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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">Dh8fk5dJ5FtRJNM3TqqLCSd</article-id>
      <article-id specific-use="scielo-v2" pub-id-type="publisher-id">S0066-782X2024000400301</article-id>
      <article-id pub-id-type="other">00301</article-id>
      <article-id pub-id-type="doi">10.36660/abc.20230245</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Artigo Original</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>O &#205;ndice de Imuno Inflama&#231;&#227;o Sist&#234;mica Prev&#234; Mortalidade Hospitalar em Pacientes Submetidos &#224; Cirurgia Card&#237;aca com Circula&#231;&#227;o Extracorp&#243;rea</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0002-8299-1359</contrib-id>
          <name>
            <surname>G&#252;nt&#252;rk</surname>
            <given-names>&#304;nayet</given-names>
          </name>
          <role>Concep&#231;&#227;o e desenho da pesquisa</role>
          <role>An&#225;lise e interpreta&#231;&#227;o dos dados</role>
          <role>An&#225;lise estat&#237;stica</role>
          <role>Reda&#231;&#227;o do manuscrito</role>
          <role>Revis&#227;o cr&#237;tica do manuscrito quanto ao conte&#250;do intelectual importante</role>
          <xref ref-type="aff" rid="aff1">
            <sup>1</sup>
          </xref>
          <xref ref-type="corresp" rid="c1"/>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Ozmen</surname>
            <given-names>Rifat</given-names>
          </name>
          <role>Concep&#231;&#227;o e desenho da pesquisa</role>
          <role>Obten&#231;&#227;o de dados</role>
          <role>Reda&#231;&#227;o do manuscrito</role>
          <role>Revis&#227;o cr&#237;tica do manuscrito quanto ao conte&#250;do intelectual importante</role>
          <xref ref-type="aff" rid="aff2">
            <sup>2</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Ozocak</surname>
            <given-names>Okan</given-names>
          </name>
          <role>Concep&#231;&#227;o e desenho da pesquisa</role>
          <role>Obten&#231;&#227;o de dados</role>
          <xref ref-type="aff" rid="aff2">
            <sup>2</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>G&#252;nt&#252;rk</surname>
            <given-names>Ertu&#287;rul Emre</given-names>
          </name>
          <role>Concep&#231;&#227;o e desenho da pesquisa</role>
          <role>An&#225;lise e interpreta&#231;&#227;o dos dados</role>
          <role>Reda&#231;&#227;o do manuscrito</role>
          <xref ref-type="aff" rid="aff3">
            <sup>3</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Dagli</surname>
            <given-names>Fatma</given-names>
          </name>
          <role>Concep&#231;&#227;o e desenho da pesquisa</role>
          <role>An&#225;lise estat&#237;stica</role>
          <xref ref-type="aff" rid="aff4">
            <sup>4</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Yazici</surname>
            <given-names>Cevat</given-names>
          </name>
          <role>Concep&#231;&#227;o e desenho da pesquisa</role>
          <role>An&#225;lise e interpreta&#231;&#227;o dos dados</role>
          <role>An&#225;lise estat&#237;stica</role>
          <role>Revis&#227;o cr&#237;tica do manuscrito quanto ao conte&#250;do intelectual importante</role>
          <xref ref-type="aff" rid="aff5">
            <sup>5</sup>
          </xref>
        </contrib>
        <aff id="aff1">
          <label>1</label>
          <institution content-type="orgname">Nigde Omer Halisdemir University</institution>
          <institution content-type="orgdiv1">Faculty of Health Sciences</institution>
          <addr-line>
            <named-content content-type="city">Nigde</named-content>
          </addr-line>
          <country country="TR">Turquia</country>
          <institution content-type="original">Nigde Omer Halisdemir University, Faculty of Health Sciences, Midwifery, Nigde &#8211; Turquia</institution>
        </aff>
        <aff id="aff2">
          <label>2</label>
          <institution content-type="orgname">Erciyes University</institution>
          <institution content-type="orgdiv1">Faculty of Medicine</institution>
          <addr-line>
            <named-content content-type="city">Kayseri</named-content>
          </addr-line>
          <country country="TR">Turquia</country>
          <institution content-type="original">Erciyes University, Faculty of Medicine, Cardiovasculary Surgery, Kayseri &#8211; Turquia</institution>
        </aff>
        <aff id="aff3">
          <label>3</label>
          <institution content-type="orgname">Acibadem Hospitals Group</institution>
          <addr-line>
            <named-content content-type="city">Istanbul</named-content>
          </addr-line>
          <country country="TR">Turquia</country>
          <institution content-type="original">Acibadem Hospitals Group &#8211; Cardiology, Istanbul &#8211; Turquia</institution>
        </aff>
        <aff id="aff4">
          <label>4</label>
          <institution content-type="orgname">Cetin Sen Science and Art Center</institution>
          <addr-line>
            <named-content content-type="city">Kayseri</named-content>
          </addr-line>
          <country country="TR">Turquia</country>
          <institution content-type="original">Cetin Sen Science and Art Center &#8211; Chemistry, Kayseri &#8211; Turquia</institution>
        </aff>
        <aff id="aff5">
          <label>5</label>
          <institution content-type="orgname">Erciyes University Faculty of Medicine</institution>
          <addr-line>
            <named-content content-type="city">Kayseri</named-content>
          </addr-line>
          <country country="TR">Turquia</country>
          <institution content-type="original">Erciyes University Faculty of Medicine, Clinical Biochemistry, Kayseri &#8211; Turquia</institution>
        </aff>
      </contrib-group>
      <author-notes>
        <corresp id="c1"><bold>Correspond&#234;ncia: &#304;nayet G&#252;nt&#252;rk &#8226;</bold> Nigde Omer Halisdemir University, Faculty of Health Sciences, Midwifery &#8211; A&#351;a&#287;i Kayaba&#351;i Mah. Atat&#252;rk Bulvari Derbent Yerle&#351;kesi Nigde Ni&#287;de <postal-code>51200</postal-code> &#8211; Turquia E-mail: <email>inayetgntrk@gmail.com</email>, <email>inayetgunturk@hotmail.com</email> </corresp>
        <fn fn-type="conflict">
          <p>
            <bold>Potencial conflito de interesse</bold>
          </p>
          <p>N&#227;o h&#225; conflito com o presente artigo</p>
        </fn>
        <fn fn-type="edited-by">
          <p>Editor respons&#225;vel pela revis&#227;o: Alexandre Colafranceschi</p>
        </fn>
      </author-notes>
      <pub-date date-type="pub" publication-format="electronic">
        <day>19</day>
        <month>04</month>
        <year>2024</year>
      </pub-date>
      <pub-date date-type="collection" publication-format="electronic">
        <year>2024</year>
      </pub-date>
      <volume>121</volume>
      <issue>4</issue>
      <elocation-id>e20230245</elocation-id>
      <history>
        <date date-type="received">
          <day>15</day>
          <month>05</month>
          <year>2023</year>
        </date>
        <date date-type="rev-recd">
          <day>04</day>
          <month>09</month>
          <year>2023</year>
        </date>
        <date date-type="accepted">
          <day>18</day>
          <month>01</month>
          <year>2024</year>
        </date>
      </history>
      <permissions>
        <license license-type="open-access" xlink:href="https://creativecommons.org/licenses/by/4.0/" xml:lang="en">
          <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>O &#237;ndice de imuno-inflama&#231;&#227;o sist&#234;mica (SII), um novo &#237;ndice inflamat&#243;rio calculado usando contagens de plaquetas, neutr&#243;filos e linf&#243;citos, demonstrou ser um fator de risco independente para a identifica&#231;&#227;o de doen&#231;a arterial coronariana de alto risco em pacientes submetidos a interven&#231;&#227;o coron&#225;ria percut&#226;nea e cardiovascular e cirurgia com circula&#231;&#227;o extracorp&#243;rea (CEC). A rela&#231;&#227;o entre as taxas de mortalidade relacionadas ao SII e &#224; CEC permanece obscura.</p>
        </sec>
        <sec>
          <title>Objetivo:</title>
          <p>Esta pesquisa foi desenhada para investigar o uso do SII para prever mortalidade hospitalar em pacientes submetidos &#224; cirurgia card&#237;aca com CEC.</p>
        </sec>
        <sec>
          <title>M&#233;todos:</title>
          <p>Quatrocentos e oitenta pacientes submetidos a procedimento card&#237;aco envolvendo CEC durante 3 anos foram coletados do banco de dados do hospital. Foram comparados os dados demogr&#225;ficos, comorbidades, perfis hematol&#243;gicos e bioqu&#237;mico e dados operat&#243;rios dos grupos. An&#225;lises m&#250;ltiplas de regress&#227;o log&#237;stica foram feitas para determinar preditores independentes de mortalidade. Os fatores progn&#243;sticos foram avaliados por an&#225;lise multivariada e os valores preditivos de SII, rela&#231;&#227;o neutr&#243;filo-linf&#243;cito (NLR) e raz&#227;o plaqueta-linf&#243;cito (PLR) para mortalidade foram comparados. Um valor de p &lt;0,05 foi considerado significativo.</p>
        </sec>
        <sec>
          <title>Resultados:</title>
          <p>Dos 480 pacientes, 78 desenvolveram mortalidade hospitalar ap&#243;s cirurgia card&#237;aca. O SII foi um preditor independente de mortalidade hospitalar (odds ratio: 1,003, intervalo de confian&#231;a de 95%: 1,001-1,005, p&lt;0,001). O valor de corte do SII foi &gt;811,93 com sensibilidade de 65% e especificidade de 65% (&#225;rea sob a curva: 0,690). Os valores preditivos de SII, PLR e NLR foram pr&#243;ximos entre si.</p>
        </sec>
        <sec>
          <title>Conclus&#227;o:</title>
          <p>Altos escores pr&#233;-operat&#243;rios do SII podem ser usados para determina&#231;&#227;o precoce de tratamentos apropriados, o que pode melhorar os resultados cir&#250;rgicos de cirurgia card&#237;aca no futuro.</p>
        </sec>
      </abstract>
      <abstract abstract-type="graphical">
        <p>
          <fig id="f1">
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            </alternatives>
          </fig>
        </p>
      </abstract>
      <kwd-group xml:lang="pt">
        <title>Palavras-chave:</title>
        <kwd>Circula&#231;&#227;o Extracorp&#243;rea</kwd>
        <kwd>Inflama&#231;&#227;o</kwd>
        <kwd>Mortalidade Hospitalar</kwd>
        <kwd>Cirurgia Tor&#225;cica</kwd>
      </kwd-group>
      <counts>
        <fig-count count="4"/>
        <table-count count="8"/>
        <equation-count count="0"/>
        <ref-count count="36"/>
      </counts>
    </article-meta>
  </front>
  <body>
    <sec sec-type="intro">
      <title>Introdu&#231;&#227;o</title>
      <p>As t&#233;cnicas de circula&#231;&#227;o extracorp&#243;rea (CEC), especialmente a CEC durante a cirurgia card&#237;aca, fornecem fluxo sangu&#237;neo e oxig&#234;nio aos tecidos e &#243;rg&#227;os.<sup><xref ref-type="bibr" rid="B1">1</xref></sup> A CEC tornou-se o padr&#227;o para muitos procedimentos card&#237;acos e seu avan&#231;o est&#225; possibilitando avan&#231;os na cirurgia cardiovascular. O procedimento &#233; considerado relativamente seguro.<sup><xref ref-type="bibr" rid="B2">2</xref></sup> A CEC, por outro lado, &#233; bem conhecida por iniciar uma cascata de rea&#231;&#245;es inflamat&#243;rias, e essa resposta inflamat&#243;ria tem s&#233;rias consequ&#234;ncias cl&#237;nicas.<sup><xref ref-type="bibr" rid="B2">2</xref>-<xref ref-type="bibr" rid="B4">4</xref></sup> Como resultado, investigar o papel das altera&#231;&#245;es inflamat&#243;rias no progn&#243;stico do paciente tornou-se um alvo de alta prioridade para o desenvolvimento de estrat&#233;gias terap&#234;uticas e preventivas.<sup><xref ref-type="bibr" rid="B5">5</xref></sup> Para esse fim, muitos mediadores, como n&#237;veis de citocinas pr&#243;-inflamat&#243;rias, como IL-6, TNF, sistema de coagula&#231;&#227;o/fibrinol&#237;tico e marcadores de ativa&#231;&#227;o do complemento foram investigados em rela&#231;&#227;o &#224; resposta inflamat&#243;ria relacionada &#224; CEC.<sup><xref ref-type="bibr" rid="B5">5</xref>,<xref ref-type="bibr" rid="B6">6</xref></sup></p>
      <p>Por&#233;m, quando s&#227;o considerados fatores como facilidade de mensura&#231;&#227;o e interpreta&#231;&#227;o, bem como baixo custo, tais par&#226;metros de hemograma continuam a ser amplamente utilizados. Embora um aumento no n&#250;mero de gl&#243;bulos brancos seja aceito como um marcador geral para a resposta inflamat&#243;ria desencadeada por v&#225;rios estimulantes, seu valor preditivo &#233; insuficiente.<sup><xref ref-type="bibr" rid="B7">7</xref></sup> Portanto, h&#225; uma &#234;nfase recente em &#237;ndices hematol&#243;gicos, como a rela&#231;&#227;o neutr&#243;filos-linf&#243;citos (RNL) e rela&#231;&#227;o plaquetas-linf&#243;citos (RPL), como marcadores de inflama&#231;&#227;o perioperat&#243;ria, considerando a proposi&#231;&#227;o de complica&#231;&#245;es p&#243;s-operat&#243;rias.<sup><xref ref-type="bibr" rid="B8">8</xref></sup></p>
