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  <front>
    <journal-meta>
      <journal-id journal-id-type="nlm-ta">Arq Bras Cardiol</journal-id>
      <journal-id journal-id-type="publisher-id">abc</journal-id>
      <journal-title-group>
        <journal-title>Arquivos Brasileiros de Cardiologia</journal-title>
        <abbrev-journal-title abbrev-type="publisher">Arq. Bras. Cardiol.</abbrev-journal-title>
      </journal-title-group>
      <issn pub-type="ppub">0066-782X</issn>
      <issn pub-type="epub">1678-4170</issn>
      <publisher>
        <publisher-name>Sociedade Brasileira de Cardiologia - SBC</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id specific-use="scielo-v3" pub-id-type="publisher-id">CGszD8v6TwdsWJvQv7SWq7n</article-id>
      <article-id specific-use="scielo-v2" pub-id-type="publisher-id">S0066-782X2020001200660</article-id>
      <article-id pub-id-type="publisher-id">abc.20200385</article-id>
      <article-id pub-id-type="doi">10.36660/abc.20200385</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Artigo Original</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Valor Progn&#243;stico da Troponina T e do Pept&#237;deo Natriur&#233;tico Tipo B em Pacientes Internados por COVID-19</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0002-9755-8849</contrib-id>
          <name>
            <surname>Almeida</surname>
            <given-names>Gustavo Luiz Gouv&#234;a de</given-names>
            <suffix>Junior</suffix>
          </name>
          <xref ref-type="aff" rid="aff1">
            <sup>1</sup>
          </xref>
          <xref ref-type="corresp" rid="c1"/>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0002-7062-1705</contrib-id>
          <name>
            <surname>Braga</surname>
            <given-names>Fabricio</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Jorge</surname>
            <given-names>Jos&#233; Kezen</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Nobre</surname>
            <given-names>Gustavo Freitas</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Kalichsztein</surname>
            <given-names>Marcelo</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Faria</surname>
            <given-names>Paula de Medeiros Pache de</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Bussade</surname>
            <given-names>Bruno</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Penna</surname>
            <given-names>Guilherme Loures</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Alves</surname>
            <given-names>Vitor Oliveira</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0001-9778-1795</contrib-id>
          <name>
            <surname>Pereira</surname>
            <given-names>Marcella Alecrim</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0002-7717-9577</contrib-id>
          <name>
            <surname>Gorgulho</surname>
            <given-names>Paula de Castro</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Faria</surname>
            <given-names>Milena Rego dos Santos Espelta de</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Drumond</surname>
            <given-names>Luis Eduardo</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Carpinete</surname>
            <given-names>Fabrini Batista Soares</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Neno</surname>
            <given-names>Ana Carolina Lessa Brand&#227;o</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Neno</surname>
            <given-names>Augusto C&#233;sar de Ara&#250;jo</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">
            <sup>1</sup>
          </xref>
        </contrib>
        <aff id="aff1">
          <label>1</label>
          <institution content-type="orgname">Casa de Sa&#250;de S&#227;o Jos&#233;</institution>
          <addr-line>
            <named-content content-type="city">Rio de Janeiro</named-content>
            <named-content content-type="state">RJ</named-content>
          </addr-line>
          <country country="BR">Brasil</country>
          <institution content-type="original">Casa de Sa&#250;de S&#227;o Jos&#233;, Rio de Janeiro, RJ &#8211; Brasil</institution>
        </aff>
      </contrib-group>
      <author-notes>
        <corresp id="c1"><bold>Correspond&#234;ncia: Gustavo Luiz Gouv&#234;a Almeida Junior &#8226;</bold> Casa de Sa&#250;de S&#227;o Jos&#233; - Macedo Sobrinho, 21. CEP <postal-code>22271-080</postal-code>, Humait&#225;, RJ &#8211; Brasil. E-mail: <email>dr.ggouvea@gmail.com</email></corresp>
        <fn fn-type="con">
          <p>
            <bold>Contribui&#231;&#227;o dos Autores</bold>
          </p>
          <p>Concep&#231;&#227;o e desenho da pesquisa: Almeida Junior GLG, Braga F, Jorge JK, Faria PMP, Gorgulho PC, Espelta M, Drumond LE, Carpinete FBS, Neno ACA; Obten&#231;&#227;o de dados: Almeida Junior GLG, Nobre GF, Kalichsztein M, Faria PMP, Bussade B, Penna GL, Alves VO, Pereira MA, Gorgulho PC, Espelta M, Drumond LE, Carpinete FBS, Neno ACLB; An&#225;lise e interpreta&#231;&#227;o dos dados e Reda&#231;&#227;o do manuscrito: Almeida Junior GLG, Braga F; An&#225;lise estat&#237;stica: Braga F; Revis&#227;o cr&#237;tica do manuscrito quanto ao conte&#250;do intelectual importante: Almeida Junior GLG, Braga F, Jorge JK, Nobre GF, Kalichsztein M, Neno ACA.</p>
        </fn>
        <fn fn-type="conflict">
          <p>
            <bold>Potencial Conflito de Interesses</bold>
          </p>
          <p>Declaro n&#227;o haver conflito de interesses pertinentes.</p>
        </fn>
      </author-notes>
      <pub-date publication-format="electronic" date-type="pub">
        <day>23</day>
        <month>10</month>
        <year>2020</year>
      </pub-date>
      <pub-date publication-format="electronic" date-type="collection">
        <month>10</month>
        <year>2020</year>
      </pub-date>
      <volume>115</volume>
      <issue>4</issue>
      <fpage>660</fpage>
      <lpage>666</lpage>
      <history>
        <date date-type="received">
          <day>27</day>
          <month>04</month>
          <year>2020</year>
        </date>
        <date date-type="rev-recd">
          <day>14</day>
          <month>06</month>
          <year>2020</year>
        </date>
        <date date-type="accepted">
          <day>01</day>
          <month>07</month>
          <year>2020</year>
        </date>
      </history>
      <permissions>
        <license license-type="open-access" xml:lang="en" xlink:href="https://creativecommons.org/licenses/by/4.0/">
          <license-p>This is an open-access article distributed under the terms of the Creative Commons Attribution License</license-p>
        </license>
      </permissions>
      <abstract>
        <title>Resumo</title>
        <sec>
          <title>Fundamento:</title>
          <p>A COVID-19 causa grave acometimento pulmonar, por&#233;m o sistema cardiovascular tamb&#233;m pode ser afetado por miocardite, insufici&#234;ncia card&#237;aca e choque. A eleva&#231;&#227;o de biomarcadores card&#237;acos tem sido associada a um pior progn&#243;stico.</p>
        </sec>
        <sec>
          <title>Objetivos:</title>
          <p>Avaliar o valor progn&#243;stico da Troponina T (TnT) e do pept&#237;deo natriur&#233;tico tipo B (BNP) em pacientes internados por Covid-19.</p>
        </sec>
        <sec>
          <title>M&#233;todos:</title>
          <p>Amostra de conveni&#234;ncia de pacientes hospitalizados por COVID-19. Foram coletados dados dos prontu&#225;rios com o objetivo de avaliar a rela&#231;&#227;o da TnT e o BNP medidos nas primeiras 24h de admiss&#227;o com o desfecho combinado (DC) &#243;bito ou necessidade de ventila&#231;&#227;o mec&#226;nica. An&#225;lise univariada comparou os grupos com e sem DC. Modelo multivariado de Cox foi utilizada para determinar preditores independentes do DC.</p>
        </sec>
        <sec>
          <title>Resultados:</title>
          <p>Avaliamos 183 pacientes (idade=66,8&#177;17 anos, sendo 65,6% do sexo masculino). Tempo de acompanhamento foi de 7 dias (1 a 39 dias). O DC ocorreu em 24% dos pacientes. As medianas de TnT e BNP foram 0,011 e 0,041 ng/dl (p&lt;0,001); 64 e 198 pg/dl (p&lt;0,001) respectivamente para os grupos sem e com DC. Na an&#225;lise univariada, al&#233;m de TnT e BNP, idade, presen&#231;a de doen&#231;a coronariana, satura&#231;&#227;o de oxig&#234;nio, linf&#243;citos, d&#237;mero-D, prote&#237;na C reativa titulada (PCR-t) e creatinina, foram diferentes entre os grupos com e sem desfechos. Na an&#225;lise multivariada <italic>boostraped</italic> apenas TnT (1,12[IC95%1,03-1,47]) e PCR-t (1,04[IC95%1,00-1,10]) foram preditores independentes do DC.</p>
        </sec>
        <sec>
          <title>Conclus&#227;o:</title>
          <p>Nas primeiras 24h de admiss&#227;o, TnT, mas n&#227;o o BNP, foi marcador independente de mortalidade ou necessidade de ventila&#231;&#227;o mec&#226;nica invasiva. Este dado refor&#231;a ainda mais a import&#226;ncia cl&#237;nica do acometimento card&#237;aco da COVID-19. (AArq Bras Cardiol. 2020; 115(4):660-666)</p>
        </sec>
      </abstract>
      <kwd-group xml:lang="pt">
        <title>Palavras-chave:</title>
        <kwd>Betacoronav&#237;rus</kwd>
        <kwd>SARS-CoV-2</kwd>
        <kwd>Pandemia</kwd>
        <kwd>Biomarcadores</kwd>
        <kwd>Pacientes Internados</kwd>
        <kwd>Troponina T</kwd>
        <kwd>Peptideo Natriur&#233;tico Tipo B</kwd>
        <kwd>Doen&#231;as Cardiovasculares/complica&#231;&#245;es</kwd>
      </kwd-group>
      <counts>
        <fig-count count="4"/>
        <table-count count="6"/>
        <equation-count count="0"/>
        <ref-count count="17"/>
        <page-count count="7"/>
      </counts>
    </article-meta>
  </front>
  <body>
    <sec sec-type="intro">
      <title>Introdu&#231;&#227;o</title>
      <p>O mundo vive atualmente a pandemia de uma doen&#231;a denominada pela <italic>World Health Organization</italic> (WHO) como COVID-19, causada por um novo coronav&#237;rus (SARS-Cov-220). O <italic>International Committee on Taxonomy of Viruses</italic> ent&#227;o denominou o v&#237;rus como SARS-CoV-2<xref ref-type="bibr" rid="B1"><sup>1</sup></xref> (s&#237;ndrome respirat&#243;ria aguda severa coronav&#237;rus 2). A atual pandemia teve origem na China, em dezembro de 2019, na cidade de Wuhan, capital da prov&#237;ncia de Hubei. Rapidamente se espalhou globalmente e quando esse artigo foi escrito, j&#225; infectou mais de 4,5 milh&#245;es de pessoas, causando mais de 300.000 mortes. No Brasil mais de 200 mil pessoas j&#225; foram infectadas, sendo 15 mil delas v&#237;timas fatais.</p>
