Evidence map›Paper›PMID 39297626›Full record

ArticleJournal of clinical microbiology2024

Evaluation of the STANDARD M10 MDR-TB and MTB/NTM assays for the detection of

Bruno Luukinen, Janne Aittoniemi, Terhi Miikkulainen-Lahti, Silja Mentula, Anu Pätäri-Sampo

Abstract readEvaluation Study
In one paragraph

Article in Journal of clinical microbiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
–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

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Rapid identification of majorFrontiers in cellular and infection microbiology · 2025
    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.

Bruno LuukinenDepartment of Clinical Microbiology, HUS Diagnostic Center, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.ORCID 0000-0003-3578-782X
Janne AittoniemiDepartment of Clinical Microbiology, Fimlab Laboratories, Tampere, Finland.
Terhi Miikkulainen-LahtiDepartment of Clinical Microbiology, HUS Diagnostic Center, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
Silja MentulaDepartment of Health Security, Finnish Institute for Health and Welfare, Helsinki, Finland.
Anu Pätäri-SampoDepartment of Clinical Microbiology, HUS Diagnostic Center, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.

Funding

Foundation of the Finnish Anti-Tuberculosis AssociationHUS Diagnostic CenterTampere Tuberculosis Foundation
6 · The paper itself

Abstract

Rapid detection is crucial for tuberculosis (TB) control. GeneXpert (Cepheid) is a widely used PCR system, known for its simplicity, random access, and point-of-care compatibility. SD BIOSENSOR recently introduced a similar system, STANDARD M10, including a IMPORTANCE: The molecular diagnostic STANDARD M10 system is highly analogous to the widely established GeneXpert system, which significantly increases the relevance of this evaluation study in the field of rapid detection of

Indexed as

IsoniazidMycobacterium tuberculosisNontuberculous MycobacteriaRifampinSensitivity and SpecificityTuberculosis, Multidrug-ResistantAntitubercular AgentsHumansIncidenceMicrobial Sensitivity TestsMolecular Diagnostic TechniquesMycobacterium Infections, NontuberculousAntitubercular AgentsIsoniazidRifampinmultidrug resistanceMycobacteriumMycobacterium tuberculosisnontuberculous mycobacteriarapid teststuberculosis

Identifiers

PMID39297626
PMCPMC11481502

What OpenQuestion holds

Textmetadata
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.