      <p>O &#237;ndice de inflama&#231;&#227;o imunol&#243;gica sist&#234;mica (SII), um novo &#237;ndice inflamat&#243;rio calculado usando contagens de plaquetas, neutr&#243;filos e linf&#243;citos, demonstrou ser um forte marcador progn&#243;stico em uma variedade de c&#226;nceres.<sup><xref ref-type="bibr" rid="B9">9</xref>,<xref ref-type="bibr" rid="B10">10</xref></sup> Al&#233;m disso, foi demonstrado que o SII &#233; fator de risco independente para identifica&#231;&#227;o de doen&#231;a arterial coronariana de alto risco em pacientes submetidos &#224; interven&#231;&#227;o coronariana percut&#226;nea, fibrila&#231;&#227;o atrial p&#243;s-operat&#243;ria ap&#243;s cirurgia de revasculariza&#231;&#227;o do mioc&#225;rdio, fator progn&#243;stico para endocardite infecciosa e presen&#231;a de ectasia arterial coronariana isolada.<sup><xref ref-type="bibr" rid="B11">11</xref>-<xref ref-type="bibr" rid="B14">14</xref></sup> Por&#233;m, a rela&#231;&#227;o entre SII e complica&#231;&#245;es relacionadas &#224; CEC, especialmente em termos de taxa de mortalidade hospitalar, permanece obscura.</p>
      <p>Diante disso, o presente estudo procurou elucidar a associa&#231;&#227;o independente entre SII e a ocorr&#234;ncia de mortalidade em curto prazo em pacientes submetidos &#224; cirurgia card&#237;aca com CEC, a fim de fornecer um marcador preditivo para interven&#231;&#245;es terap&#234;uticas o mais precocemente poss&#237;vel.</p>
    </sec>
    <sec sec-type="methods">
      <title>M&#233;todos</title>
      <p>O estudo foi realizado e aprovado pelo Comit&#234; de &#201;tica Local (N&#250;mero de aprova&#231;&#227;o: 2021/608). Devido &#224; natureza retrospectiva do estudo, o consentimento informado individual por escrito foi dispensado.</p>
      <p>Foram coletados pacientes submetidos a procedimento card&#237;aco envolvendo CEC ao longo de 3 anos (de 2018 a 2021). N&#227;o houve sele&#231;&#227;o baseada na opera&#231;&#227;o usada. Dados pr&#233;-operat&#243;rios de 480 pacientes adultos foram obtidos do banco de dados do hospital. Os seguintes dados foram coletados para todos os sujeitos: dados demogr&#225;ficos (idade, sexo, tabagismo); presen&#231;a de comorbidades (doen&#231;a pulmonar obstrutiva cr&#244;nica, hipertens&#227;o arterial, dislipidemia, diabetes medicamentoso e insufici&#234;ncia renal cr&#244;nica); resultados laboratoriais pr&#233;-operat&#243;rios [hemograma completo (CBC), nitrog&#234;nio ureico no sangue (BUN), creatinina s&#233;rica (SCr), AST, ALT, colesterol total (C-Total), HDL-C, LDL-C, glucose,&#8230; etc.]; tipo de opera&#231;&#227;o cir&#250;rgica, CEC e dura&#231;&#227;o do pin&#231;amento a&#243;rtico. O SII foi definido como contagem de plaquetas x contagem de neutr&#243;filos/linf&#243;citos. Foram exclu&#237;dos pacientes submetidos a suporte de vida extracorp&#243;reo pr&#233;-operat&#243;rio, infec&#231;&#227;o ativa, condi&#231;&#245;es inflamat&#243;rias cr&#244;nicas, malignidade e uso de terapia imunossupressora, bem como pacientes com dados incompletos.</p>
      <p>Este estudo incluiu pacientes submetidos &#224; esternotomia mediana sob anestesia geral pela mesma equipe cir&#250;rgica. Todos os pacientes receberam terapia anticoagulante padr&#227;o com heparina n&#227;o fracionada intravenosa. Canula&#231;&#227;o a&#243;rtica padr&#227;o e venosa de duplo est&#225;gio foi aplicada aos pacientes que atingiram o valor efetivo de coagula&#231;&#227;o ativada ap&#243;s hepariniza&#231;&#227;o sist&#234;mica. A cirurgia eletiva isolada de revasculariza&#231;&#227;o do mioc&#225;rdio foi realizada induzindo parada card&#237;aca com cardioplegia sangu&#237;nea fria hipercal&#234;mica anter&#243;grada e CEC. Durante o procedimento cir&#250;rgico, os pacientes foram resfriados a 32-33 &#8304;C. A cardioplegia sangu&#237;nea fria foi administrada antegradamente a cada 20 minutos. A aplica&#231;&#227;o t&#243;pica de solu&#231;&#227;o salina isot&#244;nica fria tamb&#233;m foi utilizada nos pacientes nesse per&#237;odo. A art&#233;ria mam&#225;ria interna esquerda foi utilizada como enxerto arterial e a veia safena magna como enxerto venoso. Ap&#243;s a remo&#231;&#227;o do pin&#231;amento cruzado e o cora&#231;&#227;o come&#231;ar a bater, foram realizadas anastomoses distais sob o pin&#231;amento cruzado e anastomoses proximais sob o pin&#231;amento lateral em todos os pacientes.</p>
      <p>Os pacientes foram divididos em dois grupos com base na presen&#231;a de mortalidade operat&#243;ria, que inclu&#237;a qualquer morte, independentemente da causa, ocorrida dentro de dias de interna&#231;&#227;o ap&#243;s a cirurgia. As causas de morte, que inclu&#237;ram fal&#234;ncia de m&#250;ltiplos &#243;rg&#227;os, disfun&#231;&#227;o neurol&#243;gica permanente (acidente vascular cerebral/coma), insufici&#234;ncia circulat&#243;ria e choque t&#243;xico infeccioso, foram determinadas com base na documenta&#231;&#227;o da condi&#231;&#227;o cl&#237;nica em prontu&#225;rios m&#233;dicos.</p>
      <sec>
        <title>An&#225;lise estat&#237;stica</title>
        <p>A an&#225;lise estat&#237;stica foi realizada utilizando SPSS 23.0 (SPSS Company, Chicago, IL) para Windows. As vari&#225;veis cont&#237;nuas foram descritas por meio de mediana e intervalo interquartil devido &#224; falta de distribui&#231;&#227;o normal, testadas pelo teste de Shapiro-Wilk. Os testes U de Mann-Whitney foram utilizados para compara&#231;&#245;es entre os grupos de sobreviv&#234;ncia e n&#227;o sobreviv&#234;ncia. Os testes qui-quadrado ou exato de Fisher foram utilizados para comparar os dois grupos em vari&#225;veis categ&#243;ricas, que foram ent&#227;o resumidas por meio de contagens e porcentagens. A &#225;rea sob a curva (AUC) da curva caracter&#237;stica de opera&#231;&#227;o do receptor (ROC) foi calculada para determinar o valor de corte ideal de SII, NLR e PLR para prever a mortalidade. An&#225;lises de regress&#227;o log&#237;stica univariada e multivariada foram realizadas para identificar preditores independentes de ocorr&#234;ncia de mortalidade. Para an&#225;lise secund&#225;ria, para comparar os grupos de acordo com os valores de corte do SII, foi utilizado o teste U de Mann-Whitney. Um valor de p &lt;0,05 foi considerado significativo.</p>
      </sec>
    </sec>
    <sec sec-type="results">
      <title>Resultados</title>
      <p>Nos pacientes inclu&#237;dos no estudo, um total de 78 pacientes desenvolveram mortalidade hospitalar. As caracter&#237;sticas demogr&#225;ficas, perioperat&#243;rias e a an&#225;lise laboratorial pr&#233;-operat&#243;ria s&#227;o apresentadas na <xref ref-type="table" rid="t1">Tabela 1</xref>.</p>
      <table-wrap id="t1">
        <label>Tabela 1</label>
        <caption>
          <title>Compara&#231;&#245;es demogr&#225;ficas e an&#225;lises laboratoriais de rotina entre sobreviventes e n&#227;o sobreviventes</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 style="background-color:#76B4CF;">
              <th align="left" valign="middle">Caracter&#237;sticas</th>
              <th align="center" valign="middle">Sobreviventes (n=402)</th>
              <th align="center" valign="middle">N&#227;o sobreviventes (n=78)</th>
              <th align="center" valign="middle">Valor-p</th>
            </tr>
          </thead>
          <tbody style="border-bottom: thin solid; border-color: #000000">
            <tr>
              <td align="left" valign="top">Idade (anos)</td>
              <td align="center" valign="top">63 (55-68)</td>
              <td align="center" valign="top">67 (60-73)</td>
              <td align="center" valign="top">&lt;0,001</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td align="left" valign="top">G&#234;nero F/M, n (%)</td>
              <td align="center" valign="top">79 (19,7)/323 (80,3)</td>
              <td align="center" valign="top">28 (37,5)/50 (62,5)</td>
              <td align="center" valign="top">0,002</td>
            </tr>
            <tr>
              <td align="left" valign="top">Perman&#234;ncia Hospitalar (Dia)</td>
              <td align="center" valign="top">14,0 (10,0-17,5)</td>
              <td align="center" valign="top">9,0 (4,5-15,0)</td>
              <td align="center" valign="top">&lt;0,001</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td align="left" valign="top">Perman&#234;ncia na Unidade de Terapia Intensiva (Dia)</td>
              <td align="center" valign="top">4,0 (3,0-5,0)</td>
              <td align="center" valign="top">3,0 (1,0-6,0)</td>
              <td align="center" valign="top">&lt;0,001</td>
            </tr>
            <tr>
              <td align="left" valign="top">Perman&#234;ncia p&#243;s-operat&#243;ria (dia)</td>
              <td align="center" valign="top">7,0 (6,0-10,0)</td>
              <td align="center" valign="top">2,0 (0,0-6,5)</td>
              <td align="center" valign="top">&lt;0,001</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td align="left" valign="top">Dura&#231;&#227;o do desvio cardiopulmonar (m&#237;n.)</td>
              <td align="center" valign="top">100 (85-145)</td>
              <td align="center" valign="top">105 (80-140)</td>
              <td align="center" valign="top">0,637</td>
            </tr>
            <tr>
              <td align="left" valign="top">Dura&#231;&#227;o do grampo cruzado (min.)</td>
              <td align="center" valign="top">50 (45-65)</td>
              <td align="center" valign="top">55 (45-80)</td>
              <td align="center" valign="top">0,328</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td align="left" colspan="4" valign="top">
                <bold>Par&#226;metros laboratoriais</bold>
              </td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td align="left" valign="top">Hemoglobina, g/dL</td>
              <td align="center" valign="top">14h30 (13h00-15h40)</td>
              <td align="center" valign="top">13,45(12,47-14,62)</td>
              <td align="center" valign="top">0,005</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td align="left" valign="top">WBC, 109/L</td>
              <td align="center" valign="top">8,93 (7,15-11,09)</td>
              <td align="center" valign="top">8,63 (7,06-11,51)</td>
              <td align="center" valign="top">0,907</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td align="left" valign="top">Neutr&#243;filo, 109/L</td>
              <td align="center" valign="top">5,61 (4,40-6,96)</td>
              <td align="center" valign="top">6,28 (5,26-7,79)</td>
              <td align="center" valign="top">0,069</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td align="left" valign="top">Linf&#243;cito, 109/L</td>
              <td align="center" valign="top">2,11 (1,62-2,74)</td>
              <td align="center" valign="top">1,83 (1,28-2,37)</td>
              <td align="center" valign="top">0,001</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td align="left" valign="top">Propor&#231;&#227;o de linf&#243;citos neutr&#243;filos</td>
              <td align="center" valign="top">2,62 (1,95-3,51)</td>
              <td align="center" valign="top">3,50 (2,54-5,00)</td>
              <td align="center" valign="top">&lt;0,001</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td align="left" valign="top">Plaquetas, 109/L</td>
              <td align="center" valign="top">251,50 (215,00-292,50)</td>
              <td align="center" valign="top">261,00 (235,00-299,25)</td>
              <td align="center" valign="top">0,058</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td align="left" valign="top">Propor&#231;&#227;o de linf&#243;citos plaquet&#225;rios</td>
              <td align="center" valign="top">119,56 (90,03-156,18)</td>
              <td align="center" valign="top">158,43 (112,90-210,53)</td>
              <td align="center" valign="top">&lt;0,001</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td align="left" valign="top">&#205;ndice de Imuno-Inflama&#231;&#227;o Sist&#234;mica (x109/L)</td>
              <td align="center" valign="top">654,25 (465,49-936,46)</td>
              <td align="center" valign="top">948,33(642,60-1355,60)</td>
              <td align="center" valign="top">&lt;0,001</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td align="left" valign="top">Ureia, mg/dL</td>
              <td align="center" valign="top">17h85 (13h97-22h30)</td>
              <td align="center" valign="top">19h50 (14,67-24,82)</td>
              <td align="center" valign="top">0,105</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td align="left" valign="top">SCr, mg/dL</td>
              <td align="center" valign="top">0,92 (0,80-1,10)</td>
              <td align="center" valign="top">1,00 (0,82-1,27)</td>
