Evidence map›Paper›PMID 31910223›Full record

ArticlePloS one2020

A pre-clinical validation plan to evaluate analytical sensitivities of molecular diagnostics such as BD MAX MDR-TB, Xpert MTB/Rif Ultra and FluoroType MTB.

Markus Beutler, Sara Plesnik, Marina Mihalic, Laura Olbrich, Norbert Heinrich, Samuel Schumacher, Michael Lindner, Ina Koch, Wolfgang Grasse, Christoph Metzger-Boddien and 2 more

Open access · goldAbstract readComparative StudyEvaluation Study
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
0.3field-weighted citation impact, top 28% of its field
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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.

  1. Pooled it
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  6. Review
  7. 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

12 authors at 4 institutions in 2 countries.

Markus BeutlerInstitute of Microbiology and Laboratory Medicine, Department IML Red GmbH, WHO-Supranational Reference Laboratory of Tuberculosis, Munich-Gauting, Germany.ORCID 0000-0002-4323-462X
Sara PlesnikInstitute of Microbiology and Laboratory Medicine, Department IML Red GmbH, WHO-Supranational Reference Laboratory of Tuberculosis, Munich-Gauting, Germany.
Marina MihalicInstitute of Microbiology and Laboratory Medicine, Department IML Red GmbH, WHO-Supranational Reference Laboratory of Tuberculosis, Munich-Gauting, Germany.
Laura OlbrichDivision of Infectious Diseases and Tropical Medicine, LMU University Hospital, Munich, Germany.
Norbert HeinrichDivision of Infectious Diseases and Tropical Medicine, LMU University Hospital, Munich, Germany.
Samuel SchumacherFoundation for Innovative New Diagnostics, Geneva, Switzerland.
Michael LindnerAsklepios Fachkliniken München-Gauting, Munich, Germany.
Ina KochAsklepios Fachkliniken München-Gauting, Munich, Germany.ORCID 0000-0002-8766-017X
Wolfgang Grassegerbion GmbH & Co. KG, Kornwestheim, Germany.
Christoph Metzger-Boddiengerbion GmbH & Co. KG, Kornwestheim, Germany.
Sabine Hofmann-ThielInstitute of Microbiology and Laboratory Medicine, Department IML Red GmbH, WHO-Supranational Reference Laboratory of Tuberculosis, Munich-Gauting, Germany.
Harald HoffmannInstitute of Microbiology and Laboratory Medicine, Department IML Red GmbH, WHO-Supranational Reference Laboratory of Tuberculosis, Munich-Gauting, Germany.
Asklepios Fachkliniken München-Gauting · DELMU Klinikum · DESynlab (Germany) · DEFIND · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rapid diagnosis of tuberculosis (TB) and antibiotic resistances are imperative to initiate effective treatment and to stop transmission of the disease. A new generation of more sensitive, automated molecular TB diagnostic tests has been recently launched giving microbiologists more choice between several assays with the potential to detect resistance markers for rifampicin and isoniazid. In this study, we determined analytical sensitivities as 95% limits of detection (LoD95) for Xpert MTB/Rif Ultra (XP-Ultra) and BD-MAX MDR-TB (BD-MAX) as two representatives of the new test generation, in comparison to the conventional FluoroType MTB (FT-MTB). Test matrices used were physiological saline solution, human and a mucin-based artificial sputum (MUCAS) each spiked with Mycobacterium tuberculosis in declining culture- and qPCR-controlled concentrations. With BD-MAX, XP-Ultra, and FT-MTB, we measured LoD95TB values of 2.1 cfu/ml (CI95%: 0.9-23.3), 3.1 cfu/ml (CI95%: 1.2-88.9), and 52.1 cfu/ml (CI95%: 16.7-664.4) in human sputum; of 6.3 cfu/ml (CI95%: 2.9-31.8), 1.5 cfu/ml (CI95%: 0.7-5.0), and 30.4 cfu/ml (CI95%: 17.4-60.7) in MUCAS; and of 2.3 cfu/ml (CI95%: 1.1-12.0), 11.5 cfu/ml (CI95%: 5.6-47.3), and 129.1 cfu/ml (CI95%: 82.8-273.8) in saline solution, respectively. LoD95 of resistance markers were 9 to 48 times higher compared to LoD95TB. BD-MAX and XP-Ultra have an equal and significantly increased analytical sensitivity compared to conventional tests. MUCAS resembled human sputum, while both yielded significantly different results than normal saline. MUCAS proved to be suitable for quality control of PCR assays for TB diagnostics.

Indexed as

Antibiotics, AntitubercularDrug Resistance, Multiple, BacterialHumansLimit of DetectionMicrobial Sensitivity TestsMolecular Diagnostic TechniquesMycobacterium tuberculosisQuality ControlReagent Kits, DiagnosticReal-Time Polymerase Chain ReactionSputumTuberculosis, Multidrug-ResistantTuberculosis, PulmonaryAntibiotics, AntitubercularReagent Kits, Diagnostic

Identifiers

PMID31910223
PMCPMC6946130
OpenAlexW2999314875

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.