MétaCan
Menu
Back to cohort
Record W3038963949 · doi:10.1136/gutjnl-2020-321829

Reorganisation of faecal microbiota transplant services during the COVID-19 pandemic

2020· article· en· W3038963949 on OpenAlexaff
Gianluca Ianiro, Benjamin H. Mullish, Colleen Kelly, Zain Kassam, Ed J. Kuijper, Siew C. Ng, Tariq Iqbal, Jessica R. Allegretti, Stefano Bibbò, Harry Sokol, Faming Zhang, Monika Fischer, Samuel P. Costello, Josbert J. Keller, Luca Masucci, Joffrey van Prehn, Gianluca Quaranta, Mohammed Nabil Quraishi, Jonathan Segal, Dina Kao, Reetta Satokari, Maurizio Sanguinetti, Herbert Tilg, Antonio Gasbarrini, Giovanni Cammarota

Bibliographic record

VenueGut · 2020
Typearticle
Languageen
FieldMedicine
TopicClostridium difficile and Clostridium perfringens research
Canadian institutionsUniversity of Alberta
FundersMinistero della SaluteNational Institute for Health and Care Research
KeywordsPandemicInfection controlMedicineCoronavirus disease 2019 (COVID-19)Health carePatient safetyHealth professionalsClostridium difficileIntensive care medicineFecal bacteriotherapySevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakClostridioidesMedical emergencyEnvironmental healthOutbreakVirologyInternal medicineBiologyDiseasePolitical science

Abstract

fetched live from OpenAlex

The COVID-19 pandemic has led to an exponential increase in SARS-CoV-2 infections and associated deaths, and represents a significant challenge to healthcare professionals and facilities. Individual countries have taken several prevention and containment actions to control the spread of infection, including measures to guarantee safety of both healthcare professionals and patients who are at increased risk of infection from COVID-19. Faecal microbiota transplantation (FMT) has a well-established role in the treatment of Clostridioides difficile infection. In the time of the pandemic, FMT centres and stool banks are required to adopt a workflow that continues to ensure reliable patient access to FMT while maintaining safety and quality of procedures. In this position paper, based on the best available evidence, worldwide FMT experts provide guidance on issues relating to the impact of COVID-19 on FMT, including patient selection, donor recruitment and selection, stool manufacturing, FMT procedures, patient follow-up and research activities.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.390

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.053
GPT teacher head0.308
Teacher spread0.256 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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".

Quick stats

Citations150
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueGutSame topicClostridium difficile and Clostridium perfringens researchFrench-language works237,207