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Infectious Medicine 2022, 1(2): 81-87 https://doi.org/10.1016/j.imj.2022.04.002
Original Article | Open Access | Issue | Published: 22 April 2022

Clinical characteristics of COVID-19 hospitalized patients associated with mortality: A cohort study in Spain

Show Author's Information Manuel Lozanoa,b( ),  Adina Iftimic,  Alvaro Briz-Redond,  Juanjo Peiróc,  Lara Manyesa,  María Oteroe,  Mayte Ballestere,  M. Dolores de las Marinasf,  Juan Carlos Cataláe,  José de Andrése,g,  Carolina Romeroe,h
Preventive Medicine and Public Health, Food Sciences, Toxicology and Forensic Medicine Department, Universitat de València, Valencia, Spain
Epidemiology and Environmental Health Joint Research Unit, FISABIO−Universitat Jaume I−Universitat de València, Valencia, Spain
Department of Statistics and Operations Research, University of Valencia, Valencia, Spain
Statistics Office, City Council of Valencia, Valencia, Spain
Department of Anesthesia, Critical Care and Pain Unit, University General Hospital, Valencia, Spain
Division of Allergy and Immunology, University General Hospital, Valencia, Spain
Anesthesia Unit-Surgical Specialties Department, Valencia University Medical School, Valencia, Spain
Division of Research Methodology, European University, Valencia, Spain
Keywords:
COVID-19, SARS-CoV-2, Mortality, Epidemiology, Respiratory insufficiency, Proportional hazard model, Pandemics, Coronavirus infections
Cite this article:
Lozano M, Iftimi A, Briz-Redon A, et al. Clinical characteristics of COVID-19 hospitalized patients associated with mortality: A cohort study in Spain. Infectious Medicine, 2022, 1(2): 81-87. https://doi.org/10.1016/j.imj.2022.04.002
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Abstract Full text Electronic supplementary material About this article
Background

The heterogeneity of patients with COVID-19 may explain the wide variation of mortality rate due to the population characteristics, presence of comorbidities and clinical manifestations.

Methods

In this study, we analyzed 5342 patients' recordings and selected a cohort of 177 hospitalized patients with a poor prognosis at an early stage. We assessed during 6 months their symptomatology, coexisting health conditions, clinical measures and health assistance related to mortality. Multiple Cox proportional hazards models were built to identify the associated factors with mortality risk.

Results

We observed that cough and kidney failure triplicate the mortality risk and both bilirubin levels and oncologic condition are shown as the most associated with the demise, increasing in four and ten times the risk, respectively. Other clinical characteristics such as fever, diabetes mellitus, breathing frequency, neutrophil-lymphocyte ratio, oxygen saturation, and troponin levels, were also related to mortality risk of in-hospital death.

Conclusions

The present study shows that some symptomatology, comorbidities and clinical measures could be the target of prevention tools to improve survival rates.


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Abstract
Full text
Outline
Electronic supplementary material
About this article

Clinical characteristics of COVID-19 hospitalized patients associated with mortality: A cohort study in Spain

Show Author's information Manuel Lozanoa,b( ), Adina Iftimic, Alvaro Briz-Redond, Juanjo Peiróc, Lara Manyesa, María Oteroe, Mayte Ballestere, M. Dolores de las Marinasf, Juan Carlos Cataláe, José de Andrése,g, Carolina Romeroe,h
Preventive Medicine and Public Health, Food Sciences, Toxicology and Forensic Medicine Department, Universitat de València, Valencia, Spain
Epidemiology and Environmental Health Joint Research Unit, FISABIO−Universitat Jaume I−Universitat de València, Valencia, Spain
Department of Statistics and Operations Research, University of Valencia, Valencia, Spain
Statistics Office, City Council of Valencia, Valencia, Spain
Department of Anesthesia, Critical Care and Pain Unit, University General Hospital, Valencia, Spain
Division of Allergy and Immunology, University General Hospital, Valencia, Spain
Anesthesia Unit-Surgical Specialties Department, Valencia University Medical School, Valencia, Spain
Division of Research Methodology, European University, Valencia, Spain

Abstract

Background

The heterogeneity of patients with COVID-19 may explain the wide variation of mortality rate due to the population characteristics, presence of comorbidities and clinical manifestations.

Methods

In this study, we analyzed 5342 patients' recordings and selected a cohort of 177 hospitalized patients with a poor prognosis at an early stage. We assessed during 6 months their symptomatology, coexisting health conditions, clinical measures and health assistance related to mortality. Multiple Cox proportional hazards models were built to identify the associated factors with mortality risk.

Results

We observed that cough and kidney failure triplicate the mortality risk and both bilirubin levels and oncologic condition are shown as the most associated with the demise, increasing in four and ten times the risk, respectively. Other clinical characteristics such as fever, diabetes mellitus, breathing frequency, neutrophil-lymphocyte ratio, oxygen saturation, and troponin levels, were also related to mortality risk of in-hospital death.

Conclusions

The present study shows that some symptomatology, comorbidities and clinical measures could be the target of prevention tools to improve survival rates.

Keywords: COVID-19, SARS-CoV-2, Mortality, Epidemiology, Respiratory insufficiency, Proportional hazard model, Pandemics, Coronavirus infections

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Publication history

Received: 09 December 2021
Revised: 25 March 2022
Accepted: 17 April 2022
Published: 22 April 2022
Issue date: June 2022

Copyright

© 2022 The Author(s). Published by Elsevier Ltd on behalf of Tsinghua University Press.

Acknowledgements

Acknowledgements

This study was supported by the Innovation, Universities, Science and Digital Society Council through the Valencia Innovation Agency (AVI); grant 851255 from the European Research Council under the European Union's Horizon 2020 research and innovation program; and from the Universitat de València.

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This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

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