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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 pub-id-type="publisher-id" specific-use="scielo-v3">QdztY5tBPthTc7Tvc4FLY8q</article-id>
      <article-id pub-id-type="other">01190</article-id>
      <article-id pub-id-type="publisher-id" specific-use="scielo-v2">S0066-782X2020001401190</article-id>
      <article-id pub-id-type="publisher-id">abc.20201127</article-id>
      <article-id pub-id-type="doi">10.36660/abc.20201127</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Carta Cient&#237;fica</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>T&#243;picos Emergentes em Insufici&#234;ncia Card&#237;aca: O Futuro na Insufici&#234;ncia Card&#237;aca: Telemonitoramento, <italic>Wearables</italic> , Intelig&#234;ncia Artificial e Ensino na Era P&#243;s-Pandemia</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0003-3778-7153</contrib-id>
          <name>
            <surname>Freitas</surname>
            <given-names>Aguinaldo F</given-names>
            <suffix>Jr</suffix>
          </name>
          <xref ref-type="aff" rid="aff1">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0002-2924-7328</contrib-id>
          <name>
            <surname>Silveira</surname>
            <given-names>F&#225;bio S.</given-names>
          </name>
          <xref ref-type="aff" rid="aff2">
            <sup>2</sup>
          </xref>
          <xref ref-type="aff" rid="aff3">
            <sup>3</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0001-5170-0144</contrib-id>
          <name>
            <surname>Concei&#231;&#227;o-Souza</surname>
            <given-names>Germano E.</given-names>
          </name>
          <xref ref-type="aff" rid="aff4">
            <sup>4</sup>
          </xref>
          <xref ref-type="aff" rid="aff5">
            <sup>5</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0001-6014-5533</contrib-id>
          <name>
            <surname>Canesin</surname>
            <given-names>Manoel F.</given-names>
          </name>
          <xref ref-type="aff" rid="aff6">
            <sup>6</sup>
          </xref>
          <xref ref-type="aff" rid="aff7">
            <sup>7</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0002-0706-0933</contrib-id>
          <name>
            <surname>Schwartzmann</surname>
            <given-names>Pedro V.</given-names>
          </name>
          <xref ref-type="aff" rid="aff8">
            <sup>8</sup>
          </xref>
          <xref ref-type="aff" rid="aff9">
            <sup>9</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0001-7577-8018</contrib-id>
          <name>
            <surname>Bernardez-Pereira</surname>
            <given-names>Sabrina</given-names>
          </name>
          <xref ref-type="aff" rid="aff10">
            <sup>10</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0002-4488-9601</contrib-id>
          <name>
            <surname>Bestetti</surname>
            <given-names>Reinaldo B.</given-names>
          </name>
          <xref ref-type="aff" rid="aff11">
            <sup>11</sup>
          </xref>
        </contrib>
      </contrib-group>
      <aff id="aff1">
        <label>1</label>
        <institution content-type="orgdiv1">Hospital das Cl&#237;nicas</institution>
        <institution content-type="orgname">Universidade Federal de Goi&#225;s</institution>
        <addr-line>
          <named-content content-type="city">Goi&#226;nia</named-content>
          <named-content content-type="state">GO</named-content>
        </addr-line>
        <country country="BR">Brasil</country>
        <institution content-type="original">Hospital das Cl&#237;nicas da Universidade Federal de Goi&#225;s (HC-UFG), Goi&#226;nia, GO - Brasil</institution>
      </aff>
      <aff id="aff2">
        <label>2</label>
        <institution content-type="orgname">Funda&#231;&#227;o Benefic&#234;ncia Hospital de Cirurgia</institution>
        <addr-line>
          <named-content content-type="city">Aracaju</named-content>
          <named-content content-type="state">SE</named-content>
        </addr-line>
        <country country="BR">Brasil</country>
        <institution content-type="original">Funda&#231;&#227;o Benefic&#234;ncia Hospital de Cirurgia (FBHC-Ebserh), Aracaju, SE - Brasil</institution>
