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Abstract
Description: The GRADE (Grading of Recommendations, Assessment, Development and Evaluations) 'Summary of findings' (SoF) tables represent a valuable development to facilitate the development of clear and transparent conclusions from evidence synthesis. The guidance provided for authors focuses on the applying the SoF to reviews based on statistical synthesis, yet over 20% of Cochrane Reviews include narrative syntheses of quantitative data. These reviews typically incorporate high levels of statistical and conceptual heterogeneity, which precludes calculation of quantitative effect estimates. Although the principles of the assessment domains such as inconsistency, imprecision, and indirectness still apply to these reviews, preparing SoF tables for these reviews can be challenging.
The aims of this workshop are, to:
- provide guidance about how to apply the GRADE domains to reviews where there is no quantitative estimate of effect;
- provide guidance on production of SoF tables for quantitative data which has been synthesized narratively using a selection of worked examples;
- obtain author feedback about the challenges of applying GRADE domains and SoF tables to narratively synthesised data;
- improve GRADE and SoF guidance for outcomes that are synthesised narratively.
The workshop will use examples of narrative reviews that have used SoF tables to highlight and identify challenges in the appropriate application of GRADE domains.
The aims of this workshop are, to:
- provide guidance about how to apply the GRADE domains to reviews where there is no quantitative estimate of effect;
- provide guidance on production of SoF tables for quantitative data which has been synthesized narratively using a selection of worked examples;
- obtain author feedback about the challenges of applying GRADE domains and SoF tables to narratively synthesised data;
- improve GRADE and SoF guidance for outcomes that are synthesised narratively.
The workshop will use examples of narrative reviews that have used SoF tables to highlight and identify challenges in the appropriate application of GRADE domains.