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Mapping each pre-existing condition’s association to short-term and long-term COVID-19 complications

Understanding the relationships between pre-existing conditions and complications of COVID-19 infection is critical to identifying which patients will develop severe disease. Here, we leverage ~1.1 million clinical notes from 1803 hospitalized COVID-19 patients and deep neural network models to char...

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Autores principales: Venkatakrishnan, A. J., Pawlowski, Colin, Zemmour, David, Hughes, Travis, Anand, Akash, Berner, Gabriela, Kayal, Nikhil, Puranik, Arjun, Conrad, Ian, Bade, Sairam, Barve, Rakesh, Sinha, Purushottam, O‘Horo, John C., Badley, Andrew D., Halamka, John, Soundararajan, Venky
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8316410/
https://www.ncbi.nlm.nih.gov/pubmed/34315980
http://dx.doi.org/10.1038/s41746-021-00484-7
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author Venkatakrishnan, A. J.
Pawlowski, Colin
Zemmour, David
Hughes, Travis
Anand, Akash
Berner, Gabriela
Kayal, Nikhil
Puranik, Arjun
Conrad, Ian
Bade, Sairam
Barve, Rakesh
Sinha, Purushottam
O‘Horo, John C.
Badley, Andrew D.
Halamka, John
Soundararajan, Venky
author_facet Venkatakrishnan, A. J.
Pawlowski, Colin
Zemmour, David
Hughes, Travis
Anand, Akash
Berner, Gabriela
Kayal, Nikhil
Puranik, Arjun
Conrad, Ian
Bade, Sairam
Barve, Rakesh
Sinha, Purushottam
O‘Horo, John C.
Badley, Andrew D.
Halamka, John
Soundararajan, Venky
author_sort Venkatakrishnan, A. J.
collection PubMed
description Understanding the relationships between pre-existing conditions and complications of COVID-19 infection is critical to identifying which patients will develop severe disease. Here, we leverage ~1.1 million clinical notes from 1803 hospitalized COVID-19 patients and deep neural network models to characterize associations between 21 pre-existing conditions and the development of 20 complications (e.g. respiratory, cardiovascular, renal, and hematologic) of COVID-19 infection throughout the course of infection (i.e. 0–30 days, 31–60 days, and 61–90 days). Pleural effusion was the most frequent complication of early COVID-19 infection (89/1803 patients, 4.9%) followed by cardiac arrhythmia (45/1803 patients, 2.5%). Notably, hypertension was the most significant risk factor associated with 10 different complications including acute respiratory distress syndrome, cardiac arrhythmia, and anemia. The onset of new complications after 30 days is rare and most commonly involves pleural effusion (31–60 days: 11 patients, 61–90 days: 9 patients). Lastly, comparing the rates of complications with a propensity-matched COVID-negative hospitalized population confirmed the importance of hypertension as a risk factor for early-onset complications. Overall, the associations between pre-COVID conditions and COVID-associated complications presented here may form the basis for the development of risk assessment scores to guide clinical care pathways.
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spelling pubmed-83164102021-08-02 Mapping each pre-existing condition’s association to short-term and long-term COVID-19 complications Venkatakrishnan, A. J. Pawlowski, Colin Zemmour, David Hughes, Travis Anand, Akash Berner, Gabriela Kayal, Nikhil Puranik, Arjun Conrad, Ian Bade, Sairam Barve, Rakesh Sinha, Purushottam O‘Horo, John C. Badley, Andrew D. Halamka, John Soundararajan, Venky NPJ Digit Med Article Understanding the relationships between pre-existing conditions and complications of COVID-19 infection is critical to identifying which patients will develop severe disease. Here, we leverage ~1.1 million clinical notes from 1803 hospitalized COVID-19 patients and deep neural network models to characterize associations between 21 pre-existing conditions and the development of 20 complications (e.g. respiratory, cardiovascular, renal, and hematologic) of COVID-19 infection throughout the course of infection (i.e. 0–30 days, 31–60 days, and 61–90 days). Pleural effusion was the most frequent complication of early COVID-19 infection (89/1803 patients, 4.9%) followed by cardiac arrhythmia (45/1803 patients, 2.5%). Notably, hypertension was the most significant risk factor associated with 10 different complications including acute respiratory distress syndrome, cardiac arrhythmia, and anemia. The onset of new complications after 30 days is rare and most commonly involves pleural effusion (31–60 days: 11 patients, 61–90 days: 9 patients). Lastly, comparing the rates of complications with a propensity-matched COVID-negative hospitalized population confirmed the importance of hypertension as a risk factor for early-onset complications. Overall, the associations between pre-COVID conditions and COVID-associated complications presented here may form the basis for the development of risk assessment scores to guide clinical care pathways. Nature Publishing Group UK 2021-07-27 /pmc/articles/PMC8316410/ /pubmed/34315980 http://dx.doi.org/10.1038/s41746-021-00484-7 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Venkatakrishnan, A. J.
Pawlowski, Colin
Zemmour, David
Hughes, Travis
Anand, Akash
Berner, Gabriela
Kayal, Nikhil
Puranik, Arjun
Conrad, Ian
Bade, Sairam
Barve, Rakesh
Sinha, Purushottam
O‘Horo, John C.
Badley, Andrew D.
Halamka, John
Soundararajan, Venky
Mapping each pre-existing condition’s association to short-term and long-term COVID-19 complications
title Mapping each pre-existing condition’s association to short-term and long-term COVID-19 complications
title_full Mapping each pre-existing condition’s association to short-term and long-term COVID-19 complications
title_fullStr Mapping each pre-existing condition’s association to short-term and long-term COVID-19 complications
title_full_unstemmed Mapping each pre-existing condition’s association to short-term and long-term COVID-19 complications
title_short Mapping each pre-existing condition’s association to short-term and long-term COVID-19 complications
title_sort mapping each pre-existing condition’s association to short-term and long-term covid-19 complications
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8316410/
https://www.ncbi.nlm.nih.gov/pubmed/34315980
http://dx.doi.org/10.1038/s41746-021-00484-7
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