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. 2021 Apr:57:34-41.
doi: 10.1016/j.arbres.2021.02.021. Epub 2021 Mar 9.

Characteristics and Risk Factors Associated With Mortality in a Multicenter Spanish Cohort of Patients With COVID-19 Pneumonia

José Ramón Muñoz-Rodríguez  1   2 , Francisco Javier Gómez-Romero  1   2 , José Manuel Pérez-Ortiz  1   2 , Pilar López-Juárez  1 , Juan Luis Santiago  1   3 , Leticia Serrano-Oviedo  1 , Francisco Javier Redondo-Calvo  1   2   4   5 ; COVID-19 SESCAM Network
Affiliations

Characteristics and Risk Factors Associated With Mortality in a Multicenter Spanish Cohort of Patients With COVID-19 Pneumonia

José Ramón Muñoz-Rodríguez et al. Arch Bronconeumol. 2021 Apr.

Abstract
in English, Spanish

Introduction: Spain is one of the countries with the highest number of COVID-19 patients. Unfortunately, few data for regions are available.

Objectives: This study aimed to describe the characteristics and independent risk factors associated with COVID-19 mortality in Castilla-La Mancha, Spain.

Methods: Cohort and multicenter study in all 14 public hospitals of the Castilla-La Mancha Health Service. Baseline characteristics, preexisting comorbidities, symptoms, clinical features and treatments were included. Multivariable logistic regression was used to evaluate factors associated with death and Kaplan-Meier test to examine survival probability. Statistical significance was considered with p < 0.05 (95% CI). SPSS (version 24.0 for Windows) and R 4.0.2 (R Statistics) software were used.

Results: The cohort comprised 12,126 patients sequentially attended between February 11 and May 11, 2020. The mean age of patients was 66.4 years; 5667 (46.7%) were women. Six protective factors against exitus were defined: female sex, anosmia, cough, chloroquine and azithromycin. The risk factors were: age over 50, obesity, cardiac pathology, fever, dyspnea, lung infiltrates, lymphopenia, D-dimer above 1000 ng/mL, and mechanical ventilation requirement. Survival analysis showed higher survival rate in women (75.7%) than men (72.1%). Cumulative survival was 87.5% for non-hospitalized patients, 70.2% for patients admitted to hospital and 61.2% in ICU patients. Additionally, survival probability decreased with increasing age range.

Conclusion: Determination of protective or death-promoting factors could be useful to stratify patients by severity criteria and to improve COVID-19 care management.

Introducción: España es uno de los países con mayor número de pacientes con COVID-19. Desafortunadamente, se dispone de pocos datos por regiones.

Objetivos: Describir las características y los factores de riesgo independientes asociados a mortalidad por COVID-19 en Castilla-La Mancha, España.

Métodos: Estudio de cohorte, multicéntrico de los 14 hospitales públicos de Castilla-La Mancha. Se evaluaron las características clínicas, comorbilidades preexistentes, síntomas y tratamientos. Se utilizó una regresión logística multivariable para evaluar los factores asociados a muerte y Kaplan-Meier para medir supervivencia. Se consideró significación estadística con p < 0,05 (IC 95%). Se utilizaron los programas SPSS (versión 24.0 para Windows) y R 4.0.2 (R Statistics).

Resultados: Se estudiaron 12.126 pacientes atendidos secuencialmente entre el 11 de febrero y el 11 de mayo de 2020. La edad media fue de 66,4 años; 5.667 (46,7%) fueron mujeres. Se definieron seis factores protectores contra el exitus: sexo femenino, anosmia, tos, cloroquina y azitromicina. Los factores de riesgo fueron: edad superior a 50, obesidad, patología cardíaca, fiebre, disnea, infiltrados pulmonares, linfopenia, dímero-D > 1.000 ng/mL y necesidad de ventilación mecánica. Se observó mayor tasa de supervivencia en mujeres (75,7%) que en hombres (72,1%). La supervivencia acumulada fue del 87,5% para pacientes no hospitalizados, 70,2% para admitidos en planta hospitalaria y 61,2% en la Unidad de Cuidados Intensivos (UCI). Además, la probabilidad de supervivencia disminuyó con el aumento del rango de edad.

Conclusión: La determinación de los factores protectores o favorecedores de muerte podría ser útil para estratificar pacientes por criterios de gravedad y mejorar la atención frente a la COVID-19.

Keywords: Covid-19; Mortality; Pandemic; Pneumonia; Risk factors.

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Figures

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Graphical abstract
Fig. 1
Fig. 1
Study design flowchart.
Fig. 2
Fig. 2
Forest plot of the multivariable-adjusted risk model for exitus (non-survivors). OR: odds ratio; HBP: high blood pressure.
Fig. 3
Fig. 3
Survival time to exitus of the total patients. (A) Without distinctions. (B) By gender. (C) According to admission. (D) By age range.
See this image and copyright information in PMC

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