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Clustering Analysis Identified Three Long COVID Phenotypes and Their Association with General Health Status and Working Ability
Background/aim: This study aimed to distinguish different phenotypes of long COVID through the post-COVID syndrome (PCS) score based on long-term persistent symptoms following COVID-19 and evaluate whether these symptoms affect general health and work ability. In addition, the study identified predi...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10253616/ https://www.ncbi.nlm.nih.gov/pubmed/37297812 http://dx.doi.org/10.3390/jcm12113617 |
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author | Kisiel, Marta A. Lee, Seika Malmquist, Sara Rykatkin, Oliver Holgert, Sebastian Janols, Helena Janson, Christer Zhou, Xingwu |
author_facet | Kisiel, Marta A. Lee, Seika Malmquist, Sara Rykatkin, Oliver Holgert, Sebastian Janols, Helena Janson, Christer Zhou, Xingwu |
author_sort | Kisiel, Marta A. |
collection | PubMed |
description | Background/aim: This study aimed to distinguish different phenotypes of long COVID through the post-COVID syndrome (PCS) score based on long-term persistent symptoms following COVID-19 and evaluate whether these symptoms affect general health and work ability. In addition, the study identified predictors for severe long COVID. Method: This cluster analysis included cross-sectional data from three cohorts of patients after COVID-19: non-hospitalized (n = 401), hospitalized (n = 98) and those enrolled at the post-COVID outpatient’s clinic (n = 85). All the subjects responded to the survey on persistent long-term symptoms and sociodemographic and clinical factors. K-Means cluster analysis and ordinal logistic regression were used to create PCS scores that were used to distinguish patients’ phenotypes. Results: 506 patients with complete data on persistent symptoms were divided into three distinct phenotypes: none/mild (59%), moderate (22%) and severe (19%). The patients with severe phenotype, with the predominating symptoms were fatigue, cognitive impairment and depression, had the most reduced general health status and work ability. Smoking, snuff, body mass index (BMI), diabetes, chronic pain and symptom severity at COVID-19 onset were factors predicting severe phenotype. Conclusion: This study suggested three phenotypes of long COVID, where the most severe was associated with the highest impact on general health status and working ability. This knowledge on long COVID phenotypes could be used by clinicians to support their medical decisions regarding prioritizing and more detailed follow-up of some patient groups. |
format | Online Article Text |
id | pubmed-10253616 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-102536162023-06-10 Clustering Analysis Identified Three Long COVID Phenotypes and Their Association with General Health Status and Working Ability Kisiel, Marta A. Lee, Seika Malmquist, Sara Rykatkin, Oliver Holgert, Sebastian Janols, Helena Janson, Christer Zhou, Xingwu J Clin Med Article Background/aim: This study aimed to distinguish different phenotypes of long COVID through the post-COVID syndrome (PCS) score based on long-term persistent symptoms following COVID-19 and evaluate whether these symptoms affect general health and work ability. In addition, the study identified predictors for severe long COVID. Method: This cluster analysis included cross-sectional data from three cohorts of patients after COVID-19: non-hospitalized (n = 401), hospitalized (n = 98) and those enrolled at the post-COVID outpatient’s clinic (n = 85). All the subjects responded to the survey on persistent long-term symptoms and sociodemographic and clinical factors. K-Means cluster analysis and ordinal logistic regression were used to create PCS scores that were used to distinguish patients’ phenotypes. Results: 506 patients with complete data on persistent symptoms were divided into three distinct phenotypes: none/mild (59%), moderate (22%) and severe (19%). The patients with severe phenotype, with the predominating symptoms were fatigue, cognitive impairment and depression, had the most reduced general health status and work ability. Smoking, snuff, body mass index (BMI), diabetes, chronic pain and symptom severity at COVID-19 onset were factors predicting severe phenotype. Conclusion: This study suggested three phenotypes of long COVID, where the most severe was associated with the highest impact on general health status and working ability. This knowledge on long COVID phenotypes could be used by clinicians to support their medical decisions regarding prioritizing and more detailed follow-up of some patient groups. MDPI 2023-05-23 /pmc/articles/PMC10253616/ /pubmed/37297812 http://dx.doi.org/10.3390/jcm12113617 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Kisiel, Marta A. Lee, Seika Malmquist, Sara Rykatkin, Oliver Holgert, Sebastian Janols, Helena Janson, Christer Zhou, Xingwu Clustering Analysis Identified Three Long COVID Phenotypes and Their Association with General Health Status and Working Ability |
title | Clustering Analysis Identified Three Long COVID Phenotypes and Their Association with General Health Status and Working Ability |
title_full | Clustering Analysis Identified Three Long COVID Phenotypes and Their Association with General Health Status and Working Ability |
title_fullStr | Clustering Analysis Identified Three Long COVID Phenotypes and Their Association with General Health Status and Working Ability |
title_full_unstemmed | Clustering Analysis Identified Three Long COVID Phenotypes and Their Association with General Health Status and Working Ability |
title_short | Clustering Analysis Identified Three Long COVID Phenotypes and Their Association with General Health Status and Working Ability |
title_sort | clustering analysis identified three long covid phenotypes and their association with general health status and working ability |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10253616/ https://www.ncbi.nlm.nih.gov/pubmed/37297812 http://dx.doi.org/10.3390/jcm12113617 |
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