Evidence map›Paper›PMID 40503841›Full record

ArticleMicrobiology spectrum2025

Accelerating extrapulmonary tuberculosis diagnosis with a rapid molecular assay.

Christelle Guillet-Caruba, Caroline Bénet, Haroun Jmel, Florence Doucet-Populaire, Nadège Bourgeois-Nicolaos

Abstract read
In one paragraph

Article in Microbiology spectrum, 2025. 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.

  1. Article
  2. Article
  3. Article
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

5 authors.

Christelle Guillet-CarubaAP-HP Université Paris-Saclay Hôpital Antoine Béclère, Service de Bactériologie-Hygiène, Clamart, France.ORCID 0009-0000-5754-076X
Caroline BénetAP-HP Université Paris-Saclay Hôpital Antoine Béclère, Service de Bactériologie-Hygiène, Clamart, France.
Haroun JmelAP-HP Université Paris-Saclay Hôpital Antoine Béclère, Service de Bactériologie-Hygiène, Clamart, France.
Florence Doucet-PopulaireAP-HP Université Paris-Saclay Hôpital Antoine Béclère, Service de Bactériologie-Hygiène, Clamart, France.ORCID 0000-0002-1923-8495
Nadège Bourgeois-NicolaosAP-HP Université Paris-Saclay Hôpital Antoine Béclère, Service de Bactériologie-Hygiène, Clamart, France.ORCID 0000-0002-4736-3234

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Extrapulmonary tuberculosis (EPTB) is characterized by a very low bacterial load and could remain undiagnosed for a long time in a number of cases due to atypical presentation. Conventional methods and their time to results are not always helpful in rapidly making an EPTB diagnosis and initiating appropriate treatment. In order to accelerate the bacteriological confirmation, we evaluated the benefits of systematically using nucleic acid amplification test (NAAT) on extrapulmonary specimens for TB diagnosis in a developed country. From November 2017 to March 2021, all extrapulmonary samples received at the mycobacteriology department were subjected to both conventional methods and Xpert MTB/RIF Ultra. The time savings and the diagnostic performance of reflex tests were evaluated. During the study period, 691 samples were included, 85 (12.3%) were NAAT positive for

Indexed as

Molecular Diagnostic TechniquesMycobacterium tuberculosisNucleic Acid Amplification TechniquesTuberculosisAdultFemaleHumansMaleMiddle AgedSensitivity and SpecificityTime FactorsTuberculosis, Extrapulmonaryextrapulmonary tuberculosislymph node tuberculosismolecular methodsMycobacterium tuberculosisnucleic acid technologyrifampin resistancetime to resultXpert MTB/RIF Ultra

Identifiers

PMID40503841
PMCPMC12323321

What OpenQuestion holds

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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 OpenQuestion graph.