Evidence map›Paper›PMID 19864480›Full record

ArticleJournal of clinical microbiology2010

Rapid detection of Mycobacterium tuberculosis and rifampin resistance by use of on-demand, near-patient technology.

Danica Helb, Martin Jones, Elizabeth Story, Catharina Boehme, Ellen Wallace, Ken Ho, JoAnn Kop, Michelle R Owens, Richard Rodgers, Padmapriya Banada and 15 more

Registry-linked trialAbstract readEvaluation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of clinical microbiology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02776150 (Multi Center Clinical Research and Evaluation of Melting Technology for Rapid Detection of Drug Resistant Tuberculosis), which is not on this map. Cited by 450 papers, 14 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
450citing papers in PubMed, 14 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.

NCT02776150 unknown statusnot on this mapstarted 2016, after this paper: background citation

Multi Center Clinical Research and Evaluation of Melting Technology for Rapid Detection of Drug Resistant Tuberculosis

TypeobservationalSponsorBeijing HospitalRan2016 to 2019Enrolled3,100ConditionsTuberculosis, Pulmonary
3 · Its place in the literature

Who cites it

450 citing papers in PubMed, 14 syntheses or guidelines pooled it.

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  13. Treatment outcomes, diagnostic and therapeutic impact: Xpert vs. smear. A systematic review and meta-analysis.The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease · 2019
    Pooled it
  14. XpertThe Cochrane database of systematic reviews · 2018
    Pooled it
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390 more citing papers are in PubMed but not listed here.

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

25 authors.

Danica HelbDepartment of Medicine, New Jersey Medical School, University of Medicine and Dentistry, New Jersey, Newark, New Jersey 07103, USA.
Martin Jones
Elizabeth Story
Catharina Boehme
Ellen Wallace
Ken Ho
JoAnn Kop
Michelle R Owens
Richard Rodgers
Padmapriya Banada
Hassan Safi
Robert Blakemore
N T Ngoc Lan
Edward C Jones-López
Michael Levi
Michele Burday
Irene Ayakaka
Roy D Mugerwa
Bill McMillan
Emily Winn-Deen
Lee Christel
Peter Dailey
Mark D Perkins
David H Persing
David Alland

Funding

Sample Processing Cartridges for Rapid PCR TB DetectionR42AI052523 · NIAID · CEPHEID · PI ALLAND, DAVID · 2006 to 2008
$4.0M
Sample Processing Cartridges for Rapid PCR TB DetectionR41AI052523 · NIAID · CEPHEID · PI ALLAND, DAVID · 2002 to 2002
$376k
NIAID NIH HHS R41 AI052523NIAID NIH HHS R41-AI52523NIAID NIH HHS R42 AI052523NIAID NIH HHS R42-AI52523
6 · The paper itself

Abstract

Current nucleic acid amplification methods to detect Mycobacterium tuberculosis are complex, labor-intensive, and technically challenging. We developed and performed the first analysis of the Cepheid Gene Xpert System's MTB/RIF assay, an integrated hands-free sputum-processing and real-time PCR system with rapid on-demand, near-patient technology, to simultaneously detect M. tuberculosis and rifampin resistance. Analytic tests of M. tuberculosis DNA demonstrated a limit of detection (LOD) of 4.5 genomes per reaction. Studies using sputum spiked with known numbers of M. tuberculosis CFU predicted a clinical LOD of 131 CFU/ml. Killing studies showed that the assay's buffer decreased M. tuberculosis viability by at least 8 logs, substantially reducing biohazards. Tests of 23 different commonly occurring rifampin resistance mutations demonstrated that all 23 (100%) would be identified as rifampin resistant. An analysis of 20 nontuberculosis mycobacteria species confirmed high assay specificity. A small clinical validation study of 107 clinical sputum samples from suspected tuberculosis cases in Vietnam detected 29/29 (100%) smear-positive culture-positive cases and 33/39 (84.6%) or 38/53 (71.7%) smear-negative culture-positive cases, as determined by growth on solid medium or on both solid and liquid media, respectively. M. tuberculosis was not detected in 25/25 (100%) of the culture-negative samples. A study of 64 smear-positive culture-positive sputa from retreatment tuberculosis cases in Uganda detected 63/64 (98.4%) culture-positive cases and 9/9 (100%) cases of rifampin resistance. Rifampin resistance was excluded in 54/55 (98.2%) susceptible cases. Specificity rose to 100% after correcting for a conventional susceptibility test error. In conclusion, this highly sensitive and simple-to-use system can detect M. tuberculosis directly from sputum in less than 2 h.

Indexed as

Drug Resistance, BacterialPoint-of-Care SystemsAdolescentAdultAgedAntitubercular AgentsBacteriological TechniquesFemaleHumansMaleMiddle AgedMycobacterium tuberculosisPolymerase Chain ReactionRifampinSensitivity and SpecificitySputumAntitubercular AgentsRifampin

Identifiers

PMID19864480
PMCPMC2812290

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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.