Evidence map›Paper›PMID 27733630›Full record

ArticleJournal of clinical microbiology2016

Evaluation of the Abbott RealTime MTB and RealTime MTB INH/RIF Assays for Direct Detection of Mycobacterium tuberculosis Complex and Resistance Markers in Respiratory and Extrapulmonary Specimens.

Sabine Hofmann-Thiel, Nikolay Molodtsov, Uladzimir Antonenka, Harald Hoffmann

Open access · bronzeAbstract readEvaluation Study
In one paragraph

Article in Journal of clinical microbiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
5.1field-weighted citation impact, top 4% 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

21 citing papers in PubMed, 1 synthesis or guideline pooled it, 45 citations in OpenAlex.

  1. Pooled it
  2. Clinical performance of the Abbott RealTime Mycobacterium tuberculosis (MTB) PCR on bronchoscopic specimens for diagnosing pulmonary tuberculosis.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2026
    Article
  3. Article
  4. Abbott realtime MTB assay for detecting Mycobacterium tuberculosis complex in respiratory specimens: a cost-benefit analysis.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2024
    Article
  5. Article
  6. Development of DNA Bio-chip for Detection of Mutations ofIndian journal of clinical biochemistry : IJCB · 2023
    Article
  7. Article
  8. Observational
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Performance of Xpert MTB/RIF, Xpert Ultra, and Abbott RealTiJournal of clinical microbiology · 2018
    Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Performance of the Abbott RealTiJournal of clinical microbiology · 2017
    Article
  20. Review
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

4 authors at 1 institution in 1 country.

Sabine Hofmann-Thielsynlab MVZ Gauting, Gauting, Germany sabine.hofmann-thiel@synlab.com.
Nikolay MolodtsovIML red, WHO-Supranational Reference Laboratory of Tuberculosis, Gauting, Germany.
Uladzimir AntonenkaIML red, WHO-Supranational Reference Laboratory of Tuberculosis, Gauting, Germany.
Harald Hoffmannsynlab MVZ Gauting, Gauting, Germany.
Synlab (Germany) · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Abbott RealTime MTB (RT MTB) assay is a new automated nucleic acid amplification test for the detection of Mycobacterium tuberculosis complex (MTBC) in clinical specimens. In combination with the RealTime MTB INH/RIF (RT MTB INH/RIF) resistance assay, which can be applied to RT MTB-positive specimens as an add-on assay, the tests also indicate the genetic markers of resistance to isoniazid (INH) and rifampin (RIF). We aimed to evaluate the diagnostic sensitivity and specificity of RT MTB using different types of respiratory and extrapulmonary specimens and to compare performance characteristics directly with those of the FluoroType MTB assay. The resistance results obtained by RT MTB INH/RIF were compared to those from the GenoType MTBDRplus and from phenotypic drug susceptibility testing. A total of 715 clinical specimens were analyzed. Compared to culture, the overall sensitivity of RT MTB was 92.1%; the sensitivity rates for smear-positive and smear-negative samples were 100% and 76.2%, respectively. The sensitivities of smear-negative specimens were almost identical for respiratory (76.3%) and extrapulmonary (76%) specimens. Specificity rates were 100% and 95.8% for culture-negative specimens and those that grew nontuberculous mycobacteria, respectively. RT MTB INH/RIF was applied to 233 RT MTB-positive samples and identified resistance markers in 7.7% of samples. Agreement with phenotypic and genotypic drug susceptibility testing was 99.5%. In conclusion, RT MTB and RT MTB INH/RIF allow for the rapid and accurate diagnosis of tuberculosis (TB) in different types of specimens and reliably indicate resistance markers. The strengths of this system are the comparably high sensitivity with paucibacillary specimens, its ability to detect INH and RIF resistance, and its high-throughput capacities.

Indexed as

Antitubercular AgentsDrug Resistance, Multiple, BacterialHumansIsoniazidMicrobial Sensitivity TestsMolecular Diagnostic TechniquesMycobacterium tuberculosisNontuberculous MycobacteriaNucleic Acid Amplification TechniquesRifampinSensitivity and SpecificityTuberculosis, PulmonaryAntitubercular AgentsIsoniazidRifampin

Identifiers

PMID27733630
PMCPMC5121395
OpenAlexW2530419011

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.