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Predictors of in-hospital COVID-19 mortality: A comprehensive systematic review and meta-analysis exploring differences by age, sex and health conditions

OBJECTIVE: Risk factors for in-hospital mortality in confirmed COVID-19 patients have been summarized in numerous meta-analyses, but it is still unclear whether they vary according to the age, sex and health conditions of the studied populations. This study explored these variables as potential mort...

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Autores principales: Mesas, Arthur Eumann, Cavero-Redondo, Iván, Álvarez-Bueno, Celia, Sarriá Cabrera, Marcos Aparecido, Maffei de Andrade, Selma, Sequí-Dominguez, Irene, Martínez-Vizcaíno, Vicente
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7608886/
https://www.ncbi.nlm.nih.gov/pubmed/33141836
http://dx.doi.org/10.1371/journal.pone.0241742
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author Mesas, Arthur Eumann
Cavero-Redondo, Iván
Álvarez-Bueno, Celia
Sarriá Cabrera, Marcos Aparecido
Maffei de Andrade, Selma
Sequí-Dominguez, Irene
Martínez-Vizcaíno, Vicente
author_facet Mesas, Arthur Eumann
Cavero-Redondo, Iván
Álvarez-Bueno, Celia
Sarriá Cabrera, Marcos Aparecido
Maffei de Andrade, Selma
Sequí-Dominguez, Irene
Martínez-Vizcaíno, Vicente
author_sort Mesas, Arthur Eumann
collection PubMed
description OBJECTIVE: Risk factors for in-hospital mortality in confirmed COVID-19 patients have been summarized in numerous meta-analyses, but it is still unclear whether they vary according to the age, sex and health conditions of the studied populations. This study explored these variables as potential mortality predictors. METHODS: A systematic review was conducted by searching the MEDLINE, Scopus, and Web of Science databases of studies available through July 27, 2020. The pooled risk was estimated with the odds ratio (p-OR) or effect size (p-ES) obtained through random-effects meta-analyses. Subgroup analyses and meta-regression were applied to explore differences by age, sex and health conditions. The MOOSE guidelines were strictly followed. RESULTS: The meta-analysis included 60 studies, with a total of 51,225 patients (12,458 [24.3%] deaths) from hospitals in 13 countries. A higher in-hospital mortality risk was found for dyspnoea (p-OR = 2.5), smoking (p-OR = 1.6) and several comorbidities (p-OR range: 1.8 to 4.7) and laboratory parameters (p-ES range: 0.3 to -2.6). Age was the main source of heterogeneity, followed by sex and health condition. The following predictors were more markedly associated with mortality in studies with patients with a mean age ≤60 years: dyspnoea (p-OR = 4.3), smoking (p-OR = 2.8), kidney disease (p-OR = 3.8), hypertension (p-OR = 3.7), malignancy (p-OR = 3.7), diabetes (p-OR = 3.2), pulmonary disease (p-OR = 3.1), decreased platelet count (p-ES = -1.7), decreased haemoglobin concentration (p-ES = -0.6), increased creatinine (p-ES = 2.4), increased interleukin-6 (p-ES = 2.4) and increased cardiac troponin I (p-ES = 0.7). On the other hand, in addition to comorbidities, the most important mortality predictors in studies with older patients were albumin (p-ES = -3.1), total bilirubin (p-ES = 0.7), AST (p-ES = 1.8), ALT (p-ES = 0.4), urea nitrogen (p-ES), C-reactive protein (p-ES = 2.7), LDH (p-ES = 2.4) and ferritin (p-ES = 1.7). Obesity was associated with increased mortality only in studies with fewer chronic or critical patients (p-OR = 1.8). CONCLUSION: The prognostic effect of clinical conditions on COVID-19 mortality vary substantially according to the mean age of patients. PROSPERO REGISTRATION NUMBER: CRD42020176595.
