first version (https://gradeai.med.up.pt/) for GRADErater.
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Automated ratings following the guidance of the GRADE Book
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Access to a text report justifying all automated ratings
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All ratings can be manually modified, ensuring human oversight
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Generation of exportable meta-analysis results and SoF-ready tables
Automated GRADE CoEGRADErater
GRADE Living Map
GRADE Living Map (GLM), a living index of official content by the GRADE Working Group:
Antonio Bognanni, Bernardo Sousa-Pinto, Jessie McGowan, Marina Davoli, Jun Xia, Nicole Skoetz, Philipp Dahm, Sue Brennan, Rafael José Vieira, Reem A. Mustafa, Joerg J. Meerpohl, Miranda Langendam, Elie Akl, Ignacio Neumann, Holger J. Schünemann,
The GRADE Living Map (GLM): the interactive and living index of GRADE content. A statement by the GRADE Guidance Group,
Journal of Clinical Epidemiology,
https://doi.org/10.1016/j.jclinepi.2026.112419.
(https://www.sciencedirect.com/science/article/pii/S0895435626002957)
GRADE Educational Resources
Collection: GRADE assessment of certainty of evidence series
Cochrane Webinars
McMaster University GRADE Online Learning Modules: Find research work, training materials, and resources to support guideline development.
GRADE Book: Review the official publication of the GRADE working group, which is the most comprehensive and up-to-date resource on the GRADE approach.
GRADE Book on YouTube: Watch videos on concepts from the GRADE Book.
GIN-McMaster Guideline Development Checklist: learn about the topics and items included in the GIN-McMaster Guideline Development Checklist
Hanan Khalil, Angela Johns-Hayden, Kathryn Kynoch
Journal of Clinical Epidemiology
gray literature search & appraisal, Whether gray literature should be analyzed separately vs pooled
Incorporating non-randomized studies into critical care CPGs
Alexandre Tran, David Granton, Eddy Fan, Bram Rochwerg, American Journal of Respiratory and Critical Care Medicine, Volume 212, Issue 4, April 2026
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Addresses major gap: lack of RCTs in critical care guidelines.
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Explains how non-randomized studies (NRSI) can complement RCTs using GRADE framework.
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Introduces target trial emulation + causal inference methods.
A decision algorithm for assessing indirectness in core GRADE
GRADE notes 6: Three strategies to determine the clinically important thresholds for outcomes in evidence-based guideline development study presents three approaches that can be utilized to guide the establishment of three clinically important thresholds in the evaluation of the imprecision and inconsistency domains in certainty assessments of evidence and to inform judgement about the strength of the corresponding recommendation.
Guideline organizations' guidance documents paper 1: Introduction
Guideline organizations' guidance documents paper 2: priority setting
Guideline organizations’ guidance documents paper 3: contributions and authorship
Guideline organizations’ guidance documents paper 4: interest-holder engagement
Guideline organizations' guidance documents paper 5: conflict of interest and funding
Guideline organizations’ guidance documents paper 6: adaptation of practice guidelines
Guideline organizations’ guidance documents paper 7: updating practice guidelines
Guideline organizations' guidance documents paper 8: considering equity
Guideline organizations' guidance documents paper 9: co-operative approaches
Core GRADE 1: overview of the Core GRADE approach
Core GRADE 2: choosing the target of certainty rating and assessing imprecision
Core GRADE 5: rating certainty of evidence—assessing indirectness
Core GRADE 3: rating certainty of evidence—assessing inconsistency
Core GRADE 6: presenting the evidence in summary of findings tables
Core GRADE 7: principles for moving from evidence to recommendations and decisions