      <p>Coronaviroses habitualmente causam doen&#231;a pulmonar e intestinal aguda, o que faz de seus principais sintomas serem tosse, febre, dispneia, diarreia, n&#225;useas e v&#244;mitos. Todavia, desde seu in&#237;cio na China relatos crescentes de seu acometimento do sistema cardiovascular t&#234;m alertado a comunidade cient&#237;fica. Eleva&#231;&#227;o de biomarcadores card&#237;acos, como Troponina T (TnT) e pept&#237;deo natriur&#233;tico tipo B (BNP) tem sido associada a um pior progn&#243;stico.<xref ref-type="bibr" rid="B2"><sup>2</sup></xref> Guo et al.,<xref ref-type="bibr" rid="B2"><sup>2</sup></xref> numa coorte de 187 pacientes hospitalizados na cidade de Wuhan, verificaram que 27,8% dos pacientes apresentaram eleva&#231;&#227;o da TnT e a presen&#231;a de complica&#231;&#245;es como necessidade de ventila&#231;&#227;o mec&#226;nica foi maior neste grupo. Os n&#237;veis de N-terminal-pro-pept&#237;deo natriur&#233;tico tipo B (NT-Pro-BNP) tiveram correla&#231;&#227;o linear positiva significativa com a TnT. Liu et al.,<xref ref-type="bibr" rid="B3"><sup>3</sup></xref> demonstram que n&#237;veis de BNP&gt;100 pg/ml tamb&#233;m estiveram associados a um risco maior de complica&#231;&#245;es em pacientes com COVID-19. Entretanto, ambos os estudos se limitaram a realizar an&#225;lise univariada dos dados.</p>
      <p>Em recente an&#225;lise de pacientes recuperados de COVID-19, Huang et al.,<xref ref-type="bibr" rid="B4"><sup>4</sup></xref> demonstrou que a resson&#226;ncia magn&#233;tica card&#237;aca (RMC) foi anormal em 58%. Realce tardio, express&#227;o de fibrose mioc&#225;rdica, esteve presente em 31% dos pacientes. Por&#233;m n&#227;o houve diferen&#231;as nem de TnT nem de BNP entre os grupos com e sem altera&#231;&#245;es na RMC.</p>
      <p>O envolvimento card&#237;aco na COVID-19 &#233; uma realidade, por&#233;m o potencial preditivo dos marcadores card&#237;acos ainda precisa ser mais bem avaliado.</p>
      <p>No presente artigo avaliamos a presen&#231;a e o impacto dos biomarcadores card&#237;acos TnT e do BNP, medidos nas primeiras 24h de admiss&#227;o hospitalar na evolu&#231;&#227;o cl&#237;nica de pacientes admitidos por COVID-19.</p>
    </sec>
    <sec sec-type="methods">
      <title>M&#233;todos</title>
      <p>Amostra de conveni&#234;ncia de an&#225;lise de banco de dados de pacientes internados por COVID-19 em hospital terci&#225;rio na cidade do Rio de Janeiro. Foram revisados os prontu&#225;rios m&#233;dicos de pacientes que preenchiam os crit&#233;rios de s&#237;ndrome cl&#237;nica compat&#237;vel com COVID-19 pela WHO<xref ref-type="bibr" rid="B5"><sup>5</sup></xref> e que posteriormente tiveram seu diagn&#243;stico confirmado atrav&#233;s de <italic>swab</italic> de nasofaringe pelo m&#233;todo de rea&#231;&#227;o em cadeia da polimerase (PCR) em tempo real. Dados cl&#237;nicos e laboratoriais foram coletados dessa popula&#231;&#227;o. A TnT ultrassens&#237;vel foi dosada pelo m&#233;todo de eletroquimioluminesc&#234;ncia (Elecsys&#174; Troponin T Gen 5 STAT, Laborat&#243;rio Roche) e seu valor de corte foi de &lt; 0,014 ng/mL e o BNP) pelo m&#233;todo imunoensaio por fluoresc&#234;ncia (Triage&#174; BNP; Alere) e seu valor de corte &#233; &lt; 100 pg/mL. Foram ainda analisados sexo, peso, altura, presen&#231;a de comorbidade (doen&#231;a coronariana [DAC], doen&#231;a pulmonar, acidente vascular cerebral, diabetes, hipertens&#227;o arterial, doen&#231;a renal cr&#244;nica [DRC] e c&#226;ncer), tempo de sintomas na chegada ao hospital (dias), press&#227;o sist&#243;lica (PAS; mmHg), frequ&#234;ncia card&#237;aca (batimentos por minuto) e satura&#231;&#227;o arterial de oxig&#234;nio (%) na admiss&#227;o, leuc&#243;citos totais (c&#233;lulas/mm<sup>3</sup>), linf&#243;citos (c&#233;lulas/mm<sup>3</sup>), prote&#237;na C reativa titulada (PCR-t; mg/dl), creatinina (mg/dl), d&#237;mero-D (ng-dl) e ferritina (ng/ml). Todos os par&#226;metros cl&#237;nicos e laboratoriais foram obtidos nas primeiras 24 horas da admiss&#227;o.</p>
      <p>O desfecho cl&#237;nico avaliado foi a combina&#231;&#227;o de morte por todas as causas ou necessidade de ventila&#231;&#227;o mec&#226;nica (VM).</p>
      <p>O estudo foi conduzido de acordo com os padr&#245;es da declara&#231;&#227;o de Helsinque para pesquisa humana. Foi solicitado ao CEP dispensa do termo de consentimento livre e esclarecido, por se tratar de estudo observacional, retrospectivo, de an&#225;lise de prontu&#225;rio m&#233;dico.</p>
      <sec>
        <title>An&#225;lise Estat&#237;stica</title>
        <p>As vari&#225;veis cont&#237;nuas foram expressas em m&#233;dia e desvio padr&#227;o ou mediana e intervalo interquartil e comparadas pelos testes T-student n&#227;o-pareado ou U-Mann-Whitney de acordo com a presen&#231;a ou n&#227;o de distribui&#231;&#227;o normal. A presen&#231;a de distribui&#231;&#227;o normal foi avaliada pelo teste de Kolmogorov-Smirnov. As vari&#225;veis categ&#243;ricas foram expressas em frequ&#234;ncias (%) e comparadas atrav&#233;s do teste de Chi-quadrado e exato de Fisher.</p>
        <p>Os pacientes foram agrupados em quartis de acordo com os valores de TnT e a evolu&#231;&#227;o dos seus grupos foi comparada atrav&#233;s da curva de Kaplan-Meier e a diferen&#231;a entre os grupos estabelecida pelo teste de log rank.</p>
        <p>An&#225;lise de sobrevida multivariada de Cox foi desenvolvida com objetivo de identificar preditores independentes de morte e/ou necessidade de VM. Nesses modelos foram inclu&#237;das as vari&#225;veis com erro alfa menos que 5% na an&#225;lise univariada. Utilizamos a an&#225;lise multivariada de sobrevida, pois consideramos mais apropriada para um estudo progn&#243;stico. Para verificar a estabilidade do resultado, e eventuais vieses gerados por <italic>overfitting</italic>, a t&#233;cnica de <italic>bootstraping</italic> com 1.000 amostra foi empregada.<xref ref-type="bibr" rid="B6"><sup>6</sup></xref><sup>,</sup><xref ref-type="bibr" rid="B7"><sup>7</sup></xref></p>
        <p>A signific&#226;ncia estat&#237;stica foi definida por uma probabilidade de erro alfa &lt;5%. A an&#225;lise estat&#237;stica foi feita utilizando o programa SPSS (SPSS 22.0 para Windows, IBM SPSS, IL, USA).</p>
      </sec>
    </sec>
    <sec sec-type="results">
      <title>Resultados</title>
      <p>Foram analisados 183 pacientes. Tempo mediano de acompanhamento foi de 7 dias (1 a 39 dias). A <xref ref-type="table" rid="t1">Tabela 1</xref> descreve as caracter&#237;sticas da popula&#231;&#227;o.</p>
      <table-wrap id="t1">
        <label>Tabela 1</label>
        <caption>
          <title>Caracter&#237;sticas da popula&#231;&#227;o</title>
        </caption>
        <table frame="hsides" rules="groups">
          <colgroup width="50%">
            <col/>
            <col/>
          </colgroup>
          <thead style="border-top: thin solid; border-bottom: thin solid; border-color: #000000">
            <tr>
              <th align="left" valign="middle">N</th>
              <th align="center" valign="middle">183</th>
            </tr>
          </thead>
          <tbody style="border-bottom: thin solid; border-color: #000000">
            <tr>
              <td align="left" valign="middle">Idade (anos)</td>
              <td align="center" valign="middle">66,8&#177;17</td>
            </tr>
            <tr>
              <td align="left" valign="middle">Peso</td>
              <td align="center" valign="middle">80&#177;19</td>
            </tr>
            <tr>
              <td align="left" valign="middle">Altura</td>
              <td align="center" valign="middle">169&#177;15</td>
            </tr>
            <tr>
              <td align="left" valign="middle">Sexo Masculino (%)</td>
              <td align="center" valign="middle">65,6</td>
            </tr>
            <tr>
              <td align="left" valign="middle">DAC (%)</td>
              <td align="center" valign="middle">19,1</td>
            </tr>
            <tr>
              <td align="left" valign="middle">Doen&#231;a Pulmonar (%)</td>
              <td align="center" valign="middle">15,8</td>
            </tr>
            <tr>
              <td align="left" valign="middle">AVC (%)</td>
              <td align="center" valign="middle">4,4</td>
            </tr>
            <tr>
              <td align="left" valign="middle">Diabetes (%)</td>
              <td align="center" valign="middle">19,7</td>
            </tr>
            <tr>
              <td align="left" valign="middle">HAS (%)</td>
              <td align="center" valign="middle">53,6</td>
            </tr>
            <tr>
              <td align="left" valign="middle">C&#226;ncer (%)</td>
              <td align="center" valign="middle">9,8</td>
            </tr>
            <tr>
              <td align="left" valign="middle">DRC (%)</td>
              <td align="center" valign="middle">2,2</td>
            </tr>
            <tr>
              <td align="left" valign="middle">Tempo de Sintomas</td>
              <td align="center" valign="middle">6(3;8)</td>
            </tr>
            <tr>
              <td align="left" valign="middle">PAS</td>
              <td align="center" valign="middle">128&#177;19</td>
            </tr>
            <tr>
              <td align="left" valign="middle">FC</td>
              <td align="center" valign="middle">85&#177;16</td>
            </tr>
            <tr>
              <td align="left" valign="middle">SatO<sub>2</sub></td>
              <td align="center" valign="middle">93,6&#177;5,4</td>
            </tr>
            <tr>
              <td align="left" valign="middle">Leuc&#243;citos</td>
              <td align="center" valign="middle">6710(4760;9100)</td>
            </tr>
            <tr>
              <td align="left" valign="middle">Linf&#243;citos</td>
              <td align="center" valign="middle">1070(740;1400)</td>
            </tr>
            <tr>
              <td align="left" valign="middle">PCR-t</td>
              <td align="center" valign="middle">9,94(5,48;18,39)</td>
            </tr>
            <tr>
              <td align="left" valign="middle">Creatinina</td>
              <td align="center" valign="middle">0,98(0,78;1,26)</td>
            </tr>
            <tr>
              <td align="left" valign="middle">BNP</td>
              <td align="center" valign="middle">84(21;197,5)</td>
            </tr>
            <tr>
              <td align="left" valign="middle">TnT</td>
              <td align="center" valign="middle">0,011(0,006;0,033)</td>
            </tr>
            <tr>
              <td align="left" valign="middle">D&#237;mero D</td>
              <td align="center" valign="middle">906(482;1429)</td>
            </tr>
            <tr>
              <td align="left" valign="middle">Ferritina</td>
              <td align="center" valign="middle">720(378;1303)</td>
            </tr>
            <tr>
              <td align="left" valign="middle">&#211;bitos (%)</td>
              <td align="center" valign="middle">15,3</td>
            </tr>
            <tr>
              <td align="left" valign="middle">VM (%)</td>
              <td align="center" valign="middle">16,9</td>
            </tr>
            <tr>