              <td align="center" valign="top">0,042</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td align="left" valign="top">eGFR</td>
              <td align="center" valign="top">84,49 (68,20-96,12)</td>
              <td align="center" valign="top">77,93 (55,83-90,63)</td>
              <td align="center" valign="top">&lt;0,001</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td align="left" valign="top">AST (U/L)</td>
              <td align="center" valign="top">21,9 (17,65-32,07)</td>
              <td align="center" valign="top">23h00 (18h00-34h00)</td>
              <td align="center" valign="top">0,493</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td align="left" valign="top">ALT (U/L)</td>
              <td align="center" valign="top">21h00 (15h00-28h00)</td>
              <td align="center" valign="top">19,3 (13,60-28,00)</td>
              <td align="center" valign="top">0,244</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td align="left" valign="top">Glicose, mg/dL</td>
              <td align="center" valign="top">127 (104-177)</td>
              <td align="center" valign="top">136 (112-195)</td>
              <td align="center" valign="top">0,082</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td align="left" valign="top">Triglicer&#237;deo, mg/dL</td>
              <td align="center" valign="top">178,00(164,00-213,00)</td>
              <td align="center" valign="top">134,50 (107,75-171,25)</td>
              <td align="center" valign="top">0,002</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td align="left" valign="top">Colesterol total, mg/dL</td>
              <td align="center" valign="top">186,00 (157,00-224,70)</td>
              <td align="center" valign="top">175,00 (158,25-191,00)</td>
              <td align="center" valign="top">0,024</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td align="left" valign="top">Colesterol HDL, mg/dL</td>
              <td align="center" valign="top">38,05 (35,07-43,92)</td>
              <td align="center" valign="top">40,55 (34,75-45,00)</td>
              <td align="center" valign="top">0,141</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td align="left" valign="top">Colesterol LDL, mg/dL</td>
              <td align="center" valign="top">105,00 (96,17-127,65)</td>
              <td align="center" valign="top">103,74(86,55-121,72)</td>
              <td align="center" valign="top">0,224</td>
            </tr>
            <tr>
              <td align="left" colspan="4" valign="top">
                <bold>Comorbidades, n (%)</bold>
              </td>
            </tr>
            <tr>
              <td align="left" valign="top">Hipertens&#227;o</td>
              <td align="center" valign="top">128 (34,1)</td>
              <td align="center" valign="top">30 (53,6)</td>
              <td align="center" valign="top">0,007</td>
            </tr>
            <tr>
              <td align="left" valign="top">Doen&#231;a renal cr&#244;nica</td>
              <td align="center" valign="top">9 (2,4)</td>
              <td align="center" valign="top">6 (10,7)</td>
              <td align="center" valign="top">0,007</td>
            </tr>
            <tr>
              <td align="left" valign="top">Hiperlipidemia</td>
              <td align="center" valign="top">6 (1,6)</td>
              <td align="center" valign="top">1 (1,8)</td>
              <td align="center" valign="top">0,999</td>
            </tr>
            <tr>
              <td align="left" valign="top">Diabetes Mellitus</td>
              <td align="center" valign="top">107 (28,5)</td>
              <td align="center" valign="top">20 (39,7)</td>
              <td align="center" valign="top">0,275</td>
            </tr>
            <tr>
              <td align="left" valign="top">Doen&#231;a pulmonar obstrutiva cr&#244;nica</td>
              <td align="center" valign="top">14 (3,7)</td>
              <td align="center" valign="top">4 (7,1)</td>
              <td align="center" valign="top">0,272</td>
            </tr>
            <tr>
              <td align="left" valign="top">Tabagismo</td>
              <td align="center" valign="top">6 (1,6)</td>
              <td align="center" valign="top">1 (1,8)</td>
              <td align="center" valign="top">0,999</td>
            </tr>
          </tbody>
        </table>
        <table-wrap-foot>
          <fn id="TFN1">
            <p>p: Diferen&#231;as estat&#237;sticas entre sobreviventes e n&#227;o sobreviventes. Os dados foram expressos como mediana e intervalo interquartil; %50 (%25-%75). As vari&#225;veis categ&#243;ricas s&#227;o expressas em porcentagens.</p>
          </fn>
        </table-wrap-foot>
      </table-wrap>
      <p>Na an&#225;lise univariada, as seguintes vari&#225;veis pr&#233;-operat&#243;rias foram consideradas preditoras significativas de mortalidade: sexo, idade, SII, NLR, PLR, hemoglobina, SCr, eGFR, triglicer&#237;deos, C-total, hipertens&#227;o e doen&#231;a renal cr&#244;nica (<xref ref-type="table" rid="t2">Tabela 2</xref>). Uma an&#225;lise multivariada dos mesmos par&#226;metros revelou que sexo, idade e SII, SCr, triglicer&#237;deos e hipertens&#227;o permaneceram preditores independentes de mortalidade hospitalar (<xref ref-type="table" rid="t2">Tabela 2</xref>).</p>
      <table-wrap id="t2">
        <label>Tabela 2</label>
        <caption>
          <title>An&#225;lise de regress&#227;o log&#237;stica univariada e multivariada dos fatores de risco pr&#233;-operat&#243;rios para predi&#231;&#227;o de mortalidade</title>
        </caption>
        <table frame="hsides" rules="groups">
          <colgroup width="11%">
            <col/>
            <col/>
            <col/>
            <col/>
            <col/>
            <col/>
            <col/>
            <col/>
            <col/>
          </colgroup>
          <thead style="border-top: thin solid; border-bottom: thin solid; border-color: #000000">
            <tr style="background-color:#76B4CF;">
              <th align="left" rowspan="3" valign="middle">Vari&#225;veis</th>
              <th align="center" colspan="4" style="border-bottom: thin solid; border-color: #000000" valign="middle">An&#225;lise Univariada</th>
              <th align="center" colspan="4" style="border-bottom: thin solid; border-color: #000000" valign="middle">An&#225;lise multivariada</th>
            </tr>
            <tr style="background-color:#76B4CF;">
              <th align="center" rowspan="2" valign="middle">OR</th>
              <th align="center" colspan="2" style="border-bottom: thin solid; border-color: #000000" valign="middle">IC 95%</th>
              <th align="center" rowspan="2" valign="middle">Valor-p</th>
              <th align="center" rowspan="2" valign="middle">OR</th>
              <th align="center" colspan="2" style="border-bottom: thin solid; border-color: #000000" valign="middle">IC 95%</th>
              <th align="center" rowspan="2" valign="middle">Valor-p</th>
            </tr>
            <tr style="background-color:#76B4CF;">
              <th align="center" valign="middle">Inferior</th>
              <th align="center" valign="middle">Superior</th>
              <th align="center" valign="middle">Inferior</th>
              <th align="center" valign="middle">Superior</th>
            </tr>
          </thead>
          <tbody style="border-bottom: thin solid; border-color: #000000">
            <tr>
              <td align="left" valign="top">G&#234;nero</td>
              <td align="center" valign="top">0,438</td>
              <td align="center" valign="top">0,259</td>
              <td align="center" valign="top">0,740</td>
              <td align="center" valign="top">0,002</td>
              <td align="center" valign="top">2.129</td>
              <td align="center" valign="top">1.204</td>
              <td align="center" valign="top">3.766</td>
              <td align="center" valign="top">0,009</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td align="left" valign="top">Idade</td>
              <td align="center" valign="top">1,043</td>
              <td align="center" valign="top">1,016</td>
              <td align="center" valign="top">1,071</td>
              <td align="center" valign="top">0,002</td>
              <td align="center" valign="top">1,029</td>
              <td align="center" valign="top">1,001</td>
              <td align="center" valign="top">1,058</td>
              <td align="center" valign="top">0,044</td>
            </tr>
            <tr>
              <td align="left" valign="top">SII</td>
              <td align="center" valign="top">1,002</td>
              <td align="center" valign="top">1,001</td>
              <td align="center" valign="top">1,003</td>
              <td align="center" valign="top">&lt;0,001</td>
              <td align="center" valign="top">1,003</td>
              <td align="center" valign="top">1,001</td>
              <td align="center" valign="top">1,005</td>
              <td align="center" valign="top">&lt;0,001</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td align="left" valign="top">NLR</td>
              <td align="center" valign="top">1,176</td>
              <td align="center" valign="top">1,084</td>
              <td align="center" valign="top">1,275</td>
              <td align="center" valign="top">&lt;0,001</td>
              <td align="center" valign="top"/>
              <td align="center" valign="top"/>
              <td align="center" valign="top"/>
              <td align="center" valign="top"/>
            </tr>
            <tr>
              <td align="left" valign="top">PLR</td>
              <td align="center" valign="top">1,005</td>
              <td align="center" valign="top">1,002</td>
              <td align="center" valign="top">1,008</td>
              <td align="center" valign="top">&lt;0,001</td>
              <td align="center" valign="top"/>
              <td align="center" valign="top"/>
              <td align="center" valign="top"/>
              <td align="center" valign="top"/>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td align="left" valign="top">Hemoglobina</td>
              <td align="center" valign="top">0,853</td>
              <td align="center" valign="top">0,753</td>
              <td align="center" valign="top">0,965</td>
              <td align="center" valign="top">0,012</td>
              <td align="center" valign="top"/>
              <td align="center" valign="top"/>
              <td align="center" valign="top"/>
              <td align="center" valign="top"/>
            </tr>
            <tr>
              <td align="left" valign="top">SCr</td>
              <td align="center" valign="top">1,356</td>
              <td align="center" valign="top">1,069</td>
              <td align="center" valign="top">1,721</td>
              <td align="center" valign="top">0,012</td>
              <td align="center" valign="top">1,523</td>
              <td align="center" valign="top">1,173</td>
              <td align="center" valign="top">1,977</td>
              <td align="center" valign="top">0,002</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td align="left" valign="top">eGFR</td>
              <td align="center" valign="top">0,982</td>
              <td align="center" valign="top">0,972</td>
              <td align="center" valign="top">0,992</td>
              <td align="center" valign="top">0,001</td>
              <td align="center" valign="top"/>
              <td align="center" valign="top"/>
              <td align="center" valign="top"/>
              <td align="center" valign="top"/>
            </tr>
            <tr>
              <td align="left" valign="top">Triglicer&#237;deo</td>
              <td align="center" valign="top">0,996</td>
              <td align="center" valign="top">0,993</td>
              <td align="center" valign="top">0,999</td>
              <td align="center" valign="top">0,021</td>
              <td align="center" valign="top">0,995</td>
              <td align="center" valign="top">0,991</td>
              <td align="center" valign="top">0,998</td>
              <td align="center" valign="top">0,005</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td align="left" valign="top">Colesterol total</td>
              <td align="center" valign="top">0,889</td>
              <td align="center" valign="top">0,886</td>
              <td align="center" valign="top">0,892</td>
              <td align="center" valign="top">0,035</td>
              <td align="center" valign="top"/>
              <td align="center" valign="top"/>
              <td align="center" valign="top"/>
              <td align="center" valign="top"/>
            </tr>
            <tr>
              <td align="left" valign="top">Hipertens&#227;o</td>
              <td align="center" valign="top">0,491</td>
              <td align="center" valign="top">0,301</td>
              <td align="center" valign="top">0,801</td>
              <td align="center" valign="top">0,004</td>
              <td align="center" valign="top">1,878</td>
