MétaCan
Menu
Back to cohort
Record W1966827469 · doi:10.1080/10408398.2012.760515

The Impact of Dietary Interventions on the Symptoms of Inflammatory Bowel Disease: A Systematic Review

2015· review· en· W1966827469 on OpenAlexaff
Ashley Charlebois, Greg Rosenfeld, Brian Bressler

Bibliographic record

VenueCritical Reviews in Food Science and Nutrition · 2015
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsSt. Paul's HospitalUniversity of British Columbia
Fundersnot available
KeywordsMedicineInflammatory bowel diseaseDiseasePsychological interventionClinical trialInternal medicineDietary managementIntervention (counseling)Physical therapyPsychiatry

Abstract

fetched live from OpenAlex

Diet may be a successful part of the treatment plan for improving outcome in patients with inflammatory bowel disease (IBD). This study aimed to systematically review all published clinical trials evaluating the effects of a regular diet on symptoms of IBD. Three medical databases were searched for clinical trials evaluating an intervention that involved dietary manipulation using a regular diet on adults with IBD whose symptoms were objectively measured before and after the intervention. The most common types of regular diet interventions that we observed in the literature fell into the following three categories: low residue/low fiber diets, exclusion diets, or other specific diets. Of all included studies, the few that were of higher quality and that observed a statistically significant improvement in symptoms in the diet group compared to the control group fell under the exclusion diet group or the other specific diet group. We were able to identify several high quality clinical trials evaluating dietary manipulations on symptoms of IBD. Exclusion diets and the low FODMAP diet are two areas identified in this review that show promise for having therapeutic benefits for patients with IBD.

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)0.005
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.020
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.065
GPT teacher head0.398
Teacher spread0.333 · 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 designSystematic review
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

Citations70
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueCritical Reviews in Food Science and NutritionSame topicInflammatory Bowel DiseaseFrench-language works237,207