Evidence map›Paper›PMID 32627443›Full record

Observational studyJournal of Korean medical science2020

The Correlation of Comorbidities on the Mortality in Patients with COVID-19: an Observational Study Based on the Korean National Health Insurance Big Data.

Dong Wook Kim, Kyeong Hyang Byeon, Jaiyong Kim, Kyu Dong Cho, Nakyoung Lee

Registry-linked trialAbstract readObservational Study
In one paragraph

Observational study in Journal of Korean medical science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04631861 (Physical Activity and the Risk of COVID-19 Infection and Mortality), which is not on this map. Cited by 34 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 3 pooled it
–field-weighted citation impact
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.

NCT04631861 completednot on this map

Physical Activity and the Risk of COVID-19 Infection and Mortality

TypeobservationalSponsorWonju Severance Christian HospitalRan2014 to 2020Enrolled132,069ConditionsCovid19
3 · Its place in the literature

Who cites it

34 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  4. Article
  5. Artificial intelligence applications in health insurances: a scoping review.Cost effectiveness and resource allocation : C/E · 2025
    Review
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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.

Dong Wook Kim *Health Insurance Research Institute, National Health Insurance Service, Wonju, Korea.ORCID https://orcid.org/0000-0002-4478-3794
Kyeong Hyang Byeon *Department of Preventive Medicine, Hanyang University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0002-4986-514X
Jaiyong KimInstitute of Artificial Intelligence and Big Data in Medicine, Yonsei University Wonju College of Medicine, Wonju, Korea. dockjy2@gmail.com.ORCID https://orcid.org/0000-0003-0985-7871
Kyu Dong ChoHealth Insurance Research Institute, National Health Insurance Service, Wonju, Korea.ORCID https://orcid.org/0000-0002-3267-489X
Nakyoung LeeDepartment of Preventive Medicine, Hanyang University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0002-3867-4508

Funding

Government-wide R&D Fund project for infectious disease research
6 · The paper itself

Abstract

backgroundMortality of coronavirus disease 2019 (COVID-19) is a major concern for quarantine departments in all countries. This is because the mortality of infectious diseases determines the basic policy stance of measures to prevent infectious diseases. Early screening of high-risk groups and taking action are the basics of disease management. This study examined the correlation of comorbidities on the mortality of patients with COVID-19.

methodsWe constructed epidemiologic characteristics and medical history database based on the Korean National Health Insurance Service Big Data and linked COVID-19 registry data of Korea Centers for Disease Control & Prevention (KCDC) for this emergent observational cohort study. A total of 9,148 patients with confirmed COVID-19 were included. Mortalities by sex, age, district, income level and all range of comorbidities classified by International Classification of Diseases-10 based 298 categories were estimated.

resultsThere were 3,556 male confirmed cases, 67 deaths, and crude death rate (CDR) of 1.88%. There were 5,592 females, 63 deaths, and CDR of 1.13%. The most confirmed cases were 1,352 patients between the ages of 20 to 24, followed by 25 to 29. As a result of multivariate logistic regression analysis that adjusted epidemiologic factors to view the risk of death, the odds ratio of death would be hemorrhagic conditions and other diseases of blood and blood-forming organs 3.88-fold (95% confidence interval [CI], 1.52-9.88), heart failure 3.17-fold (95% CI, 1.88-5.34), renal failure 3.07-fold (95% CI, 1.43-6.61), prostate malignant neoplasm 2.88-fold (95% CI, 1.01-8.22), acute myocardial infarction 2.38-fold (95% CI, 1.03-5.49), diabetes was 1.82-fold (95% CI, 1.25-2.67), and other ischemic heart disease 1.71-fold (95% CI, 1.09-2.66).

conclusionWe hope that this study could provide information on high risk groups for preemptive interventions. In the future, if a vaccine for COVID-19 is developed, it is expected that this study will be the basic data for recommending immunization by selecting those with chronic disease that had high risk of death, as recommended target diseases for vaccination.

Indexed as

ComorbidityAdultAgedBetacoronavirusBig DataChronic DiseaseCoronavirus InfectionsCOVID-19FemaleHumansMaleMiddle AgedNational Health ProgramsPandemicsPneumonia, ViralRepublic of KoreaChronic DiseasesComorbiditiesCOVID-19Mortality Risk

Identifiers

PMID32627443
PMCPMC7338208

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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.