<?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>1684-1824</journal-id>
<journal-title><![CDATA[Revista Médica Electrónica]]></journal-title>
<abbrev-journal-title><![CDATA[Rev.Med.Electrón.]]></abbrev-journal-title>
<issn>1684-1824</issn>
<publisher>
<publisher-name><![CDATA[Universidad de Ciencias Médicas de Matanzas]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1684-18242021000203047</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Aplicación de un modelo cubano predictivo de mortalidad en pacientes graves por covid-19 en Lombardía, Italia]]></article-title>
<article-title xml:lang="en"><![CDATA[Application of a Cuban mortality-predictive model in seriously-ill patients with Covid-19 in Lombardy, Italy]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[García Álvarez]]></surname>
<given-names><![CDATA[Pedro Julio]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Morejón Ramos]]></surname>
<given-names><![CDATA[Leodan]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Grasso Leyva]]></surname>
<given-names><![CDATA[Fernando]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Hospital Militar Dr. Carlos J. Finlay  ]]></institution>
<addr-line><![CDATA[ La Habana]]></addr-line>
<country>Cuba</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>04</month>
<year>2021</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>04</month>
<year>2021</year>
</pub-date>
<volume>43</volume>
<numero>2</numero>
<fpage>3047</fpage>
<lpage>3060</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://scielo.sld.cu/scielo.php?script=sci_arttext&amp;pid=S1684-18242021000203047&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.sld.cu/scielo.php?script=sci_abstract&amp;pid=S1684-18242021000203047&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.sld.cu/scielo.php?script=sci_pdf&amp;pid=S1684-18242021000203047&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[RESUMEN  Introducción: la neumonía por covid-19 es la enfermedad infecciosa que ha revolucionado al mundo en los últimos meses. El diagnóstico pasa por varios momentos: el cuadro clínico, la analítica sanguínea y las imágenes. La estratificación del riesgo de muerte es muy importante para optimizar los recursos.  Objetivos:  validar un modelo matemático cubano predictivo de mortalidad en pacientes ingresados por covid-19.  Materiales y métodos:  estudio de cohorte con 191 pacientes, que ingresaron graves en el Hospital Mayor de Crema, en la provincia de Cremona, región de Lombardía (Italia), en el período de abril a mayo de 2020. El universo estuvo constituido por 191 pacientes, y no se tomó muestra alguna. Las variables fueron: edad, estado del paciente, niveles de creatinina plasmática, frecuencia respiratoria, frecuencia cardiaca, presión arterial, niveles de oxígeno y de dióxido de carbono en sangre, valor del sodio y de hemoglobina.  Resultados:  mortalidad del 22 % en pacientes graves y críticos, con media de la edad (grupo 1: 59 años) (grupo 2: 73 años); t-Student = 0,00. Test de Hosmer-Lemenshow (0,766) con elevado ajuste. Sensibilidad = 93 %. Área bajo la curva = 0,957. Porcentaje de aciertos en la regresión logística de 86,4 % y en la red neuronal de 91,2 %. Media del modelo por grupos (grupo 1: 4 458) (grupo 2: 2 911) t-Student = 0,00.  Conclusiones:  el modelo demostró ser muy útil en el flujograma de pacientes atendidos con la covid-19. Permitió detectar tempranamente (a los cinco días del ingreso) los pacientes con alto riesgo de muerte y discriminar aquellos que no tendrían este riesgo, de manera que pudieran ser tratados en unidades de cuidados mínimos.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[ABSTRACT  Introduction:  COVID-19 pneumonia is an infectious disease that has revolutionized the world in the last months. The diagnosis goes thought several moments: clinical features, blood analytic and images. Death risk stratification is very important to optimize resources.  Objective:  to validate the Cuban mathematic predictive model of mortality in patients admitted due to COVID-19.  