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A phenome-wide association study (PheWAS) of COVID-19 outcomes by race using the electronic health records data in Michigan Medicine
BACKGROUND: We perform a phenome-wide scan to identify pre-existing conditions related to COVID-19 susceptibility and prognosis across the medical phenome and how they vary by race. METHODS: The study is comprised of 53,853 patients who were tested/positive for COVID-19 between March 10 and Septembe...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7418740/ https://www.ncbi.nlm.nih.gov/pubmed/32793923 http://dx.doi.org/10.1101/2020.06.29.20141564 |
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author | Salvatore, Maxwell Gu, Tian Mack, Jasmine A. Sankar, Swaraaj Prabhu Patil, Snehal Valley, Thomas S. Singh, Karandeep Nallamothu, Brahmajee K. Kheterpal, Sachin Lisabeth, Lynda Fritsche, Lars G. Mukherjee, Bhramar |
author_facet | Salvatore, Maxwell Gu, Tian Mack, Jasmine A. Sankar, Swaraaj Prabhu Patil, Snehal Valley, Thomas S. Singh, Karandeep Nallamothu, Brahmajee K. Kheterpal, Sachin Lisabeth, Lynda Fritsche, Lars G. Mukherjee, Bhramar |
author_sort | Salvatore, Maxwell |
collection | PubMed |
description | BACKGROUND: We perform a phenome-wide scan to identify pre-existing conditions related to COVID-19 susceptibility and prognosis across the medical phenome and how they vary by race. METHODS: The study is comprised of 53,853 patients who were tested/positive for COVID-19 between March 10 and September 2, 2020 at a large academic medical center. RESULTS: Pre-existing conditions strongly associated with hospitalization were renal failure, pulmonary heart disease, and respiratory failure. Hematopoietic conditions were associated with ICU admission/mortality and mental disorders were associated with mortality in non-Hispanic Whites. Circulatory system and genitourinary conditions were associated with ICU admission/mortality in non-Hispanic Blacks. CONCLUSIONS: Understanding pre-existing clinical diagnoses related to COVID-19 outcomes informs the need for targeted screening to support specific vulnerable populations to improve disease prevention and healthcare delivery. |
format | Online Article Text |
id | pubmed-7418740 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-74187402020-08-13 A phenome-wide association study (PheWAS) of COVID-19 outcomes by race using the electronic health records data in Michigan Medicine Salvatore, Maxwell Gu, Tian Mack, Jasmine A. Sankar, Swaraaj Prabhu Patil, Snehal Valley, Thomas S. Singh, Karandeep Nallamothu, Brahmajee K. Kheterpal, Sachin Lisabeth, Lynda Fritsche, Lars G. Mukherjee, Bhramar medRxiv Article BACKGROUND: We perform a phenome-wide scan to identify pre-existing conditions related to COVID-19 susceptibility and prognosis across the medical phenome and how they vary by race. METHODS: The study is comprised of 53,853 patients who were tested/positive for COVID-19 between March 10 and September 2, 2020 at a large academic medical center. RESULTS: Pre-existing conditions strongly associated with hospitalization were renal failure, pulmonary heart disease, and respiratory failure. Hematopoietic conditions were associated with ICU admission/mortality and mental disorders were associated with mortality in non-Hispanic Whites. Circulatory system and genitourinary conditions were associated with ICU admission/mortality in non-Hispanic Blacks. CONCLUSIONS: Understanding pre-existing clinical diagnoses related to COVID-19 outcomes informs the need for targeted screening to support specific vulnerable populations to improve disease prevention and healthcare delivery. Cold Spring Harbor Laboratory 2021-02-20 /pmc/articles/PMC7418740/ /pubmed/32793923 http://dx.doi.org/10.1101/2020.06.29.20141564 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator. |
spellingShingle | Article Salvatore, Maxwell Gu, Tian Mack, Jasmine A. Sankar, Swaraaj Prabhu Patil, Snehal Valley, Thomas S. Singh, Karandeep Nallamothu, Brahmajee K. Kheterpal, Sachin Lisabeth, Lynda Fritsche, Lars G. Mukherjee, Bhramar A phenome-wide association study (PheWAS) of COVID-19 outcomes by race using the electronic health records data in Michigan Medicine |
title | A phenome-wide association study (PheWAS) of COVID-19 outcomes by race using the electronic health records data in Michigan Medicine |
title_full | A phenome-wide association study (PheWAS) of COVID-19 outcomes by race using the electronic health records data in Michigan Medicine |
title_fullStr | A phenome-wide association study (PheWAS) of COVID-19 outcomes by race using the electronic health records data in Michigan Medicine |
title_full_unstemmed | A phenome-wide association study (PheWAS) of COVID-19 outcomes by race using the electronic health records data in Michigan Medicine |
title_short | A phenome-wide association study (PheWAS) of COVID-19 outcomes by race using the electronic health records data in Michigan Medicine |
title_sort | phenome-wide association study (phewas) of covid-19 outcomes by race using the electronic health records data in michigan medicine |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7418740/ https://www.ncbi.nlm.nih.gov/pubmed/32793923 http://dx.doi.org/10.1101/2020.06.29.20141564 |
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