              <td align="center" valign="top">1,106</td>
              <td align="center" valign="top">3,189</td>
              <td align="center" valign="top">0,020</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td align="left" valign="top">Doen&#231;a renal cr&#244;nica</td>
              <td align="center" valign="top">0,285</td>
              <td align="center" valign="top">0,107</td>
              <td align="center" valign="top">0,761</td>
              <td align="center" valign="top">0,012</td>
              <td align="center" valign="top"/>
              <td align="center" valign="top"/>
              <td align="center" valign="top"/>
              <td align="center" valign="top"/>
            </tr>
          </tbody>
        </table>
        <table-wrap-foot>
          <fn id="TFN2">
            <p>IC: intervalo de confian&#231;a; RNL: raz&#227;o de linf&#243;citos neutr&#243;filos; RPL: propor&#231;&#227;o de linf&#243;citos plaquet&#225;rios; SII: &#237;ndice de imuno-inflama&#231;&#227;o sist&#234;mica.</p>
          </fn>
        </table-wrap-foot>
      </table-wrap>
      <p>Pela an&#225;lise das caracter&#237;sticas operacionais do receptor, NLR, PLR e SII previram mortalidade em pacientes; a &#225;rea sob a curva de 0,664 (IC 95% 0,599-0,729); 0,655 (IC 95% 0,587-0,723) e 0,690 (IC 95% 0,630-0,751), respectivamente (<xref ref-type="table" rid="t3">Tabela 3</xref>, <xref ref-type="fig" rid="f2">Figura 1</xref>). Os valores de corte para NLR, PLR e SII para prever mortalidade hospitalar foram 3,31 (58% de sensibilidade, 71% de especificidade), 132,76 (65% de sensibilidade, 60% de especificidade) e 811,93 (65% de sensibilidade, 65% de especificidade), respectivamente (<xref ref-type="table" rid="t3">Tabela 3</xref>).</p>
      <table-wrap id="t3">
        <label>Tabela 3</label>
        <caption>
          <title>Valores de corte apropriados de NLR, PLR e SII</title>
        </caption>
        <table frame="hsides" rules="groups">
          <colgroup width="12%">
            <col/>
            <col/>
            <col/>
            <col/>
            <col/>
            <col/>
            <col/>
            <col/>
          </colgroup>
          <thead style="border-top: thin solid; border-bottom: thin solid; border-color: #000000">
            <tr style="background-color:#76B4CF;">
              <th align="left" rowspan="2" valign="middle"/>
              <th align="center" rowspan="2" valign="middle">AUC</th>
              <th align="center" rowspan="2" valign="middle">Valor-p</th>
              <th align="center" colspan="2" style="border-bottom: thin solid; border-color: #000000" valign="middle">% 95 IC</th>
              <th align="center" rowspan="2" valign="middle">Valor de corte</th>
              <th align="center" rowspan="2" valign="middle">Sensibilidade</th>
              <th align="center" rowspan="2" valign="middle">Especificidade</th>
            </tr>
            <tr style="background-color:#76B4CF;">
              <th align="center" valign="middle">Inferior</th>
              <th align="center" valign="middle">Superior</th>
            </tr>
          </thead>
          <tbody style="border-bottom: thin solid; border-color: #000000">
            <tr style="background-color:#C7DFEC">
              <td align="left" valign="top">NLR</td>
              <td align="center" valign="top">0,664</td>
              <td align="center" valign="top">&lt;0,001</td>
              <td align="center" valign="top">0,599</td>
              <td align="center" valign="top">0,729</td>
              <td align="center" valign="top">3.31</td>
              <td align="center" valign="top">0,577</td>
              <td align="center" valign="top">0,711</td>
            </tr>
            <tr>
              <td align="left" valign="top">PLR</td>
              <td align="center" valign="top">0,655</td>
              <td align="center" valign="top">&lt;0,001</td>
              <td align="center" valign="top">0,587</td>
              <td align="center" valign="top">0,723</td>
              <td align="center" valign="top">132,76</td>
              <td align="center" valign="top">0,654</td>
              <td align="center" valign="top">0,595</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td align="left" valign="top">SII</td>
              <td align="center" valign="top">0,690</td>
              <td align="center" valign="top">&lt;0,001</td>
              <td align="center" valign="top">0,630</td>
              <td align="center" valign="top">0,751</td>
              <td align="center" valign="top">811.93</td>
              <td align="center" valign="top">0,654</td>
              <td align="center" valign="top">0,652</td>
            </tr>
          </tbody>
        </table>
        <table-wrap-foot>
          <fn id="TFN3">
            <p>AUC: &#225;rea sob a Curva; IC: intervalo de confian&#231;a; RNL: raz&#227;o de linf&#243;citos neutr&#243;filos; RPL: propor&#231;&#227;o de linf&#243;citos plaquet&#225;rios; SII: &#205;ndice de Imuno-inflama&#231;&#227;o Sist&#234;mica.</p>
          </fn>
        </table-wrap-foot>
      </table-wrap>
      <fig id="f2">
        <label>Figura 1</label>
        <caption>
          <title>An&#225;lise da curva operacional do receptor de NLR, PLR e SII.</title>
        </caption>
        <graphic xlink:href="1678-4170-abc-121-04-e20230245-30245-gf01.tif"/></fig>
      <p>Em rela&#231;&#227;o aos desfechos secund&#225;rios, o tempo de interna&#231;&#227;o hospitalar e p&#243;s-operat&#243;ria foi significativamente maior para pacientes com n&#237;veis elevados de SII. No entanto, os tempos de perman&#234;ncia na unidade de terapia intensiva foram semelhantes entre os grupos (<xref ref-type="table" rid="t4">Tabela 4</xref>). A <xref ref-type="fig" rid="f1">Figura Central</xref> destaca os principais resultados do estudo.</p>
      <table-wrap id="t4">
        <label>Tabela 4</label>
        <caption>
          <title>Resultados p&#243;s-operat&#243;rios para grupos SII</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 style="background-color:#76B4CF;">
              <th align="left" valign="middle">Caracter&#237;sticas</th>
              <th align="center" valign="middle">SII &#8805; 811,93 <break/>(n=173)</th>
              <th align="center" valign="middle">SII &lt; 811,93 <break/>(n=307)</th>
              <th align="center" valign="middle">Valor-p</th>
            </tr>
          </thead>
          <tbody style="border-bottom: thin solid; border-color: #000000">
            <tr>
              <td align="left" valign="top">Perman&#234;ncia Hospitalar (Dia)</td>
              <td align="center" valign="top">14,0 (10,0-17,0)</td>
              <td align="center" valign="top">11,0 (7,0-17,0)</td>
              <td align="center" valign="top">0,001</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td align="left" valign="top">Perman&#234;ncia p&#243;s-operat&#243;ria (dia)</td>
              <td align="center" valign="top">7,0 (6,0-10,0)</td>
              <td align="center" valign="top">2,0 (5,0-7,75)</td>
              <td align="center" valign="top">0,022</td>
            </tr>
            <tr>
              <td align="left" valign="top">Perman&#234;ncia na Unidade de Terapia Intensiva (Dia)</td>
              <td align="center" valign="top">4,0 (3,0-5,0)</td>
              <td align="center" valign="top">3,0 (2,0-5,0)</td>
              <td align="center" valign="top">0,114</td>
            </tr>
          </tbody>
        </table>
        <table-wrap-foot>
          <fn id="TFN4">
            <p>p: Diferen&#231;as estat&#237;sticas entre grupos. Os dados foram expressos como mediana e intervalo interquartil; %50 (%25-%75).</p>
          </fn>
        </table-wrap-foot>
      </table-wrap>
    </sec>
    <sec sec-type="discussion">
      <title>Discuss&#227;o</title>
      <p>Na an&#225;lise univariada, o presente estudo demonstrou que SII, hemoglobina, NLR, PLR, SCr, eGFR, triglicer&#237;deos e Total-C poderiam ser usados como par&#226;metros de rotina para prever mortalidade hospitalar em pacientes submetidos &#224; cirurgia card&#237;aca por CEC, juntamente com outros par&#226;metros cl&#237;nicos e demogr&#225;ficos (idade, sexo, doen&#231;a renal cr&#244;nica e hipertens&#227;o). No entanto, o SII surgiu como par&#226;metro hematol&#243;gico, e a SCr e os triglicer&#237;deos como par&#226;metros bioqu&#237;micos, para prever de forma independente a mortalidade hospitalar ap&#243;s cirurgia de CEC.</p>
      <p>Por diversos motivos, como contato do sangue com a superf&#237;cie extracorp&#243;rea, trauma cir&#250;rgico, endotoxemia e les&#227;o de isquemia-reperfus&#227;o, a CEC resulta na libera&#231;&#227;o de citocinas pr&#243;-inflamat&#243;rias, que podem se transformar em cascata, levando a uma grave resposta imunoinflamat&#243;ria no organismo. Acredita-se que a principal causa de morbidade e mortalidade p&#243;s-operat&#243;ria seja a resposta do paciente.<sup><xref ref-type="bibr" rid="B1">1</xref>,<xref ref-type="bibr" rid="B15">15</xref></sup> Como o desenvolvimento de estrat&#233;gias preventivas nesta &#225;rea requer a identifica&#231;&#227;o de fatores de risco, principalmente durante o per&#237;odo pr&#233;-operat&#243;rio, muitos estudos t&#234;m se concentrado nessa dire&#231;&#227;o.</p>
      <p>Os &#237;ndices, calculados com f&#243;rmulas matem&#225;ticas simples, entre c&#233;lulas de um hemograma completo, que muitas vezes &#233; realizado rotineiramente, s&#227;o considerados evid&#234;ncias valiosas para obter mais informa&#231;&#245;es sobre a inflama&#231;&#227;o sist&#234;mica. No entanto, os par&#226;metros leucocit&#225;rios individuais s&#227;o suscet&#237;veis a altera&#231;&#245;es por condi&#231;&#245;es externas (desidrata&#231;&#227;o, hemodilui&#231;&#227;o, etc.), e os &#237;ndices do tipo NLR s&#227;o relativamente mais est&#225;veis.<sup><xref ref-type="bibr" rid="B16">16</xref></sup> Al&#233;m disso, como esses &#237;ndices permitem a avalia&#231;&#227;o conjunta de diferentes vias (imunes e inflamat&#243;rias), eles revelam resultados mais significativos do que sozinhos.<sup><xref ref-type="bibr" rid="B17">17</xref>-<xref ref-type="bibr" rid="B19">19</xref></sup> A previs&#227;o de risco pela NLR e PLR tem sido estudada h&#225; muitos anos em muitos campos da medicina.<sup><xref ref-type="bibr" rid="B20">20</xref>-<xref ref-type="bibr" rid="B22">22</xref></sup> Al&#233;m disso, especialmente nos &#250;ltimos anos, tanto a PLR quanto a NLR foram identificadas como marcadores significativos. para resultados p&#243;s-operat&#243;rios de cirurgia.<sup><xref ref-type="bibr" rid="B17">17</xref>,<xref ref-type="bibr" rid="B18">18</xref>,<xref ref-type="bibr" rid="B23">23</xref>,<xref ref-type="bibr" rid="B24">24</xref></sup> Em uma meta-an&#225;lise de 3.108 pacientes, Tan et al. mostraram que altos n&#237;veis de NLR pr&#233;-operat&#243;rios estavam associados &#224; mortalidade e morbidade por todas as causas.<sup><xref ref-type="bibr" rid="B23">23</xref></sup> Outro estudo realizado por Parlar e &#350;a&#351;k&#305;n relatou que PLR e NLR, medidos tanto no pr&#233; quanto no p&#243;s-operat&#243;rio, estavam associados &#224; les&#227;o renal aguda (LRA) p&#243;s-operat&#243;ria, e eles relataram que os valores medidos no p&#243;s-operat&#243;rio foram mais preditivos.<sup><xref ref-type="bibr" rid="B25">25</xref></sup> Em contrapartida, Navani et al. e He et al., que investigaram a rela&#231;&#227;o entre RPL e o desenvolvimento de fibrila&#231;&#227;o atrial p&#243;s-operat&#243;ria e RNL e LRA, respectivamente, n&#227;o conseguiram mostrar uma rela&#231;&#227;o significativa.<sup><xref ref-type="bibr" rid="B26">26</xref>,<xref ref-type="bibr" rid="B27">27</xref></sup> Esses resultados conflitantes podem estar associados a diferen&#231;as na metodologia estat&#237;stica e na popula&#231;&#227;o do estudo. Outra raz&#227;o para a n&#227;o padroniza&#231;&#227;o das medidas de resultados utilizadas tamb&#233;m pode ser considerada.<sup><xref ref-type="bibr" rid="B28">28</xref></sup></p>
      <p>At&#233; onde sabemos, esta &#233; a primeira vez na literatura que um novo &#237;ndice, SII, usado para desfechos cl&#237;nicos para diversos tipos de c&#226;ncer, avaliou a mortalidade hospitalar em pacientes que usaram CEC al&#233;m de RNL e RPL. O trabalho de Selcuk et al. &#233; o mais semelhante ao presente estudo.<sup><xref ref-type="bibr" rid="B29">29</xref></sup> No entanto, diferentemente do nosso estudo, que analisou a mortalidade intra-hospitalar, eles examinaram as rela&#231;&#245;es entre SII, NLR e PLR pr&#233;-operat&#243;rios e o desenvolvimento de fibrila&#231;&#227;o atrial p&#243;s-operat&#243;ria (FAPO). Eles descobriram que, semelhantemente ao presente estudo, todos os tr&#234;s &#237;ndices foram significativos nas an&#225;lises univariadas, mas apenas o SII poderia ser considerado um fator de risco independente nas an&#225;lises multivariadas. No entanto, mostraram maior valor preditivo para SII (AUC: 0,7107) para FAPO em compara&#231;&#227;o com NLR e PLR (AUC: 0,6740 e 0,6426, respectivamente). Essa diferen&#231;a pode ser explicada pelo fato de que os fatores que podem causar a mortalidade e sua patog&#234;nese est&#227;o distribu&#237;dos por uma faixa mais ampla. Isto tamb&#233;m foi consistente com o argumento de Navani et al. em rela&#231;&#227;o &#224; PLR inalterada em pacientes submetidos &#224; cirurgia card&#237;aca, uma vez que o efeito das plaquetas na patog&#234;nese da FAPO n&#227;o &#233; pronunciado.<sup><xref ref-type="bibr" rid="B26">26</xref></sup></p>