Materials and methods:  cohort study with 191 seriously-ill patients who were admitted to Maggiore di Crema Hospital, Cremona, Lombardy region, Italy, in the period April-May 2020. The universe were 191 patients and no sample was chosen. The variables were: age; patient&#8217;s status; plasma creatinine levels; respiratory rate; heart rate; arterial pressure; blood oxygen and carbon dioxide levels; values of sodium and hemoglobin.  Results:  22 % of mortality in seriously-ill and critical patients, with average age in Group 1: 59 years, in Group 2: 73 years; t-Student = 0.00. Hosmer-Lemenshow test (0.766) with high adjustment. Sensitivity= 93 %. Area below the curve=0.957. Success percentage in logistic regression of 86.4 % and 91.2 % in the neuronal net. Model media per groups: Group 1= 4 458; Group 2= 2 911, t-Student = 0.00.  Conclusions:  the model showed to be very useful in the flow chart of patients attended with COVID-19. It allowed to early detect the patients at high death risk five days from admission and discriminating those who were not at risk, in a way that they could be treated in minimal care units.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[mortalidad]]></kwd>
<kwd lng="es"><![CDATA[covid-19]]></kwd>
<kwd lng="es"><![CDATA[modelo predictivo]]></kwd>
<kwd lng="en"><![CDATA[mortality]]></kwd>
<kwd lng="en"><![CDATA[COVID-19]]></kwd>
<kwd lng="en"><![CDATA[predictive model]]></kwd>
</kwd-group>
</article-meta>
</front><back>
<ref-list>
<ref id="B1">
<label>1</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Li]]></surname>
<given-names><![CDATA[X]]></given-names>
</name>
<name>
<surname><![CDATA[Xu]]></surname>
<given-names><![CDATA[S]]></given-names>
</name>
<name>
<surname><![CDATA[Yu]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Risk factors for severity and mortality in adult COVID-19 in patients in Wuhan]]></article-title>
<source><![CDATA[J Allergy Clin Immunol]]></source>
<year>2020</year>
<volume>146</volume>
<numero>1</numero>
<issue>1</issue>
<page-range>110-8</page-range></nlm-citation>
</ref>
<ref id="B2">
<label>2</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Jekarl]]></surname>
<given-names><![CDATA[DW]]></given-names>
</name>
<name>
<surname><![CDATA[Lee]]></surname>
<given-names><![CDATA[S]]></given-names>
</name>
<name>
<surname><![CDATA[Kim]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Procalcitonin as a prognostic marker for sepsis based on SEPSIS-3]]></article-title>
<source><![CDATA[J Clin Lab Anal]]></source>
<year>2019</year>
<volume>33</volume>
<numero>9</numero>
<issue>9</issue>
</nlm-citation>
</ref>
<ref id="B3">
<label>3</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Ochoa Sangrador]]></surname>
<given-names><![CDATA[C]]></given-names>
</name>
<name>
<surname><![CDATA[Garmendia Leiza]]></surname>
<given-names><![CDATA[JR]]></given-names>
</name>
<name>
<surname><![CDATA[Pérez Boillos]]></surname>
<given-names><![CDATA[MJ]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Impacto de la COVID-19 en la mortalidad de la comunidad autónoma de Castilla y León]]></article-title>
<source><![CDATA[Gac Sanit]]></source>
<year>2020</year>
</nlm-citation>
</ref>
<ref id="B4">
<label>4</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Sánchez-Álvarez]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Pérez Fontán]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
<name>
<surname><![CDATA[Jiménez Martín]]></surname>
<given-names><![CDATA[C]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Situación de la infección por SARS-CoV-2 en pacientes en tratamiento renal sustitutivo. Informe del Registro COVID-19 de la Sociedad Española de Nefrología]]></article-title>
<source><![CDATA[Nefrología]]></source>
<year>2020</year>
<volume>40</volume>
<numero>3</numero>
<issue>3</issue>
<page-range>272-8</page-range></nlm-citation>
</ref>
<ref id="B5">
<label>5</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Pallarés Carratalá]]></surname>
<given-names><![CDATA[V]]></given-names>
</name>
<name>
<surname><![CDATA[Górriz-Zambrano]]></surname>
<given-names><![CDATA[C]]></given-names>
</name>
<name>
<surname><![CDATA[Morillas Ariño]]></surname>
