Evidence map›Paper›PMID 38832230›Full record

ArticleFrontiers in public health2024

Unraveling tuberculosis patient cluster transmission chains: integrating WGS-based network with clinical and epidemiological insights.

Darja Sadovska, Iveta Ozere, Ilva Pole, Jānis Ķimsis, Annija Vaivode, Anda Vīksna, Inga Norvaiša, Ineta Bogdanova, Viktorija Ulanova, Valentīna Čapligina and 2 more

Abstract read
In one paragraph

Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Darja SadovskaLaboratory of Molecular Microbiology, Latvian Biomedical Research and Study Centre, Riga, Latvia.
Iveta OzereCentre of Tuberculosis and Lung Diseases, Riga East University Hospital, Upeslejas, Latvia.
Ilva PoleCentre of Tuberculosis and Lung Diseases, Riga East University Hospital, Upeslejas, Latvia.
Jānis ĶimsisLaboratory of Molecular Microbiology, Latvian Biomedical Research and Study Centre, Riga, Latvia.
Annija VaivodeLaboratory of Molecular Microbiology, Latvian Biomedical Research and Study Centre, Riga, Latvia.
Anda VīksnaCentre of Tuberculosis and Lung Diseases, Riga East University Hospital, Upeslejas, Latvia.
Inga NorvaišaCentre of Tuberculosis and Lung Diseases, Riga East University Hospital, Upeslejas, Latvia.
Ineta BogdanovaCentre of Tuberculosis and Lung Diseases, Riga East University Hospital, Upeslejas, Latvia.
Viktorija UlanovaLaboratory of Molecular Microbiology, Latvian Biomedical Research and Study Centre, Riga, Latvia.
Valentīna ČapliginaLaboratory of Molecular Microbiology, Latvian Biomedical Research and Study Centre, Riga, Latvia.
Dace BandereDepartment of Pharmaceutical Chemistry, Riga Stradiņš University, Riga, Latvia.
Renāte RankaLaboratory of Molecular Microbiology, Latvian Biomedical Research and Study Centre, Riga, Latvia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Tuberculosis remains a global health threat, and the World Health Organization reports a limited reduction in disease incidence rates, including both new and relapse cases. Therefore, studies targeting tuberculosis transmission chains and recurrent episodes are crucial for developing the most effective control measures. Herein, multiple tuberculosis clusters were retrospectively investigated by integrating patients' epidemiological and clinical information with median-joining networks recreated based on whole genome sequencing (WGS) data of Methods: Epidemiologically linked tuberculosis patient clusters were identified during the source case investigation for pediatric tuberculosis patients. Only Results: We investigated 18 clusters comprising 100 active tuberculosis patients 29 of whom were children at the time of diagnosis; nine patients experienced recurrent episodes. Conclusion: The complex approach of integrating tuberculosis cluster WGS-data-based median-joining networks with relevant epidemiological and clinical data proved valuable in delineating epidemiologically linked patient transmission chains and deciphering causes of recurrent tuberculosis episodes within clusters.

Indexed as

Mycobacterium tuberculosisTuberculosisWhole Genome SequencingAdolescentAdultChildChild, PreschoolCluster AnalysisFemaleHumansInfantMaleRetrospective StudiesnetworkreactivationrecurrencereinfectiontransmissiontuberculosisWGS

Identifiers

PMID38832230
PMCPMC11144917

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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.