Evidence map›Paper›PMID 30319279›Full record

ArticleInfection and drug resistance2018

Evaluation of the GenoType MTBDR

Jiyong Jian, Xinyu Yang, Jun Yang, Liang Chen

Abstract read
In one paragraph

Article in Infection and drug resistance, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Rapid Extensively Drug-Resistant (XDR) TB Diagnosis: An In-House DNA Biochip for Drug Resistance Detection and Mutation Profiling ofThe Canadian journal of infectious diseases & medical microbiology = Journal canadien des maladies infectieuses et de la microbiologie medicale · 2026
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  8. Isolation and Characterization of Carbapenem-ResistantThe Canadian journal of infectious diseases & medical microbiology = Journal canadien des maladies infectieuses et de la microbiologie medicale · 2023
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  15. Analysis of drug resistance and mutation profiles inThe Journal of international medical research · 2021
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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.

Jiyong JianClinical Laboratory Medicine, Beijing Shijitan Hospital, Capital Medical University, Beijing, China, chenliang6950@163.com.
Xinyu YangCentral Laboratory, Beijing Research Institute for Tuberculosis Control, Beijing, China.
Jun YangDepartment of Sterilized supplying, PLA 306 Hospital, Beijing, China.
Liang ChenClinical Laboratory Medicine, Beijing Shijitan Hospital, Capital Medical University, Beijing, China, chenliang6950@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe incidence of tuberculosis (TB), especially multidrug-resistant TB (MDR-TB) and extensively drug-resistant TB (XDR-TB), continues to increase alarmingly worldwide. Molecular line probe assays (LPAs) are endorsed by the World Health Organization for the fast detection of MDR-TB and XDR-TB. The aim of this study was to evaluate the performance of LPAs in China.

methodsWe analyzed MDR-TB and XDR-TB in 96 isolates from Beijing by using culture-based drug susceptibility testing (DST) and LPAs to compare the detection rate of the two methods.

resultsCompared to phenotypic DST, the GenoType

conclusionOur study showed that, in combination with phenotypic DST, application of the LPAs might be an efficient and reliable supplementary DST assay for rapid susceptibility screening of MDR-TB and XDR-TB. Using LPAs in countries with high MDR/XDR burden allows for appropriate and timely treatment, which will reduce transmission rates and morbidity, and improve treatment outcomes in patients.

Indexed as

line probe assayMDR-TBMycobacterium tuberculosisphenotypic drug susceptibility testingXDR-TB

Identifiers

PMID30319279
PMCPMC6171507

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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.