      <p>Por&#233;m, embora n&#227;o tenham utilizado o SII diretamente, h&#225; estudos na literatura que utilizam a rela&#231;&#227;o neutr&#243;filos/linf&#243;citos*plaquetas (NLPR), que &#233; calculada de forma diferente.<sup><xref ref-type="bibr" rid="B19">19</xref>,<xref ref-type="bibr" rid="B30">30</xref>,<xref ref-type="bibr" rid="B31">31</xref></sup> Koo et al. sugeriram que um aumento da rela&#231;&#227;o NLPR pr&#233;-operat&#243;ria estava associado a uma sobrevida pobre em longo prazo e que a NLPR pr&#233;-operat&#243;ria pode ser um marcador preditivo independente superior de sobrevida em cinco anos do que a NLR pr&#233;-operat&#243;ria e a contagem de plaquetas.<sup><xref ref-type="bibr" rid="B19">19</xref></sup> Pelo contr&#225;rio, Abanoz e Engin n&#227;o conseguiram mostrar uma rela&#231;&#227;o entre o desenvolvimento de eventos adversos maiores, incluindo mortalidade hospitalar, ap&#243;s cirurgia de revasculariza&#231;&#227;o do mioc&#225;rdio e NLPR pr&#233;-operat&#243;ria. Entretanto, ap&#243;s p&#243;s-cardiotomia, mostraram que a NLPR &#233; um fator de risco independente mais preditivo.<sup><xref ref-type="bibr" rid="B31">31</xref></sup></p>
      <p>No presente estudo, idade, sexo, triglicer&#237;deos, n&#237;veis de SCr e presen&#231;a de hipertens&#227;o tamb&#233;m foram encontrados como fatores de risco independentes. Os resultados s&#227;o geralmente compat&#237;veis com estudos semelhantes sobre morbidade e mortalidade na literatura.<sup><xref ref-type="bibr" rid="B27">27</xref>,<xref ref-type="bibr" rid="B32">32</xref>-<xref ref-type="bibr" rid="B34">34</xref></sup> A CrS, que &#233; um par&#226;metro muito importante na avalia&#231;&#227;o das fun&#231;&#245;es renais, foi associada a mau progn&#243;stico em pacientes de cirurgia card&#237;aca.<sup><xref ref-type="bibr" rid="B35">35</xref></sup> Doen&#231;as card&#237;acas e renais, tanto agudas quanto cr&#244;nicas, interagem ao longo de muitas vias comuns, incluindo mecanismos inflamat&#243;rios e imunol&#243;gicos.<sup><xref ref-type="bibr" rid="B36">36</xref></sup> Portanto, a insufici&#234;ncia renal aprofunda ainda mais a insufici&#234;ncia card&#237;aca e contribui para um aumento na mortalidade dos pacientes. Al&#233;m disso, descobriu-se que a hipertens&#227;o tamb&#233;m est&#225; associada ao acidente vascular cerebral, que &#233; uma causa comum de morte.<sup><xref ref-type="bibr" rid="B33">33</xref></sup></p>
      <p>No entanto, o presente estudo tem algumas limita&#231;&#245;es. Primeiro, este foi um estudo unic&#234;ntrico. Portanto, o efeito do manejo perioperat&#243;rio e cir&#250;rgico, bem como as caracter&#237;sticas do paciente, poderiam potencialmente distorcer os resultados, e pode-se dizer que nosso estudo tem uma amostra relativamente pequena. Em segundo lugar, tem um desenho retrospectivo, que apresenta preconceitos. A principal for&#231;a deste estudo, por outro lado, &#233; que este &#233; o primeiro estudo a descrever a utilidade do SII como um par&#226;metro pr&#233;-operat&#243;rio associado ao risco para mortalidade intra-hospitalar ap&#243;s CEC. Embora n&#227;o seja um teste diagn&#243;stico, esse par&#226;metro de rotina &#233; &#250;til como uma ferramenta de f&#225;cil acesso para prever poss&#237;veis complica&#231;&#245;es ap&#243;s a CEC.</p>
    </sec>
    <sec sec-type="conclusions">
      <title>Conclus&#227;o</title>
      <p>Altos escores pr&#233;-operat&#243;rios do SII podem ser usados para determina&#231;&#227;o precoce de tratamentos apropriados, o que pode melhorar os resultados cir&#250;rgicos de cirurgia card&#237;aca no futuro. Al&#233;m disso, quando os pacientes foram reagrupados com base nos valores de corte do SII no presente estudo, observou-se que a perman&#234;ncia hospitalar e o tempo de interna&#231;&#227;o p&#243;s-operat&#243;ria aumentaram significativamente no grupo com SII alto. Este estudo tamb&#233;m ajudar&#225; a fornecer benef&#237;cios econ&#244;micos, pois esses resultados podem estar associados ao aumento dos custos de atendimento ao paciente. Acreditamos que nosso estudo inspirar&#225; mais pesquisas em larga escala sobre os efeitos adversos p&#243;s-operat&#243;rios.</p>
    </sec>
  </body>
  <back>
    <fn-group>
      <fn fn-type="financial-disclosure" 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 fn-type="other" id="fn3">
        <p>
          <bold>Aprova&#231;&#227;o &#233;tica e consentimento informado</bold>
        </p>
        <p>Este estudo foi aprovado pelo Comit&#234; de &#201;tica do Erciyes Universitesi Tip Fakultesi sob o n&#250;mero de protocolo 2021/608. Todos os procedimentos envolvidos nesse estudo est&#227;o de acordo com a Declara&#231;&#227;o de Helsinki de 1975, atualizada em 2013.</p>
      </fn>
    </fn-group>
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          <label>3</label>
          <addr-line>
            <named-content content-type="city">Istanbul</named-content>
          </addr-line>
          <country country="TR">Turkey</country>
          <institution content-type="original">Acibadem Hospitals Group &#8211; Cardiology, Istanbul &#8211; Turkey</institution>
        </aff>
        <aff id="aff9">
          <label>4</label>
          <addr-line>
            <named-content content-type="city">Kayseri</named-content>
          </addr-line>
          <country country="TR">Turkey</country>
          <institution content-type="original">Cetin Sen Science and Art Center &#8211; Chemistry, Kayseri &#8211; Turkey</institution>
        </aff>
        <aff id="aff10">
          <label>5</label>
          <addr-line>
            <named-content content-type="city">Kayseri</named-content>
          </addr-line>
          <country country="TR">Turkey</country>
          <institution content-type="original">Erciyes University Faculty of Medicine, Clinical Biochemistry, Kayseri &#8211; Turkey</institution>
        </aff>
      </contrib-group>
      <author-notes>
        <corresp id="c2"><bold>Mailing Address: &#304;nayet G&#252;nt&#252;rk &#8226;</bold> Nigde Omer Halisdemir University, Faculty of Health Sciences, Midwifery &#8211; A&#351;a&#287;&#305; Kayaba&#351;&#305; Mah. Atat&#252;rk Bulvar&#305; Derbent Yerle&#351;kesi Nigde Ni&#287;de <postal-code>51200</postal-code> &#8211; Turkey E-mail: <email>inayetgntrk@gmail.com</email>, <email>inayetgunturk@ohu.edu.tr</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>
        <fn fn-type="edited-by">
          <p>Editor responsible for the review: Alexandre Colafranceschi</p>
        </fn>
      </author-notes>
      <abstract>
        <title>Abstract</title>
        <sec>
          <title>Background:</title>
          <p>Systemic immune-inflammation index (SII), a new inflammatory index calculated using platelet, neutrophil, and lymphocyte counts, has been demonstrated to be an independent risk factor for the identification of high-risk coronary artery disease in patients undergoing percutaneous coronary intervention and cardiovascular surgery with cardiopulmonary bypass (CPB). The relationship between SII and CPB-related mortality rates remains unclear.</p>
        </sec>
        <sec>
          <title>Objective:</title>
          <p>This research was designed to investigate the use of SII to predict in-hospital mortality in patients undergoing cardiac surgery with CPB.</p>
        </sec>
        <sec>
          <title>Methods:</title>
          <p>Four hundred eighty patients who underwent a cardiac procedure involving CPB over 3 years, were obtained from the hospital's database. The demographic data, comorbidities, hematological and biochemical profiles, and operative data of the groups were compared. Multiple logistic regression analyses were done to determine independent predictors of mortality. Prognostic factors were assessed by multivariate analysis, and the predictive values of SII, neutrophil-lymphocyte ratio (NLR), and platelet-lymphocyte ratio (PLR) for mortality were compared. A p-value &lt;0.05 was considered significant.</p>
        </sec>
        <sec>
          <title>Results:</title>
          <p>Of 480 patients, 78 developed in-hospital mortality after cardiac surgery. SII was an independent predictor of in-hospital mortality (Odds ratio: 1.003, 95% confidence interval: 1.001-1.005, p&lt;0.001). The cut-off value of the SII was &gt;811.93 with 65% sensitivity and 65% specificity (area under the curve: 0.690). The predictive values of SII, PLR, and NLR were close to each other.</p>
        </sec>
        <sec>
          <title>Conclusion:</title>
          <p>High preoperative SII scores can be used for early determination of appropriate treatments, which may improve surgical outcomes of cardiac surgery in the future.</p>
        </sec>
      </abstract>
      <kwd-group xml:lang="en">
        <title>Keywords:</title>
        <kwd>Extracorporeal Circulation</kwd>
        <kwd>Inflammation</kwd>
        <kwd>Hospital Mortality</kwd>
        <kwd>Thoracic Surgery</kwd>
      </kwd-group>
    </front-stub>
    <body>
      <fig id="f3">
        <graphic xlink:href="1678-4170-abc-121-04-e20230245-30245-gf01-en.tif"/></fig>
      <sec sec-type="intro">
        <title>Introduction</title>
        <p>Extracorporeal circulation techniques, especially cardiopulmonary bypass (CPB) during cardiac surgery, provide blood flow and oxygen to tissues and organs.<sup><xref ref-type="bibr" rid="B1">1</xref></sup> CPB has become the standard for many cardiac procedures, and its advancement is enabling advances in cardiovascular surgery. The procedure is considered to be relatively safe.<sup><xref ref-type="bibr" rid="B2">2</xref></sup> CPB, on the other hand, is well known for initiating an inflammatory reaction cascade, and this inflammatory response has serious clinical consequences.<sup><xref ref-type="bibr" rid="B2">2</xref>-<xref ref-type="bibr" rid="B4">4</xref></sup> As a result, investigating the role of inflammatory changes in patient prognosis has become a high-priority target for the development of both therapeutic and preventive strategies.<sup><xref ref-type="bibr" rid="B5">5</xref></sup> For this purpose, many mediators such as pro-inflammatory cytokine levels such as IL-6, TNF, coagulation/fibrinolytic system, and complement activation markers have been investigated in relation to the CPB-related inflammatory response.<sup><xref ref-type="bibr" rid="B5">5</xref>,<xref ref-type="bibr" rid="B6">6</xref></sup></p>
        <p>However, when factors such as ease of measurement and interpretation, as well as low cost, are considered, such blood count parameters continue to be widely used. Although an increase in the number of white blood cells is accepted as a general marker for the inflammatory response triggered by various stimulants, its predictive value is insufficient.<sup><xref ref-type="bibr" rid="B7">7</xref></sup> Therefore, there is a recent emphasis on hematologic indices, such as neutrophil-lymphocyte ratio (NLR) and platelet-lymphocyte ratio (PLR), as markers of perioperative inflammation, considering the proposition of postoperative complications.<sup><xref ref-type="bibr" rid="B8">8</xref></sup></p>
        <p>The systemic immune-inflammation index (SII), a new inflammatory index calculated using platelet, neutrophil, and lymphocyte counts, has been shown to be a strong prognostic marker in a variety of cancers.<sup><xref ref-type="bibr" rid="B9">9</xref>,<xref ref-type="bibr" rid="B10">10</xref></sup> In addition, SII has been shown to be an independent risk factor for the identification of high-risk coronary artery disease in patients undergoing percutaneous coronary intervention, postoperative atrial fibrillation after coronary artery bypass grafting, a prognostic factor for infective endocarditis, and presence of isolated coronary artery ectasia.<sup><xref ref-type="bibr" rid="B11">11</xref>-<xref ref-type="bibr" rid="B14">14</xref></sup> However, the relationship between SII and CPB-related complications, especially in terms of in-hospital mortality rate, remains unclear.</p>
        <p>In light of this, the current study sought to elucidate the independent association between SII and the occurrence of short-term mortality in patients who underwent on-pump cardiac surgery in order to provide a predictive marker for therapeutic interventions as early as possible.</p>
      </sec>
      <sec sec-type="methods">
        <title>Methods</title>
