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Irritable bowel syndrome and probiotics: from rationale to clinical use

2005· review· en· W2010985566 on OpenAlexaff
Elena F. Verdú, Stephen M. Collins

Bibliographic record

VenueCurrent Opinion in Gastroenterology · 2005
Typereview
Languageen
FieldMedicine
TopicGastrointestinal motility and disorders
Canadian institutionsMcMaster University
Fundersnot available
KeywordsIrritable bowel syndromeMedicineClinical trialIntensive care medicineProbioticMEDLINEInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Few therapies are of proven efficacy in irritable bowel syndrome. Thus, there is great interest in the development of a natural therapy that can be both safe and effective. An understanding that probiotics are heterogeneous, with multiple targets and mechanisms of action, is fundamental to the development of clinical trials. RECENT FINDINGS: A bidirectional model for the pathogenesis of irritable bowel syndrome is proposed in which gut-driven and brain-driven mechanisms contribute to the genesis of gut dysfunction and symptoms. In-vitro and animal studies have generated most of the mechanistic rationale for the use of probiotics in functional bowel disorders. A MEDLINE search of publications from 1989 to date revealed only eight placebo-controlled clinical trials on the subject of probiotics and irritable bowel syndrome. All these studies suffer from methodologic problems. By contrast, numerous reviews have been published in the past 2 years on this subject. SUMMARY: Animal research will continue to identify novel targets and elucidate the mechanisms of action of probiotics, thus providing a rational basis for their use in irritable bowel syndrome. The notion of treating irritable bowel syndrome with probiotics is particularly attractive to patients and generates great interest, although clinical evidence is not yet sufficient to enable clear guidelines to be designed. Large, well-designed, controlled clinical trials using specific probiotics are warranted.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.884
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.201
GPT teacher head0.436
Teacher spread0.234 · 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 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

Citations34
Published2005
Admission routes1
Has abstractyes

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