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Record W4400426509 · doi:10.1093/ofid/ofae381

Donor-Derived <i>Bartonella quintana</i> Infection in Solid Organ Transplantation: An Emerging Public Health Issue With Diagnostic Challenges

2024· review· en· W4400426509 on OpenAlexaffabout
Carl Boodman, Óscar García, Dima Kabbani, Armelle Pérez Cortés Villalobos, Amy Beeson, Grace E. Marx, Johan van Griensven, Karen Doucette

Bibliographic record

VenueOpen Forum Infectious Diseases · 2024
Typereview
Languageen
FieldImmunology and Microbiology
TopicBartonella species infections research
Canadian institutionsUniversity of AlbertaUniversity of Manitoba
Fundersnot available
KeywordsBacillary angiomatosisMedicineTransplantationOrgan transplantationContext (archaeology)Intensive care medicineBacteremiaOutbreakPublic healthDiseaseBartonella henselaeImmunologyPathologyInternal medicineSerologyBiologyAntibioticsMicrobiology

Abstract

fetched live from OpenAlex

Abstract Bartonella quintana is a louse-borne intracellular bacterium that remains a neglected cause of bacteremia, bacillary angiomatosis, and infective endocarditis among individuals experiencing poverty. In October 2023, Health Canada notified Canadian organ transplantation programs of an outbreak of donor-derived B quintana infection. From March to August 2023, 5 cases of donor-derived B quintana disease were acquired in Alberta, Canada, from 3 deceased donors who had experienced homelessness. Similar cases recently occurred in the United States. In this article, we discuss strategies to screen organ donors and monitor transplant recipients for B quintana infection using epidemiologic risk factors, physical examination signs, and laboratory diagnostic tests. We review the limitations of existing diagnostic tests for B quintana and describe how these problems may be magnified in the organ transplantation context.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.002
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 head0.064
GPT teacher head0.380
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations7
Published2024
Admission routes2
Has abstractyes

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