        <p>The study was conducted and approved by the Local Ethics Committee (Approval number: 2021/608). Due to the retrospective nature of the study, individual informed written consent was waived.</p>
        <p>Patients who underwent a cardiac procedure involving CPB over 3 years (from 2018 to 2021) were collected. There was no operation-based selection used. Preoperative data for 480 adult patients was obtained from the hospital's database. The following data was collected for all the subjects: demographics (age, gender, smoking); the presence of comorbidities (chronic obstructive pulmonary disease, arterial hypertension, dyslipidemia, diabetes on medication, and chronic renal failure); preoperative laboratory results [complete blood count (CBC), blood urea nitrogen (BUN), serum creatinine (SCr), AST, ALT, total cholesterol (Total-C), HDL-C, LDL-C, glukoz, etc.]; type of surgical operation, CPB and aortic cross-clamp duration. The SII was defined as platelet count x neutrophil/lymphocyte count. Patients undergoing preoperative extracorporeal life support, active infection, chronic inflammatory conditions, malignancy, and the use of immunosuppressive therapy, as well as patients with incomplete data, were excluded.</p>
        <p>This study included patients who underwent median sternotomy under general anesthesia by the same surgical team. All patients received standard anticoagulant therapy with intravenous unfractionated heparin. Standard aortic and dual-stage venous cannulation was applied to the patients who reached the effective activated coagulation value after systemic heparinization. Isolated elective CABG surgery was carried out by inducing cardiac arrest with antegrade hyperkalemic cold blood cardioplegia and CPB. During the surgical procedure, patients were cooled to 32-33 &#8304;C. Cold blood cardioplegia was administered antegradely every 20 minutes. The topical cold isotonic saline application was also used on the patients during this period. The left internal mammary artery was used as an arterial graft, and the great saphenous vein was used as a venous graft. After the cross-clamp was removed and the heart started to beat, distal anastomoses were performed under the cross-clamp, and proximal anastomoses were performed under the side-clamp in all patients.</p>
        <p>The patients were divided into two groups based on the presence of operative mortality, which included any death, regardless of cause, occurring within days of hospital stay after surgery. The causes of death, which included multiple organ failure, permanent neurologic dysfunction (stroke/coma), circulatory failure, and infectious toxic shock, were determined based on the clinical condition documentation in medical records.</p>
        <sec>
          <title>Statistical analysis</title>
          <p>Statistical analysis was performed using SPSS 23.0 (SPSS Company, Chicago, IL) for Windows. Continuous variables were described using median and interquartile range due to their lack of normal distribution, tested using the Shapiro-Wilk test. Mann-Whitney U tests were used for comparisons between the survival and non-survival groups. The Chi-square or Fisher's exact tests were used to compare both groups on categorical variables, which were then summarized using counts and percentages. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve was calculated to determine the optimal cut-off value of SII, NLR, and PLR to predict mortality. Univariate and multivariate logistic regression analyses were performed to identify independent predictors of the occurrence of mortality. For secondary analysis, to compare groups according to cut-off values of SII, the Mann-Whitney U test was used. A p-value &lt;0.05 was considered significant.</p>
        </sec>
      </sec>
      <sec sec-type="results">
        <title>Results</title>
        <p>In patients included in the study, a total of 78 patients developed in-hospital mortality. The demographic and perioperative characteristics and preoperative laboratory analysis are presented in <xref ref-type="table" rid="t5">Table 1</xref>.</p>
        <table-wrap id="t5">
          <label>Table 1</label>
          <caption>
            <title>Comparisons of demographics and routine laboratory analysis between survivors and non-survivor</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 style="background-color:#76B4CF;">
                <th align="left" valign="middle">Characteristics</th>
                <th align="center" valign="middle">Survivors (n=402)</th>
                <th align="center" valign="middle">Non-survivors (n=78)</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="top">Age (year)</td>
                <td align="center" valign="top">63 (55-68)</td>
                <td align="center" valign="top">67 (60-73)</td>
                <td align="center" valign="top">&lt;0.001</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td align="left" valign="top">Gender F/M, n (%)</td>
                <td align="center" valign="top">79 (19.7)/323 (80.3)</td>
                <td align="center" valign="top">28 (37.5)/50 (62.5)</td>
                <td align="center" valign="top">0.002</td>
              </tr>
              <tr>
                <td align="left" valign="top">Hospital Stay (Day)</td>
                <td align="center" valign="top">14.0 (10.0-17.5)</td>
                <td align="center" valign="top">9.0 (4.5-15.0)</td>
                <td align="center" valign="top">&lt;0.001</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td align="left" valign="top">Intensive Care Unit Stay (Day)</td>
                <td align="center" valign="top">4.0 (3.0-5.0)</td>
                <td align="center" valign="top">3.0 (1.0-6.0)</td>
                <td align="center" valign="top">&lt;0.001</td>
              </tr>
              <tr>
                <td align="left" valign="top">Postoperative Stay (Day)</td>
                <td align="center" valign="top">7.0 (6.0-10.0)</td>
                <td align="center" valign="top">2.0 (0.0-6.5)</td>
                <td align="center" valign="top">&lt;0.001</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td align="left" valign="top">Cardiopulmonary Bypass Duration (Min.)</td>
                <td align="center" valign="top">100 (85-145)</td>
                <td align="center" valign="top">105 (80-140)</td>
                <td align="center" valign="top">0.637</td>
              </tr>
              <tr>
                <td align="left" valign="top">Cross-Clamp Duration (Min.)</td>
                <td align="center" valign="top">50 (45-65)</td>
                <td align="center" valign="top">55 (45-80)</td>
                <td align="center" valign="top">0.328</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td align="left" colspan="4" valign="top">
                  <bold>Laboratory parameters</bold>
                </td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td align="left" valign="top">Haemoglobin, g/dL</td>
                <td align="center" valign="top">14.30 (13.00-15.40)</td>
                <td align="center" valign="top">13.45(12.47-14.62)</td>
                <td align="center" valign="top">0.005</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td align="left" valign="top">WBC, 10<sup>9</sup>/L</td>
                <td align="center" valign="top">8.93 (7.15-11.09)</td>
                <td align="center" valign="top">8.63 (7.06-11.51)</td>
                <td align="center" valign="top">0.907</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td align="left" valign="top">Neutrophil, 10<sup>9</sup>/L</td>
                <td align="center" valign="top">5.61 (4.40-6.96)</td>
                <td align="center" valign="top">6.28 (5.26-7.79)</td>
                <td align="center" valign="top">0.069</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td align="left" valign="top">Lymphocyte, 10<sup>9</sup>/L</td>
                <td align="center" valign="top">2.11 (1.62-2.74)</td>
                <td align="center" valign="top">1.83 (1.28-2.37)</td>
                <td align="center" valign="top">0.001</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td align="left" valign="top">Neutrophil Lymphocyte Ratio</td>
                <td align="center" valign="top">2.62 (1.95-3.51)</td>
                <td align="center" valign="top">3.50 (2.54-5.00)</td>
                <td align="center" valign="top">&lt;0.001</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td align="left" valign="top">Platelet, 10<sup>9</sup>/L</td>
                <td align="center" valign="top">251.50 (215.00-292.50)</td>
                <td align="center" valign="top">261.00 (235.00-299.25)</td>
                <td align="center" valign="top">0.058</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td align="left" valign="top">Platelet Lymphocyte Ratio</td>
                <td align="center" valign="top">119.56 (90.03-156.18)</td>
                <td align="center" valign="top">158.43 (112.90-210.53)</td>
                <td align="center" valign="top">&lt;0.001</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td align="left" valign="top">Systemic Immune-Inflammation Index (x10<sup>9</sup>/L)</td>
                <td align="center" valign="top">654.25 (465.49-936.46)</td>
                <td align="center" valign="top">948.33(642.60-1355.60)</td>
                <td align="center" valign="top">&lt;0.001</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td align="left" valign="top">Urea, mg/dL</td>
                <td align="center" valign="top">17.85 (13.97-22.30)</td>
                <td align="center" valign="top">19.50 (14.67-24.82)</td>
                <td align="center" valign="top">0.105</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td align="left" valign="top">SCr, mg/dL</td>
                <td align="center" valign="top">0.92 (0.80-1.10)</td>
                <td align="center" valign="top">1.00 (0.82-1.27)</td>
                <td align="center" valign="top">0.042</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td align="left" valign="top">eGFR</td>
                <td align="center" valign="top">84.49 (68.20-96.12)</td>
                <td align="center" valign="top">77.93 (55.83-90.63)</td>
                <td align="center" valign="top">&lt;0.001</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td align="left" valign="top">AST (U/L)</td>
                <td align="center" valign="top">21.9 (17.65-32.07)</td>
                <td align="center" valign="top">23.0 (18.00-34.00)</td>
                <td align="center" valign="top">0.493</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td align="left" valign="top">ALT (U/L)</td>
                <td align="center" valign="top">21.0 (15.00-28.00)</td>
                <td align="center" valign="top">19.3 (13.60-28.00)</td>
                <td align="center" valign="top">0.244</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td align="left" valign="top">Glucose, mg/dL</td>
                <td align="center" valign="top">127 (104-177)</td>
                <td align="center" valign="top">136 (112-195)</td>
                <td align="center" valign="top">0.082</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td align="left" valign="top">Triglyceride, mg/dL</td>
                <td align="center" valign="top">178.00(164.00-213.00)</td>
                <td align="center" valign="top">134.50 (107.75-171.25)</td>
                <td align="center" valign="top">0.002</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td align="left" valign="top">Total cholesterol, mg/dL</td>
                <td align="center" valign="top">186.00 (157.00-224.70)</td>
                <td align="center" valign="top">175.00 (158.25-191.00)</td>
                <td align="center" valign="top">0.024</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td align="left" valign="top">HDL-cholesterol, mg/dL</td>
                <td align="center" valign="top">38.05 (35.07-43.92)</td>
                <td align="center" valign="top">40.55 (34.75-45.00)</td>
                <td align="center" valign="top">0.141</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td align="left" valign="top">LDL-cholesterol, mg/dL</td>
                <td align="center" valign="top">105.00 (96.17-127.65)</td>
                <td align="center" valign="top">103.74(86.55-121.72)</td>
                <td align="center" valign="top">0.224</td>
              </tr>
              <tr>
                <td align="left" colspan="4" valign="top">
                  <bold>Comorbidities, n (%)</bold>
                </td>
              </tr>
              <tr>
                <td align="left" valign="top">Hypertension</td>
                <td align="center" valign="top">128 (34.1)</td>
                <td align="center" valign="top">30 (53.6)</td>
                <td align="center" valign="top">0.007</td>
              </tr>
              <tr>
                <td align="left" valign="top">Chronic renal disease</td>
                <td align="center" valign="top">9 (2.4)</td>
