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Record W4389347991 · doi:10.1111/codi.16741

European Society of Coloproctology: Guidelines for diagnosis and treatment of cryptoglandular anal fistula

2023· review· en· W4389347991 on OpenAlexaff
Lillian Reza, K. W. A. Göttgens, Jos Kleijnen, Stéphanie O. Breukink, Peter C. Ambe, Felix Aigner, Erman Aytaç, Gabriele Bislenghi, Andreas Nordholm‐Carstensen, Hossam Elfeki, Gaetano Gallo, Ugo Grossi, Barış Gülcü, Nusrat Iqbal, Rosa M. Jiménez-Rodríguez, Sezai Leventoğlu, Giorgio Lisi, Francesco Litta, Phillip Lung, Mónica Millán, Ersin Öztürk, Charlene Sackitey, Mostafa Shalaby, Jasper Stijns, Phil Tozer, D. D. E. Zimmerman

Bibliographic record

VenueColorectal Disease · 2023
Typereview
Languageen
FieldMedicine
TopicAnorectal Disease Treatments and Outcomes
Canadian institutionsUniversity Hospital Foundation
FundersEuropean Society of Coloproctology
KeywordsMedicineGuidelineAnal fistulaPopulationMEDLINEFistulaFamily medicineSurgeryPathology

Abstract

fetched live from OpenAlex

AIM: The primary aim of the European Society of Coloproctology (ESCP) Guideline Development Group (GDG) was to produce high-quality, evidence-based guidelines for the management of cryptoglandular anal fistula with input from a multidisciplinary group and using transparent, reproducible methodology. METHODS: Previously published methodology in guideline development by the ESCP has been replicated in this project. The guideline development process followed the requirements of the AGREE-S tool kit. Six phases can be identified in the methodology. Phase one sets the scope of the guideline, which addresses the diagnostic and therapeutic management of perianal abscess and cryptoglandular anal fistula in adult patients presenting to secondary care. The target population for this guideline are healthcare practitioners in secondary care and patients interested in understanding the clinical evidence available for various surgical interventions for anal fistula. Phase two involved formulation of the GDG. The GDG consisted of 21 coloproctologists, three research fellows, a radiologist and a methodologist. Stakeholders were chosen for their clinical and academic involvement in the management of anal fistula as well as being representative of the geographical variation among the ESCP membership. Five patients were recruited from patient groups to review the draft guideline. These patients attended two virtual meetings to discuss the evidence and suggest amendments. In phase three, patient/population, intervention, comparison and outcomes questions were formulated by the GDG. The GDG ratified 250 questions and chose 45 for inclusion in the guideline. In phase four, critical and important outcomes were confirmed for inclusion. Important outcomes were pain and wound healing. Critical outcomes were fistula healing, fistula recurrence and incontinence. These outcomes formed part of the inclusion criteria for the literature search. In phase five, a literature search was performed of MEDLINE (Ovid), PubMed, Embase (Ovid) and the Cochrane Database of Systematic Reviews by eight teams of the GDG. Data were extracted and submitted for review by the GDG in a draft guideline. The most recent systematic reviews were prioritized for inclusion. Studies published since the most recent systematic review were included in our analysis by conducting a new meta-analysis using Review manager. In phase six, recommendations were formulated, using grading of recommendations, assessment, development, and evaluations, in three virtual meetings of the GDG. RESULTS: In seven sections covering the diagnostic and therapeutic management of perianal abscess and cryptoglandular anal fistula, there are 42 recommendations. CONCLUSION: This is an up-to-date international guideline on the management of cryptoglandular anal fistula using methodology prescribed by the AGREE enterprise.

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)0.015
metaresearch head score (Gemma)0.035
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.035
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0060.004
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0030.002
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0050.003

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 head0.220
GPT teacher head0.437
Teacher spread0.217 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations67
Published2023
Admission routes1
Has abstractyes

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