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Record W2563145691 · doi:10.1093/ofid/ofw172.1671

Prospective Laboratory Evaluation of Fecal Microbiota Transplantation Donors: Results From an International Public Stool Bank

2016· article· en· W2563145691 on OpenAlexaff
Kelly Ling, Emily Koelsch, Nancy Dubois, Kelsey OʼBrien, Zachery Stoltzner, Pratik Panchal, Kanchana Amaratunga, Zain Kassam, Majdi Osman

Bibliographic record

VenueOpen Forum Infectious Diseases · 2016
Typearticle
Languageen
FieldMedicine
TopicClostridium difficile and Clostridium perfringens research
Canadian institutionsOttawa Hospital
Fundersnot available
KeywordsFecal bacteriotherapyMedicineFecesTransplantationProspective cohort studyGut floraInternal medicineGastroenterologyImmunologyMicrobiologyClostridium difficileAntibioticsBiology

Abstract

fetched live from OpenAlex

Background. Clostridium difficile infection (CDI) is a public health threat, and fecal microbiota transplantation (FMT) is an effective therapy for recurrent CDI. Stool banks have emerged to reduce logistic complexity and enhance access to safe FMT. However, there is variability in pathogen-testing protocols and a paucity of data on the etiology of laboratory exclusions for universal stool donors. Methods. Consecutive candidate donors were evaluated from 10 January 2014 to 21 April 2016 in the greater Boston area. Candidates who passed an initial 178-point clinical assessment, including body mass index and waist circumference, were invited to undergo stool and serological-based tests at a Clinical Laboratory Improvement Amendments–certified laboratory (figure 1). Candidate donors who met the initial clinical and laboratory testing inclusion criteria were enrolled as active donors, and stool was collected for 60 days. All material collected during the 60-day period was held in quarantine until the donor passed a second identical clinical and laboratory assessment. All stool and serology panels performed in the study period on candidate and active donors were included. Results. Overall, 131 candidate donors passed clinical evaluation and proceed to have stool and serology testing. Overall, 65 pathogens were detected among 56 donors, primarily parasitic (32%), viral (34%), and bacterial (28%) pathogens (figure 2). Among ova and parasite exclusions, Blastocystis hominis (52%) and Endolimax nana (29%) were most common, despite ruling out high-risk travel exposures. Among viral pathogens, rotavirus (86%) was most common, although no overt risk factors were identified. Bacterial pathogens detected among the asymptomatic cohort also included Helicobacter pylori, vancomycin-resistant enterococcus, C. difficile, and Cryptosporidium. Of the 56 donors, 18 subjects (32%) had an abnormal laboratory test at their 60-day screen following a first set of normal investigations. No blood-borne infections were identified. Conclusion. Asymptomatic rotavirus and B. hominis are the most common laboratory etiologies of exclusion despite ruling out risk factors. Accordingly, FMT donors should be screened for these pathogens and continuous laboratory testing should be considered by stool banks, given the ongoing risk of asymptomatic pathogen carriage. Disclosures. K. Ling, OpenBiome: Employee, Salary; E. Koelsch, OpenBiome: Employee, Salary; N. Dubois, OpenBiome: Employee, Salary; K. O'Brien, OpenBiome: Employee, Salary; Z. Stoltzner, OpenBiome: Employee, Salary; P. Panchal, OpenBiome: Consultant, Consulting fee; Z. Kassam, OpenBiome: Employee, Salary; Finch Scientific: Consultant and Shareholder, Equity and Research support; M. Osman, OpenBiome: Employee, Salary

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.032
GPT teacher head0.343
Teacher spread0.311 · 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 designObservational
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

Citations8
Published2016
Admission routes1
Has abstractyes

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