Evidence map›Paper›PMID 33352326›Full record

ArticleInternational journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases2021

Association of prescribed medications with the risk of COVID-19 infection and severity among adults in South Korea.

Kyungmin Huh, Wonjun Ji, Minsun Kang, Jinwook Hong, Gi Hwan Bae, Rugyeom Lee, Yewon Na, Jaehun Jung

Abstract read
In one paragraph

Article in International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 6 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.

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

17 citing papers in PubMed, 6 syntheses or guidelines 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

8 authors.

Kyungmin HuhDivision of Infectious Diseases, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351, South Korea.
Wonjun JiDepartment of Pulmonary and Critical Care Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, 05505, South Korea.
Minsun KangArtificial Intelligence and Big-Data Convergence Center, Gil Medical Center, Gachon University College of Medicine, Incheon, 21565, South Korea.
Jinwook HongArtificial Intelligence and Big-Data Convergence Center, Gil Medical Center, Gachon University College of Medicine, Incheon, 21565, South Korea.
Gi Hwan BaeArtificial Intelligence and Big-Data Convergence Center, Gil Medical Center, Gachon University College of Medicine, Incheon, 21565, South Korea.
Rugyeom LeeArtificial Intelligence and Big-Data Convergence Center, Gil Medical Center, Gachon University College of Medicine, Incheon, 21565, South Korea.
Yewon NaArtificial Intelligence and Big-Data Convergence Center, Gil Medical Center, Gachon University College of Medicine, Incheon, 21565, South Korea.
Jaehun JungArtificial Intelligence and Big-Data Convergence Center, Gil Medical Center, Gachon University College of Medicine, Incheon, 21565, South Korea; Department of Preventive Medicine, Gachon University College of Medicine, Incheon, 21565, South Korea. Electronic address: eastside1st@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesConcerns have been expressed that some drugs may increase susceptibility to SARS-CoV-2 infection. In contrast, other drugs have generated interest as potential therapeutic agents.

methodsAll adults aged ≥18 years who were tested for COVID-19 were included. Exposure was defined as a prescription of study drugs which would have been continued until 7 days prior to test for COVID-19 or later. The outcome measures were the diagnosis of COVID-19 and severe COVID-19. Disease risk score matching and multiple logistic regression was used.

resultsMatched claims and testing results were available for 219,961 subjects, of whom 7,341 (3.34%) were diagnosed with COVID-19. Patients were matched to 36,705 controls, and the subset of 878 patients of severe COVID-19 also matched with 1,927 mild-to-moderate patients. Angiotensin receptor blockers were not associated with either the diagnosis of COVID-19 (adjusted OR [aOR], 1.02; 95% confidence interval [CI], 0.90-1.15) or severe disease (aOR, 1.11; 95% CI, 0.87-1.42). The use of hydroxychloroquine was not associated with a lower risk for COVID-19 (aOR, 0.94; 95% CI, 0.53-1.66) or severe disease (aOR, 3.51; 95% CI, 0.76-16.22).

conclusionsIn this national claims data-based case-control study, no commonly prescribed medications were associated with risk of COVID-19 infection or COVID-19 severity.

Indexed as

SARS-CoV-2AdultAgedAngiotensin Receptor AntagonistsCOVID-19Disease SusceptibilityFemaleHumansHydroxychloroquineLogistic ModelsMaleMiddle AgedRetrospective StudiesRisk FactorsSeverity of Illness IndexAngiotensin Receptor AntagonistsHydroxychloroquineCOVID-19Disease risk scoreProphylaxisSouth KoreaTreatment

Identifiers

PMID33352326
PMCPMC7749643

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Registered trials

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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.