazards regression models were used to determine risk factors of mortality. Seven-thousand eight-hundred eighty-three patients (19.4%) died during the 1-year follow-up period. In the multivariable Cox regression analysis, advanced age and comorbidities were significant determinants of long-term mortality. Expedited discharge due to ICU bed shortage was associated with higher risk. The rate of hospitalization in the year prior to the critical care admission was 28 hospitalized days/1,000 d; post critical care was 88 hospitalized days/1,000 d for those who were still alive; and 57 hospitalized days/1,000 d and 412 hospitalized days/1,000 d for those who died by the end of the study, respectively. CONCLUSIONS: One in five ICU survivors die within 1 year, with advanced age and comorbidity being significant predictors of outcome, leading to high resource use. Care process factors indicating high system stress were associated with increased risk. More detailed understanding is needed on the effects of the potentially modifiable factors to optimize service delivery and improve long-term outcomes of the critically ill.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。