Evidence of Coxiella burnetii and Bartonella species infections among patients with persistent febrile illness in four low- and middle-income countries
Bibliographic record
Abstract
OBJECTIVES: This study investigated whether infections due to Coxiella burnetii, Bartonella species or Tropheryma whipplei could be identified among biobanked samples associated with persistent fever in four low- or middle-income countries. METHODS: The NIDIAG consortium ("Better DIAGnosis of Neglected Infectious Diseases") prospectively investigated in 2013-2014 the aetiological spectrum of 1922 patients with persistent febrile illness (fever greater than 7 days) in Cambodia, Nepal, Sudan, and the Democratic Republic of Congo (DRC). Our study retrospectively tested serum and blood samples from the 745 patients (38.8%) who remained without an identified cause of fever. Indirect immunofluorescent antibody assays (IFA) were performed (except in the DRC) to assess immunoglobulin response to C. burnetii and Bartonella antigens. DNA extracts from whole blood samples were tested for C. burnetii, Bartonella genus, B. quintana, B. henselae and T. whipplei by qPCR. RESULTS: Evidence of infection with C. burnetii or Bartonella sp. was found in 124 persistent fever cases (16.6%). IFA for IgG to C. burnetii phase I and II antigens identified 59 (7.9%) positive sera: 31/333 (9.3%) from Sudan, 16/278 (5.8%) from Nepal, and 12/54 (22.2%) from Cambodia. Eight individuals had C. burnetii anti-phase I IgG titres ≥ 1:800. Bartonella IFA identified 60 (8.1%) IgG positive sera, with 49/278 (17.6%) positive samples from Nepal, 7/333 (2.1%) from Sudan and 4/54 (7.4%) from Cambodia. One serum from Sudan had anti-Bartonella IgG titres of 1:800. C. burnetii DNA was detected from blood in 3 individuals from Sudan and one individual from the DRC, whereas B. quintana DNA was present in a blood sample from a Nepalese individual. All qPCR tests for T. whipplei were negative. DISCUSSION: Direct and indirect evidence of C. burnetii or Bartonella sp. infections was observed in persistent fever cases. Further studies are necessary to elucidate the burden of these diseases in low- or middle-income countries.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".