Evidence map›Paper›PMID 35677999›Full record

ArticleJournal of preventive medicine and public health = Yebang Uihakhoe chi2022

Cohort Profile: Korean Tuberculosis and Post-Tuberculosis Cohort Constructed by Linking the Korean National Tuberculosis Surveillance System and National Health Information Database.

Dawoon Jeong, Hee-Yeon Kang, Jinsun Kim, Hyewon Lee, Bit-Na Yoo, Hee-Sun Kim, Hongjo Choi

Open access · goldAbstract read
In one paragraph

Article in Journal of preventive medicine and public health = Yebang Uihakhoe chi, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
1.8field-weighted citation impact, top 13% 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

15 citing papers in PubMed, 18 citations in OpenAlex.

  1. Proposed approaches for public health surveillance: A literature review for the Canadian National HIV Surveillance Program.Canada communicable disease report = Releve des maladies transmissibles au Canada · 2025
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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

7 authors at 5 institutions in 1 country.

Dawoon JeongThe Korean Institute of Tuberculosis, Korean National Tuberculosis Association, Cheongju, Korea.
Hee-Yeon KangDepartment of Health Policy and Management, Seoul National University College of Medicine, Seoul, Korea.
Jinsun KimDivision of Tuberculosis Prevention and Control, Bureau of Infectious Disease Policy, Korea Disease Control and Prevention Agency, Cheongju, Korea.
Hyewon LeeDivision of Tuberculosis Prevention and Control, Bureau of Infectious Disease Policy, Korea Disease Control and Prevention Agency, Cheongju, Korea.
Bit-Na YooNational Evidence-based Collaborating Agency, Seoul, Korea.
Hee-Sun KimNational Evidence-based Collaborating Agency, Seoul, Korea.
Hongjo ChoiDepartment of Preventive Medicine, Konyang University College of Medicine, Daejeon, Korea.
Korea Disease Control and Prevention Agency · KRNational Evidenc- based healthcare Collaborating Agency · KRKonyang University · KRKorea National Tuberculosis Association · KRSeoul National University · KR

Funding

Korean National Tuberculosis AssociationMinistry of Health and WelfareNational Evidence-based Healthcare Collaborating Agency NC19-002National Evidence-based Healthcare Collaborating Agency NC20-003National Evidence-based Healthcare Collaborating Agency NC21-001
6 · The paper itself

Abstract

We aimed to review the current data composition of the Korean Tuberculosis and Post-Tuberculosis Cohort, which was constructed by linking the Korean Tuberculosis Surveillance System (KNTSS; established and operated by the Korean Disease Control and Prevention Agency since 2000) and the National Health Information Database (NHID; established by the National Health Insurance Service in 2012). The following data were linked: KNTSS data pertaining to patients diagnosed with tuberculosis between 2011 and 2018, NHID data of patients with a history of tuberculosis and related diseases between 2006 and 2018, and data (obtained from the Statistics Korea database) on causes of death. Data from 300 117 tuberculosis patients (177 206 men and 122 911 women) were linked. The rate of treatment success for new cases was highest in 2015 (86.7%), with a gradual decrease thereafter. The treatment success rate for previously treated cases showed an increasing trend until 2014 (79.0%) and decreased thereafter. In total, 53 906 deaths were confirmed among tuberculosis patients included in the cohort. The Korean Tuberculosis and Post-Tuberculosis Cohort can be used to analyze different measurement variables in an integrated manner depending on the data source. Therefore, these cohort data can be used in future epidemiological studies and research on policy-effect analysis, treatment outcome analysis, and health-related behaviors such as treatment discontinuation.

Indexed as

TuberculosisCohort StudiesDatabases, FactualFemaleHumansMaleNational Health ProgramsRepublic of KoreaCohort studiesDatabaseInformation storage and retrievalTreatment outcomeTuberculosis

Identifiers

PMID35677999
PMCPMC9201096
OpenAlexW4224265389

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.