              <td align="left" valign="middle">&#211;bito e/ou VM (%)</td>
              <td align="center" valign="middle">24</td>
            </tr>
            <tr>
              <td align="left" valign="middle">Interna&#231;&#227;o em UTI (%)</td>
              <td align="center" valign="middle">42,6</td>
            </tr>
          </tbody>
        </table>
        <table-wrap-foot>
          <fn id="TFN1">
            <p>DAC: doen&#231;a arterial coronariana; AVC: acidente vascular cerebral; HAS: hipertens&#227;o; DRC: doen&#231;a renal cr&#244;nica; PAS: press&#227;o arterial sist&#243;lica; FC: frequ&#234;ncia card&#237;aca; SatO<sub>2</sub>: satura&#231;&#227;o de oxig&#234;nio; PCR-t: prote&#237;na C reativa titulada; BNP: pept&#237;deo natriur&#233;tico tipo B; TnT: Troponina T; VM: ventila&#231;&#227;o mec&#226;nica; UTI: unidade de terapia intensiva.</p>
          </fn>
        </table-wrap-foot>
      </table-wrap>
      <p>Vinte e oito pacientes morreram e 31 precisaram de VM ao longo do per&#237;odo analisado. O desfecho combinado (DC) (&#243;bito e/ou VM esteve presente em 44 (24%) dos pacientes.</p>
      <p>A <xref ref-type="table" rid="t2">Tabela 2</xref> demonstra a an&#225;lise univariada nos grupos com e sem DC. Os pacientes com DC eram mais idosos; tinham maior preval&#234;ncia de DAC; satura&#231;&#227;o de oxig&#234;nio mais baixa, menor n&#250;mero de linf&#243;citos; PCR-t, creatinina, BNP, TnT e d&#237;mero-D mais elevados que o grupo sem desfecho. Essas foram as vari&#225;veis inclu&#237;das no modelo multivariado de COX cujo resultado est&#225; demonstrado na <xref ref-type="table" rid="t3">Tabela 3</xref>.</p>
      <table-wrap id="t2">
        <label>Tabela 2</label>
        <caption>
          <title>An&#225;lise Univariada</title>
        </caption>
        <table frame="hsides" rules="groups">
          <colgroup width="25%">
            <col/>
            <col/>
            <col/>
            <col/>
          </colgroup>
          <thead style="border-top: thin solid; border-bottom: thin solid; border-color: #000000">
            <tr>
              <th align="left" valign="middle"/>
              <th align="center" valign="middle">Vivo e sem VM</th>
              <th align="center" valign="middle">&#211;bito ou com VM</th>
              <th align="center" valign="middle">Valor de p</th>
            </tr>
          </thead>
          <tbody style="border-bottom: thin solid; border-color: #000000">
            <tr>
              <td align="left" valign="middle">N</td>
              <td align="center" valign="middle">139</td>
              <td align="center" valign="middle">44</td>
              <td align="center" valign="middle"/>
            </tr>
            <tr>
              <td align="left" valign="middle">Idade (anos)</td>
              <td align="center" valign="middle">64&#177;16</td>
              <td align="center" valign="middle">75,7&#177;16</td>
              <td align="center" valign="middle">&lt;0,001</td>
            </tr>
            <tr>
              <td align="left" valign="middle">Peso</td>
              <td align="center" valign="middle">82&#177;20</td>
              <td align="center" valign="middle">75,5&#177;14</td>
              <td align="center" valign="middle">0,116</td>
            </tr>
            <tr>
              <td align="left" valign="middle">Altura</td>
              <td align="center" valign="middle">169,8&#177;14</td>
              <td align="center" valign="middle">168,6&#177;19</td>
              <td align="center" valign="middle">0,858</td>
            </tr>
            <tr>
              <td align="left" valign="middle">Homem/Mulheres</td>
              <td align="center" valign="middle">86/53</td>
              <td align="center" valign="middle">34/10</td>
              <td align="center" valign="middle">0,061</td>
            </tr>
            <tr>
              <td align="left" valign="middle">DAC (%)</td>
              <td align="center" valign="middle">14,4</td>
              <td align="center" valign="middle">34,1</td>
              <td align="center" valign="middle">0,004</td>
            </tr>
            <tr>
              <td align="left" valign="middle">Doen&#231;a Pulmonar (%)</td>
              <td align="center" valign="middle">14,4</td>
              <td align="center" valign="middle">20,5</td>
              <td align="center" valign="middle">0,337</td>
            </tr>
            <tr>
              <td align="left" valign="middle">AVC (%)</td>
              <td align="center" valign="middle">3,6</td>
              <td align="center" valign="middle">6,8</td>
              <td align="center" valign="middle">0,401</td>
            </tr>
            <tr>
              <td align="left" valign="middle">Diabetes (%)</td>
              <td align="center" valign="middle">20,1</td>
              <td align="center" valign="middle">18,2</td>
              <td align="center" valign="middle">0,775</td>
            </tr>
            <tr>
              <td align="left" valign="middle">HAS (%)</td>
              <td align="center" valign="middle">51,1</td>
              <td align="center" valign="middle">61,4</td>
              <td align="center" valign="middle">0,233</td>
            </tr>
            <tr>
              <td align="left" valign="middle">C&#226;ncer (%)</td>
              <td align="center" valign="middle">8,6</td>
              <td align="center" valign="middle">13,6</td>
              <td align="center" valign="middle">0,311</td>
            </tr>
            <tr>
              <td align="left" valign="middle">DRC (%)</td>
              <td align="center" valign="middle">1,4</td>
              <td align="center" valign="middle">4,5</td>
              <td align="center" valign="middle">0,244</td>
            </tr>
            <tr>
              <td align="left" valign="middle">Tempo de Sintomas</td>
              <td align="center" valign="middle">6(3;8)</td>
              <td align="center" valign="middle">4(2,25;7)</td>
              <td align="center" valign="middle">0,14</td>
            </tr>
            <tr>
              <td align="left" valign="middle">PAS</td>
              <td align="center" valign="middle">127,9&#177;19</td>
              <td align="center" valign="middle">128,3&#177;21</td>
              <td align="center" valign="middle">0,911</td>
            </tr>
            <tr>
              <td align="left" valign="middle">FC</td>
              <td align="center" valign="middle">85,6&#177;17</td>
              <td align="center" valign="middle">87&#177;13</td>
              <td align="center" valign="middle">0,405</td>
            </tr>
            <tr>
              <td align="left" valign="middle">SatO<sub>2</sub></td>
              <td align="center" valign="middle">94,3&#177;5</td>
              <td align="center" valign="middle">91,7&#177;7</td>
              <td align="center" valign="middle">0,036</td>
            </tr>
            <tr>
              <td align="left" valign="middle">Leuc&#243;citos</td>
              <td align="center" valign="middle">6510(4715;8905)</td>
              <td align="center" valign="middle">7490(5680;10190)</td>
              <td align="center" valign="middle">0,083</td>
            </tr>
            <tr>
              <td align="left" valign="middle">Linf&#243;citos</td>
              <td align="center" valign="middle">1120(832,5;1470)</td>
              <td align="center" valign="middle">750(540;1190)</td>
              <td align="center" valign="middle">0,001</td>
            </tr>
            <tr>
              <td align="left" valign="middle">PCR-t</td>
              <td align="center" valign="middle">9,54(4,5325;16,9525)</td>
              <td align="center" valign="middle">13,64(7,04;24,74)</td>
              <td align="center" valign="middle">0,011</td>
            </tr>
            <tr>
              <td align="left" valign="middle">Creatinina</td>
              <td align="center" valign="middle">0,92(0,7575;1,0925)</td>
              <td align="center" valign="middle">1,3(1,01;1,91)</td>
              <td align="center" valign="middle">&lt;0,001</td>
            </tr>
            <tr>
              <td align="left" valign="middle">BNP</td>
              <td align="center" valign="middle">64,5(16,75;138)</td>
              <td align="center" valign="middle">198(45;619)</td>
              <td align="center" valign="middle">&lt;0,001</td>
            </tr>
            <tr>
              <td align="left" valign="middle">TnT</td>
              <td align="center" valign="middle">0,01(0,006;0,017)</td>
              <td align="center" valign="middle">0,041(0,012;0,072)</td>
              <td align="center" valign="middle">&lt;0,001</td>
            </tr>
            <tr>
              <td align="left" valign="middle">D&#237;mero D</td>
              <td align="center" valign="middle">741(452,75;1254,75)</td>
              <td align="center" valign="middle">1315(776;2200)</td>
              <td align="center" valign="middle">&lt;0,001</td>
            </tr>
            <tr>
              <td align="left" valign="middle">Ferritina</td>
              <td align="center" valign="middle">654(375,5;1204,75)</td>
              <td align="center" valign="middle">976(401,5;1543)</td>
              <td align="center" valign="middle">0,255</td>
            </tr>
          </tbody>
        </table>
        <table-wrap-foot>
          <fn id="TFN2">
            <p>DAC: doen&#231;a arterial coronariana; AVC: acidente vascular cerebral; HAS: hipertens&#227;o; DRC: doen&#231;a renal cr&#244;nica; PAS: press&#227;o arterial sist&#243;lica; FC: frequ&#234;ncia card&#237;aca; SatO<sub>2</sub>: satura&#231;&#227;o de oxig&#234;nio; PCR-t: prote&#237;na C reativa titulada; BNP: pept&#237;deo natriur&#233;tico tipo B; TnT: Troponina T.</p>
          </fn>
        </table-wrap-foot>
      </table-wrap>
      <table-wrap id="t3">
        <label>Tabela 3</label>
        <caption>
          <title>An&#225;lise multivariada de Cox com 1.000 <italic>bootstraped</italic></title>
        </caption>
        <table frame="hsides" rules="groups">
          <colgroup width="33%">
            <col/>
            <col/>
            <col/>
          </colgroup>
          <thead style="border-top: thin solid; border-bottom: thin solid; border-color: #000000">
            <tr>
              <th align="left" valign="middle">Vari&#225;veis</th>
              <th align="center" valign="middle">HR (IC95%)</th>
              <th align="center" valign="middle">HR (IC95%) <italic>bootstraped</italic></th>
            </tr>
          </thead>
          <tbody style="border-bottom: thin solid; border-color: #000000">
            <tr>
              <td align="left" valign="middle">Idade (anos)</td>
              <td align="center" valign="middle">1,02(0,99-1,04)</td>
              <td align="center" valign="middle">1,02(0,97-1,05)</td>
            </tr>
            <tr>