                <td align="center" valign="top">6 (10.7)</td>
                <td align="center" valign="top">0.007</td>
              </tr>
              <tr>
                <td align="left" valign="top">Hyperlipidemia</td>
                <td align="center" valign="top">6 (1.6)</td>
                <td align="center" valign="top">1 (1.8)</td>
                <td align="center" valign="top">0.999</td>
              </tr>
              <tr>
                <td align="left" valign="top">Diabetes Mellitus</td>
                <td align="center" valign="top">107 (28.5)</td>
                <td align="center" valign="top">20 (39.7)</td>
                <td align="center" valign="top">0.275</td>
              </tr>
              <tr>
                <td align="left" valign="top">Chronic Obstructive Pulmonary Disease</td>
                <td align="center" valign="top">14 (3.7)</td>
                <td align="center" valign="top">4 (7.1)</td>
                <td align="center" valign="top">0.272</td>
              </tr>
              <tr>
                <td align="left" valign="top">Smoking</td>
                <td align="center" valign="top">6 (1.6)</td>
                <td align="center" valign="top">1 (1.8)</td>
                <td align="center" valign="top">0.999</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn id="TFN5">
              <p>p: Statistically differences between survivors and non-survivors. The data were expressed as median and interquartile range; %50 (%25- %75). Categorical variables are expressed as percentages.</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
        <p>On univariate analysis, the following preoperative variables were found to be significant predictors of mortality: gender, age, SII, NLR, PLR, hemoglobin, SCr, eGFR, triglyceride, Total-C, hypertension, and chronic renal disease (<xref ref-type="table" rid="t6">Table 2</xref>). A multivariate analysis of the same parameters revealed that gender, age, and SII, SCr, triglyceride, and hypertension remained independent predictors of in-hospital mortality (<xref ref-type="table" rid="t6">Table 2</xref>).</p>
        <table-wrap id="t6">
          <label>Table 2</label>
          <caption>
            <title>Univariate and Multivariate Logistic Regression Analysis of the Preoperative Risk Factors for Predicting Mortality</title>
          </caption>
          <table frame="hsides" rules="groups">
            <colgroup width="11%">
              <col/>
              <col/>
              <col/>
              <col/>
              <col/>
              <col/>
              <col/>
              <col/>
              <col/>
            </colgroup>
            <thead style="border-top: thin solid; border-bottom: thin solid; border-color: #000000">
              <tr style="background-color:#76B4CF;">
                <th align="left" rowspan="3" valign="middle">Variables</th>
                <th align="center" colspan="4" style="border-bottom: thin solid; border-color: #000000" valign="middle">Univariate Analysis</th>
                <th align="center" colspan="4" style="border-bottom: thin solid; border-color: #000000" valign="middle">Multivariate Analysis</th>
              </tr>
              <tr style="background-color:#76B4CF;">
                <th align="center" rowspan="2" valign="middle">OR</th>
                <th align="center" colspan="2" style="border-bottom: thin solid; border-color: #000000" valign="middle">95 % CI</th>
                <th align="center" rowspan="2" valign="middle">p Value</th>
                <th align="center" rowspan="2" valign="middle">OR</th>
                <th align="center" colspan="2" style="border-bottom: thin solid; border-color: #000000" valign="middle">95 % CI</th>
                <th align="center" rowspan="2" valign="middle">p Value</th>
              </tr>
              <tr style="background-color:#76B4CF;">
                <th align="center" valign="middle">Lower</th>
                <th align="center" valign="middle">Upper</th>
                <th align="center" valign="middle">Lower</th>
                <th align="center" valign="middle">Upper</th>
              </tr>
            </thead>
            <tbody style="border-bottom: thin solid; border-color: #000000">
              <tr>
                <td align="left" valign="top">Gender</td>
                <td align="center" valign="top">0.438</td>
                <td align="center" valign="top">0.259</td>
                <td align="center" valign="top">0.740</td>
                <td align="center" valign="top">0.002</td>
                <td align="center" valign="top">2.129</td>
                <td align="center" valign="top">1.204</td>
                <td align="center" valign="top">3.766</td>
                <td align="center" valign="top">0.009</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td align="left" valign="top">Age</td>
                <td align="center" valign="top">1.043</td>
                <td align="center" valign="top">1.016</td>
                <td align="center" valign="top">1.071</td>
                <td align="center" valign="top">0.002</td>
                <td align="center" valign="top">1.029</td>
                <td align="center" valign="top">1.001</td>
                <td align="center" valign="top">1.058</td>
                <td align="center" valign="top">0.044</td>
              </tr>
              <tr>
                <td align="left" valign="top">SII</td>
                <td align="center" valign="top">1.002</td>
                <td align="center" valign="top">1.001</td>
                <td align="center" valign="top">1.003</td>
                <td align="center" valign="top">&lt;0.001</td>
                <td align="center" valign="top">1.003</td>
                <td align="center" valign="top">1.001</td>
                <td align="center" valign="top">1.005</td>
                <td align="center" valign="top">&lt;0.001</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td align="left" valign="top">NLR</td>
                <td align="center" valign="top">1.176</td>
                <td align="center" valign="top">1.084</td>
                <td align="center" valign="top">1.275</td>
                <td align="center" valign="top">&lt;0.001</td>
                <td align="center" valign="top"/>
                <td align="center" valign="top"/>
                <td align="center" valign="top"/>
                <td align="center" valign="top"/>
              </tr>
              <tr>
                <td align="left" valign="top">PLR</td>
                <td align="center" valign="top">1.005</td>
                <td align="center" valign="top">1.002</td>
                <td align="center" valign="top">1.008</td>
                <td align="center" valign="top">&lt;0.001</td>
                <td align="center" valign="top"/>
                <td align="center" valign="top"/>
                <td align="center" valign="top"/>
                <td align="center" valign="top"/>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td align="left" valign="top">Hemoglobin</td>
                <td align="center" valign="top">0.853</td>
                <td align="center" valign="top">0.753</td>
                <td align="center" valign="top">0.965</td>
                <td align="center" valign="top">0.012</td>
                <td align="center" valign="top"/>
                <td align="center" valign="top"/>
                <td align="center" valign="top"/>
                <td align="center" valign="top"/>
              </tr>
              <tr>
                <td align="left" valign="top">SCr</td>
                <td align="center" valign="top">1.356</td>
                <td align="center" valign="top">1.069</td>
                <td align="center" valign="top">1.721</td>
                <td align="center" valign="top">0.012</td>
                <td align="center" valign="top">1.523</td>
                <td align="center" valign="top">1.173</td>
                <td align="center" valign="top">1.977</td>
                <td align="center" valign="top">0.002</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td align="left" valign="top">eGFR</td>
                <td align="center" valign="top">0.982</td>
                <td align="center" valign="top">0.972</td>
                <td align="center" valign="top">0.992</td>
                <td align="center" valign="top">0.001</td>
                <td align="center" valign="top"/>
                <td align="center" valign="top"/>
                <td align="center" valign="top"/>
                <td align="center" valign="top"/>
              </tr>
              <tr>
                <td align="left" valign="top">Triglyceride</td>
                <td align="center" valign="top">0.996</td>
                <td align="center" valign="top">0.993</td>
                <td align="center" valign="top">0.999</td>
                <td align="center" valign="top">0.021</td>
                <td align="center" valign="top">0.995</td>
                <td align="center" valign="top">0.991</td>
                <td align="center" valign="top">0.998</td>
                <td align="center" valign="top">0.005</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td align="left" valign="top">Total cholesterol</td>
                <td align="center" valign="top">0.889</td>
                <td align="center" valign="top">0.886</td>
                <td align="center" valign="top">0.892</td>
                <td align="center" valign="top">0.035</td>
                <td align="center" valign="top"/>
                <td align="center" valign="top"/>
                <td align="center" valign="top"/>
                <td align="center" valign="top"/>
              </tr>
              <tr>
                <td align="left" valign="top">Hypertension</td>
                <td align="center" valign="top">0.491</td>
                <td align="center" valign="top">0.301</td>
                <td align="center" valign="top">0.801</td>
                <td align="center" valign="top">0.004</td>
                <td align="center" valign="top">1.878</td>
                <td align="center" valign="top">1.106</td>
                <td align="center" valign="top">3.189</td>
                <td align="center" valign="top">0.020</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td align="left" valign="top">Chronic renal disease</td>
                <td align="center" valign="top">0.285</td>
                <td align="center" valign="top">0.107</td>
                <td align="center" valign="top">0.761</td>
                <td align="center" valign="top">0.012</td>
                <td align="center" valign="top"/>
                <td align="center" valign="top"/>
                <td align="center" valign="top"/>
                <td align="center" valign="top"/>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn id="TFN6">
              <p>CI: confidence interval; NLR: neutrophil lymphocyte ratio; PLR: platelet lymphocyte ratio; SII: Systemic Immune-Inflammation Index.</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
        <p>By receiver operating characteristic analysis, NLR, PLR, and SII predicted mortality in patients; the area under the curve of 0.664 (95% CI 0.599-0.729); 0.655 (95% CI 0.587-0.723), and 0.690 (95% CI 0.630-0.751), respectively (<xref ref-type="table" rid="t7">Table 3</xref>, <xref ref-type="fig" rid="f4">Figure 1</xref>). The cut-off values for NLR, PLR, and SII for predicting in-hospital mortality were 3.31 (58% sensitivity, 71% specificity), 132.76 (65% sensitivity, 60% specificity), and 811.93 (65% sensitivity, 65% specificity), respectively (<xref ref-type="table" rid="t7">Table 3</xref>).</p>
        <table-wrap id="t7">
          <label>Table 3</label>
          <caption>
            <title>Appropriate Cut-off Values of NLR, PLR, and SII</title>
          </caption>
          <table frame="hsides" rules="groups">
            <colgroup width="12%">
              <col/>
              <col/>
              <col/>
              <col/>
              <col/>
              <col/>
              <col/>
              <col/>
            </colgroup>
            <thead style="border-top: thin solid; border-bottom: thin solid; border-color: #000000">
              <tr style="background-color:#76B4CF;">
                <th align="center" valign="middle"/>
                <th align="center" rowspan="2" valign="middle">AUC</th>
                <th align="center" rowspan="2" valign="middle">p Value</th>
                <th align="center" colspan="2" style="border-bottom: thin solid; border-color: #000000" valign="middle">% 95 CI</th>
                <th align="center" rowspan="2" valign="middle">Cut-off Value</th>
                <th align="center" rowspan="2" valign="middle">Sensitivity</th>
                <th align="center" rowspan="2" valign="middle">Specificity</th>
              </tr>
              <tr style="background-color:#76B4CF;">
                <th align="center" valign="middle"/>
