tetano
Editor, Senior Moderator
Clin Exp Med
. 2023 Apr 7.
doi: 10.1007/s10238-023-01057-6. Online ahead of print.
Five cluster classifications of long COVID and their background factors: A cross-sectional study in Japan
Tomoya Tsuchida[SUP] 1 [/SUP], Naohito Yoshimura[SUP] 2 [/SUP], Kosuke Ishizuka[SUP] 3 [/SUP], Kohta Katayama[SUP] 3 [/SUP], Yoko Inoue[SUP] 3 [/SUP], Masanori Hirose[SUP] 3 [/SUP], Yu Nakagama[SUP] 4 5 [/SUP], Yasutoshi Kido[SUP] 4 5 [/SUP], Hiroki Sugimori[SUP] 6 [/SUP], Takahide Matsuda[SUP] 3 [/SUP], Yoshiyuki Ohira[SUP] 3 [/SUP]
Affiliations
Abstract
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.
Keywords: Cluster classification; Coronavirus disease 2019; Long COVID; Symptoms.
. 2023 Apr 7.
doi: 10.1007/s10238-023-01057-6. Online ahead of print.
Five cluster classifications of long COVID and their background factors: A cross-sectional study in Japan
Tomoya Tsuchida[SUP] 1 [/SUP], Naohito Yoshimura[SUP] 2 [/SUP], Kosuke Ishizuka[SUP] 3 [/SUP], Kohta Katayama[SUP] 3 [/SUP], Yoko Inoue[SUP] 3 [/SUP], Masanori Hirose[SUP] 3 [/SUP], Yu Nakagama[SUP] 4 5 [/SUP], Yasutoshi Kido[SUP] 4 5 [/SUP], Hiroki Sugimori[SUP] 6 [/SUP], Takahide Matsuda[SUP] 3 [/SUP], Yoshiyuki Ohira[SUP] 3 [/SUP]
Affiliations
- PMID: 37027067
- DOI: 10.1007/s10238-023-01057-6
Abstract
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.
Keywords: Cluster classification; Coronavirus disease 2019; Long COVID; Symptoms.