Test combination to detect latent Leishmania infection: A prevalence study in a newly endemic area for L. infantum, northeastern Italy
Bibliographic record
Abstract
BACKGROUND: Most people infected with Leishmania remain asymptomatic, which is a common element that may promote the resurgence of clinically evident leishmaniasis in individuals with impaired cell-mediated immune responses. Unfortunately, there is no universally accepted assay to identify asymptomatic infection. This cross-sectional study focuses on the employment of three methods targeting different features of the parasitic infection to be used in combination for the screening of latent leishmaniasis in a newly endemic area of northeastern Italy. METHODOLOGY/PRINCIPAL FINDINGS: The selected methods included highly sensitive Real-Time PCR for detection of parasitic kinetoplast (k)DNA in peripheral blood, Western Blot (WB) for detection of specific IgG, and Whole Blood stimulation Assay (WBA) to evaluate the anti-leishmanial T-cell response by quantifying the production of IL-2 after stimulation of patients' blood with Leishmania specific antigens. Among 145 individuals living in a municipality of the Bologna province, northeastern Italy, recruited and screened for Leishmania infection, 23 subjects tested positive (15.9%) to one or more tests. Positive serology was the most common marker of latent leishmaniasis (15/145, 10%), followed by the detection of specific cell-mediated response (12/145, 8%), while only few individuals (6/145, 4%) harbored parasitic DNA in the blood. CONCLUSIONS/SIGNIFICANCE: Combining different tests substantially increased the yield of positivity in detecting latent Leishmania infection. The test combination that we employed in this study appears to be effective to accurately identify latent leishmaniasis in an endemic area.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".