<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>1028-4818</journal-id>
<journal-title><![CDATA[Multimed]]></journal-title>
<abbrev-journal-title><![CDATA[Multimed]]></abbrev-journal-title>
<issn>1028-4818</issn>
<publisher>
<publisher-name><![CDATA[Centro Provincial de Información de Ciencias Médicas]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1028-48182023000100018</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Asociación de la comorbilidad y biomarcadores con el riesgo de morir por COVID-19 en pacientes graves]]></article-title>
<article-title xml:lang="en"><![CDATA[Association of comorbidity and biomarkers with the risk of death by COVID-19 in critically ill patients]]></article-title>
<article-title xml:lang="pt"><![CDATA[Associação de comorbidade e biomarcadores com o risco de morrer de COVID-19 em pacientes gravemente enfermos]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Naranjo Flores]]></surname>
<given-names><![CDATA[Liannys Lidia]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Álvarez Aliaga]]></surname>
<given-names><![CDATA[Alexis]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[González Aguilera]]></surname>
<given-names><![CDATA[Julio César]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Suárez Quesada]]></surname>
<given-names><![CDATA[Alexis]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Quesada Vázquez]]></surname>
<given-names><![CDATA[Andrés José]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad de Ciencias Médicas de Granma Hospital General Provincial Carlos Manuel de Céspedes ]]></institution>
<addr-line><![CDATA[Bayamo Granma]]></addr-line>
<country>Cuba</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>00</month>
<year>2023</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>00</month>
<year>2023</year>
</pub-date>
<volume>27</volume>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://scielo.sld.cu/scielo.php?script=sci_arttext&amp;pid=S1028-48182023000100018&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.sld.cu/scielo.php?script=sci_abstract&amp;pid=S1028-48182023000100018&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.sld.cu/scielo.php?script=sci_pdf&amp;pid=S1028-48182023000100018&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[RESUMEN  Introducción: el síndrome respiratorio agudo grave se convirtió en una pandemia, y ocasionó elevada morbilidad y mortalidad a nivel mundial, al no contarse con un tratamiento eficaz ni el reconocimiento oportuno de los individuos de peor pronóstico.  Objetivo: evaluar la capacidad de pronosticar el riesgo de morir en los pacientes con la COVID-19, mediante un modelo basado en factores pronósticos.  Métodos: se realizó un estudio de analítico de cohorte en pacientes con la COVID-19 atendidos en los servicios del hospital &#8220;Covid-19&#8221; del hospital provincial general &#8220;Carlos Manuel de Céspedes&#8221; del municipio Bayamo, provincia de Granma, desde el 1ero de enero 2020 hasta el 31 de diciembre de 2022.  Resultados: el modelo de regresión logística binaria ajustado por el método introducir, demostró que los factores sobresalientes fueron padecer de cáncer (OR= 8,21; IC 95% = 1,58-11,35; p= 0,023) seguido de proteína C reactiva (OR= 7,91; IC 95% = 4,46-9,87; p= 0,000) y la hipertensión arterial (OR= 7,15; IC 95 %= 4,41-11,42; p= 0,000). La prueba de Hosmer y Lemeshow con valor de p= 0,582 con indicador de buena calibración del modelo. El área bajo la curva COR fue de 0,894 (intervalo de confianza: 0,846-0,942; p=0,000) demostrando la validez del modelo.  Conclusiones: se demuestra el lugar que ocupan el antecedente de cáncer y de hipertensión arterial como comorbilidad relacionada con el riesgo de morir por la COVID-19, así como los reactantes de inflamación, donde sobresalen la proteína C reactiva, la deshidrogenasa láctica y la eritrosedimentación. Se obtiene un modelo con capacidad discriminativa adecuada.