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spelling pubmed-76088862020-11-10 Predictors of in-hospital COVID-19 mortality: A comprehensive systematic review and meta-analysis exploring differences by age, sex and health conditions Mesas, Arthur Eumann Cavero-Redondo, Iván Álvarez-Bueno, Celia Sarriá Cabrera, Marcos Aparecido Maffei de Andrade, Selma Sequí-Dominguez, Irene Martínez-Vizcaíno, Vicente PLoS One Research Article OBJECTIVE: Risk factors for in-hospital mortality in confirmed COVID-19 patients have been summarized in numerous meta-analyses, but it is still unclear whether they vary according to the age, sex and health conditions of the studied populations. This study explored these variables as potential mortality predictors. METHODS: A systematic review was conducted by searching the MEDLINE, Scopus, and Web of Science databases of studies available through July 27, 2020. The pooled risk was estimated with the odds ratio (p-OR) or effect size (p-ES) obtained through random-effects meta-analyses. Subgroup analyses and meta-regression were applied to explore differences by age, sex and health conditions. The MOOSE guidelines were strictly followed. RESULTS: The meta-analysis included 60 studies, with a total of 51,225 patients (12,458 [24.3%] deaths) from hospitals in 13 countries. A higher in-hospital mortality risk was found for dyspnoea (p-OR = 2.5), smoking (p-OR = 1.6) and several comorbidities (p-OR range: 1.8 to 4.7) and laboratory parameters (p-ES range: 0.3 to -2.6). Age was the main source of heterogeneity, followed by sex and health condition. The following predictors were more markedly associated with mortality in studies with patients with a mean age ≤60 years: dyspnoea (p-OR = 4.3), smoking (p-OR = 2.8), kidney disease (p-OR = 3.8), hypertension (p-OR = 3.7), malignancy (p-OR = 3.7), diabetes (p-OR = 3.2), pulmonary disease (p-OR = 3.1), decreased platelet count (p-ES = -1.7), decreased haemoglobin concentration (p-ES = -0.6), increased creatinine (p-ES = 2.4), increased interleukin-6 (p-ES = 2.4) and increased cardiac troponin I (p-ES = 0.7). On the other hand, in addition to comorbidities, the most important mortality predictors in studies with older patients were albumin (p-ES = -3.1), total bilirubin (p-ES = 0.7), AST (p-ES = 1.8), ALT (p-ES = 0.4), urea nitrogen (p-ES), C-reactive protein (p-ES = 2.7), LDH (p-ES = 2.4) and ferritin (p-ES = 1.7). Obesity was associated with increased mortality only in studies with fewer chronic or critical patients (p-OR = 1.8). CONCLUSION: The prognostic effect of clinical conditions on COVID-19 mortality vary substantially according to the mean age of patients. PROSPERO REGISTRATION NUMBER: CRD42020176595. Public Library of Science 2020-11-03 /pmc/articles/PMC7608886/ /pubmed/33141836 http://dx.doi.org/10.1371/journal.pone.0241742 Text en © 2020 Mesas et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Mesas, Arthur Eumann
Cavero-Redondo, Iván
Álvarez-Bueno, Celia
Sarriá Cabrera, Marcos Aparecido
Maffei de Andrade, Selma
Sequí-Dominguez, Irene
Martínez-Vizcaíno, Vicente
Predictors of in-hospital COVID-19 mortality: A comprehensive systematic review and meta-analysis exploring differences by age, sex and health conditions
title Predictors of in-hospital COVID-19 mortality: A comprehensive systematic review and meta-analysis exploring differences by age, sex and health conditions
title_full Predictors of in-hospital COVID-19 mortality: A comprehensive systematic review and meta-analysis exploring differences by age, sex and health conditions
title_fullStr Predictors of in-hospital COVID-19 mortality: A comprehensive systematic review and meta-analysis exploring differences by age, sex and health conditions
title_full_unstemmed Predictors of in-hospital COVID-19 mortality: A comprehensive systematic review and meta-analysis exploring differences by age, sex and health conditions
title_short Predictors of in-hospital COVID-19 mortality: A comprehensive systematic review and meta-analysis exploring differences by age, sex and health conditions
title_sort predictors of in-hospital covid-19 mortality: a comprehensive systematic review and meta-analysis exploring differences by age, sex and health conditions
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7608886/
https://www.ncbi.nlm.nih.gov/pubmed/33141836
http://dx.doi.org/10.1371/journal.pone.0241742
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