<given-names><![CDATA[C]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[COVID-19 y enfermedad cardiovascular y renal: ¿Dónde estamos? ¿Hacia dónde vamos? Medicina de Familia]]></article-title>
<source><![CDATA[Semergen]]></source>
<year>2020</year>
<volume>46</volume>
<numero>1</numero>
<issue>1</issue>
<page-range>78-87</page-range></nlm-citation>
</ref>
<ref id="B6">
<label>6</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Medeiros Figueiredo]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Daponte Codina]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Moreira Marculino]]></surname>
<given-names><![CDATA[D]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Factores asociados a la incidencia y la mortalidad por COVID-19 en las comunidades autónomas]]></article-title>
<source><![CDATA[Gac Sanit]]></source>
<year>2020</year>
</nlm-citation>
</ref>
<ref id="B7">
<label>7</label><nlm-citation citation-type="journal">
<collab>Epidemiology Working Group for NCIP Epidemic Response</collab>
<article-title xml:lang=""><![CDATA[The epidemiological characteristics of an outbreak of 2019 novel coronavirus diseases (COVID-19) in China]]></article-title>
<source><![CDATA[Zhonghua Liu Xing Bing Xue Za Zhi]]></source>
<year>2020</year>
<volume>41</volume>
<numero>2</numero>
<issue>2</issue>
<page-range>145-51</page-range></nlm-citation>
</ref>
<ref id="B8">
<label>8</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[García Álvarez]]></surname>
<given-names><![CDATA[PJ]]></given-names>
</name>
<name>
<surname><![CDATA[García Albero]]></surname>
<given-names><![CDATA[ÁP]]></given-names>
</name>
<name>
<surname><![CDATA[Santana Álvarez]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Modelo matemático predictivo de mortalidad por neumonía adquirida en la comunidad]]></article-title>
<source><![CDATA[Arch Méd Camagüey]]></source>
<year>2018</year>
<volume>22</volume>
<numero>2</numero>
<issue>2</issue>
<page-range>10 p</page-range></nlm-citation>
</ref>
<ref id="B9">
<label>9</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Rodríguez]]></surname>
<given-names><![CDATA[Y]]></given-names>
</name>
<name>
<surname><![CDATA[Novelli]]></surname>
<given-names><![CDATA[L]]></given-names>
</name>
<name>
<surname><![CDATA[Rojas]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Autoinflammatory and autoimmune conditions at the crossroad of COVID-19]]></article-title>
<source><![CDATA[J Autoimmun]]></source>
<year>2020</year>
<volume>114</volume>
<page-range>102506</page-range></nlm-citation>
</ref>
<ref id="B10">
<label>10</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Zhang]]></surname>
<given-names><![CDATA[L]]></given-names>
</name>
<name>
<surname><![CDATA[Yan]]></surname>
<given-names><![CDATA[X]]></given-names>
</name>
<name>
<surname><![CDATA[Fan]]></surname>
<given-names><![CDATA[Q]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[D-dimer levels on admission to predict in-hospital mortality in patients with Covid-19]]></article-title>
<source><![CDATA[J Thromb Haemost]]></source>
<year>2020</year>
<volume>18</volume>
<numero>6</numero>
<issue>6</issue>
<page-range>1324-9</page-range></nlm-citation>
</ref>
<ref id="B11">
<label>11</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Perrotta]]></surname>
<given-names><![CDATA[F]]></given-names>
</name>
<name>
<surname><![CDATA[Corbi]]></surname>
<given-names><![CDATA[G]]></given-names>
</name>
<name>
<surname><![CDATA[Mazzeo]]></surname>
<given-names><![CDATA[G]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[COVID-19 and the elderly: insights into pathogenesis and clinical decision-making]]></article-title>
<source><![CDATA[Aging Clin Exp Res]]></source>
<year>2020</year>
<volume>32</volume>
<page-range>1599-608</page-range></nlm-citation>
</ref>
<ref id="B12">
<label>12</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Wang]]></surname>
<given-names><![CDATA[L]]></given-names>
</name>
<name>
<surname><![CDATA[He]]></surname>
<given-names><![CDATA[W]]></given-names>
</name>
<name>
<surname><![CDATA[Yu]]></surname>
