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Assessing Smoking Status and Risk of SARS-CoV-2 Infection: A Machine Learning Approach among Veterans

The role of smoking in the risk of SARS-CoV-2 infection is unclear. We used a retrospective cohort design to study data from veterans’ Electronic Medical Record to assess the impact of smoking on the risk of SARS-CoV-2 infection. Veterans tested for the SARS-CoV-2 virus from 02/01/2020 to 02/28/2021...

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Autores principales: Nono Djotsa, Alice B. S., Helmer, Drew A., Park, Catherine, Lynch, Kristine E., Sharafkhaneh, Amir, Naik, Aanand D., Razjouyan, Javad, Amos, Christopher I.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9319659/
https://www.ncbi.nlm.nih.gov/pubmed/35885771
http://dx.doi.org/10.3390/healthcare10071244
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author Nono Djotsa, Alice B. S.
Helmer, Drew A.
Park, Catherine
Lynch, Kristine E.
Sharafkhaneh, Amir
Naik, Aanand D.
Razjouyan, Javad
Amos, Christopher I.
author_facet Nono Djotsa, Alice B. S.
Helmer, Drew A.
Park, Catherine
Lynch, Kristine E.
Sharafkhaneh, Amir
Naik, Aanand D.
Razjouyan, Javad
Amos, Christopher I.
author_sort Nono Djotsa, Alice B. S.
collection PubMed
description The role of smoking in the risk of SARS-CoV-2 infection is unclear. We used a retrospective cohort design to study data from veterans’ Electronic Medical Record to assess the impact of smoking on the risk of SARS-CoV-2 infection. Veterans tested for the SARS-CoV-2 virus from 02/01/2020 to 02/28/2021 were classified as: Never Smokers (NS), Former Smokers (FS), and Current Smokers (CS). We report the adjusted odds ratios (aOR) for potential confounders obtained from a cascade machine learning algorithm. We found a 19.6% positivity rate among 1,176,306 veterans tested for SARS-CoV-2 infection. The positivity proportion among NS (22.0%) was higher compared with FS (19.2%) and CS (11.5%). The adjusted odds of testing positive for CS (aOR:0.51; 95%CI: 0.50, 0.52) and FS (aOR:0.89; 95%CI:0.88, 0.90) were significantly lower compared with NS. Four pre-existing conditions, including dementia, lower respiratory infections, pneumonia, and septic shock, were associated with a higher risk of testing positive, whereas the use of the decongestant drug phenylephrine or having a history of cancer were associated with a lower risk. CS and FS compared with NS had lower risks of testing positive for SARS-CoV-2. These findings highlight our evolving understanding of the role of smoking status on the risk of SARS-CoV-2 infection.
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spelling pubmed-93196592022-07-27 Assessing Smoking Status and Risk of SARS-CoV-2 Infection: A Machine Learning Approach among Veterans Nono Djotsa, Alice B. S. Helmer, Drew A. Park, Catherine Lynch, Kristine E. Sharafkhaneh, Amir Naik, Aanand D. Razjouyan, Javad Amos, Christopher I. Healthcare (Basel) Article The role of smoking in the risk of SARS-CoV-2 infection is unclear. We used a retrospective cohort design to study data from veterans’ Electronic Medical Record to assess the impact of smoking on the risk of SARS-CoV-2 infection. Veterans tested for the SARS-CoV-2 virus from 02/01/2020 to 02/28/2021 were classified as: Never Smokers (NS), Former Smokers (FS), and Current Smokers (CS). We report the adjusted odds ratios (aOR) for potential confounders obtained from a cascade machine learning algorithm. We found a 19.6% positivity rate among 1,176,306 veterans tested for SARS-CoV-2 infection. The positivity proportion among NS (22.0%) was higher compared with FS (19.2%) and CS (11.5%). The adjusted odds of testing positive for CS (aOR:0.51; 95%CI: 0.50, 0.52) and FS (aOR:0.89; 95%CI:0.88, 0.90) were significantly lower compared with NS. Four pre-existing conditions, including dementia, lower respiratory infections, pneumonia, and septic shock, were associated with a higher risk of testing positive, whereas the use of the decongestant drug phenylephrine or having a history of cancer were associated with a lower risk. CS and FS compared with NS had lower risks of testing positive for SARS-CoV-2. These findings highlight our evolving understanding of the role of smoking status on the risk of SARS-CoV-2 infection. MDPI 2022-07-04 /pmc/articles/PMC9319659/ /pubmed/35885771 http://dx.doi.org/10.3390/healthcare10071244 Text en © 2022 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
Nono Djotsa, Alice B. S.
Helmer, Drew A.
Park, Catherine
Lynch, Kristine E.
Sharafkhaneh, Amir
Naik, Aanand D.
Razjouyan, Javad
Amos, Christopher I.
Assessing Smoking Status and Risk of SARS-CoV-2 Infection: A Machine Learning Approach among Veterans
title Assessing Smoking Status and Risk of SARS-CoV-2 Infection: A Machine Learning Approach among Veterans
title_full Assessing Smoking Status and Risk of SARS-CoV-2 Infection: A Machine Learning Approach among Veterans
title_fullStr Assessing Smoking Status and Risk of SARS-CoV-2 Infection: A Machine Learning Approach among Veterans
title_full_unstemmed Assessing Smoking Status and Risk of SARS-CoV-2 Infection: A Machine Learning Approach among Veterans
title_short Assessing Smoking Status and Risk of SARS-CoV-2 Infection: A Machine Learning Approach among Veterans
title_sort assessing smoking status and risk of sars-cov-2 infection: a machine learning approach among veterans
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9319659/
https://www.ncbi.nlm.nih.gov/pubmed/35885771
http://dx.doi.org/10.3390/healthcare10071244
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