Infectious Diseases (ID) Learning Unit: How Rapidly to Evaluate for Active Tuberculosis Disease in Low-Prevalence Settings.

Natasha Chida, Maunank Shah

Open access · goldAbstract read

In one paragraph

Article in Open forum infectious diseases, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

0.2field-weighted citation impact, top 40% 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

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

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

2 authors at 2 institutions in 1 country.

Natasha ChidaDepartment of Medicine, Division of Infectious Diseases , Johns Hopkins University , Baltimore, Maryland.

Maunank ShahDepartment of Medicine, Division of Infectious Diseases , Johns Hopkins University , Baltimore, Maryland.

Johns Hopkins Medicine · USJohns Hopkins University · US

Funding

RESEARCH TRAINING IN MICROBIAL DISEASEST32AI007291 · NIAID · JOHNS HOPKINS UNIVERSITY · PI JOEL N BLANKSON, Sara Elizabeth Cosgrove · 1986 to 2026

$9.1M

Implementation Science Approaches for Novel TB Diagnostics in HIV Prevalent AreasK23AI089259 · NIAID · JOHNS HOPKINS UNIVERSITY · PI SHAH, MAUNANK · 2011 to 2015

$681k

NIAID NIH HHS K23 AI089259NIAID NIH HHS T32 AI007291

6 · The paper itself

Abstract

With declining tuberculosis (TB) incidence in low-prevalence settings, many clinicians are likely unaware that the approach to diagnosing active TB is evolving with newer technologies. Rapid molecular assays are commercially available, and more are likely to enter the market in the coming years. These tests, such as the Xpert MTB/RIF, which can detect TB and drug-resistance in 2 hours, are increasingly used in settings with higher TB prevalence; however, uptake has been slower in low-prevalence settings. Newer algorithms incorporating rapid TB diagnostics have the ability to alter current clinical and infection control practice patterns. In this learning unit, we review current and newly available tests for the detection of active TB disease and their usage in low-prevalence settings.

Indexed as

diagnosisnucleic acid amplification teststuberculosis

Identifiers

PMID27186583

DOI10.1093/ofid/ofw058

PMCPMC4866567

OpenAlexW2344969797

What OpenQuestion holds

Textmetadata

LicenceCC BY-NC-ND

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.