<given-names><![CDATA[X]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Coronavirus disease 2019 in elderly patients: Characteristics and prognostic factors based on 4-week follow-up]]></article-title>
<source><![CDATA[J Infect]]></source>
<year>2020</year>
<volume>80</volume>
<numero>6</numero>
<issue>6</issue>
<page-range>639-45</page-range></nlm-citation>
</ref>
<ref id="B13">
<label>13</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Kang]]></surname>
<given-names><![CDATA[S]]></given-names>
</name>
<name>
<surname><![CDATA[Peng]]></surname>
<given-names><![CDATA[W]]></given-names>
</name>
<name>
<surname><![CDATA[Zhu]]></surname>
<given-names><![CDATA[Y]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Recent progress in understanding 2019 novel coronavirus (SARS-CoV-2) associated with human respiratory disease: detection, mechanisms and treatment]]></article-title>
<source><![CDATA[Int J Antimicrob Agents]]></source>
<year>2020</year>
<volume>55</volume>
<numero>5</numero>
<issue>5</issue>
<page-range>105950</page-range></nlm-citation>
</ref>
<ref id="B14">
<label>14</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Du]]></surname>
<given-names><![CDATA[RH]]></given-names>
</name>
<name>
<surname><![CDATA[Liang]]></surname>
<given-names><![CDATA[LR]]></given-names>
</name>
<name>
<surname><![CDATA[Yang]]></surname>
<given-names><![CDATA[CQ]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Predictors of mortality for patients with COVID-19 pneumonia caused by SARS-CoV-2: a prospective cohort study]]></article-title>
<source><![CDATA[Eur Respir J]]></source>
<year>2020</year>
<volume>55</volume>
<numero>5</numero>
<issue>5</issue>
<page-range>2000524</page-range></nlm-citation>
</ref>
<ref id="B15">
<label>15</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Melin]]></surname>
<given-names><![CDATA[P]]></given-names>
</name>
<name>
<surname><![CDATA[Monica]]></surname>
<given-names><![CDATA[JC]]></given-names>
</name>
<name>
<surname><![CDATA[Sánchez]]></surname>
<given-names><![CDATA[D]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Multiple Ensemble Neural Network Models with Fuzzy Response Aggregation for Predicting COVID-19 Time Series: The Case of Mexico]]></article-title>
<source><![CDATA[Healthcare (Basel)]]></source>
<year>2020</year>
<volume>8</volume>
<numero>2</numero>
<issue>2</issue>
<page-range>181</page-range></nlm-citation>
</ref>
<ref id="B16">
<label>16</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[García Álvarez]]></surname>
<given-names><![CDATA[PJ]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Aplicación de redes neuronales en la predicción de mortalidad por neumonía]]></article-title>
<source><![CDATA[Rev Médica Electrón]]></source>
<year>2018</year>
<volume>40</volume>
<numero>5</numero>
<issue>5</issue>
</nlm-citation>
</ref>
<ref id="B17">
<label>17</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Ruan]]></surname>
<given-names><![CDATA[Q]]></given-names>
</name>
<name>
<surname><![CDATA[Yang]]></surname>
<given-names><![CDATA[K]]></given-names>
</name>
<name>
<surname><![CDATA[Wang]]></surname>
<given-names><![CDATA[W]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Clinical predictors of mortality due to COVID-19 based on an analysis of data of 150 patients from Wuhan, China]]></article-title>
<source><![CDATA[Intensive Care Med]]></source>
<year>2020</year>
<volume>46</volume>
<numero>5</numero>
<issue>5</issue>
<page-range>846-8</page-range></nlm-citation>
</ref>
<ref id="B18">
<label>18</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Boukhris]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
<name>
<surname><![CDATA[Hillani]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Moroni]]></surname>
<given-names><![CDATA[F]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Cardiovascular Implications of the COVID-19 Pandemic: A Global Perspective]]></article-title>
<source><![CDATA[Can J Cardiol]]></source>
<year>2020</year>
<volume>36</volume>
<numero>7</numero>
<issue>7</issue>
<page-range>1068-80</page-range></nlm-citation>
</ref>
</ref-list>
</back>
</article>
