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Record W4281858153 · doi:10.3390/jcm11113045

The Optimal Management of Fistulizing Crohn’s Disease: Evidence beyond Randomized Clinical Trials

2022· review· en· W4281858153 on OpenAlexaff
Panu Wetwittayakhlang, Alex Al Khoury, Gustavo Drügg Hahn, Péter L. Lakatos

Bibliographic record

VenueJournal of Clinical Medicine · 2022
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsMedicineRandomized controlled trialCrohn's diseaseIntensive care medicineDiseaseClinical trialQuality of life (healthcare)Expert opinionEvidence-based medicineSurgeryInternal medicineAlternative medicinePathology

Abstract

fetched live from OpenAlex

Fistulizing Crohn's disease (FCD) remains the most challenging aspect of treating patients with CD. FCD can occur in up to 30% of patients with CD and may lead to significant disability and impaired quality of life. The optimal treatment strategies for FCD require a multidisciplinary approach, including a combined medical and surgical approach. The therapeutic options for FCD are limited due to sparse evidence from randomized clinical trials (RCTs). The current recommendations are mainly based on post hoc analysis from RCTs, real-world clinical studies and expert opinion. There is variation in everyday clinical practice amongst gastroenterologists and surgeons. The evidence for anti-tumor necrosis factor therapy is the strongest in the treatment of FCD. However, long-term fistula healing can be achieved in only 30-50% of patients. In recent years, emerging data in the advent of therapeutic modalities, including the use of new biologic agents, therapeutic drug monitoring, novel surgical methods and mesenchymal stem cell therapy, have been shown to improve outcomes in achieving fistula healing. This review summarizes the existing literature on current and emerging therapies to provide guidance beyond RCTs in managing FCD.

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)0.113
metaresearch head score (Gemma)0.115
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.923
Threshold uncertainty score0.929

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1130.115
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0070.006
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.251
GPT teacher head0.538
Teacher spread0.287 · 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; both teacher heads agree on what is shown here.

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

Citations33
Published2022
Admission routes1
Has abstractyes

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