ArticleMicroorganisms2026
Evaluation of a Fluorescence Immunoassay-Based IGRA for Latent Tuberculosis Diagnosis: A Simplified, Cost-Effective Alternative.
Article in Microorganisms, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Advances in rapid detection technologies for zoonotic diseases: a one health-oriented review.Frontiers in cellular and infection microbiology · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
Approximately 25% of the global population is estimated to have latent tuberculosis infection (LTBI), with a 5-10% lifetime risk of progression to active disease. Although interferon-gamma release assays (IGRAs) are widely used for LTBI diagnosis, their high cost and operational complexity limit large-scale implementation in resource-limited settings. This study evaluated the diagnostic performance of a low-complexity, rapid, fluorescence-based point-of-care assay, ichroma IGRA-TB, for LTBI detection. A total of 300 participants enrolled at TB Screening and Treatment Centers and the Dhaka Hospital of icddr,b were categorized as healthy controls (
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.