                <th align="center" valign="middle">Lower</th>
                <th align="center" valign="middle">Upper</th>
              </tr>
            </thead>
            <tbody style="border-bottom: thin solid; border-color: #000000">
              <tr style="background-color:#C7DFEC">
                <td align="left" valign="top">NLR</td>
                <td align="center" valign="top">0.664</td>
                <td align="center" valign="top">&lt;0.001</td>
                <td align="center" valign="top">0.599</td>
                <td align="center" valign="top">0.729</td>
                <td align="center" valign="top">3.31</td>
                <td align="center" valign="top">0.577</td>
                <td align="center" valign="top">0.711</td>
              </tr>
              <tr>
                <td align="left" valign="top">PLR</td>
                <td align="center" valign="top">0.655</td>
                <td align="center" valign="top">&lt;0.001</td>
                <td align="center" valign="top">0.587</td>
                <td align="center" valign="top">0.723</td>
                <td align="center" valign="top">132.76</td>
                <td align="center" valign="top">0.654</td>
                <td align="center" valign="top">0.595</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td align="left" valign="top">SII</td>
                <td align="center" valign="top">0.690</td>
                <td align="center" valign="top">&lt;0.001</td>
                <td align="center" valign="top">0.630</td>
                <td align="center" valign="top">0.751</td>
                <td align="center" valign="top">811.93</td>
                <td align="center" valign="top">0.654</td>
                <td align="center" valign="top">0.652</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn id="TFN7">
              <p>AUC: area under the curve; CI: confidence interval; NLR: neutrophil lymphocyte ratio; PLR: platelet lymphocyte ratio; SII: Systemic Immune-Inflammation Index.</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
        <fig id="f4">
          <label>Figure 1</label>
          <caption>
            <title>Receiver Operating Curve Analysis of NLR, PLR and SII .</title>
          </caption>
          <graphic xlink:href="1678-4170-abc-121-04-e20230245-30245-gf02-en.tif"/></fig>
        <p>Regarding secondary outcomes, the duration of hospital and postoperative stays was significantly longer for patients with high SII levels. However, the durations of intensive care unit stays were similar between groups (<xref ref-type="table" rid="t8">Table 4</xref>). The <xref ref-type="fig" rid="f3">central illustration</xref> highlights the main results of the study.</p>
        <table-wrap id="t8">
          <label>Table 4</label>
          <caption>
            <title>Postoperative outcomes for SII groups</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 style="background-color:#76B4CF;">
                <th align="left" valign="middle">Characteristics</th>
                <th align="center" valign="middle">SII &#8805; 811.93 <break/>(n=173)</th>
                <th align="center" valign="middle">SII &lt; 811.93 <break/>(n=307)</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="top">Hospital Stay (Day)</td>
                <td align="center" valign="top">14.0 (10.0-17.0)</td>
                <td align="center" valign="top">11.0 (7.0-17.0)</td>
                <td align="center" valign="top">0.001</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td align="left" valign="top">Postoperative Stay (Day)</td>
                <td align="center" valign="top">7.0 (6.0-10.0)</td>
                <td align="center" valign="top">2.0 (5.0-7.75)</td>
                <td align="center" valign="top">0.022</td>
              </tr>
              <tr>
                <td align="left" valign="top">Intensive Care Unit Stay (Day)</td>
                <td align="center" valign="top">4.0 (3.0-5.0)</td>
                <td align="center" valign="top">3.0 (2.0-5.0)</td>
                <td align="center" valign="top">0.114</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn id="TFN8">
              <p>p: Statistically differences between groups. The data were expressed as median and interquartile range; %50 (%25- %75).</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
      </sec>
      <sec sec-type="discussion">
        <title>Discussion</title>
        <p>On univariate analysis, the current study demonstrated that SII, hemoglobin, NLR, PLR, SCr, eGFR, triglyceride, and Total-C could be used as routine parameters for predicting in-hospital mortality in patients who underwent cardiac surgery by CPB, along with other clinical and demographic parameters (age, gender, chronic renal disease, and hypertension). However, SII emerged as a hematologic, and SCr and triglyceride as biochemical parameters, to independently predict in-hospital mortality after CPB surgery.</p>
        <p>For many reasons, such as contact of blood with the extracorporeal surface, surgical trauma, endotoxemia, and ischemia-reperfusion injury, CPB results in the release of pro-inflammatory cytokines, which can be transformed into a cascade, leading to a serious immune-inflammatory response in the organism. The primary cause of postoperative morbidity and mortality is thought to be the patient's response.<sup><xref ref-type="bibr" rid="B1">1</xref>,<xref ref-type="bibr" rid="B15">15</xref></sup> Since the development of preventive strategies in this area requires the identification of risk factors, particularly during the preoperative period, many studies have focused on this direction.</p>
        <p>Indices, calculated with simple mathematical formulas, between cells from a CBC, which is often routinely performed, are sought to be valuable evidence to gain further information on systemic inflammation. However, individual leukocyte parameters are susceptible to alteration by external conditions (dehydration, hemodilution, etc.), and NLR-like indices are relatively more stable.<sup><xref ref-type="bibr" rid="B16">16</xref></sup> Also, since these indices allow the evaluation of different pathways (immune and inflammatory) together, they reveal more meaningful results than alone.<sup><xref ref-type="bibr" rid="B17">17</xref>-<xref ref-type="bibr" rid="B19">19</xref></sup> Risk prediction by the NLR and PLR has been studied for many years in many fields of medicine.<sup><xref ref-type="bibr" rid="B20">20</xref>-<xref ref-type="bibr" rid="B22">22</xref></sup> Moreover, especially in recent years, both PLR and NLR have been identified as significant markers for postoperative surgery outcomes.<sup><xref ref-type="bibr" rid="B17">17</xref>,<xref ref-type="bibr" rid="B18">18</xref>,<xref ref-type="bibr" rid="B23">23</xref>,<xref ref-type="bibr" rid="B24">24</xref></sup> In a meta-analysis of 3108 patients, Tan et al. showed that high preoperative NLR levels were associated with all-cause mortality and morbidity.<sup><xref ref-type="bibr" rid="B23">23</xref></sup> Another study by Parlar and &#350;a&#351;k&#305;n reported that PLR and NLR, measured both preoperatively and postoperatively, were associated with postoperative acute kidney injury (AKI), and they reported that the values measured in the postoperative period were more predictive.<sup><xref ref-type="bibr" rid="B25">25</xref></sup> In contrast, Navani et al. and He et al., who investigated the relationship between PLR and the development of postoperative atrial fibrillation and NLR and AKI, respectively, could not show a significant relationship.<sup><xref ref-type="bibr" rid="B26">26</xref>,<xref ref-type="bibr" rid="B27">27</xref></sup> These conflicting results may be associated with differences in statistical methodology and study population. Another reason for the non-standardization of the outcome measures used can also be considered.<sup><xref ref-type="bibr" rid="B28">28</xref></sup></p>
        <p>To the best of our knowledge, this is the first time in the literature that a new index, SII, which is used for clinical outcomes for several cancers, was evaluated in-hospital mortality in patients who used CPB in addition to NLR and PLR. The work of Selcuk et al. is the most similar to the current study.<sup><xref ref-type="bibr" rid="B29">29</xref></sup> However, unlike our study, which looked at in-hospital mortality, they examined the relationships between preoperative SII, NLR, and PLR and the development of postoperative atrial fibrillation (POAF). They found that similarly to the current study, all three indexes were significant in univariate analyses, but only SII could be considered an independent risk factor in multivariate analyses. However, they showed a higher predictive value for SII (AUC: 0.7107) for POAF compared to NLR and PLR (AUC: 0.6740 and 0.6426, respectively). This difference can be explained by the fact that the factors that may cause mortality and their pathogenesis are spread over a wider range. This was also consistent with the argument by Navani et al. regarding the unchanged PLR in patients undergoing cardiac surgery, as the effect of platelets on the pathogenesis of POAF is not pronounced.<sup><xref ref-type="bibr" rid="B26">26</xref></sup></p>
        <p>However, although they did not use the SII directly, there are studies in the literature that use the neutrophil/lymphocyte* platelet ratio (NLPR), which is calculated using a different way.<sup><xref ref-type="bibr" rid="B19">19</xref>,<xref ref-type="bibr" rid="B30">30</xref>,<xref ref-type="bibr" rid="B31">31</xref></sup> Koo et al. suggested that an increased preoperative NLPR ratio was associated with poor long-term survival and that preoperative NLPR may be a superior independent predictive marker of five-year survival than preoperative NLR and platelet counts.<sup><xref ref-type="bibr" rid="B19">19</xref></sup> On the contrary, Abanoz and Engin could not show a relationship between the development of major adverse events, including in-hospital mortality, after coronary artery bypass grafting and preoperative NLPR. However, after post-cardiotomy, they showed NLPR to be a more predictive independent risk factor.<sup><xref ref-type="bibr" rid="B31">31</xref></sup></p>
        <p>In the current study, age, gender, triglyceride, SCr levels, and the presence of hypertension were also found as independent risk factors. The results are generally compatible with similar studies on morbidity and mortality in the literature.<sup><xref ref-type="bibr" rid="B27">27</xref>,<xref ref-type="bibr" rid="B32">32</xref>-<xref ref-type="bibr" rid="B34">34</xref></sup> SCr, which is a very important parameter in the evaluation of renal functions, was associated with poor prognosis in cardiac surgery patients.<sup><xref ref-type="bibr" rid="B35">35</xref></sup> Cardiac and renal diseases, acutely as well as chronically, interact along many common pathways, including inflammatory and immunological mechanisms.<sup><xref ref-type="bibr" rid="B36">36</xref></sup> Therefore, renal failure further deepens cardiac failure and contributes to an increase in mortality in patients. Furthermore, hypertension was also found to be associated with stroke, which is a common cause of death.<sup><xref ref-type="bibr" rid="B33">33</xref></sup></p>
        <p>Nonetheless, the current study has some limitations. First, this was a single-center study. Therefore, the effect of perioperative and surgical management, as well as patient characteristics, could potentially skew the results, and it can be said that our study has a relatively small sample size. Second, it has a retrospective design, which has biases. The main strength of this study, on the other hand, is that this is the first study to describe the utility of SII as a preoperative risk-associated parameter for in-hospital mortality after CPB. Although not a diagnostic test, this routine parameter is useful as an easily accessible tool for predicting potential complications after CPB.</p>
      </sec>
      <sec sec-type="conclusions">
        <title>Conclusion</title>
        <p>High preoperative SII scores can be used for early determination of appropriate treatments, which may improve surgical outcomes of cardiac surgery in the future. In addition, when patients were regrouped based on SII cut-off values in the current study, it was observed that hospital stay and postoperative length of stay increased significantly in the SII high group. This study will also help provide economic benefits as these results can be associated with increased patient care costs. We believe that our study will inspire more large-scale research into postoperative adverse effects.</p>
      </sec>
    </body>
    <back>
      <fn-group>
        <fn fn-type="financial-disclosure" id="fn5">
          <p>
            <bold>Sources of funding</bold>
          </p>
          <p>There were no external funding sources for this study.</p>
        </fn>
        <fn fn-type="other" id="fn6">
          <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>
