Evidence map›Paper›PMID 22825465›Full record

ArticleJournal of immigrant and minority health2013

Intensified case-finding for latent tuberculosis infection among the Baltimore City Hispanic population.

Meghana Desale, Patrick Bringardner, Sheila Fitzgerald, Kathleen Page, Maunank Shah

Open access · greenAbstract read
In one paragraph

Article in Journal of immigrant and minority health, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 4 pooled it
0.5field-weighted citation impact, top 37% 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

8 citing papers in PubMed, 4 syntheses or guidelines pooled it, 11 citations in OpenAlex.

  1. Pooled it
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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

5 authors at 2 institutions in 1 country.

Meghana DesaleDivision of Infectious Disease, Center for TB Research, Johns Hopkins University School of Medicine, 1503 East Jefferson St, Room 118, Baltimore, MD 21231, USA. mshah28@jhmi.edu
Patrick Bringardner
Sheila Fitzgerald
Kathleen Page
Maunank Shah
Johns Hopkins University · USJohns Hopkins Medicine · US

Funding

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 AI089259
6 · The paper itself

Abstract

Foreign-born immigrants are at high risk for latent TB infection (LTBI). In conjunction with the Baltimore City Health Department (BCHD), student volunteers conducted intensified LTBI case-finding (ICF) using tuberculin skin testing (TST) in the Hispanic community from 2006-2010. We sought to determine the yield of ICF and estimate the LTBI prevalence. Retrospective cross-sectional study. Among 478 individuals screened, 164 (34.3 %) had a positive TST, 227 (47.5 %) had a negative TST, and 87 (18.2 %) did not return. Among those who completed screening, the prevalence of LTBI was 164/391 (41.9, 95 % CI 0.37-0.47). ICF referrals accounted for 4.4 % of all LTBI referrals to BCHD and for 41 % of referrals among Hispanics. We found a high rate of undiagnosed LTBI within the Hispanic community. This student-run ICF program accounted for almost half of all LTBI cases among Hispanics. Community resources are needed to target this high-risk population.

Indexed as

AdultBaltimoreCommunity-Institutional RelationsCross-Sectional StudiesEmigrants and ImmigrantsFemaleHispanic or LatinoHumansLatent TuberculosisMaleMass ScreeningMiddle AgedReferral and ConsultationRetrospective StudiesRisk AssessmentStudents

Identifiers

PMID22825465
PMCPMC3521081
OpenAlexW2019547690

What OpenQuestion holds

Textmetadata
LicenceTDM
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.