Suppr超能文献

使用功能活动能力测量来预测入住老年康复病房患者的出院去向:一项可行性研究。

Use of a functional mobility measure to predict discharge destinations for patients admitted to an older adult rehabilitation ward: A feasibility study.

作者信息

Tillson Trish, Rohan Maheswaran, Larmer Peter J

机构信息

Auckland City Hospital, Auckland, New Zealand.

Department of Biostatistics and Epidemiology, Auckland University of Technology, Auckland, New Zealand.

出版信息

Australas J Ageing. 2018 Mar;37(1):E12-E16. doi: 10.1111/ajag.12491. Epub 2017 Dec 27.

Abstract

OBJECTIVE

To investigate whether the discharge destination for older adults can be predicted using functional mobility as measured by the Modified Elderly Mobility Scale (MEMS), associated with demographic and primary reason for admission variables.

METHODS

A retrospective cohort population audit of 257 patients admitted and discharged from four tertiary older adult rehabilitation wards in a three-month period. A number of predictor variables were considered alongside the discharge destination.

RESULTS

Multinomial statistical modelling established that MEMS prior to (P < 0.001), MEMS on completion (P = 0.009) of rehabilitation physiotherapy and primary reason for admission (P = 0.002) were significant variables to predict discharge destination. The model correctly predicted 71% of observed patient discharge destinations.

CONCLUSION

The MEMS in conjunction with primary reason for admission was able to predict discharge destination with 71% accuracy in a heterogeneous population of older adults following rehabilitation.

摘要

目的

探讨能否使用改良老年活动量表(MEMS)所测量的功能活动能力,并结合人口统计学和入院主要原因变量,来预测老年人的出院去向。

方法

对三个月内从四个三级老年康复病房收治并出院的257例患者进行回顾性队列人群审计。除出院去向外,还考虑了一些预测变量。

结果

多项统计建模表明,康复物理治疗前的MEMS(P < 0.001)、康复物理治疗结束时的MEMS(P = 0.009)以及入院主要原因(P = 0.002)是预测出院去向的显著变量。该模型正确预测了71%的观察到的患者出院去向。

结论

在异质性老年人群康复后,MEMS结合入院主要原因能够以71%的准确率预测出院去向。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验