              <td align="left" valign="middle">DAC (%)</td>
              <td align="center" valign="middle">1,09(0,47-2,53)</td>
              <td align="center" valign="middle">1,09(0,36-2,84)</td>
            </tr>
            <tr>
              <td align="left" valign="middle">SatO<sub>2</sub> (%)</td>
              <td align="center" valign="middle">0,92(0,87-0,97)</td>
              <td align="center" valign="middle">0,92(0,85-1,01)</td>
            </tr>
            <tr>
              <td align="left" valign="middle">Linf&#243;citos (cada 100 c&#233;lulas/mm<sup>3</sup>)</td>
              <td align="center" valign="middle">1,01(0,95-1,07)</td>
              <td align="center" valign="middle">1,01(0,87-1,06)</td>
            </tr>
            <tr>
              <td align="left" valign="middle">D&#237;mero D (500 Ung/ml)</td>
              <td align="center" valign="middle">0,99(0,97-1,01)</td>
              <td align="center" valign="middle">0,99(0,92-1,03)</td>
            </tr>
            <tr>
              <td align="left" valign="middle">PCR-t (mg/dl)</td>
              <td align="center" valign="middle">1,04(1,01-1,08)</td>
              <td align="center" valign="middle">1,04(1,00-1,10)</td>
            </tr>
            <tr>
              <td align="left" valign="middle">Creatinina (mg/dl)</td>
              <td align="center" valign="middle">0,9(0,62-1,3)</td>
              <td align="center" valign="middle">0,9(0,55-2,17)</td>
            </tr>
            <tr>
              <td align="left" valign="middle">TnT (incremento de 0,014 ng/dl)</td>
              <td align="center" valign="middle">1,13(1,05-1,21)</td>
              <td align="center" valign="middle">1,12(1,03-1,47)</td>
            </tr>
            <tr>
              <td align="left" valign="middle">BNP (incremento de 100 pg/ml)</td>
              <td align="center" valign="middle">1,05(0,95-1,15)</td>
              <td align="center" valign="middle">1,05(0,81-1,23)</td>
            </tr>
          </tbody>
        </table>
        <table-wrap-foot>
          <fn id="TFN3">
            <p>DAC: doen&#231;a arterial coronariana; SatO<sub>2</sub>: satura&#231;&#227;o de oxig&#234;nio; PCR-t: prote&#237;na C reativa titulada; TnT: Troponina T; BNP: pept&#237;deo natriur&#233;tico tipo B.</p>
          </fn>
        </table-wrap-foot>
      </table-wrap>
      <p>Todos os biomarcadores citados foram inclu&#237;dos na an&#225;lise multivariada e ap&#243;s a an&#225;lise de <italic>bootstrap</italic> apenas a TnT e a PCR-t estiveram de forma independente associada ao DC.</p>
      <p>A <xref ref-type="fig" rid="f1">Figura 1</xref> ilustra as diferen&#231;as de desfecho combinado por quartil de TnT. A mortalidade mais do que dobra entre Q1 e Q2; e Q3 e Q4, e aumenta mais de 60% entre Q2 e Q3. A <xref ref-type="fig" rid="f2">Figura 2</xref> mostra a probabilidade do evento ao longo do tempo para cada um dos quartis de TnT. Ap&#243;s 20 dias da admiss&#227;o, a sobrevida livre de eventos para o Q1 de troponina T (TnT&#8804;0,006ng/dl) foi de 89,8% e para o Q4 (TnT&#8805;0,03ng/dl) foi de 15,2%.</p>
      <fig id="f1">
        <label>Figura 1</label>
        <caption>
          <title>Diferen&#231;as de desfecho combinado por quartil de Troponina. VM: ventila&#231;&#227;o mec&#226;nica; TnT: Troponina T.</title>
        </caption>
        <graphic xlink:href="1678-4170-abc-115-04-0660-00385-gf01.tif"/></fig>
      <fig id="f2">
        <label>Figura 2</label>
        <caption>
          <title>Probabilidade do desfecho combinado ao longo do tempo para cada um dos quartis de Troponina. TnT: troponina T.</title>
        </caption>
        <graphic xlink:href="1678-4170-abc-115-04-0660-00385-gf02.tif"/></fig>
    </sec>
    <sec sec-type="discussion">
      <title>Discuss&#227;o</title>
      <p>Esse estudo refor&#231;a a impress&#227;o j&#225; levantada por outros autores de que a eleva&#231;&#227;o de TnT, al&#233;m de prevalente, est&#225; associada a evolu&#231;&#227;o para formas graves de COVID-19. A luz dos nossos conhecimentos este &#233; o segundo estudo, primeiro no Brasil, h&#225; identificar a TnT como preditor independente de pior progn&#243;stico em pacientes com COVID-19. Shi et al. em coorte chinesa de desenho semelhante, demonstrou que a eleva&#231;&#227;o de troponina na admiss&#227;o aumentou em 3,41(IC95% 1,62-716) o risco de morte em pacientes com COVID-19.<xref ref-type="bibr" rid="B8"><sup>8</sup></xref> Nela pacientes com aumento da troponina tiveram uma maior taxa de VM invasiva frente aos que n&#227;o tiveram eleva&#231;&#227;o da troponina (18 de 82 [22,0%] vs. 14 de 334 [4,2%]; p&lt; 0,001). Al&#233;m disso a mortalidade tamb&#233;m foi maior naqueles com inj&#250;ria mioc&#225;rdica frente aos sem inj&#250;ria (42 de 82 [51,2%] vs. 15 de 334 [4,5%]; p&lt; 0,001). Todavia, epidemia de outras doen&#231;as virais como a Dengue na China tiveram preval&#234;ncia e progn&#243;stico de miocardite bem diferentes que o Brasil, e outros pa&#237;ses.<xref ref-type="bibr" rid="B9"><sup>9</sup></xref><sup>,</sup><xref ref-type="bibr" rid="B10"><sup>10</sup></xref> Nosso trabalho demonstra que este n&#227;o parece ser o caso da COVID-19, onde, em popula&#231;&#245;es ocidentais e orientais, a preval&#234;ncia de inj&#250;ria mioc&#225;rdica &#233; prevalente e associada a pior progn&#243;stico. Dentre os desfechos desfavor&#225;veis encontram-se insufici&#234;ncia card&#237;aca, arritmias, VM e morte.<xref ref-type="bibr" rid="B11"><sup>11</sup></xref></p>
      <p>Entre os mecanismos propostos para a agress&#227;o mioc&#225;rdica causada pelo SARS-CoV-2, temos principalmente a chamada &#8220;tempestade de citocinas&#8221; que &#233; desencadeada por um desequil&#237;brio nas respostas celulares dos linf&#243;citos T helper Tipo 1 e Tipo 2. A Interleucina-6 (IL-6) &#233; uma das que se elevam como resultado desse desequil&#237;brio celular, sendo inclusive um marcador de mortalidade j&#225; identificado. Essas citocinas agridem o mioc&#225;rdio, causando eleva&#231;&#227;o da troponina e disfun&#231;&#227;o card&#237;aca.<xref ref-type="bibr" rid="B12"><sup>12</sup></xref> Uma metan&#225;lise de quatro estudos chineses publicados como correspond&#234;ncia, envolvendo 341 pacientes foi publicada recentemente.<xref ref-type="bibr" rid="B13"><sup>13</sup></xref> A preval&#234;ncia de eleva&#231;&#227;o de troponina (acima do percentil 99%) foi de 8 a 12%, e seus valores foram significativamente mais elevados em pacientes com formas mais graves de COVID-19. Portanto, a monitoriza&#231;&#227;o da troponina pode ajudar a identificar um subgrupo com maior chance de um curso cl&#237;nico pior.</p>
      <p>Um importante achado no estudo de Guo et al.<xref ref-type="bibr" rid="B5"><sup>5</sup></xref> foi que a eleva&#231;&#227;o da troponina foi um marcador mais forte para mortalidade do que a presen&#231;a de doen&#231;a cardiovascular (DCV) pr&#233;via. Pacientes com hist&#243;rico de DCV, mas com troponina normal tiveram mortalidade menor que aqueles sem hist&#243;ria de DCV, mas que elevaram troponina na interna&#231;&#227;o. Al&#233;m disso, tanto a TnT quanto NT-pro-BNP aumentaram de forma significativa ao longo da interna&#231;&#227;o naqueles que evolu&#237;ram para &#243;bito e isto n&#227;o foi observado naqueles que sobreviveram.</p>
      <p>Na nossa coorte ficou muito bem demonstrada a rela&#231;&#227;o da eleva&#231;&#227;o da TnT e o DC de morte ou VM, chegando ao ponto de que mais da metade dos pacientes no &#250;ltimo quartil de troponina (&gt;0,03ng/dL) tiveram evolu&#231;&#227;o desfavor&#225;vel. Isso pode ajudar de forma pr&#225;tica a identificar na admiss&#227;o aqueles pacientes com maior risco intra-hospitalar de pior curso cl&#237;nico.</p>
      <p>Quanto ao BNP/NT-pro-NBP, alguns estudos tamb&#233;m sugerem ser um marcador progn&#243;stico importante. Os poss&#237;veis mecanismos para eleva&#231;&#227;o do BNP na infec&#231;&#227;o por SARS-Cov-2 v&#227;o desde a eleva&#231;&#227;o secund&#225;ria a agress&#227;o inflamat&#243;ria do mioc&#225;rdio (tempestade de citocinas), j&#225; descrita, que resulta em disfun&#231;&#227;o card&#237;aca e aumento das press&#245;es de enchimento ventricular, at&#233; mesmo a agress&#227;o direta do cardiomi&#243;cito pelo v&#237;rus pelo s&#237;tio de liga&#231;&#227;o da enzima conversora da angiotensina 2 e pela hipoxemia mioc&#225;rdica induzida pela inj&#250;ria pulmonar aguda. O primeiro estudo que mostrou que o NT-Pro-BNP &#233; um marcador de mortalidade foi publicado por Gao et al.,<xref ref-type="bibr" rid="B14"><sup>14</sup></xref> 54 pacientes com disfun&#231;&#227;o respirat&#243;ria importante (frequ&#234;ncia respirat&#243;ria &#8805;30/min ou SatO<sub>2</sub> &#8804;93% ou rela&#231;&#227;o entre press&#227;o arterial de O<sub>2</sub>/fra&#231;&#227;o inspirada de oxig&#234;nio &#8804; 300 mmHg). Pacientes com NT-proBNP&gt; 88,64 pg/mL mostraram uma sobrevida cumulativa no segmento de 15 dias significativamente menor do que aqueles com valores abaixo desse valor. Na nossa coorte apesar de um preditor de risco na an&#225;lise univariada, o BNP n&#227;o se mostrou um marcador independente de risco quando utilizado o modelo multivariado. Isso pode ser explicado por um efeito de colinearidade entre TnT e BNP, uma vez que j&#225; foi demonstrado grande correla&#231;&#227;o entre estes marcadores na COVID-19.</p>
      <p>A prote&#237;na C reativa titulada al&#233;m da TnT, tamb&#233;m esteve associada independentemente a um pior progn&#243;stico em nossa coorte. De fato, outros trabalhos j&#225; v&#234;m sinalizando a correla&#231;&#227;o que existe entre a PCR-t e a severidade da infec&#231;&#227;o por COVID-19,<xref ref-type="bibr" rid="B15"><sup>15</sup></xref><sup>,</sup><xref ref-type="bibr" rid="B16"><sup>16</sup></xref> o que suporta os achados do nosso trabalho.</p>
      <p>O presente estudo mostrou a rela&#231;&#227;o entre a eleva&#231;&#227;o da TnT e o risco para &#243;bito ou necessidade de VM. Em contrapartida, a eleva&#231;&#227;o do BNP, apesar de na an&#225;lise univariada ter se mostrado um fator de risco para o DC de VM ou &#243;bito, n&#227;o se mostrou um preditor independente na nossa amostra. De fato, recente artigo de revis&#227;o de Costa et al.,<xref ref-type="bibr" rid="B17"><sup>17</sup></xref> estabeleceu fluxograma de abordagem cardiol&#243;gica de pacientes com COVID-19 e a troponina foi o &#250;nico marcador laboratorial sugerido para definir interna&#231;&#227;o em unidade de terapia intensiva, independentemente da presen&#231;a de hist&#243;ria de DCV.</p>
      <sec>
        <title>Limita&#231;&#245;es</title>
