Evidence map›Paper›PMID 24089608›Full record

ArticleCurrent respiratory medicine reviews2013

Using Xpert MTB/RIF.

Mark P Nicol, Andrew Whitelaw, Stevens Wendy

Open access · bronzeAbstract read
In one paragraph

Article in Current respiratory medicine reviews, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
0.7field-weighted citation impact, top 30% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Review
  4. More Than a Decade of GeneXpertDiagnostics (Basel, Switzerland) · 2023
    Article
  5. Diagnosis of paediatric TB using XpertThe international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease · 2022
    Article
  6. Article
  7. Article
  8. Epidemiological aspects, clinical manifestations, and prevention of pediatric tuberculosis from the perspective of the End TB Strategy.Jornal brasileiro de pneumologia : publicacao oficial da Sociedade Brasileira de Pneumologia e Tisilogia · 2018
    Review
  9. Article
  10. The Point-of-Care Laboratory in Clinical Microbiology.Clinical microbiology reviews · 2016
    Review
  11. 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

3 authors at 3 institutions in 1 country.

Mark P NicolDivision of Medical Microbiology, Department of Clinical Laboratory Sciences, Institute of Infectious Diseases and Molecular Medicine, University of Cape Town, South Africa ; National Health Laboratory Service, South Africa.
Andrew Whitelaw
Stevens Wendy
National Health Laboratory Service · ZAUniversity of Cape Town · ZAUniversity of the Witwatersrand · ZA

Funding

Wellcome Trust
6 · The paper itself

Abstract

Xpert MTB/RIF is an automated real-time polymerase chain reaction test for simultaneous detection of tuberculosis and rifampicin resistance. Xpert MTB/RIF has demonstrated excellent accuracy in clinical evaluation studies, but has reduced sensitivity for detection of smear-negative tuberculosis. Since sample processing and detection are largely automated, Xpert MTB/RIF is potentially suitable for implementation in resource-limited settings. There are, however, a number of practical constraints to the use of Xpert at the point-of-care. Xpert remains a relatively costly test, and clear demonstration of cost-effectiveness will be needed to support efforts to scale up testing in high burden countries.

Indexed as

Cost-effectivenessdetectiondiagnosisrifampicintuberculosisXpert MTB/RIF.

Identifiers

PMID24089608
PMCPMC3785149
OpenAlexW2081881788

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.