Evidence map›Paper›PMID 42038554›Full record

ArticleInternational journal of microbiology2026

Evaluation of Xpert MTB/XDR and Deeplex Myc-TB for the Rapid Detection of Drug Resistance in

Mirae Park, Priya Solanki, Timothy Daniel McHugh, Onn Min Kon, Giovanni Satta

Abstract read
In one paragraph

Article in International journal of microbiology, 2026. 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. Review
  2. Heteroresistance inFrontiers in cellular and infection microbiology · 2026
    Review
  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.

Mirae ParkDepartment of Respiratory Medicine, St Mary's Hospital, Imperial College Healthcare NHS Trust, London, UK, nhs.uk.ORCID https://orcid.org/0000-0002-7015-5943
Priya SolankiUCL-TB and Centre for Clinical Microbiology, Division of Infection & Immunity, Royal Free Campus, University College London, London, UK, ucl.ac.uk.
Timothy Daniel McHughUCL-TB and Centre for Clinical Microbiology, Division of Infection & Immunity, Royal Free Campus, University College London, London, UK, ucl.ac.uk.ORCID https://orcid.org/0000-0003-4658-8594
Onn Min KonDepartment of Respiratory Medicine, St Mary's Hospital, Imperial College Healthcare NHS Trust, London, UK, nhs.uk.ORCID https://orcid.org/0000-0003-2647-4688
Giovanni SattaUCL-TB and Centre for Clinical Microbiology, Division of Infection & Immunity, Royal Free Campus, University College London, London, UK, ucl.ac.uk.ORCID https://orcid.org/0000-0002-0120-7885

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: Rapid identification of drug-resistant tuberculosis remains critical for the initiation of appropriate treatment regimens, improved success rates and reduction in the development of drug resistance. In this study, we compared the diagnostic performance of two novel diagnostic tests, Xpert MTB/XDR and Deeplex Myc-TB (both CE marked). Methods: Twenty clinical isolates of Results: Xpert MTB/XDR had a total concordance of 68% and Deeplex Myc-TB had a total concordance of 100% when compared to WGS and phenotypic drug susceptibility testing. Xpert TB/XDR had a lower limit of detection for identifying MTB at 10^3 CFU/mL, whereas Deeplex Myc-TB required at least 10^4 CFU/mL. Both Xpert MTB/XDR and Deeplex Myc-TB were able to detect the wild type MTB without any cross-reactivity with the drug-resistant Mab. For heteroresistance detection, Deeplex Myc-TB was able to detect down to 1% admix of the resistant isolates (1 out of 4), whilst Xpert MTB/XDR was only able to detect down to 10% in 1 out of 4 mixtures of isolates tested. Conclusion: Both platforms represent an attractive option for the rapid detection of drug resistance and heteroresistance contributing to the management of complex cases, but further studies are needed to assess their real clinical impact.

Identifiers

PMID42038554
PMCPMC13108590

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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.