      </aff>
      <aff id="aff3">
        <label>3</label>
        <institution content-type="orgname">Centro de Pesquisa Cl&#237;nica do Cora&#231;&#227;o</institution>
        <addr-line>
          <named-content content-type="city">Aracaju</named-content>
          <named-content content-type="state">SE</named-content>
        </addr-line>
        <country country="BR">Brasil</country>
        <institution content-type="original">Centro de Pesquisa Cl&#237;nica do Cora&#231;&#227;o, Aracaju, SE - Brasil</institution>
      </aff>
      <aff id="aff4">
        <label>4</label>
        <institution content-type="orgname">Hospital Alem&#227;o Oswaldo Cruz</institution>
        <addr-line>
          <named-content content-type="city">S&#227;o Paulo</named-content>
          <named-content content-type="state">SP</named-content>
        </addr-line>
        <country country="BR">Brasil</country>
        <institution content-type="original">Hospital Alem&#227;o Oswaldo Cruz, S&#227;o Paulo, SP - Brasil</institution>
      </aff>
      <aff id="aff5">
        <label>5</label>
        <institution content-type="orgname">Hospital Regional de S&#227;o Jos&#233; dos Campos</institution>
        <addr-line>
          <named-content content-type="city">S&#227;o Jos&#233; dos Campos</named-content>
          <named-content content-type="state">SP</named-content>
        </addr-line>
        <country country="BR">Brasil</country>
        <institution content-type="original">Hospital Regional de S&#227;o Jos&#233; dos Campos, S&#227;o Jos&#233; dos Campos, SP - Brasil</institution>
      </aff>
      <aff id="aff6">
        <label>6</label>
        <institution content-type="orgdiv1">Hospital Universit&#225;rio</institution>
        <institution content-type="orgname">Universidade Estadual de Londrina</institution>
        <addr-line>
          <named-content content-type="city">Londrina</named-content>
          <named-content content-type="state">PR</named-content>
        </addr-line>
        <country country="BR">Brasil</country>
        <institution content-type="original">Hospital Universit&#225;rio - Universidade Estadual de Londrina (HU-UEL), Londrina, PR - Brasil</institution>
      </aff>
      <aff id="aff7">
        <label>7</label>
        <institution content-type="orgname">ACTIVE - Metodologias Ativas de Ensino</institution>
        <addr-line>
          <named-content content-type="city">S&#227;o Paulo</named-content>
          <named-content content-type="state">SP</named-content>
        </addr-line>
        <country country="BR">Brasil</country>
        <institution content-type="original">ACTIVE - Metodologias Ativas de Ensino, S&#227;o Paulo, SP - Brasil</institution>
      </aff>
      <aff id="aff8">
        <label>8</label>
        <institution content-type="orgname">Hospital Unimed Ribeir&#227;o Preto</institution>
        <addr-line>
          <named-content content-type="city">Ribeir&#227;o Preto</named-content>
          <named-content content-type="state">SP</named-content>
        </addr-line>
        <country country="BR">Brasil</country>
        <institution content-type="original">Hospital Unimed Ribeir&#227;o Preto, Ribeir&#227;o Preto, SP - Brasil</institution>
      </aff>
      <aff id="aff9">
        <label>9</label>
        <institution content-type="orgname">Centro Avan&#231;ado de Pesquisa, Ensino e Diagn&#243;stico</institution>
        <addr-line>
          <named-content content-type="city">Ribeir&#227;o Preto</named-content>
          <named-content content-type="state">SP</named-content>
        </addr-line>
        <country country="BR">Brasil</country>
        <institution content-type="original">Centro Avan&#231;ado de Pesquisa, Ensino e Diagn&#243;stico (Caped), Ribeir&#227;o Preto, SP - Brasil</institution>
      </aff>
      <aff id="aff10">
        <label>10</label>
        <institution content-type="orgname">Hospital de Cora&#231;&#227;o</institution>
        <addr-line>
          <named-content content-type="city">S&#227;o Paulo</named-content>
          <named-content content-type="state">SP</named-content>
        </addr-line>
        <country country="BR">Brasil</country>
        <institution content-type="original">Hospital de Cora&#231;&#227;o (HCor), S&#227;o Paulo, SP - Brasil</institution>
