Evidence map›Paper›PMID 39451477›Full record

ArticleHealthcare (Basel, Switzerland)2024

Prevalence, Risk Factors, and Impact of Long COVID Among Adults in South Korea.

Ha-Eun Son, Young-Seoub Hong, Seungho Lee, Hyunjin Son

Abstract read
In one paragraph

Article in Healthcare (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
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

4 authors.

Ha-Eun SonDepartment of Preventive Medicine, College of Medicine, Dong-A University, Busan 49201, Republic of Korea.
Young-Seoub HongDepartment of Preventive Medicine, College of Medicine, Dong-A University, Busan 49201, Republic of Korea.ORCID 0000-0002-9037-3761
Seungho LeeDepartment of Preventive Medicine, College of Medicine, Dong-A University, Busan 49201, Republic of Korea.ORCID 0000-0001-7069-267X
Hyunjin SonDepartment of Preventive Medicine, College of Medicine, Dong-A University, Busan 49201, Republic of Korea.ORCID 0000-0002-6571-5109

Funding

The National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) 2022R1F1A106619512
6 · The paper itself

Abstract

objectivesThis study aimed to identify the prevalence, risk factors, and impact of long COVID in a community-based representative sample of patients with COVID-19 aged 19-64 years.

methodsA total of 975 participants completed online or telephone surveys at 1 and 3 months post-diagnosis, covering persistent symptoms, daily activity limitations, vaccination status, and underlying diseases.

resultsLong COVID, as defined by the WHO criteria, had a prevalence of 19.7-24.9% in females and 12.7% in males. Logistic regression revealed that the odds of having long COVID symptoms were higher among females compared to males (OR, 2.43; 95% CI, 1.53-3.87), and higher in those aged ≥ 30 years compared to those aged 19-29 years: 30-39 years (OR, 2.91; 95% CI, 1.59-5.33), 40-49 years (OR, 2.72; 95% CI, 1.51-4.89), and 50-64 years (OR, 1.96; 95% CI, 1.10-3.49). Additionally, patients with underlying diseases had higher odds of long COVID symptoms compared to those without underlying diseases (OR, 1.81; 95% CI, 1.24-2.64). Among those with long COVID, 54.2% experienced daily activity limitations, and 40.6% received treatment. Furthermore, lower income groups faced greater daily activity limitations but had similar treatment rates to higher income groups.

conclusionsThese findings emphasize the need for interest in and the development of programs to support these low-income populations.

Indexed as

COVID-19daily activity limitationspost-COVID-19 conditionprevalencerisk factorssymptoms

Identifiers

PMID39451477
PMCPMC11506880

What OpenQuestion holds

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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.