        <p>Dados de eletrocardiograma (ECG) e ecocardiograma (ECO) n&#227;o foram inclu&#237;dos na an&#225;lise. Isso porque menos de 70% dos pacientes da amostra tem esses dados. O paciente COVID-19 &#233; um grande consumidor de recursos hospitalares notoriamente EPI e por isso esses exames s&#243; s&#227;o solicitados quando estritamente necess&#225;rios e indicados. Isso tamb&#233;m valeu para n&#227;o avaliarmos os biomarcadores como vari&#225;veis cont&#237;nuas ao longo do tempo. N&#227;o utilizamos coletas seriadas de rotina desses biomarcadores. Cada entrada no leito de isolamento para coleta de biomarcadores ou de outros exames, salvo estritamente necess&#225;rio, aumenta os custos, a utiliza&#231;&#227;o de EPIs e o risco para a equipe de sa&#250;de. Portanto, inclu&#237;-los (ECG, ECO e biomarcadores coletados seriadamente) exigiria uma estrat&#233;gia de tratamento de dados faltantes que, na nossa opini&#227;o, comprometeria a an&#225;lise.</p>
        <p>Outra limita&#231;&#227;o &#233; de que com muitos preditores na an&#225;lise univariada e um n&#250;mero de desfechos relativamente pequenos para o tamanho amostral, a t&#233;cnica de <italic>bootstrap</italic> n&#227;o elimina a possibilidade de <italic>overfitting</italic>.</p>
      </sec>
    </sec>
    <sec sec-type="conclusions">
      <title>Conclus&#227;o</title>
      <p>A TnT, mas n&#227;o o BNP, foi um marcador independente de risco para mortalidade ou necessidade de VM invasiva em pacientes hospitalizados por COVID-19. Estes dados refor&#231;am ainda mais a utiliza&#231;&#227;o deste biomarcador na estratifica&#231;&#227;o de risco dos pacientes com COVID-19.</p>
    </sec>
  </body>
  <back>
    <fn-group>
      <fn fn-type="supported-by" id="fn1">
        <p>
          <bold>Fontes de Financiamento</bold>
        </p>
        <p>O presente estudo n&#227;o teve fontes de financiamento externas.</p>
      </fn>
      <fn fn-type="other" id="fn2">
        <p>
          <bold>Vincula&#231;&#227;o Acad&#234;mica</bold>
        </p>
        <p>N&#227;o h&#225; vincula&#231;&#227;o deste estudo a programas de p&#243;s-gradua&#231;&#227;o.</p>
      </fn>
    </fn-group>
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  </back>
  <sub-article article-type="translation" id="S01" xml:lang="en">
    <front-stub>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Original Article</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Prognostic Value of Troponin-T and B-Type Natriuretic Peptide in Patients Hospitalized for COVID-19</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0002-9755-8849</contrib-id>
          <name>
            <surname>Almeida</surname>
            <given-names>Gustavo Luiz Gouv&#234;a de</given-names>
            <suffix>Junior</suffix>
          </name>
          <xref ref-type="aff" rid="aff2">
            <sup>1</sup>
          </xref>
          <xref ref-type="corresp" rid="c2"/>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0002-7062-1705</contrib-id>
          <name>
            <surname>Braga</surname>
            <given-names>Fabricio</given-names>
          </name>
          <xref ref-type="aff" rid="aff2">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Jorge</surname>
            <given-names>Jos&#233; Kezen</given-names>
          </name>
          <xref ref-type="aff" rid="aff2">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Nobre</surname>
            <given-names>Gustavo Freitas</given-names>
          </name>
          <xref ref-type="aff" rid="aff2">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Kalichsztein</surname>
            <given-names>Marcelo</given-names>
          </name>
          <xref ref-type="aff" rid="aff2">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Faria</surname>
            <given-names>Paula de Medeiros Pache de</given-names>
          </name>
          <xref ref-type="aff" rid="aff2">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Bussade</surname>
            <given-names>Bruno</given-names>
          </name>
          <xref ref-type="aff" rid="aff2">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Penna</surname>
            <given-names>Guilherme Loures</given-names>
          </name>
          <xref ref-type="aff" rid="aff2">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Alves</surname>
            <given-names>Vitor Oliveira</given-names>
          </name>
          <xref ref-type="aff" rid="aff2">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0001-9778-1795</contrib-id>
          <name>
            <surname>Pereira</surname>
            <given-names>Marcella Alecrim</given-names>
          </name>
          <xref ref-type="aff" rid="aff2">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0002-7717-9577</contrib-id>
          <name>
            <surname>Gorgulho</surname>
            <given-names>Paula de Castro</given-names>
          </name>
          <xref ref-type="aff" rid="aff2">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Faria</surname>
            <given-names>Milena Rego dos Santos Espelta de</given-names>
          </name>
          <xref ref-type="aff" rid="aff2">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Drumond</surname>
            <given-names>Luis Eduardo</given-names>
          </name>
          <xref ref-type="aff" rid="aff2">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Carpinete</surname>
            <given-names>Fabrini Batista Soares</given-names>
          </name>
          <xref ref-type="aff" rid="aff2">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Neno</surname>
            <given-names>Ana Carolina Lessa Brand&#227;o</given-names>
          </name>
          <xref ref-type="aff" rid="aff2">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Neno</surname>
            <given-names>Augusto C&#233;sar de Ara&#250;jo</given-names>
          </name>
          <xref ref-type="aff" rid="aff2">
            <sup>1</sup>
          </xref>
        </contrib>
        <aff id="aff2">
          <label>1</label>
          <addr-line>
            <named-content content-type="city">Rio de Janeiro</named-content>
            <named-content content-type="state">RJ</named-content>
          </addr-line>
          <country country="BR">Brazil</country>
          <institution content-type="original">Casa de Sa&#250;de S&#227;o Jos&#233;, Rio de Janeiro, RJ &#8211; Brazil</institution>
        </aff>
      </contrib-group>
      <author-notes>
        <corresp id="c2"><bold>Mailing Address: Gustavo Luiz Gouv&#234;a Almeida Junior &#8226;</bold> Casa de Sa&#250;de S&#227;o Jos&#233; - Macedo Sobrinho, 21. Postal Code <postal-code>22271-080</postal-code>, Humait&#225;, RJ &#8211; Brazil. E-mail: <email>dr.ggouvea@gmail.com</email></corresp>
        <fn fn-type="conflict">
          <p>
            <bold>Potential Conflict of Interest</bold>
          </p>
          <p>No potential conflict of interest relevant to this article was reported.</p>
        </fn>
      </author-notes>
      <abstract>
        <title>Abstract</title>
        <sec>
          <title>Background:</title>
          <p>COVID-19 causes severe pulmonary involvement, but the cardiovascular system can also be affected by myocarditis, heart failure and shock. The increase in cardiac biomarkers has been associated with a worse prognosis.</p>
        </sec>
        <sec>
          <title>Objectives:</title>
          <p>To evaluate the prognostic value of Troponin-T (TNT) and natriuretic peptide (BNP) in patients hospitalized for Covid-19.</p>
        </sec>
        <sec>
          <title>Methods:</title>
          <p>This was a convenience sample of patients hospitalized for COVID-19. Data were collected from medical records to assess the association of TnT and BNP measured in the first 24 hours of hospital admission with the combined outcome (CO) of death or need for mechanical ventilation. Univariate analysis was used to compare the groups with and without the CO. Cox's multivariate model was used to determine independent predictors of the CO.</p>
        </sec>
        <sec>
          <title>Results:</title>
          <p>We evaluated 183 patients (age = 66.8&#177;17 years, 65.6% of which were males). The time of follow-up was 7 days (range 1 to 39 days). The CO occurred in 24% of the patients. The median troponin-T and BNP levels were 0.011 and 0.041ng/dL (p &lt;0.001); 64 and 198 pg/dL (p &lt;0.001), respectively, for the groups without and with the CO. In the univariate analysis, in addition to TnT and BNP, age, presence of coronary disease, oxygen saturation, lymphocytes, D-dimer, t-CRP and creatinine, were different between groups with and without outcomes. In the bootstrap multivariate analysis, only TnT (1.12 [95% CI 1.03-1.47]) and t-CRP (1.04 [95% CI 1.00-1.10]) were independent predictors of the CO.</p>
        </sec>
        <sec>
          <title>Conclusion:</title>
          <p>In the first 24h of admission, TnT, but not BNP, was an independent marker of mortality or need for invasive mechanical ventilation. This finding further reinforces the clinical importance of cardiac involvement in COVID-19. (Arq Bras Cardiol. 2020; 115(4):660-666)</p>
        </sec>
      </abstract>
      <kwd-group xml:lang="en">
        <title>Keywords:</title>
        <kwd>Betacoronavirus</kwd>
        <kwd>SARS-CoV-2</kwd>
        <kwd>Pandemics</kwd>
        <kwd>Biomarkers</kwd>
        <kwd>Inpatients</kwd>
        <kwd>Troponin T</kwd>
        <kwd>Natriuretic Peptide, B Type</kwd>
        <kwd>Cardiovascular Diseases/complications</kwd>
      </kwd-group>
    </front-stub>
    <body>
      <sec sec-type="intro">
        <title>Introduction</title>
        <p>The world is currently experiencing the pandemic of a disease called COVID-19 by the World Health Organization (WHO), caused by a new coronavirus (SARS-Cov-2). The International Committee on Taxonomy of Viruses then called the virus SARS-CoV-2<xref ref-type="bibr" rid="B1"><sup>1</sup></xref> (severe acute respiratory syndrome coronavirus-2). The current pandemic originated in China in December 2019 in the city of Wuhan, capital of the Hubei province. It quickly spread globally and by the time this article was written, it has already infected more than 4.5 million people, causing more than 300,000 deaths. In Brazil, more than 200,000 people have already been infected, of which 15,000 died due to COVID-19.</p>
        <p>Coronaviruses usually cause acute lung and intestinal disease, of which its main symptoms are cough, fever, dyspnea, diarrhea, nausea and vomiting. However, since its appearance in China, there have been growing reports of its cardiovascular system involvement, which have alerted the scientific community. Elevated cardiac biomarkers, such as Troponin-T (TnT) and brain natriuretic peptide (BNP) has been associated with a worse prognosis<xref ref-type="bibr" rid="B2"><sup>2</sup></xref>. Guo et al.,<xref ref-type="bibr" rid="B2"><sup>2</sup></xref> in a cohort of 187 hospitalized patients in the city of Wuhan, found that 27.8% of the patients had an increase in TnT and the presence of complications, such as the need for mechanical ventilation, was higher in this group. The levels of N-terminal-pro-brain natriuretic peptide (NT-Pro-BNP) had a significant positive linear correlation with TnT. Liu et al.<xref ref-type="bibr" rid="B3"><sup>3</sup></xref> showed that BNP levels &gt;100pg/mL were also associated with a higher risk of complications in patients with COVID-19. However, both studies were limited to performing the univariate analysis of data.</p>
