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Record W2570248060 · doi:10.1080/19490976.2016.1278105

Fecal microbial transplantation as a therapeutic option in patients colonized with antibiotic resistant organisms

2017· review· en· W2570248060 on OpenAlexafffund
Michael Laffin, Braden Millan, Karen Madsen

Bibliographic record

VenueGut Microbes · 2017
Typereview
Languageen
FieldMedicine
TopicClostridium difficile and Clostridium perfringens research
Canadian institutionsUniversity of CalgaryUniversity of Alberta
FundersCanadian Institutes of Health Research
KeywordsClostridium difficileAntibioticsFecal bacteriotherapyAntibiotic resistanceColonisation resistanceTransplantationBiologyInflammatory bowel diseaseDiseaseGut floraIntensive care medicineMicrobiomeEnterocolitisMicrobiologyMedicineImmunologyInternal medicineBioinformatics

Abstract

fetched live from OpenAlex

Despite increasing interest in fecal microbiota transplantation (FMT), its full therapeutic potential has yet to be determined. Since its increase in popularity, FMT has been shown to be highly effective in the treatment of both Clostridium difficile infection (CDI) and its recurrent form. Interest in FMT now expands well beyond the treatment of CDI to other processes with known associations to the microbiota such as antibiotic resistant infections, inflammatory bowel disease (IBD), hepatic encephalopathy, neuropsychiatric disorders, and metabolic disease. The rampant use and misuse of antibiotics in both medicine and agriculture has resulted in an increase in antibiotic resistant organisms which pose a significant risk to human health. The purpose of this commentary is to address the general issue of antibiotic resistance in the human microbiota and the restorative potential of FMT in this area.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.054
GPT teacher head0.355
Teacher spread0.301 · 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 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

Citations37
Published2017
Admission routes2
Has abstractyes

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