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Record W2395764303 · doi:10.1097/mog.0000000000000285

Fecal transplantation

2016· review· en· W2395764303 on OpenAlexaff
Paul Moayyedi

Bibliographic record

VenueCurrent Opinion in Gastroenterology · 2016
Typereview
Languageen
FieldMedicine
TopicClostridium difficile and Clostridium perfringens research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineUlcerative colitisRandomized controlled trialInflammatory bowel diseaseInternal medicineClostridium difficileCrohn's diseaseDiseasePlaceboIntensive care medicineAntibioticsAlternative medicinePathology

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Fecal microbiota transplant (FMT) has emerged as an important treatment for antibiotic resistant or recurrent Clostridium difficile infection. There has been a great deal of media coverage of the efficacy of FMT, and patients with inflammatory bowel disease (IBD) understandably wonder if this approach would also work for them. There are also instructions on 'do it yourself' FMT therapy on the web. It is important to understand whether there is evidence that this approach is effective in IBD so that we can advise our patients appropriately. RECENT FINDINGS: Systematic reviews have identified four case series involving 27 ulcerative colitis patients with a pooled remission rate of 24% (95% confidence interval (CI) = 11-45%). Two randomized controlled trials evaluating a total of 123 active ulcerative colitis patients have given conflicting results but the pooled data do suggest benefit with a number needed to treat of 6 (95% CI = 3-33). There are four case series involving 38 patients with Crohn's disease with a clinical response in 60.5% (95% CI = 28-86%). There are no randomized trials in Crohn's disease. SUMMARY: At present there are insufficient data to recommend FMT in IBD, and patients certainly should not be administering this themselves. This remains an interesting approach to treating IBD and more studies are needed to establish the optimal method of delivery as well as randomized, placebo controlled trials to establish the efficacy of FMT.

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)0.000
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 score0.961
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
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 head0.114
GPT teacher head0.428
Teacher spread0.315 · 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

Citations19
Published2016
Admission routes1
Has abstractyes

Explore more

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