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Record W4414341880 · doi:10.1128/spectrum.01675-25

<i>Coxiella burnetii</i> and <i>Bartonella</i> species serology of febrile patients with an established infectious or inflammatory diagnosis in Sudan, Nepal, and Cambodia

2025· article· en· W4414341880 on OpenAlexaff
Carl Boodman, Sophie Edouard, Johan van Griensven, Kanika Deshpande Koirala, Basudha Khanal, Suman Rijal, Narayan Bhattarai, Sayda El Safi, Thong Phe, Kruy Lim, Pascal Lutumba, François Chappuis, Cédric P. Yansouni, Achilleas Tsoumanis, Barbara Barbé, Marjan Van Esbroeck, Kristien Verdonck, Marleen Boelaert, Nitin Gupta, Pierre‐Edouard Fournier, Emmanuel Bottieau

Bibliographic record

VenueMicrobiology Spectrum · 2025
Typearticle
Languageen
FieldImmunology and Microbiology
TopicBartonella species infections research
Canadian institutionsMcGill UniversityMcGill University Health CentreUniversity of Manitoba
Fundersnot available
KeywordsSerologySeroprevalenceEndocarditisInfective endocarditisFever of unknown originEpidemiology

Abstract

fetched live from OpenAlex

ABSTRACT Coxiella burnetii and Bartonella species cause febrile illness and infective endocarditis in low- and middle-income countries (LMICs). This study investigated whether seropositivity to C. burnetii or Bartonella could be detected among patients with persistent fever for which an infectious or inflammatory etiological diagnosis had been previously established in three LMICs. Our study tested sera from Cambodian, Nepalese, and Sudanese participants using indirect immunofluorescent antibody assays (IFA) for C. burnetii and Bartonella . Seropositivity rates for both pathogens were assessed across tropical and inflammatory etiologies of fever and compared to ubiquitous bacterial infections considered as a “reference group,” as they were not expected to cause serologic cross-reactivity. A total of 1,313 individuals underwent IFA, including 560/1,313 (42.7%) from Sudan, 432 (32.9%) from Nepal, and 321 (24.5%) from Cambodia. Overall, 57 (4.3%) and 60 (4.6%) participants tested positive for C. burnetii and Bartonella species, respectively. Forty-four (3.4%) individuals tested positive for both C. burnetii and Bartonella species (75.4% positive agreement). C. burnetii positivity did not differ significantly between the three countries ( P = 0.44), while Bartonella seropositivity was predominantly identified in Nepal ( P &lt; 0.001). Compared to the reference group, C. burnetii and Bartonella seropositivity were more common among participants with visceral leishmaniasis, P. falciparum malaria, leptospirosis, brucellosis, scrub typhus, and systemic lupus erythematosus (SLE), though only statistically significant for the latter two diagnoses. Further studies are necessary to investigate C. burnetii and Bartonella seropositivity in LMICs and to disentangle cross-reactivity, previous infection, or co-infection. IMPORTANCE Coxiella burnetii and Bartonella spp. are important but under-recognized causes of febrile illness and infective endocarditis in low- and middle-income countries (LMICs). This study evaluated the seroprevalence of these pathogens among patients with confirmed causes of persistent fever in Sudan, Nepal, and Cambodia. Despite the diagnostic utility of serologic testing for these infections, its performance in LMICs—where co-infections and background seropositivity are common—remains poorly characterized. The findings suggest notable seropositivity for C. burnetii and Bartonella among patients with a set of tropical and inflammatory diagnoses, including visceral leishmaniasis, Plasmodium falciparum malaria, leptospirosis, brucellosis, scrub typhus, and systemic lupus erythematosus. These results highlight the potential for cross-reactivity and underscore the need for context-specific validation. Enhanced understanding of serologic test characteristics is essential for accurate diagnosis in resource-limited settings.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.097
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.005
GPT teacher head0.216
Teacher spread0.211 · 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 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

Citations1
Published2025
Admission routes1
Has abstractyes

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