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在缺乏单一效应估计值的情况下对证据的确定性进行评级。

Rating the certainty in evidence in the absence of a single estimate of effect.

作者信息

Murad M Hassan, Mustafa Reem A, Schünemann Holger J, Sultan Shahnaz, Santesso Nancy

机构信息

Evidence-based Practice Center, Mayo Clinic, Rochester, Minnesota, USA.

Department of Biomedical and Health Informatics, University of Missouri-Kansas City, Kansas City, Missouri, USA.

出版信息

Evid Based Med. 2017 Jun;22(3):85-87. doi: 10.1136/ebmed-2017-110668. Epub 2017 Mar 20.

Abstract

When studies measure or report outcomes differently, it may not be feasible to pool data across studies to generate a single effect estimate (ie, perform meta-analysis). Instead, only a narrative summary of the effect across different studies might be available. Regardless of whether a single pooled effect estimate is generated or whether data are summarised narratively, decision makers need to know the certainty in the evidence in order to make informed decisions. In this guide, we illustrate how to apply the constructs of the GRADE (Grading of Recommendation, Assessment, Development and Evaluation) approach to assess the certainty in evidence when a meta-analysis has not been performed and data were summarised narratively.

摘要

当各项研究对结果的测量或报告方式不同时,将不同研究的数据合并以得出单一效应估计值(即进行荟萃分析)可能并不可行。相反,可能只能获得不同研究效应的叙述性总结。无论是否得出单一的合并效应估计值,也无论数据是进行叙述性总结,决策者都需要了解证据的确定性,以便做出明智的决策。在本指南中,我们阐述了在未进行荟萃分析且数据进行了叙述性总结时,如何应用推荐分级的评估、制定与评价(GRADE)方法的构建要素来评估证据的确定性。

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