Suppr超能文献

预测出院后对支持性服务的需求:系统评价。

Predicting the need for supportive services after discharged from hospital: a systematic review.

机构信息

Department of Medicine, Division of General Internal Medicine, The Ottawa Hospital, Civic Campus, 1053 Carling Avenue, Ottawa, Ontario, ON K1Y 4E9, Canada.

Department of Medicine, University of Ottawa, Ottawa, Ontario, Canada.

出版信息

BMC Health Serv Res. 2020 Mar 4;20(1):161. doi: 10.1186/s12913-020-4972-6.

Abstract

BACKGROUND

Some patients admitted to acute care hospital require supportive services after discharge. The objective of our review was to identify models and variables that predict the need for supportive services after discharge from acute care hospital.

METHODS

We performed a systematic review searching the MEDLINE, CINAHL, EMBASE, and COCHRANE databases from inception to May 1st 2017. We selected studies that derived and validated a prediction model for the need for supportive services after hospital discharge for patients admitted non-electively to a medical ward. We extracted cohort characteristics, model characteristics and variables screened and included in final predictive models. Risk of bias was assessed using the Quality in Prognostic Studies tool.

RESULTS

Our search identified 3362 unique references. Full text review identified 6 models. Models had good discrimination in derivation (c-statistics > 0.75) and validation (c-statistics > 0.70) cohorts. There was high quality evidence that age, impaired physical function, disabilities in performing activities of daily living, absence of an informal care giver and frailty predict the need for supportive services after discharge. Stroke was the only unique diagnosis with at least moderate evidence of an independent effect on the outcome. No models were externally validated, and all were at moderate or higher risk of bias.

CONCLUSIONS

Deficits in physical function and activities of daily living, age, absence of an informal care giver and frailty have the strongest evidence as determinants of the need for support services after hospital discharge.

TRIAL REGISTRATION

This review was registered with PROSPERO #CRD42016037144.

摘要

背景

一些入住急性护理医院的患者在出院后需要支持性服务。我们的研究目的是确定预测急性护理医院出院后需要支持性服务的模型和变量。

方法

我们进行了一项系统评价,检索了 MEDLINE、CINAHL、EMBASE 和 COCHRANE 数据库,检索时间截至 2017 年 5 月 1 日。我们选择了为非急诊入院内科病房的患者推导和验证出院后需要支持性服务预测模型的研究。我们提取了队列特征、模型特征以及筛选和纳入最终预测模型的变量。使用预后研究质量工具评估了偏倚风险。

结果

我们的搜索共确定了 3362 个独特的参考文献。全文审查确定了 6 个模型。模型在推导(C 统计量>0.75)和验证(C 统计量>0.70)队列中具有良好的区分度。有高质量证据表明,年龄、身体功能受损、日常生活活动能力障碍、无非正式照顾者和虚弱状态预测出院后需要支持性服务。中风是唯一具有独立影响结局的至少中度证据的独特诊断。没有模型经过外部验证,并且所有模型都存在中度或更高的偏倚风险。

结论

身体功能和日常生活活动能力的缺陷、年龄、无非正式照顾者和虚弱状态是预测出院后需要支持性服务的最强决定因素。

试验注册

本综述在 PROSPERO 上注册,注册号为 CRD42016037144。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c628/7057581/3eab72aa38e2/12913_2020_4972_Fig1_HTML.jpg

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