        <p>In a recent analysis of patients that recovered from COVID-19, Huang et al.<xref ref-type="bibr" rid="B4"><sup>4</sup></xref> demonstrated that cardiac magnetic resonance (CMR) imaging was abnormal in 58%. Late enhancement and myocardial fibrosis expression were present in 31% of patients. However, there were no differences in either TnT or BNP levels between groups with and without changes in CMR imaging.</p>
        <p>Cardiac involvement in COVID-19 is a reality, but the predictive potential of cardiac markers still needs to be better assessed.</p>
        <p>In the present article, we evaluated the presence and impact of cardiac biomarkers TnT and BNP, measured within the first 24 hours of hospital admission on the clinical evolution of patients admitted for COVID-19.</p>
      </sec>
      <sec sec-type="methods">
        <title>Methods</title>
        <p>This was a convenience sample obtained from the database analysis of patients admitted for COVID-19 in a tertiary hospital in the city of Rio de Janeiro, Brazil. The medical records of patients who met the criteria for a clinical syndrome compatible with COVID-19 by the WHO<xref ref-type="bibr" rid="B5"><sup>5</sup></xref> and who later had their diagnosis confirmed by a nasopharyngeal swab using the real-time polymerase chain reaction (RT-PCR) method were reviewed. Clinical and laboratory data were collected from this population. The ultrasensitive TnT was measured using the electrochemiluminescence method (Elecsys<sup>&#174;</sup> Troponin T Gen 5 STAT, Roche Laboratory) and its cutoff value was &lt;0.014ng/mL, whereas the BNP was measured by the fluorescence immunoassay method (Triage<sup>&#174;</sup> BNP; Alere) and its cutoff value was &lt;100 pg/mL.</p>
        <p>Gender, weight, height, presence of comorbidity (coronary artery disease [CAD], pulmonary disease, stroke, diabetes, arterial hypertension, chronic kidney disease [CKD] and cancer), time of symptom onset on arrival at the hospital (days), systolic blood pressure (SBP; mmHg), heart rate (beats per minute) and arterial oxygen saturation (%) on hospital admission, total leukocytes (cells/mm<sup>3</sup>), lymphocytes (cells / mm3), titrated C-reactive protein (t-CRP; mg/dL), Creatinine (mg/dL), D-dimer (ng-dL) and Ferritin (ng/mL) were also assessed. All clinical and laboratory parameters were obtained within the first 24 hours of hospital admission.</p>
        <p>The assessed clinical outcome was the combination of death from all causes or the need for mechanical ventilation (MV).</p>
        <p>The study was carried out according to the standards of the Helsinki declaration for human research. The need for the Free and Informed Consent was waived by the Research Ethics Committee, as it is an observational, retrospective study, performed through the analysis of medical records.</p>
        <sec>
          <title>Statistical Analysis</title>
          <p>The continuous variables were expressed as mean and standard deviation or median and interquartile range and compared by unpaired Student's <italic>t</italic> test or Mann-Whitney-U test according to the presence or not of normal distribution. The presence of normal distribution was assessed by the Kolmogorov-Smirnov test. Categorical variables were expressed as frequencies (%) and compared using the Chi-square test and Fisher's exact test.</p>
          <p>The patients were grouped in quartiles according to the troponin-T values and the evolution of their groups was compared using the Kaplan-Meier curve, whereas the difference between groups was established by the log rank test. Cox multivariate survival analysis was developed aiming to identify independent predictors of death and or the need for mechanical ventilation. Variables with an alpha error &lt; 5% in the univariate analysis were included in these models. The multivariate analysis of survival was used, as it was considered more appropriate for a prognostic study.</p>
          <p>To verify the stability of the result, and any biases generated by overfitting, the bootstrapping technique with 1,000 samples was used.<xref ref-type="bibr" rid="B6"><sup>6</sup></xref><sup>,</sup><xref ref-type="bibr" rid="B7"><sup>7</sup></xref></p>
          <p>Statistical significance was defined by an alpha error probability &lt;5%. Statistical analysis was performed using the SPSS program (SPSS 22.0 for Windows, IBM SPSS, IL, USA).</p>
        </sec>
      </sec>
      <sec sec-type="results">
        <title>Results</title>
        <p>A total of 183 patients were analyzed. The median follow-up time was 7 days (1 to 39 days). <xref ref-type="table" rid="t4">Table 1</xref> describes the characteristics of the population.</p>
        <table-wrap id="t4">
          <label>Table 1</label>
          <caption>
            <title>Characteristics of the population</title>
          </caption>
          <table frame="hsides" rules="groups">
            <colgroup width="50%">
              <col/>
              <col/>
            </colgroup>
            <thead style="border-top: thin solid; border-bottom: thin solid; border-color: #000000">
              <tr>
                <th align="left" valign="middle">N</th>
                <th align="center" valign="middle">183</th>
              </tr>
            </thead>
            <tbody style="border-bottom: thin solid; border-color: #000000">
              <tr>
                <td align="left" valign="middle">Age (years)</td>
                <td align="center" valign="middle">66.8&#177;17</td>
              </tr>
              <tr>
                <td align="left" valign="middle">Weight</td>
                <td align="center" valign="middle">80&#177;19</td>
              </tr>
              <tr>
                <td align="left" valign="middle">Height</td>
                <td align="center" valign="middle">169&#177;15</td>
              </tr>
              <tr>
                <td align="left" valign="middle">Male gender (%)</td>
                <td align="center" valign="middle">65.6</td>
              </tr>
              <tr>
                <td align="left" valign="middle">CAD (%)</td>
                <td align="center" valign="middle">19.1</td>
              </tr>
              <tr>
                <td align="left" valign="middle">Pulmonary disease (%)</td>
                <td align="center" valign="middle">15.8</td>
              </tr>
              <tr>
                <td align="left" valign="middle">Stroke (%)</td>
                <td align="center" valign="middle">4.4</td>
              </tr>
              <tr>
                <td align="left" valign="middle">Diabetes (%)</td>
                <td align="center" valign="middle">19.7</td>
              </tr>
              <tr>
                <td align="left" valign="middle">SAH (%)</td>
                <td align="center" valign="middle">53.6</td>
              </tr>
              <tr>
                <td align="left" valign="middle">Cancer (%)</td>
                <td align="center" valign="middle">9.8</td>
              </tr>
              <tr>
                <td align="left" valign="middle">CKD (%)</td>
                <td align="center" valign="middle">2.2</td>
              </tr>
              <tr>
                <td align="left" valign="middle">Time of symptom onset</td>
                <td align="center" valign="middle">6(3;8)</td>
              </tr>
              <tr>
                <td align="left" valign="middle">SBP</td>
                <td align="center" valign="middle">128&#177;19</td>
              </tr>
              <tr>
                <td align="left" valign="middle">HR</td>
                <td align="center" valign="middle">85&#177;16</td>
              </tr>
              <tr>
                <td align="left" valign="middle">SatO<sub>2</sub></td>
                <td align="center" valign="middle">93.6&#177;5.4</td>
              </tr>
              <tr>
                <td align="left" valign="middle">Leukocytes</td>
                <td align="center" valign="middle">6710(4760;9100)</td>
              </tr>
              <tr>
                <td align="left" valign="middle">Lymphocytes</td>
                <td align="center" valign="middle">1070(740;1400)</td>
              </tr>
              <tr>
                <td align="left" valign="middle">CRP</td>
                <td align="center" valign="middle">9.94(5.48;18.39)</td>
              </tr>
              <tr>
                <td align="left" valign="middle">Creatinine</td>
                <td align="center" valign="middle">0.98(0.78;1.26)</td>
              </tr>
              <tr>
                <td align="left" valign="middle">BNP</td>
                <td align="center" valign="middle">84(21;197.5)</td>
              </tr>
              <tr>
                <td align="left" valign="middle">TnT</td>
                <td align="center" valign="middle">0.011(0.006;0.033)</td>
              </tr>
              <tr>
                <td align="left" valign="middle">D-Dimer</td>
                <td align="center" valign="middle">906(482;1429)</td>
              </tr>
              <tr>
                <td align="left" valign="middle">Ferritin</td>
                <td align="center" valign="middle">720(378;1303)</td>
              </tr>
              <tr>
                <td align="left" valign="middle">Deaths (%)</td>
                <td align="center" valign="middle">15.3</td>
              </tr>
              <tr>
                <td align="left" valign="middle">Mechanical Ventilation &#8211; MV (%)</td>
                <td align="center" valign="middle">16.9</td>
              </tr>
              <tr>
                <td align="left" valign="middle">Death and/or MV (%)</td>
                <td align="center" valign="middle">24</td>
              </tr>
              <tr>
                <td align="left" valign="middle">Admission at ICU (%)</td>
                <td align="center" valign="middle">42.6</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn id="TFN4">
              <p>CAD: coronary artery disease; SAH: systemic arterial hypertension; CKD: chronic kidney disease; SBP: systolic blood pressure; HR: heart rate; SatO<sub>2</sub>: oxygen saturation; t-CRP: C-reactive protein; BNP: B-Type Natriuretic Peptide; TnT: Troponin-T; MV: mechanical ventilation; ICU: intensive care unit.</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
        <p>Twenty-eight patients died and 31 required mechanical ventilation during the analyzed period. The combined outcome (death and/or mechanical ventilation was present in 44 (24%) of the patients.</p>
