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Record W2793738172 · doi:10.1093/jcag/gwy009.110

A110 USE OF PROBIOTICS, PREBIOTICS AND DIETARY FIBRE SUPPLEMENTS IN PATIENTS WITH INFLAMMATORY BOWEL DISEASE

2018· article· en· W2793738172 on OpenAlexaffabout
M Silva, Richa Chibbar, Eytan Wine, Jens Walter, Karen J. Goodman, Ammar Hassanzadeh Keshteli, Rosica Valcheva, Levinus A. Dieleman

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2018
Typearticle
Languageen
FieldMedicine
TopicEosinophilic Esophagitis
Canadian institutionsUniversity of British ColumbiaUniversity of Alberta
Fundersnot available
KeywordsMedicineUlcerative colitisInflammatory bowel diseaseCalprotectinDiseaseInternal medicineSynbioticsCrohn's diseaseFaecal calprotectinGut floraGastroenterologyImmunologyProbioticBacteriaBiology

Abstract

fetched live from OpenAlex

Inflammatory bowel diseases (IBD) are chronic inflammatory conditions of the intestines likely induced by abnormal immune response to resident intestinal bacteria in genetically susceptible hosts. Probiotics, prebiotics and dietary fibres alter the gut microbiota and improve its function, thus potentially counteracting the development of inflammation. Although the role of these compounds in the prevention and management of IBD is relatively understudied, anecdotal evidence suggests widespread, undocumented use of these supplements by patients. Investigating the use of probiotics and prebiotics by IBD patients and association with disease severity may allow for optimization of therapy and improved clinical outcomes. To assess if the self-motivated intake of probiotics, prebiotics and dietary fibre supplements is associated with the disease severity in patients with IBD. We conducted a cross-sectional study of patients with a diagnosis of IBD in the University of Alberta IBD clinic. Using a 20-item questionnaire we collected data from patients on demographics, disease characteristics and knowledge and use of probiotics, prebiotics and dietary fibre supplements. We used a chart review to ascertain the occurrence of flares, disease duration and objective markers of inflammation such as fecal calprotectin (FCP) as indicators of disease severity. In this study, 100 participants (45% females) with a known diagnosis of IBD (47% Crohn’s disease, 34% ulcerative colitis, 19% IBD-unclassified) completed questionnaires. Large proportions of participants were knowledgeable about probiotics (88%) and dietary fibres (76%), but less about prebiotics (42%). The majority of users had Crohn’s disease (42% CD vs. 35% UC, p=0.33). 66% of surveyed patients had used these products as an alternate therapy. Disease flares in the last two years did not have an effect on usage (73% users vs. 71% non-users, p=0.8). The use of alternative therapies was higher in patients with longer history of IBD (77% in those with a duration >5 years vs. 22% in those with a duration <5 years, p=1.0). Close to half of patients (48%) with a fecal calprotectin (FCP) >250 µg/g (an indicator of acute disease) during the preceding six months reported supplement use, compared to 52% with FCP values below this value (P=0.11). This study shows that a large proportion of IBD patients are interested in alternative therapies for IBD. Increased flare frequency and objective markers of inflammation did not have an effect on usage. However, longer disease history was the main factor influencing the search for a “cure” by the patients. These microbiota-altering strategies have the ability to affect disease outcomes, therefore clinicians and researchers should identify and document their use. CIHR

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.007
GPT teacher head0.205
Teacher spread0.198 · 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 designObservational
Domainnot available
GenreEmpirical

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".

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Citations2
Published2018
Admission routes2
Has abstractyes

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