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Record W4411809978 · doi:10.1177/20543581251346074

The Canadian Society of Nephrology Methods for Developing and Adapting Clinical Practice Guidelines: An Update

2025· review· en· W4411809978 on OpenAlexaffabout
Somaya Zahran, Anna Mathew, Tyrone G. Harrison, Arenn Jauhal, Michelle Hladunewich, Reem A. Mustafa

Bibliographic record

VenueCanadian Journal of Kidney Health and Disease · 2025
Typereview
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreLibin Cardiovascular Institute of AlbertaImpactMcGill UniversityUniversity of CalgaryMcMaster UniversityUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsDocumentationStakeholderGuidelineMedicineContext (archaeology)Best practiceProcess managementKnowledge translationGrading (engineering)Process (computing)Relevance (law)Knowledge managementMedical educationComputer sciencePolitical sciencePublic relationsPathologyBusinessEngineering

Abstract

fetched live from OpenAlex

Purpose of the review: In this article, we provide an update on the Canadian Society of Nephrology's (CSN) process of identifying candidate topics and subsequent development of guidelines and commentaries using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE)-ADOLOPMENT methodology. We revise the process of adapting existing guidelines with the inclusion of Kidney Disease Improving Global Outcomes (KDIGO) practice points. We also describe challenges of implementing guidelines and suggest solutions to address this with description of the CSN approach to disseminating and implementing guidelines. Sources of information: The update reflects internal CSN documentation, stakeholder consultation for topic prioritization, and integration of methodological guidance from GRADE-ADOLOPMENT and international sources such as KDIGO. Methods: We reviewed and synthesized the CSN's current guideline-development process, which includes a detailed examination of internal documentation, meeting summaries, and publicly available methodological frameworks with specific focus on the application of the GRADE-ADOLOPMENT approach. We analyzed how recommendations and practice points from KDIGO are assessed for relevance, updated based on Canadian context, and integrated into the final commentary using GRADE Evidence-to-Decision (EtD) frameworks. We also examined how conflict of interest is managed, how working groups are structured, and how recommendations are prioritized. In addition, we explored the CSN's evolving strategies for dissemination and implementation, including stakeholder engagement, survey feedback, and use of knowledge-translation tools. Key findings: The CSN follows a transparent and rigorous process in guideline and commentary development. This comprehensive process considers the best-available evidence, balancing desirable and undesirable effects and patients' values, perspectives, and implications for the Canadian health care system including resources, equity, acceptability, and feasibility to maximize guideline implementation and advance the health of Canadians. Limitations: The CSN updated methods reflect the current process and may not be generalizable to other guideline organizations. The impact of CSN commentaries on clinical practice, decision-making, and policy uptake has not been formally evaluated, limiting our understanding of their contribution to health system improvement and patient outcomes. Implications: This review updates the CSN's processes for commentary working groups to identify relevant international guidelines, establish the level of agreement on included recommendations, incorporate perspectives of people with lived experience, and adjust the final product to the Canadian healthcare system before dissemination.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.490
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.699
Threshold uncertainty score0.916

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.490
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.462
GPT teacher head0.645
Teacher spread0.183 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2025
Admission routes2
Has abstractyes

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