Evidence map›Paper›PMID 40078662›Full record

ArticleBiosafety and health2024

An online survey among convalescents 5 months post SARS-CoV-2 infection in China.

Yalan Wang, Maoshun Liu, Yuanyuan Guo, Min Li, Peipei Guo, Wenjun He, Tian Ma, Peipei Liu, Yaxin Guo, Beiwei Ye and 2 more

Abstract read
In one paragraph

Article in Biosafety and health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
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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

12 authors.

Yalan WangNHC Key Laboratory of Biosafety, National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention (China CDC), Beijing 102206, China.
Maoshun LiuNHC Key Laboratory of Biosafety, National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention (China CDC), Beijing 102206, China.
Yuanyuan GuoNHC Key Laboratory of Biosafety, National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention (China CDC), Beijing 102206, China.
Min LiNHC Key Laboratory of Biosafety, National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention (China CDC), Beijing 102206, China.
Peipei GuoNHC Key Laboratory of Biosafety, National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention (China CDC), Beijing 102206, China.
Wenjun HeNHC Key Laboratory of Biosafety, National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention (China CDC), Beijing 102206, China.
Tian MaNHC Key Laboratory of Biosafety, National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention (China CDC), Beijing 102206, China.
Peipei LiuNHC Key Laboratory of Biosafety, National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention (China CDC), Beijing 102206, China.
Yaxin GuoNHC Key Laboratory of Biosafety, National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention (China CDC), Beijing 102206, China.
Beiwei YeNHC Key Laboratory of Biosafety, National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention (China CDC), Beijing 102206, China.
Jun LiuNHC Key Laboratory of Biosafety, National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention (China CDC), Beijing 102206, China.
Guizhen WuNHC Key Laboratory of Biosafety, National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention (China CDC), Beijing 102206, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The effects of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection persist months and years after recovery. We conducted an online survey to assess the health condition of convalescents approximately 5 months following the primary infection of SARS-CoV-2. The study recruited 5,510 individuals who were primary infected, 626 participants who had experienced reinfection, and 521 participants who were without infective history. The most common disorders after the primary infection group were fatigue (15.18 %), memory issue (13.13 %), post-exertional malaise (PEM, 11.68 %), and brain fog (11.29 %) at the time of survey. In addition, SARS-CoV-2 infection had an impact on the reproductive systems. In stepwise logistic regression analysis, smoking currently, with background diseases, and outpatient visits in the acute phase could be associated with moderate / severe disorders. Further analysis of different background diseases showed that allergic rhinitis, hyperlipidemia, cardiovascular disease, autoimmune diseases, neurological diseases, and asthma likely increased the risk of moderate/severe disorders. The probability of developing disorders of individuals with SARS-CoV-2 reinfection was higher before the secondary infection than uninfected people. Fatigue, PEM, muscle pain/spasms, chills, joint pain, excessive sweating at rest, headache / dizziness, sore throat or foreign body sensation in the throat, cough, expectoration, dry / painful / watery eyes, loss of appetite and constipation were associated with an increased risk of reinfection. It was essential to undertake further research with enhanced randomization in a larger sample in the community, and to strengthen the validation of the research conclusions. The findings of this study contribute to a deeper understanding of the health recovery process among coronavirus disease 2019 (COVID-19) convalescents. Moreover, the findings help identify characteristic health risk factors associated with convalescents and highlight the risk of moderate / severe disorders and reinfection. Furthermore, the findings also provide valuable guidance and reference for SARS-CoV-2 rehabilitation strategies and the prevention of reinfection, offering insights for scientific recommendations.

Indexed as

DisordersReinfectionSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)

Identifiers

PMID40078662
PMCPMC11894947

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.