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Five cluster classifications of long COVID and their background factors: A cross-sectional study in Japan
PURPOSE: The long-term symptoms of coronavirus disease 2019 (COVID-19), i.e., long COVID, have drawn research attention. Evaluating its subjective symptoms is difficult, and no established pathophysiology or treatment exists. Although there are several reports of long COVID classifications, there ar...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10081305/ https://www.ncbi.nlm.nih.gov/pubmed/37027067 http://dx.doi.org/10.1007/s10238-023-01057-6 |
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author | Tsuchida, Tomoya Yoshimura, Naohito Ishizuka, Kosuke Katayama, Kohta Inoue, Yoko Hirose, Masanori Nakagama, Yu Kido, Yasutoshi Sugimori, Hiroki Matsuda, Takahide Ohira, Yoshiyuki |
author_facet | Tsuchida, Tomoya Yoshimura, Naohito Ishizuka, Kosuke Katayama, Kohta Inoue, Yoko Hirose, Masanori Nakagama, Yu Kido, Yasutoshi Sugimori, Hiroki Matsuda, Takahide Ohira, Yoshiyuki |
author_sort | Tsuchida, Tomoya |
collection | PubMed |
description | PURPOSE: The long-term symptoms of coronavirus disease 2019 (COVID-19), i.e., long COVID, have drawn research attention. Evaluating its subjective symptoms is difficult, and no established pathophysiology or treatment exists. Although there are several reports of long COVID classifications, there are no reports comparing classifications that include patient characteristics, such as autonomic dysfunction and work status. We aimed to classify patients into clusters based on their subjective symptoms during their first outpatient visit and evaluate their background for these clusters. METHODS: Included patients visited our outpatient clinic between January 18, 2021, and May 30, 2022. They were aged ≥ 15 years and confirmed to have SARS-CoV-2 infection and residual symptoms lasting at least 2 months post-infection. Patients were evaluated using a 3-point scale for 23 symptoms and classified into five clusters (1. fatigue only; 2. fatigue, dyspnea, chest pain, palpitations, and forgetfulness; 3. fatigue, headache, insomnia, anxiety, motivation loss, low mood, and forgetfulness; 4. hair loss; and 5. taste and smell disorders) using CLUSTER. For continuous variables, each cluster was compared using the Kruskal–Wallis test. Multiple comparison tests were performed using the Dunn’s test for significant results. For nominal variables, a Chi-square test was performed; for significant results, a residual analysis was conducted with the adjusted residuals. RESULTS: Compared to patients in other cluster categories, those in cluster categories 2 and 3 had higher proportions of autonomic nervous system disorders and leaves of absence, respectively. CONCLUSIONS: Long COVID cluster classification provided an overall assessment of COVID-19. Different treatment strategies must be used based on physical and psychiatric symptoms and employment factors. |
format | Online Article Text |
id | pubmed-10081305 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-100813052023-04-07 Five cluster classifications of long COVID and their background factors: A cross-sectional study in Japan Tsuchida, Tomoya Yoshimura, Naohito Ishizuka, Kosuke Katayama, Kohta Inoue, Yoko Hirose, Masanori Nakagama, Yu Kido, Yasutoshi Sugimori, Hiroki Matsuda, Takahide Ohira, Yoshiyuki Clin Exp Med Research PURPOSE: The long-term symptoms of coronavirus disease 2019 (COVID-19), i.e., long COVID, have drawn research attention. Evaluating its subjective symptoms is difficult, and no established pathophysiology or treatment exists. Although there are several reports of long COVID classifications, there are no reports comparing classifications that include patient characteristics, such as autonomic dysfunction and work status. We aimed to classify patients into clusters based on their subjective symptoms during their first outpatient visit and evaluate their background for these clusters. METHODS: Included patients visited our outpatient clinic between January 18, 2021, and May 30, 2022. They were aged ≥ 15 years and confirmed to have SARS-CoV-2 infection and residual symptoms lasting at least 2 months post-infection. Patients were evaluated using a 3-point scale for 23 symptoms and classified into five clusters (1. fatigue only; 2. fatigue, dyspnea, chest pain, palpitations, and forgetfulness; 3. fatigue, headache, insomnia, anxiety, motivation loss, low mood, and forgetfulness; 4. hair loss; and 5. taste and smell disorders) using CLUSTER. For continuous variables, each cluster was compared using the Kruskal–Wallis test. Multiple comparison tests were performed using the Dunn’s test for significant results. For nominal variables, a Chi-square test was performed; for significant results, a residual analysis was conducted with the adjusted residuals. RESULTS: Compared to patients in other cluster categories, those in cluster categories 2 and 3 had higher proportions of autonomic nervous system disorders and leaves of absence, respectively. CONCLUSIONS: Long COVID cluster classification provided an overall assessment of COVID-19. Different treatment strategies must be used based on physical and psychiatric symptoms and employment factors. Springer International Publishing 2023-04-07 /pmc/articles/PMC10081305/ /pubmed/37027067 http://dx.doi.org/10.1007/s10238-023-01057-6 Text en © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Research Tsuchida, Tomoya Yoshimura, Naohito Ishizuka, Kosuke Katayama, Kohta Inoue, Yoko Hirose, Masanori Nakagama, Yu Kido, Yasutoshi Sugimori, Hiroki Matsuda, Takahide Ohira, Yoshiyuki Five cluster classifications of long COVID and their background factors: A cross-sectional study in Japan |
title | Five cluster classifications of long COVID and their background factors: A cross-sectional study in Japan |
title_full | Five cluster classifications of long COVID and their background factors: A cross-sectional study in Japan |
title_fullStr | Five cluster classifications of long COVID and their background factors: A cross-sectional study in Japan |
title_full_unstemmed | Five cluster classifications of long COVID and their background factors: A cross-sectional study in Japan |
title_short | Five cluster classifications of long COVID and their background factors: A cross-sectional study in Japan |
title_sort | five cluster classifications of long covid and their background factors: a cross-sectional study in japan |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10081305/ https://www.ncbi.nlm.nih.gov/pubmed/37027067 http://dx.doi.org/10.1007/s10238-023-01057-6 |
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