        <p><xref ref-type="table" rid="t5">Table 2</xref> shows the univariate analysis in the groups with and without the combined outcome. The patients with a combined outcome were older; had a higher prevalence of CAD; lower oxygen saturation, fewer lymphocytes; and higher levels of t-CRP, creatinine, BNP, TnT and D-dimer than the group without the outcome. These were the variables included in the COX multivariate model, of which results are shown in <xref ref-type="table" rid="t6">table 3</xref>.</p>
        <table-wrap id="t5">
          <label>Table 2</label>
          <caption>
            <title>Univariate Analysis</title>
          </caption>
          <table frame="hsides" rules="groups">
            <colgroup width="25%">
              <col/>
              <col/>
              <col/>
              <col/>
            </colgroup>
            <thead style="border-top: thin solid; border-bottom: thin solid; border-color: #000000">
              <tr>
                <th align="left" valign="middle"/>
                <th align="center" valign="middle">Alive without MV</th>
                <th align="center" valign="middle">Death or with MV</th>
                <th align="center" valign="middle">p-value</th>
              </tr>
            </thead>
            <tbody style="border-bottom: thin solid; border-color: #000000">
              <tr>
                <td align="left" valign="middle">N</td>
                <td align="center" valign="middle">139</td>
                <td align="center" valign="middle">44</td>
                <td align="center" valign="middle"/>
              </tr>
              <tr>
                <td align="left" valign="middle">Age (years)</td>
                <td align="center" valign="middle">64&#177;16</td>
                <td align="center" valign="middle">75.7&#177;16</td>
                <td align="center" valign="middle">&lt;0.001</td>
              </tr>
              <tr>
                <td align="left" valign="middle">Weight</td>
                <td align="center" valign="middle">82&#177;20</td>
                <td align="center" valign="middle">75.5&#177;14</td>
                <td align="center" valign="middle">0.116</td>
              </tr>
              <tr>
                <td align="left" valign="middle">Height</td>
                <td align="center" valign="middle">169.8&#177;14</td>
                <td align="center" valign="middle">168.6&#177;19</td>
                <td align="center" valign="middle">0.858</td>
              </tr>
              <tr>
                <td align="left" valign="middle">Men/Women</td>
                <td align="center" valign="middle">86/53</td>
                <td align="center" valign="middle">34/10</td>
                <td align="center" valign="middle">0.061</td>
              </tr>
              <tr>
                <td align="left" valign="middle">CAD (%)</td>
                <td align="center" valign="middle">14.4</td>
                <td align="center" valign="middle">34.1</td>
                <td align="center" valign="middle">0.004</td>
              </tr>
              <tr>
                <td align="left" valign="middle">Pulmonary disease (%)</td>
                <td align="center" valign="middle">14.4</td>
                <td align="center" valign="middle">20.5</td>
                <td align="center" valign="middle">0.337</td>
              </tr>
              <tr>
                <td align="left" valign="middle">Stroke (%)</td>
                <td align="center" valign="middle">3.6</td>
                <td align="center" valign="middle">6.8</td>
                <td align="center" valign="middle">0.401</td>
              </tr>
              <tr>
                <td align="left" valign="middle">Diabetes (%)</td>
                <td align="center" valign="middle">20.1</td>
                <td align="center" valign="middle">18.2</td>
                <td align="center" valign="middle">0.775</td>
              </tr>
              <tr>
                <td align="left" valign="middle">SAH (%)</td>
                <td align="center" valign="middle">51.1</td>
                <td align="center" valign="middle">61.4</td>
                <td align="center" valign="middle">0.233</td>
              </tr>
              <tr>
                <td align="left" valign="middle">Cancer (%)</td>
                <td align="center" valign="middle">8.6</td>
                <td align="center" valign="middle">13.6</td>
                <td align="center" valign="middle">0.311</td>
              </tr>
              <tr>
                <td align="left" valign="middle">CKD (%)</td>
                <td align="center" valign="middle">1.4</td>
                <td align="center" valign="middle">4.5</td>
                <td align="center" valign="middle">0.244</td>
              </tr>
              <tr>
                <td align="left" valign="middle">Time of symptom onset</td>
                <td align="center" valign="middle">6(3;8)</td>
                <td align="center" valign="middle">4(2.25;7)</td>
                <td align="center" valign="middle">0.14</td>
              </tr>
              <tr>
                <td align="left" valign="middle">SBP</td>
                <td align="center" valign="middle">127.9&#177;19</td>
                <td align="center" valign="middle">128.3&#177;21</td>
                <td align="center" valign="middle">0.911</td>
              </tr>
              <tr>
                <td align="left" valign="middle">HR</td>
                <td align="center" valign="middle">85.6&#177;17</td>
                <td align="center" valign="middle">87&#177;13</td>
                <td align="center" valign="middle">0.405</td>
              </tr>
              <tr>
                <td align="left" valign="middle">SatO<sub>2</sub></td>
                <td align="center" valign="middle">94.3&#177;5</td>
                <td align="center" valign="middle">91.7&#177;7</td>
                <td align="center" valign="middle">0.036</td>
              </tr>
              <tr>
                <td align="left" valign="middle">Leukocytes</td>
                <td align="center" valign="middle">6510(4715;8905)</td>
                <td align="center" valign="middle">7490(5680;10190)</td>
                <td align="center" valign="middle">0.083</td>
              </tr>
              <tr>
                <td align="left" valign="middle">Lymphocytes</td>
                <td align="center" valign="middle">1120(832.5;1470)</td>
                <td align="center" valign="middle">750(540;1190)</td>
                <td align="center" valign="middle">0.001</td>
              </tr>
              <tr>
                <td align="left" valign="middle">CRP</td>
                <td align="center" valign="middle">9.54(4.5325;16.9525)</td>
                <td align="center" valign="middle">13.64(7.04;24.74)</td>
                <td align="center" valign="middle">0.011</td>
              </tr>
              <tr>
                <td align="left" valign="middle">Creatinine</td>
                <td align="center" valign="middle">0.92(0.7575;1.0925)</td>
                <td align="center" valign="middle">1.3(1.01;1.91)</td>
                <td align="center" valign="middle">&lt;0.001</td>
              </tr>
              <tr>
                <td align="left" valign="middle">BNP</td>
                <td align="center" valign="middle">64.5(16.75;138)</td>
                <td align="center" valign="middle">198(45;619)</td>
                <td align="center" valign="middle">&lt;0.001</td>
              </tr>
              <tr>
                <td align="left" valign="middle">TnT</td>
                <td align="center" valign="middle">0.01(0.006;0.017)</td>
                <td align="center" valign="middle">0.041(0.012;0.072)</td>
                <td align="center" valign="middle">&lt;0.001</td>
              </tr>
              <tr>
                <td align="left" valign="middle">D-Dimer</td>
                <td align="center" valign="middle">741(452.75;1254.75)</td>
                <td align="center" valign="middle">1315(776;2200)</td>
                <td align="center" valign="middle">&lt;0.001</td>
              </tr>
              <tr>
                <td align="left" valign="middle">Ferritin</td>
                <td align="center" valign="middle">654(375.5;1204.75)</td>
                <td align="center" valign="middle">976(401.5;1543)</td>
                <td align="center" valign="middle">0.255</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn id="TFN5">
              <p>CAD: coronary artery disease; SAH: systemic arterial hypertension; CKD: chronic kidney disease; SBP: systolic blood pressure; HR: heart rate; SatO<sub>2</sub>: oxygen saturation; TnT: Troponin-T; MV: mechanical ventilation; ICU: intensive care unit; CRP: C-reactive protein.</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
        <table-wrap id="t6">
          <label>Table 3</label>
          <caption>
            <title>Cox multivariate analysis with 1000 bootstrapped</title>
          </caption>
          <table frame="hsides" rules="groups">
            <colgroup width="33%">
              <col/>
              <col/>
              <col/>
            </colgroup>
            <thead style="border-top: thin solid; border-bottom: thin solid; border-color: #000000">
              <tr>
                <th align="left" valign="middle">Variables</th>
                <th align="center" valign="middle">HR (95%CI)</th>
                <th align="center" valign="middle">HR (95%CI) bootstrapped</th>
              </tr>
            </thead>
            <tbody style="border-bottom: thin solid; border-color: #000000">
              <tr>
                <td align="left" valign="middle">Age (years)</td>
                <td align="center" valign="middle">1,02(0,99-1,04)</td>
                <td align="center" valign="middle">1,02(0,97-1,05)</td>
              </tr>
              <tr>
                <td align="left" valign="middle">CAD (%)</td>
                <td align="center" valign="middle">1,09(0,47-2,53)</td>
                <td align="center" valign="middle">1,09(0,36-2,84)</td>
              </tr>
              <tr>
                <td align="left" valign="middle">SatO<sub>2</sub> (%)</td>
                <td align="center" valign="middle">0,92(0,87-0,97)</td>
                <td align="center" valign="middle">0,92(0,85-1,01)</td>
              </tr>
              <tr>
                <td align="left" valign="middle">Lymphocytes (each 100 cells/mm<sup>3</sup>)</td>
                <td align="center" valign="middle">1,01(0,95-1,07)</td>
                <td align="center" valign="middle">1,01(0,87-1,06)</td>
              </tr>
              <tr>
                <td align="left" valign="middle">D-Dimer (500Ung/mL)</td>
                <td align="center" valign="middle">0,99(0,97-1,01)</td>
                <td align="center" valign="middle">0,99(0,92-1,03)</td>
              </tr>
