Evidence map›Paper›PMID 31074252›Full record

ArticleJournal of Korean medical science2019

Factors Influencing the Diagnosis and Treatment of Latent Tuberculosis among Contacts in Congregated Settings in Korea.

Ahreum Kim, Minhyeok Choi

RetractedOpen access · goldAbstract readRetracted Publication
In one paragraph

Article in Journal of Korean medical science, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 96% 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, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Ahreum KimRegional Center for Respiratory Diseases, Pusan National University Hospital, Busan, Korea.ORCID https://orcid.org/0000-0002-2930-1232
Minhyeok ChoiRegional Center for Respiratory Diseases, Pusan National University Hospital, Busan, Korea. come2mh@gmail.com.ORCID https://orcid.org/0000-0002-9611-7232
Pusan National University Hospital · KR

Funding

Korea Centers for Disease Control & Prevention 2017-71
6 · The paper itself

Abstract

backgroundThis study aimed to compare the indicators (the rates of diagnosis, need for treatment, treatment initiation, and treatment completion) of management of latent tuberculosis infection (LTBI) in contacts and to identify the impact of active tuberculosis (TB) index case characteristics on the exposed population in congregated settings, such as schools, workplaces, and medical institutes.

methodsThe data of 8,648 clusters in the TB epidemiological investigation database between 2013 and 2016 were extracted and analyzed to evaluate the indicators and perform multilevel logistic regression (MLR) analyses to identify the factors affecting each indicator.

resultsThe rates of total LTBI diagnosis, need for treatment, treatment initiation, and treatment completion were 15.2%, 10.2%, 69.4%, and 76.6%, respectively. After adjusting for other factors on MLR, the probability of diagnosis and need for treatment of latent TB in contacts was higher in most types of facilities than in schools. Conversely, treatment completion rates in these facilities were lower. Notably, the correctional institutions showed the highest odds ratio (OR) relative to school for LTBI diagnosis (OR, 6.37) and need for treatment (OR, 4.49) and the lowest OR for treatment completion (OR, 0.10).

conclusionThis study provided evidence for the implementation of latent TB control policies in congregated settings.

Indexed as

Congregated SettingsLatent Tuberculosis InfectionTuberculosisTuberculosis Epidemiological Investigation

Identifiers

PMID31074252
PMCPMC6509364
OpenAlexW2944588660

What OpenQuestion holds

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LicenceCC BY-NC
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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.