<?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>0016-3813</journal-id>
<journal-title><![CDATA[Gaceta médica de México]]></journal-title>
<abbrev-journal-title><![CDATA[Gac. Méd. Méx]]></abbrev-journal-title>
<issn>0016-3813</issn>
<publisher>
<publisher-name><![CDATA[Academia Nacional de Medicina de México A.C.]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0016-38132021000300240</article-id>
<article-id pub-id-type="doi">10.24875/gmm.20000628</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Hacia un modelo predictivo de carácter preventivo del riesgo de infección por COVID-19]]></article-title>
<article-title xml:lang="en"><![CDATA[Towards a predictive model for prevention nature of the risk of COVID-19 infection]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Toudert]]></surname>
<given-names><![CDATA[Djamel]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,El Colegio de la Frontera Norte Departamento de Estudios Urbanos y del Medio Ambiente ]]></institution>
<addr-line><![CDATA[ Baja California]]></addr-line>
<country>México</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>06</month>
<year>2021</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>06</month>
<year>2021</year>
</pub-date>
<volume>157</volume>
<numero>3</numero>
<fpage>240</fpage>
<lpage>245</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S0016-38132021000300240&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S0016-38132021000300240&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S0016-38132021000300240&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen  Introducción: La escasez de aplicaciones centradas en la persona y con vistas al desarrollo de la conciencia del riesgo que representa la pandemia de COVID-19 estimula la exploración y creación de herramientas de carácter preventivo accesibles a la población.  Objetivo: Elaboración de un modelo predictivo que permita evaluar el riesgo de letalidad ante infección por el virus SARS-CoV-2.  Métodos: Exploración de datos públicos de 16 000 pacientes positivos a COVID-19, para generar un modelo discriminante eficiente, valorado con una función score y que se expresa mediante un cuestionario autocalificado de interés preventivo.  Resultados: Se obtuvo una función lineal útil con capacidad discriminante de 0.845; la validación interna con bootstrap y la externa, con 25 % de los pacientes de prueba, mostraron diferencias marginales.  Conclusión: El modelo predictivo, basado en 15 preguntas accesibles puede convertirse en una herramienta de prevención estructurada.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract  Introduction: The scarcity of person-centered applications aimed at developing awareness on the risk posed by the COVID-19 pandemic, stimulates the exploration and creation of preventive tools that are accessible to the population.  Objective: To develop a predictive model that allows evaluating the risk of mortality in the event of SARS-CoV-2 virus infection.  Methods: Exploration of public data from 16,000 COVID-19-positive patients to generate an efficient discriminant model, evaluated with a score function and expressed by a self-rated preventive interest questionnaire.  Results: A useful linear function was obtained with a discriminant capacity of 0.845; internal validation with bootstrap and external validation, with 25 % of tested patients showing marginal differences.  Conclusion: The predictive model with statistical support, based on 15 accessible questions, can become a structured prevention tool.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[Modelo predictivo de la letalidad]]></kwd>
<kwd lng="es"><![CDATA[COVID-19]]></kwd>
<kwd lng="es"><![CDATA[Herramienta preventiva]]></kwd>
<kwd lng="es"><![CDATA[México]]></kwd>
<kwd lng="en"><![CDATA[Predictive model of mortality]]></kwd>
<kwd lng="en"><![CDATA[COVID-19]]></kwd>
<kwd lng="en"><![CDATA[Preventive tool]]></kwd>
<kwd lng="en"><![CDATA[Mexico]]></kwd>
</kwd-group>
</article-meta>
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