Frailty in general medicine patients receiving geriatric medicine liaison services is predictive of adverse outcomes

接受老年医学联络服务的内科患者的虚弱程度是预后不良的预测因素。

阅读:3

Abstract

INTRODUCTION: Frailty is in an increasing focus for acute care systems due to its association with adverse health outcomes. The Clinical Frailty Scale (CFS) is a judgement-based frailty assessment tool, which classifies the frailty status of older adults, but more research involving general medicine inpatients is necessary. The objectives of this study were to describe the predictive ability of CFS, administered by geriatric medicine trained nurses, for adverse outcomes including the following: acute unit and total length of stay (LOS), new nursing home (NH) admission, 12-month mortality and readmission within 30-day. METHODS: Design Retrospective study. Participants Patients admitted under general medicine unit and seen by the geriatric medicine liaison team in one general hospital. Main Measure CFS. RESULTS: Of 394 patients included, 60% were mild-moderately frail, and 21% severely frail. In a multivariable analysis, patients classified as severely frail (CFS 7-9) had significantly high odds of death during admission (OR = 13.64), new NH admission (OR = 34.97) and acute LOS (OR = 1.74), compared to non-frail patients (CFS1-4). Mild-moderately frail (CFS 5-6) patients had significantly higher odds for new NH admission (OR = 4.36), acute unit LOS (OR = 1.49) and total LOS (OR = 1.61) compared to non-frail patients. In a Cox regression multivariable survival analysis, the severely frail had a sixfold significantly higher likelihood (HR = 6.19) of 12-month mortality, and the mild-moderately frail had a doubled likelihood (HR = 2.13), compared to the non-frail. CONCLUSIONS: The CFS has clinical utility for identifying general medicine older inpatients at-risk of various adverse outcomes.

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。