Evidence map›Paper›PMID 41430640›Full record

ArticleClinical and experimental immunology2026

Development of a score derived from full blood count parameters to differentiate individuals with tuberculosis disease from those with tuberculosis infection.

Giusto Davide Badami, Bartolo Tamburini, Miriana Fallo, Mojtaba Shekarkar Azgomi, Francesco Dieli, Nadia Caccamo, Marco Pio La Manna

Abstract read
In one paragraph

Article in Clinical and experimental immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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.

2 · The registry

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3 · Its place in the literature

Who cites it

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Giusto Davide BadamiCentral Laboratory of Advanced Diagnosis and Biomedical Research (CLADIBIOR), Azienda Ospedaliera Universitaria Policlinico (AOUP) Paolo Giaccone, University of Palermo, Palermo, Italy.
Bartolo TamburiniCentral Laboratory of Advanced Diagnosis and Biomedical Research (CLADIBIOR), Azienda Ospedaliera Universitaria Policlinico (AOUP) Paolo Giaccone, University of Palermo, Palermo, Italy.
Miriana FalloCentral Laboratory of Advanced Diagnosis and Biomedical Research (CLADIBIOR), Azienda Ospedaliera Universitaria Policlinico (AOUP) Paolo Giaccone, University of Palermo, Palermo, Italy.
Mojtaba Shekarkar AzgomiCentral Laboratory of Advanced Diagnosis and Biomedical Research (CLADIBIOR), Azienda Ospedaliera Universitaria Policlinico (AOUP) Paolo Giaccone, University of Palermo, Palermo, Italy.
Francesco DieliCentral Laboratory of Advanced Diagnosis and Biomedical Research (CLADIBIOR), Azienda Ospedaliera Universitaria Policlinico (AOUP) Paolo Giaccone, University of Palermo, Palermo, Italy.
Nadia CaccamoCentral Laboratory of Advanced Diagnosis and Biomedical Research (CLADIBIOR), Azienda Ospedaliera Universitaria Policlinico (AOUP) Paolo Giaccone, University of Palermo, Palermo, Italy.ORCID 0000-0002-1018-5710
Marco Pio La MannaCentral Laboratory of Advanced Diagnosis and Biomedical Research (CLADIBIOR), Azienda Ospedaliera Universitaria Policlinico (AOUP) Paolo Giaccone, University of Palermo, Palermo, Italy.

Funding

MUR PRIN PNRR P202295SHW
6 · The paper itself

Abstract

In 2022, tuberculosis (TB) caused 1.3 million deaths worldwide, making it the second leading infectious cause of death. Diagnosing TB remains challenging because current immunological tests cannot distinguish between TB disease and TB infection (TBI). Research suggests that ratios such as monocyte-to-lymphocyte, neutrophil-to-lymphocyte, and platelet-to-lymphocyte, along with absolute counts of various blood cells, could help develop a low-cost and easy-to-use diagnostic tool to distinguish TB disease from TBI among IFN-γ release assay (IGRA)-positive subjects without relying on microbiological tests. We enrolled 112 TB-infected subjects and used blood cell count parameters and ratios to develop a TB score that can indicate TB status. We then validated the score in another cohort of IGRA-positive hospitalized patients. We developed a TB score based on 11 blood parameters to identify TB disease among IGRA-positive subjects, with 93% specificity and 71% sensitivity. This score can support physicians in making therapeutic decisions for IGRA-positive subjects, offering a practical approach to differentiate TB disease from TBI.

Indexed as

TuberculosisAdultAgedBlood Cell CountDiagnosis, DifferentialFemaleHumansInterferon-gamma Release TestsMaleMiddle AgedMonocytesMycobacterium tuberculosisNeutrophilsSensitivity and Specificitylymphocytesmyeloid cellsplateletsTB scoretuberculosis

Identifiers

PMID41430640
PMCPMC12782106

What Socratic holds

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LicenceCC BY-NC-ND
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Registered trials

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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 Socratic graph.