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[ABSTRACT  Introduction: severe acute respiratory syndrome became a pandemic, and caused high morbidity and mortality worldwide, since there was no effective treatment or timely recognition of individuals with the worst prognosis.  Objective: to assess the ability to predict the risk of dying in patients with COVID-19, using a model based on prognostic factors.  Methodos:  a cohort analytical study was carried out in patients with covid-19 treated in the services of the "COVID-19" hospital of the "Carlos Manuel de Céspedes" provincial general hospital of the Bayamo municipality, Granma province, since january 1, 2020 until december 31, 2022.  Results: the binary logistic regression model adjusted by the introduce method showed that the outstanding factors were, in order of importance, suffering from cancer (OR= 8.21; 95 % CI= 1.58-11.35; p= 0.023) followed by protein C reactive (OR= 7.91; 95 % CI= 4.46-9.87; p= 0.000) and arterial hypertension (OR= 7.15; 95 % CI= 4.41-11.42; p= 0.000). The Hosmer and Lemeshow test with a value of p= 0.582 with an indicator of good calibration of the model. The area under the ROC curve was 0.894 (confidence interval: 0.846-0.942; p=0.000), demonstrating the validity of the model.  Conclusions: the place of a history of cancer and high blood pressure as comorbidity related to the risk of dying from COVID-19is demonstrated, as well as inflammation reactants, where C-reactive protein, lactic dehydrogenase and erythrocyte sedimentation rate stand out. A model with adequate discriminative capacity is obtained.]]></p></abstract>
<abstract abstract-type="short" xml:lang="pt"><p><![CDATA[RESUMO  Introdução:  a síndrome respiratória aguda grave tornou-se uma pandemia, causando alta morbidade e mortalidade em todo o mundo, pois não houve tratamento efetivo ou reconhecimento oportuno de indivíduos com pior prognóstico.  Objetivo: avaliar a capacidade de prever o risco de morte em pacientes com COVID-19, utilizando um modelo baseado em fatores prognósticos.  Métodos: foi realizado um estudo de coorte analítico em pacientes com COVID-19 tratados nos serviços do hospital geral provincial "Covid-19" do hospital geral provincial "Carlos Manuel de Céspedes" no município de Bayamo, província de Granma, de 1º de janeiro de 2020 a 31 de dezembro de 2022.  Resultados:  o modelo de regressão logística binária ajustado pelo método introduce mostrou que os fatores de destaque foram ter câncer (OR= 8,21; IC 95% = 1,58-11,35; p= 0,023), seguida da proteína C reativa (OR= 7,91; IC 95% = 4,46-9,87; p= 0,000) e hipertensão arterial (OR= 7,15; IC 95%= 4,41-11,42; p= 0,000). O teste de Hosmer e Lemeshow com valor de p = 0,582 com indicador de boa calibração do modelo. A área sob a curva COR foi de 0,894 (intervalo de confiança: 0,846-0,942; p=0,000), demonstrando a validade do modelo.  Conclusões: demonstra-se o lugar ocupado pela história de câncer e hipertensão como comorbidade relacionada ao risco de morrer por COVID-19, bem como os reagentes da inflamação, onde se destacam a proteína C-reativa, a desidrogenase lática e a hemossedimentação. Obtém-se um modelo com adequada capacidade discriminativa.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[COVID-19]]></kwd>
<kwd lng="es"><![CDATA[Factores pronósticos]]></kwd>
<kwd lng="es"><![CDATA[Comorbilidad]]></kwd>
<kwd lng="es"><![CDATA[Reactantes inflamatorios]]></kwd>
<kwd lng="es"><![CDATA[Mortalidad]]></kwd>
<kwd lng="en"><![CDATA[COVID-19]]></kwd>
<kwd lng="en"><![CDATA[Prognostic factors]]></kwd>
<kwd lng="en"><![CDATA[Comorbidity]]></kwd>
<kwd lng="en"><![CDATA[Inflammatory reactants]]></kwd>
<kwd lng="en"><![CDATA[Mortality]]></kwd>
<kwd lng="pt"><![CDATA[COVID-19]]></kwd>
<kwd lng="pt"><![CDATA[Fatores prognósticos]]></kwd>
<kwd lng="pt"><![CDATA[Comorbidade]]></kwd>
<kwd lng="pt"><![CDATA[Reagentes inflamatórios]]></kwd>
<kwd lng="pt"><![CDATA[Mortalidade]]></kwd>
</kwd-group>
</article-meta>
</front><back>
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