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GRADE Guidance 34: update on rating imprecision using a minimally contextualized approach. | LitMetric

GRADE Guidance 34: update on rating imprecision using a minimally contextualized approach.

J Clin Epidemiol

Department of Health Research Methods, Evidence and Impact, McMaster University, 1280 Main Street West, Hamilton, L8S 4L8 Ontario, Canada; Department of Medicine, McMaster University, 1280 Main Street West, Hamilton, L8S 4L8 Ontario, Canada.

Published: October 2022

AI Article Synopsis

  • The study aims to update guidance for GRADE users on when to consider rating down for imprecision in research findings.
  • A project group within the GRADE Working Group held discussions to refine this guidance based on previous recommendations from 2011.
  • The updated GRADE recommendations suggest using thresholds and confidence intervals of absolute effects to determine when to rate down, emphasizing circumstances where rating down two or three levels is warranted.

Article Abstract

Objectives: The aim of this study is to provide updated guidance on when The Grading of Recommendations Assessment, Development and Evaluation (GRADE) users should consider rating down more than one level for imprecision using a minimally contextualized approach.

Study Design And Setting: Based on the first GRADE guidance addressing imprecision rating in 2011, a project group within the GRADE Working Group conducted iterative discussions and presentations at GRADE Working Group meetings to produce this guidance.

Results: GRADE suggests aligning imprecision criterion for systematic reviews and guidelines using the approach that relies on thresholds and confidence intervals (CI) of absolute effects as a primary criterion for imprecision rating (i.e., CI approach). Based on the CI approach, when a CI appreciably crosses the threshold(s) of interest, one should consider rating down two or three levels. When the CI does not cross the threshold(s) and the relative effect is large, one should implement the optimal information size (OIS) approach. If the sample size of the meta-analysis is far less than the OIS, one should consider rating down more than one level for imprecision.

Conclusion: GRADE provides updated guidance for imprecision rating in a minimally contextualized approach, with a focus on the circumstances in which one should seriously consider rating down two or three levels for imprecision.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.jclinepi.2022.07.014DOI Listing

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