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Record W4295879471 · doi:10.1016/j.waojou.2022.100679

Quality and consistency of clinical practice guidelines on the prevention of food allergy and atopic dermatitis: Systematic review protocol

2022· article· en· W4295879471 on OpenAlexaff
Agnes Sze Yin Leung, Elizabeth Huiwen Tham, Miny Samuel, Daniel Munblit, Derek K. Chu, Lamia Dahdah, Kiwako Yamamoto‐Hanada, Thulja Trikamjee, Vijay Warad, André Van Niekerk, Santiago Martínez, Anne K. Ellis, Leonard Bielory, Gustavo Cuadros, Hugo Van Bever, Dana Wallace, Mimi L.K. Tang, J. Wesley Sublett, Gary Wong

Bibliographic record

VenueWorld Allergy Organization Journal · 2022
Typearticle
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsKingston General HospitalMcMaster UniversityQueen's UniversityImpact
FundersHealth and Medical Research FundNational Medical Research CouncilMedical Research CouncilChinese University of Hong Kong
KeywordsMedicineGuidelineAtopic dermatitisProtocol (science)Systematic reviewPsychological interventionConsistency (knowledge bases)ExcellenceFood allergyAlternative medicineFamily medicineQuality (philosophy)MEDLINEAllergyPathologyNursingImmunology

Abstract

fetched live from OpenAlex

Background and aims: Allergy prevention strategies have gained significant traction as a means to attenuate the growing burden of allergic diseases over the past decade. As the evidence base for primary prevention of food allergy (FA) and atopic dermatitis (AD) is constantly advancing, clinical practice guideline (CPG) recommendations on interventions for FA and AD prevention vary in quality and consistency among professional organizations. We present a protocol for a systematic review of CPGs on primary prevention of FA and AD. Methods: We will systematically review and appraise all CPGs addressing primary prevention of FA and AD and report our findings according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Electronic databases and manual website searches from January 2011 to March 2021 without language or geographical restrictions, and supplemented by author contact, will generate the list of potentially relevant CPGs to screen. Evaluation of the methodological quality, consistency, and global applicability of shortlisted CPGs will be performed by members of the Allergy Prevention Work Group of the World Allergy Organization (WAO) using the Appraisal of Guidelines for Research and Evaluation (AGREE) II and AGREE-REX (Recommendations EXcellence). instruments. Guideline contents, consistency, and quality of the recommendations will be summarised in tabular and narrative formats. We aim to present consolidated recommendations from international guidelines of the highest methodological quality and applicability, as determined by AGREE II and AGREE-REX. Dissemination: This systematic review will provide a succinct overview of the quality and consistency of recommendations across all existing CPGs for FA and AD prevention, as well as crucial perspectives on applicability of individual recommendations in different geographical contexts. Results from this systematic review will be reported in a peer-reviewed journal. It will also inform a position statement by WAO to provide a practical framework to guide the development of future guidelines for allergy prevention worldwide. Prospero registration number: CRD42021265689.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.150
metaresearch head score (Gemma)0.230
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.850
Threshold uncertainty score0.794

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1500.230
Meta-epidemiology (narrow)0.0050.007
Meta-epidemiology (broad)0.0170.019
Bibliometrics0.0170.018
Science and technology studies0.0050.005
Scholarly communication0.0090.009
Open science0.0070.007
Research integrity0.0090.009
Insufficient payload (model declined to judge)0.0690.011

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 head0.259
GPT teacher head0.520
Teacher spread0.261 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designSystematic review
DomainReporting
GenreProtocol

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

Citations5
Published2022
Admission routes1
Has abstractyes

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