              <tr>
                <td align="left" valign="middle">CRP (mg/dL)</td>
                <td align="center" valign="middle">1,04(1,01-1,08)</td>
                <td align="center" valign="middle">1,04(1,00-1,10)</td>
              </tr>
              <tr>
                <td align="left" valign="middle">Creatinine (mg/dL)</td>
                <td align="center" valign="middle">0,9(0,62-1,3)</td>
                <td align="center" valign="middle">0,9(0,55-2,17)</td>
              </tr>
              <tr>
                <td align="left" valign="middle">TnT (increment of 0.014ng/dL)</td>
                <td align="center" valign="middle">1,13(1,05-1,21)</td>
                <td align="center" valign="middle">1,12(1,03-1,47)</td>
              </tr>
              <tr>
                <td align="left" valign="middle">BNP (increment of 100pg/mL)</td>
                <td align="center" valign="middle">1,05(0,95-1,15)</td>
                <td align="center" valign="middle">1,05(0,81-1,23)</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn id="TFN6">
              <p>CAD: coronary artery disease; SatO<sub>2:</sub> oxygen saturation; CRP: C-reactive protein; BNP: B-Type Natriuretic Peptide; TnT: Troponin-T.</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
        <p>All mentioned biomarkers were included in the multivariate analysis and after the bootstrap analysis, only TnT and t-CRP were independently associated with the combined outcome.</p>
        <p><xref ref-type="fig" rid="f3">Figure 1</xref> illustrates the differences in the combined outcome per TnT quartile. Mortality more than doubles between Q1 and Q2; and between Q3 and Q4 and increases by more than 60% between Q2 and Q3. <xref ref-type="fig" rid="f4">Figure 2</xref> shows the probability of the event over time for each of the TnT quartiles. After 20 days of admission, the event-free survival rate for the first interquartil (Q1) of troponin T (TnT&#8804;0.006ng/dl) was 89.8% and for the last interquartil (Q4) (TnT&#8805;0.03ng/dl) was 15.2%.</p>
        <fig id="f3">
          <label>Figure 1</label>
          <caption>
            <title>Differences in combined outcome by Troponin quartile. MV: mechanical ventilation; TnT: Troponin-T.</title>
          </caption>
          <graphic xlink:href="1678-4170-abc-115-04-0660-00385-gf01-en.tif"/></fig>
        <fig id="f4">
          <label>Figure 2</label>
          <caption>
            <title>Probability of the combined outcome over time for each of the Troponin quartiles. TnT: Troponin-T.</title>
          </caption>
          <graphic xlink:href="1678-4170-abc-115-04-0660-00385-gf02-en.tif"/></fig>
      </sec>
      <sec sec-type="discussion">
        <title>Discussion</title>
        <p>This study reinforces the idea previosuly raised by other authors that the increase in TnT, in addition to being prevalent, is associated with the evolution to severe forms of COVID-19. To the best of our knowledge, this is the second study, the first in Brazil, to identify TnT as an independent predictor of a worse prognosis in patients with COVID-19. Shi et al., studying a Chinese cohort with a similar design, demonstrated that increased troponin levels at hospital admission increased the risk of death in patients with COVID-19 by 3.41-fold (95%CI, 1.62-716). In this cohort, patients with increased troponin levels had a higher rate of invasive mechanical ventilation compared to those who did not have an increase in troponin (18 of 82 [22.0%] <italic>vs</italic>. 14 of 334 [4.2%]; p &lt;0.001). Additionally, mortality was also higher in those with myocardial injury compared to those without injury (42 of 82 [51.2%] vs 15 of 334 [4.5%]; p &lt;0.001). However, the epidemic of other viral diseases such as dengue in China showed very different prevalence rates and prognosis of myocarditis than Brazil, and other countries.<xref ref-type="bibr" rid="B9"><sup>9</sup></xref><sup>,</sup><xref ref-type="bibr" rid="B10"><sup>10</sup></xref> Our study shows that this does not seem to be the case for COVID-19, where, in both western and eastern populations, the prevalence of myocardial injury is prevalent and associated with a worse prognosis. Among the unfavorable outcomes are heart failure, arrhythmias, mechanical ventilation and death.<xref ref-type="bibr" rid="B11"><sup>11</sup></xref></p>
        <p>Among the mechanisms proposed for myocardial injury caused by SARS-CoV-2, there is mainly the so-called &#8220;cytokine storm&#8221;, which is triggered by an imbalance in the cell responses of Type-1 and Type-2 T-helper lymphocytes. Interleukin-6 (IL-6) is a cytokine that increases as a result of this cell imbalance and it is an already identified marker of mortality. These cytokines attack the myocardium, causing elevation in troponin levels and cardiac dysfunction.<xref ref-type="bibr" rid="B12"><sup>12</sup></xref></p>
        <p>A meta-analysis of 4 Chinese studies involving 341 patients was recently published as correspondence.<xref ref-type="bibr" rid="B13"><sup>13</sup></xref> The prevalence of troponin elevation (above the 99<sup>th</sup> percentile) ranged from 8 to 12%, and its values were significantly higher in patients with more severe forms of COVID-19. Therefore, the monitoring of troponin levels may help to identify a subgroup with a greater chance of a worse clinical course.</p>
        <p>An important finding in the study by Guo et al.<xref ref-type="bibr" rid="B5"><sup>5</sup></xref> was that the increase in troponin levels was a stronger marker for mortality than the presence of previous cardiovascular disease (CVD). Patients with a history of CVD, but with normal troponin levels had lower mortality rates than those without a history of CVD, but who had increased troponin levels at hospital admission. Moreover, both TnT and NT-pro-BNP increased significantly during hospitalization in those who died, and this increase was not observed in those who survived.</p>
        <p>In our cohort, the association between troponin-T elevation and the combined outcome of death or MV was very well demonstrated, to the point that more than half of the patients in the last quartile of troponin (&gt; 0.03ng/dL) had an unfavorable evolution. This can constitute a practical way to identify those patients with the highest in-hospital risk of a worse clinical course on admission.</p>
        <p>As for the BNP/NT-pro-BNP, some studies also suggest that it is an important prognostic marker. Possible mechanisms for the increase in BNP levels in the presence of SARS-Cov-2 infection range from the previously described elevation secondary to inflammatory myocardial injury (cytokine storm), which results in cardiac dysfunction and increased ventricular filling pressures, to the direct injury to the cardiomyocyte by the virus through the angiotensin-converting enzyme-2 binding site and due to the myocardial hypoxemia induced by acute lung injury. The first study that showed that NT-Pro-BNP is a marker of mortality was published by Gao et al.,<xref ref-type="bibr" rid="B14"><sup>14</sup></xref> evaluating 54 patients with significant respiratory dysfunction (respiratory rate &#8805;30/min or Sat O<sub>2</sub>&#8804;93% or ratio of Partial Pressure Arterial Oxygen and Fraction of Inspired Oxygen &#8804; 300mmHg). Patients with NT-proBNP &gt;88.64 pg/mL showed a significantly lower cumulative survival during the 15-day follow-up than those with levels below this value. In our cohort, despite being a risk predictor in the univariate analysis, BNP was not an independent risk marker when the multivariate model was used. This fact can be explained by a collinearity effect between TnT and BNP, as a great correlation has been demonstrated between these markers in COVID-19.</p>
        <p>In addition to TnT, the titrated C-reactive protein was also independently associated with a worse prognosis in our cohort. In fact, other studies have already indicated the presence of a correlation between t-CRP and the severity of infection by Covid-19,<xref ref-type="bibr" rid="B15"><sup>15</sup></xref><sup>,</sup><xref ref-type="bibr" rid="B16"><sup>16</sup></xref> which supports the findings of our study.</p>
        <p>The present study showed an association between elevated TnT levels and the risk of death or need for MV. In contrast, the increase in BNP levels, although it was shown to be a risk factor for the combined outcome of MV or death in the univariate analysis, was not shown to be an independent predictor in our sample. In fact, a recent review article by Costa et al.<xref ref-type="bibr" rid="B17"><sup>17</sup></xref> established a flowchart for the cardiological approach of patients with COVID-19 and troponin was the only laboratory marker suggested to define admission in the intensive care unit, regardless of the presence of a history of cardiovascular disease.</p>
        <sec>
          <title>Limitations</title>
          <p>Electrocardiogram and echocardiogram data were not included in the analysis, as less than 70% of patients in the sample had these data available. The patient with COVID-19 is a major consumer of hospital resources, notably PPE, which is why these tests are only requested when strictly necessary and indicated. This was also the reason for not evaluating biomarkers as continuous variables over time. We did not use routine serial collections of these biomarkers. Every time a healthcare professional enters the isolation area for the collection of biomarkers or other tests, unless strictly necessary, results in increased costs, the use of PPE and a risk for the entire health team. Therefore, including them (ECG, ECHO and serial collections of biomarkers) would require a strategy for treating the missing data, which in our opinion would compromise the analysis.</p>
          <p>Another limitation is that with many predictors in the univariate analysis and a number of relatively small outcomes for the sample size, the bootstrap technique does not eliminate the possibility of overfitting.</p>
        </sec>
      </sec>
      <sec sec-type="conclusions">
        <title>Conclusion</title>
        <p>Troponin T, but not BNP, was an independent risk marker for mortality or need for invasive mechanical ventilation in patients hospitalized for COVID-19. These data further reinforce the use of this biomarker in the risk stratification of patients with COVID-19.</p>
      </sec>
    </body>
    <back>
      <fn-group>
        <fn fn-type="supported-by" id="fn3">
          <p>
            <bold>Sources of Funding</bold>
          </p>
          <p>There were no external funding sources for this study.</p>
        </fn>
        <fn fn-type="other" id="fn4">
          <p>
            <bold>Study Association</bold>
          </p>
          <p>This study is not associated with any thesis or dissertation work.</p>
        </fn>
      </fn-group>
    </back>
  </sub-article>
</article>
