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Multimorbidity patterns among COVID-19 deaths: proposal for the construction of etiological models

OBJECTIVES. To describe patterns of multimorbidity among fatal cases of COVID-19, and to propose a classification of patients based on age and multimorbidity patterns to begin the construction of etiological models. METHODS. Data of Colombian confirmed deaths of COVID-19 until June 11, 2020, were in...

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Autores principales: Fernández-Niño, Julián A., Guerra-Gómez, John A., Idrovo, Alvaro J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Organización Panamericana de la Salud 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7778468/
https://www.ncbi.nlm.nih.gov/pubmed/33417654
http://dx.doi.org/10.26633/RPSP.2020.166
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author Fernández-Niño, Julián A.
Guerra-Gómez, John A.
Idrovo, Alvaro J.
author_facet Fernández-Niño, Julián A.
Guerra-Gómez, John A.
Idrovo, Alvaro J.
author_sort Fernández-Niño, Julián A.
collection PubMed
description OBJECTIVES. To describe patterns of multimorbidity among fatal cases of COVID-19, and to propose a classification of patients based on age and multimorbidity patterns to begin the construction of etiological models. METHODS. Data of Colombian confirmed deaths of COVID-19 until June 11, 2020, were included in this analysis (n=1488 deaths). Relationships between COVID-19, combinations of health conditions and age were explored using locally weighted polynomial regressions. RESULTS. The most frequent health conditions were high blood pressure, respiratory disease, diabetes, cardiovascular disease, and kidney disease. Dyads more frequents were high blood pressure with diabetes, cardiovascular disease or respiratory disease. Some multimorbidity patterns increase probability of death among older individuals, whereas other patterns are not age-related, or decrease the probability of death among older people. Not all multimorbidity increases with age, as is commonly thought. Obesity, alone or with other diseases, was associated with a higher risk of severity among young people, while the risk of the high blood pressure/diabetes dyad tends to have an inverted U distribution in relation with age. CONCLUSIONS. Classification of individuals according to multimorbidity in the medical management of COVID-19 patients is important to determine the possible etiological models and to define patient triage for hospitalization. Moreover, identification of non-infected individuals with high-risk ages and multimorbidity patterns serves to define possible interventions of selective confinement or special management.
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spelling pubmed-77784682021-01-05 Multimorbidity patterns among COVID-19 deaths: proposal for the construction of etiological models Fernández-Niño, Julián A. Guerra-Gómez, John A. Idrovo, Alvaro J. Rev Panam Salud Publica Original Research OBJECTIVES. To describe patterns of multimorbidity among fatal cases of COVID-19, and to propose a classification of patients based on age and multimorbidity patterns to begin the construction of etiological models. METHODS. Data of Colombian confirmed deaths of COVID-19 until June 11, 2020, were included in this analysis (n=1488 deaths). Relationships between COVID-19, combinations of health conditions and age were explored using locally weighted polynomial regressions. RESULTS. The most frequent health conditions were high blood pressure, respiratory disease, diabetes, cardiovascular disease, and kidney disease. Dyads more frequents were high blood pressure with diabetes, cardiovascular disease or respiratory disease. Some multimorbidity patterns increase probability of death among older individuals, whereas other patterns are not age-related, or decrease the probability of death among older people. Not all multimorbidity increases with age, as is commonly thought. Obesity, alone or with other diseases, was associated with a higher risk of severity among young people, while the risk of the high blood pressure/diabetes dyad tends to have an inverted U distribution in relation with age. CONCLUSIONS. Classification of individuals according to multimorbidity in the medical management of COVID-19 patients is important to determine the possible etiological models and to define patient triage for hospitalization. Moreover, identification of non-infected individuals with high-risk ages and multimorbidity patterns serves to define possible interventions of selective confinement or special management. Organización Panamericana de la Salud 2020-12-30 /pmc/articles/PMC7778468/ /pubmed/33417654 http://dx.doi.org/10.26633/RPSP.2020.166 Text en https://creativecommons.org/licenses/by-nc-nd/3.0/igo/legalcode This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs 3.0 IGO License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited. No modifications or commercial use of this article are permitted. In any reproduction of this article there should not be any suggestion that PAHO or this article endorse any specific organization or products. The use of the PAHO logo is not permitted. This notice should be preserved along with the article’s original URL.
spellingShingle Original Research
Fernández-Niño, Julián A.
Guerra-Gómez, John A.
Idrovo, Alvaro J.
Multimorbidity patterns among COVID-19 deaths: proposal for the construction of etiological models
title Multimorbidity patterns among COVID-19 deaths: proposal for the construction of etiological models
title_full Multimorbidity patterns among COVID-19 deaths: proposal for the construction of etiological models
title_fullStr Multimorbidity patterns among COVID-19 deaths: proposal for the construction of etiological models
title_full_unstemmed Multimorbidity patterns among COVID-19 deaths: proposal for the construction of etiological models
title_short Multimorbidity patterns among COVID-19 deaths: proposal for the construction of etiological models
title_sort multimorbidity patterns among covid-19 deaths: proposal for the construction of etiological models
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7778468/
https://www.ncbi.nlm.nih.gov/pubmed/33417654
http://dx.doi.org/10.26633/RPSP.2020.166
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