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ArticleJournal of clinical tuberculosis and other mycobacterial diseases2021

Is analysis of inflammatory biomarkers and lymphocyte subpopulations useful in prediction of tuberculosis treatment outcomes?

Greta Musteikienė, Skaidrius Miliauskas, Jurgita Zaveckienė, Daiva Urbonienė, Astra Vitkauskienė, Marius Žemaitis, Albinas Naudžiūnas

Abstract read
In one paragraph

Article in Journal of clinical tuberculosis and other mycobacterial diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

7 authors.

Greta MusteikienėDepartment of Pulmonology, Medical Academy, Lithuanian University of Health Sciences, Eiveniu 2, LT-50161 Kaunas, Lithuania.
Skaidrius MiliauskasDepartment of Pulmonology, Medical Academy, Lithuanian University of Health Sciences, Eiveniu 2, LT-50161 Kaunas, Lithuania.
Jurgita ZaveckienėDepartment of Radiology, Medical Academy, Lithuanian University of Health Sciences, Eiveniu 2, LT-50161 Kaunas, Lithuania.
Daiva UrbonienėDepartment of Laboratory Medicine, Medical Academy, Lithuanian University of Health Sciences, Eiveniu 2, LT-50161 Kaunas, Lithuania.
Astra VitkauskienėDepartment of Laboratory Medicine, Medical Academy, Lithuanian University of Health Sciences, Eiveniu 2, LT-50161 Kaunas, Lithuania.
Marius ŽemaitisDepartment of Pulmonology, Medical Academy, Lithuanian University of Health Sciences, Eiveniu 2, LT-50161 Kaunas, Lithuania.
Albinas NaudžiūnasDepartment of Internal Medicine, Medical Academy, Lithuanian University of Health Sciences, Eiveniu 2, LT-50161 Kaunas, Lithuania.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Analysis of inflammatory biomarkers and lymphocytes during the treatment of tuberculosis (TB) could yield findings that influence the routine clinical practice and use of new anti-TB drugs. This study aimed to evaluate whether the selected biomarkers-soluble intercellular adhesion molecule type 1, soluble urokinase-type plasminogen activator receptor (suPAR), and C-reactive protein (CRP)-and T-cell subpopulations are useful for predicting culture conversion, treatment outcomes, and the extent of radiological lesions (calculated using X-ray score) in patients with drug-sensitive pulmonary TB. This study included 62 patients with drug-sensitive pulmonary TB. CRP and suPAR levels significantly decreased after 1 month of treatment. Before treatment initiation, CRP and suPAR levels were significantly higher in patients without culture conversion; however, none of the selected host biomarkers appeared to significantly influence the conversion status or treatment outcomes. Some lymphocyte subpopulations were correlated with X-ray scores before TB treatment initiation, but lung destruction, as determined using X-ray scores, showed the highest correlation with the baseline CRP value. We conclude that selected host biomarkers have a very limited role in predicting TB treatment outcomes and culture conversion and do not appear to be superior to CRP in monitoring TB treatment.

Indexed as

Flow cytometrysICAM-1Sputum culture conversionsuPARTuberculosis

Identifiers

PMID34541339
PMCPMC8436121

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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 OpenQuestion graph.