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COVID Symptoms, Symptom Clusters, and Predictors for Becoming a Long-Hauler: Looking for Clarity in the Haze of the Pandemic
Emerging data suggest that the effects of infection with SARS-CoV-2 are far reaching extending beyond those with severe acute disease. Specifically, the presence of persistent symptoms after apparent resolution from COVID-19 have frequently been reported throughout the pandemic by individuals labele...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Cold Spring Harbor Laboratory
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7941647/ https://www.ncbi.nlm.nih.gov/pubmed/33688670 http://dx.doi.org/10.1101/2021.03.03.21252086 |
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author | Huang, Yong Pinto, Melissa D. Borelli, Jessica L. Mehrabadi, Milad Asgari Abrihim, Heather Dutt, Nikil Lambert, Natalie Nurmi, Erika L. Chakraborty, Rana Rahmani, Amir M. Downs, Charles A. |
author_facet | Huang, Yong Pinto, Melissa D. Borelli, Jessica L. Mehrabadi, Milad Asgari Abrihim, Heather Dutt, Nikil Lambert, Natalie Nurmi, Erika L. Chakraborty, Rana Rahmani, Amir M. Downs, Charles A. |
author_sort | Huang, Yong |
collection | PubMed |
description | Emerging data suggest that the effects of infection with SARS-CoV-2 are far reaching extending beyond those with severe acute disease. Specifically, the presence of persistent symptoms after apparent resolution from COVID-19 have frequently been reported throughout the pandemic by individuals labeled as “long-haulers”. The purpose of this study was to assess for symptoms at days 0–10 and 61+ among subjects with PCR-confirmed SARS-CoV-2 infection. The University of California COvid Research Data Set (UC CORDS) was used to identify 1407 records that met inclusion criteria. Symptoms attributable to COVID-19 were extracted from the electronic health record. Symptoms reported over the previous year prior to COVID-19 were excluded, using nonnegative matrix factorization (NMF) followed by graph lasso to assess relationships between symptoms. A model was developed predictive for becoming a long-hauler based on symptoms. 27% reported persistent symptoms after 60 days. Women were more likely to become long-haulers, and all age groups were represented with those aged 50 ± 20 years comprising 72% of cases. Presenting symptoms included palpitations, chronic rhinitis, dysgeusia, chills, insomnia, hyperhidrosis, anxiety, sore throat, and headache among others. We identified 5 symptom clusters at day 61+: chest pain-cough, dyspnea-cough, anxiety-tachycardia, abdominal pain-nausea, and low back pain-joint pain. Long-haulers represent a very significant public health concern, and there are no guidelines to address their diagnosis and management. Additional studies are urgently needed that focus on the physical, mental, and emotional impact of long-term COVID-19 survivors who become long-haulers. |
format | Online Article Text |
id | pubmed-7941647 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-79416472021-03-10 COVID Symptoms, Symptom Clusters, and Predictors for Becoming a Long-Hauler: Looking for Clarity in the Haze of the Pandemic Huang, Yong Pinto, Melissa D. Borelli, Jessica L. Mehrabadi, Milad Asgari Abrihim, Heather Dutt, Nikil Lambert, Natalie Nurmi, Erika L. Chakraborty, Rana Rahmani, Amir M. Downs, Charles A. medRxiv Article Emerging data suggest that the effects of infection with SARS-CoV-2 are far reaching extending beyond those with severe acute disease. Specifically, the presence of persistent symptoms after apparent resolution from COVID-19 have frequently been reported throughout the pandemic by individuals labeled as “long-haulers”. The purpose of this study was to assess for symptoms at days 0–10 and 61+ among subjects with PCR-confirmed SARS-CoV-2 infection. The University of California COvid Research Data Set (UC CORDS) was used to identify 1407 records that met inclusion criteria. Symptoms attributable to COVID-19 were extracted from the electronic health record. Symptoms reported over the previous year prior to COVID-19 were excluded, using nonnegative matrix factorization (NMF) followed by graph lasso to assess relationships between symptoms. A model was developed predictive for becoming a long-hauler based on symptoms. 27% reported persistent symptoms after 60 days. Women were more likely to become long-haulers, and all age groups were represented with those aged 50 ± 20 years comprising 72% of cases. Presenting symptoms included palpitations, chronic rhinitis, dysgeusia, chills, insomnia, hyperhidrosis, anxiety, sore throat, and headache among others. We identified 5 symptom clusters at day 61+: chest pain-cough, dyspnea-cough, anxiety-tachycardia, abdominal pain-nausea, and low back pain-joint pain. Long-haulers represent a very significant public health concern, and there are no guidelines to address their diagnosis and management. Additional studies are urgently needed that focus on the physical, mental, and emotional impact of long-term COVID-19 survivors who become long-haulers. Cold Spring Harbor Laboratory 2021-03-05 /pmc/articles/PMC7941647/ /pubmed/33688670 http://dx.doi.org/10.1101/2021.03.03.21252086 Text en https://creativecommons.org/licenses/by-nd/4.0/This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, and only so long as attribution is given to the creator. The license allows for commercial use. |
spellingShingle | Article Huang, Yong Pinto, Melissa D. Borelli, Jessica L. Mehrabadi, Milad Asgari Abrihim, Heather Dutt, Nikil Lambert, Natalie Nurmi, Erika L. Chakraborty, Rana Rahmani, Amir M. Downs, Charles A. COVID Symptoms, Symptom Clusters, and Predictors for Becoming a Long-Hauler: Looking for Clarity in the Haze of the Pandemic |
title | COVID Symptoms, Symptom Clusters, and Predictors for Becoming a Long-Hauler: Looking for Clarity in the Haze of the Pandemic |
title_full | COVID Symptoms, Symptom Clusters, and Predictors for Becoming a Long-Hauler: Looking for Clarity in the Haze of the Pandemic |
title_fullStr | COVID Symptoms, Symptom Clusters, and Predictors for Becoming a Long-Hauler: Looking for Clarity in the Haze of the Pandemic |
title_full_unstemmed | COVID Symptoms, Symptom Clusters, and Predictors for Becoming a Long-Hauler: Looking for Clarity in the Haze of the Pandemic |
title_short | COVID Symptoms, Symptom Clusters, and Predictors for Becoming a Long-Hauler: Looking for Clarity in the Haze of the Pandemic |
title_sort | covid symptoms, symptom clusters, and predictors for becoming a long-hauler: looking for clarity in the haze of the pandemic |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7941647/ https://www.ncbi.nlm.nih.gov/pubmed/33688670 http://dx.doi.org/10.1101/2021.03.03.21252086 |
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