• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

用 6 项简明老年评估工具预测住院死亡率:一项观察性前瞻性队列研究。

Prediction of in-hospital mortality with the 6-item Brief Geriatric Assessment tool: An observational prospective cohort study.

机构信息

Service of Geriatric Medicine and Geriatric Rehabilitation, Department of Medicine, Lausanne University Hospital, Switzerland.

Department of Neuroscience, Division of Geriatric Medicine, Angers University Hospital, Angers, France.

出版信息

Maturitas. 2018 Apr;110:57-61. doi: 10.1016/j.maturitas.2018.01.018. Epub 2018 Jan 31.

DOI:10.1016/j.maturitas.2018.01.018
PMID:29563036
Abstract

BACKGROUND

The 6-item Brief Geriatric Assessment (BGA) is a screening tool to identify frail inpatients who are at risk of adverse health events. Its predictive value for in-hospital mortality has not been examined yet.

OBJECTIVE

This study examined whether the BGA is able to predict in-hospital mortality in older patients.

METHODS

A total of 1082 participants were included in this observational prospective cohort study. At their admission to the medical wards of Angers University Hospital (France), all inpatients aged ≥65 years were screened with the BGA. Its 6 items are: age ≥85 years, male gender, polypharmacy (i.e., ≥5 drugs per day), non-use of home-help services, history of falls in the previous 6 months, and temporal disorientation (i.e., inability to give the month and/or year). Three levels (low, intermediate and high) of risk of adverse health events had previously been identified, based on different combinations of BGA items. Patients were separated into 2 groups using the occurrence of in-hospital death. The length of stay was calculated as the number of days in hospital using the hospital registry. The use of psychoactive drugs and the reason for admission were used as covariates.

RESULTS

Older inpatients who died were more frequently admitted for an acute organ failure (P < 0.001). Cox regression models showed that a priori intermediate risk (HR = 1.89, P < .001) and high risk (HR = 2.34, P < .001) risk levels predicted in-hospital mortality. Kaplan-Meier survival curves confirmed that inpatients at high risk (P = .047) and those at intermediate risk (P = .013) died earlier than patients at low risk.

CONCLUSIONS

Combinations of items on the BGA successfully predicted the risk of in-hospital mortality in this sample of older inpatients.

摘要

背景

6 项简明老年评估(BGA)是一种筛选工具,用于识别有发生不良健康事件风险的虚弱住院患者。其对住院患者死亡率的预测价值尚未得到检验。

目的

本研究旨在检验 BGA 是否能够预测老年患者的住院死亡率。

方法

本观察性前瞻性队列研究共纳入 1082 名参与者。在法国昂热大学医院的内科病房,所有年龄≥65 岁的住院患者均接受 BGA 筛查。其 6 项内容为:年龄≥85 岁、男性、多种药物(即每天≥5 种药物)、不使用家庭帮助服务、过去 6 个月内跌倒史、时间定向障碍(即无法给出月份和/或年份)。此前,根据 BGA 项目的不同组合,确定了 3 个不良健康事件风险水平(低、中、高)。根据住院期间死亡的发生情况,将患者分为 2 组。使用医院登记册计算住院天数作为住院时间。将使用精神活性药物和入院原因作为协变量。

结果

死亡的老年住院患者更常因急性器官衰竭而入院(P<0.001)。Cox 回归模型显示,预先设定的中危(HR=1.89,P<0.001)和高危(HR=2.34,P<0.001)风险水平预测了住院死亡率。Kaplan-Meier 生存曲线证实,高危(P=0.047)和中危(P=0.013)患者的死亡率高于低危患者。

结论

BGA 项目的组合成功预测了该老年住院患者样本的住院死亡率风险。

相似文献

1
Prediction of in-hospital mortality with the 6-item Brief Geriatric Assessment tool: An observational prospective cohort study.用 6 项简明老年评估工具预测住院死亡率:一项观察性前瞻性队列研究。
Maturitas. 2018 Apr;110:57-61. doi: 10.1016/j.maturitas.2018.01.018. Epub 2018 Jan 31.
2
Predicting a long hospital stay after admission to a geriatric assessment unit: Results from an observational retrospective cohort study.预测老年评估单元入院后住院时间延长:一项观察性回顾性队列研究的结果。
Maturitas. 2018 Sep;115:110-114. doi: 10.1016/j.maturitas.2018.06.014. Epub 2018 Jul 2.
3
Screening for older emergency department inpatients at risk of prolonged hospital stay: the brief geriatric assessment tool.筛查有延长住院时间风险的老年急诊科住院患者:简易老年综合评估工具。
PLoS One. 2014 Oct 15;9(10):e110135. doi: 10.1371/journal.pone.0110135. eCollection 2014.
4
Risk of in-hospital mortality following emergency department admission: results from the geriatric EDEN cohort study.急诊就诊后院内死亡率风险:老年急诊 EDEN 队列研究的结果。
J Nutr Health Aging. 2014 Jan;18(1):83-6. doi: 10.1007/s12603-013-0038-3.
5
Prediction of unplanned hospital admissions in older community dwellers using the 6-item Brief Geriatric Assessment: Results from REPERAGE, an observational prospective population-based cohort study.使用 6 项简明老年评估预测老年社区居民的非计划性住院:来自 REPERAGE 的观察性前瞻性基于人群队列研究的结果。
Maturitas. 2019 Apr;122:1-7. doi: 10.1016/j.maturitas.2019.01.002. Epub 2019 Jan 3.
6
Predicting prolonged length of hospital stay in older emergency department users: use of a novel analysis method, the Artificial Neural Network.预测老年急诊科患者住院时间延长:使用新型分析方法,人工神经网络。
Eur J Intern Med. 2015 Sep;26(7):478-82. doi: 10.1016/j.ejim.2015.06.002. Epub 2015 Jul 2.
7
Risk of Unplanned Emergency Department Readmission after an Acute-Care Hospital Discharge among Geriatric Inpatients: Results from the Geriatric EDEN Cohort Study.老年住院患者急性护理医院出院后非计划重返急诊科的风险:老年急诊科队列研究结果
J Nutr Health Aging. 2016 Feb;20(2):210-7. doi: 10.1007/s12603-015-0624-7.
8
Age effect on the prediction of risk of prolonged length hospital stay in older patients visiting the emergency department: results from a large prospective geriatric cohort study.年龄对预测老年急诊患者住院时间延长风险的影响:一项大型前瞻性老年队列研究的结果。
BMC Geriatr. 2018 May 30;18(1):127. doi: 10.1186/s12877-018-0820-5.
9
Screening for older inpatients at risk for long length of stay: which clinical tool to use?筛查有长期住院风险的老年住院患者:应使用哪种临床工具?
BMC Geriatr. 2019 Jun 6;19(1):156. doi: 10.1186/s12877-019-1165-4.
10
Screening for elderly patients admitted to the emergency department requiring specialized geriatric care.对入住急诊科且需要专科老年护理的老年患者进行筛查。
J Emerg Med. 2013 Nov;45(5):739-45. doi: 10.1016/j.jemermed.2012.11.110. Epub 2013 Jun 5.

引用本文的文献

1
Assessment of inflammatory markers, disease severity and comorbidities in very elderly patients with acute respiratory diseases.评估高龄急性呼吸道疾病患者的炎症标志物、疾病严重程度及合并症。
Arch Med Sci. 2020 Apr 18;21(2):451-462. doi: 10.5114/aoms.2020.94495. eCollection 2025.