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Record W3041900376 · doi:10.1111/tri.13696

Enteric dysbiosis in liver and kidney transplant recipients: a systematic review

2020· review· en· W3041900376 on OpenAlexaff
Saranya Sivaraj, Anita Sook Yee Chan, Elisa Pasini, Emily Chen, Bishoy Lawendy, Elizabeth C. Verna, Kymberly D. Watt, Mamatha Bhat

Bibliographic record

VenueTransplant International · 2020
Typereview
Languageen
FieldNursing
TopicClinical Nutrition and Gastroenterology
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineKidney transplantDysbiosisNephrologyInternal medicineKidney transplantationIntensive care medicineLiver transplantationKidneyGastroenterologyTransplantation

Abstract

fetched live from OpenAlex

Several factors mediate intestinal microbiome (IM) alterations in transplant recipients, including immunosuppressive (IS) and antimicrobial drugs. Studies on the structure and function of the IM in the post-transplant scenario and its role in the development of metabolic abnormalities, infection, and cancer are limited. We conducted a systematic review to study the taxonomic changes in liver (LT) and kidney (KT) transplantation, and their potential contribution to post-transplant complications. The review also includes pre-transplant taxa, which may play a critical role in microbial alterations post-transplant. Two reviewers independently screened articles, and assessed risk of bias. The review identified 13 clinical studies, which focused on adult kidney and liver transplant recipients. Patient characteristics and methodologies varied widely between studies. Ten studies reported increased an abundance of opportunistic pathogens (Enterobacteriaceae, Enterococcaceae, Fusobacteriaceae, and Streptococcaceae) followed by butyrate-producing bacteria (Lachnospiraceae and Ruminococcaceae) in nine studies in post-transplant conditions. The current evidence is mostly based on observational data and studies with no proof of causality. Therefore, further studies exploring the bacterial gene functions rather than taxonomic changes alone are in demand to better understand the potential contribution of the IM in post-transplant complications.

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: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.361
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.045
GPT teacher head0.332
Teacher spread0.287 · 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

Citations10
Published2020
Admission routes1
Has abstractyes

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