      </aff>
      <aff id="aff11">
        <label>11</label>
        <institution content-type="orgdiv1">Departamento de Medicina</institution>
        <institution content-type="orgname">Universidade de Ribeir&#227;o Preto</institution>
        <addr-line>
          <named-content content-type="city">Ribeir&#227;o Preto</named-content>
          <named-content content-type="state">SP</named-content>
        </addr-line>
        <country country="BR">Brasil</country>
        <institution content-type="original">Departamento de Medicina, Universidade de Ribeir&#227;o Preto (Unaerp), Ribeir&#227;o Preto, SP &#8211; Brasil</institution>
      </aff>
      <author-notes>
        <corresp id="c01"> Correspond&#234;ncia: Reinaldo B Bestetti &#8226; Universidade de Ribeir&#227;o Preto, Curso de Medicina - Av. Costabile Romano, 2201. CEP 14096-900, Ribeir&#227;o Preto, SP &#8211; Brasil E-mail <email>rbestetti44@gmail.com</email>
				</corresp>
        <fn fn-type="con">
          <p>Contribui&#231;&#227;o dos Autores</p>
          <p>Reda&#231;&#227;o do manuscrito: Freitas Jr. AF, Silveira FS, Concei&#231;&#227;o-Souza GE, Canesin MF, Schwartzmann PV, Bernardez-Pereira S, Bestetti RB; Revis&#227;o cr&#237;tica do manuscrito quanto ao conte&#250;do intelectual importante: Bernardez-Pereira S, Bestetti RB.</p>
        </fn>
        <fn fn-type="conflict">
          <p>Potencial Conflito de Interesses</p>
          <p>Declaro n&#227;o haver conflito de interesses pertinentes.</p>
        </fn>
      </author-notes>
      <pub-date date-type="pub" publication-format="electronic">
        <day>18</day>
        <month>01</month>
        <year>2021</year>
      </pub-date>
      <pub-date date-type="collection" publication-format="electronic">
        <month>12</month>
        <year>2020</year>
      </pub-date>
      <volume>115</volume>
      <issue>6</issue>
      <fpage>1190</fpage>
      <lpage>1192</lpage>
      <history>
        <date date-type="received">
          <day>20</day>
          <month>10</month>
          <year>2020</year>
        </date>
        <date date-type="rev-recd">
          <day>20</day>
          <month>10</month>
          <year>2020</year>
        </date>
        <date date-type="accepted">
          <day>20</day>
          <month>10</month>
          <year>2020</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 Non-Commercial License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. </license-p>
        </license>
      </permissions>
      <kwd-group xml:lang="pt">
        <kwd>Telemonitoramento</kwd>
        <kwd>Intelig&#234;ncia Artificial</kwd>
        <kwd>Insufici&#234;ncia Card&#237;aca</kwd>
        <kwd>Ensino</kwd>
      </kwd-group>
      <counts>
        <fig-count count="0"/>
        <table-count count="0"/>
        <equation-count count="0"/>
        <ref-count count="18"/>
        <page-count count="3"/>
      </counts>
    </article-meta>
  </front>
  <body>
    <sec>
      <title>Telemonitoramento na Insufici&#234;ncia Card&#237;aca (IC) e Manejo Remoto</title>
      <p>O telemonitoramento consiste no monitoramento e suporte &#224; dist&#226;ncia (TMO) do paciente com IC cr&#244;nica. O TMO pode ser n&#227;o invasivo (TMONI) ou invasivo (TMOI). O TMONI compreende liga&#231;&#245;es telef&#244;nicas, orienta&#231;&#245;es peri&#243;dicas por meio de material instrutivo, controle e monitoramento do peso corporal, v&#237;deo &#8211; chamadas e teleconsultas.<sup><xref ref-type="bibr" rid="B1">1</xref> , <xref ref-type="bibr" rid="B2">2</xref></sup> O TMOI envolve uma s&#233;rie de dispositivos implant&#225;veis que transmitem, a um servidor &#224; dist&#226;ncia, informa&#231;&#245;es hemodin&#226;micas e imped&#226;ncia intrator&#225;cica.<sup><xref ref-type="bibr" rid="B3">3</xref> , <xref ref-type="bibr" rid="B4">4</xref></sup></p>
      <p>Ensaios cl&#237;nicos de TMONI costumam ter resultados conflitantes. No entanto, metan&#225;lises envolvendo estudos observacionais e randomizados de TMOI e TMONI t&#234;m mostrado impacto positivo no progn&#243;stico de pacientes com IC. A redu&#231;&#227;o na mortalidade geral pode variar de 19 a 31% com o TMOI ou TMIONI em pacientes com IC,<sup><xref ref-type="bibr" rid="B5">5</xref> , <xref ref-type="bibr" rid="B6">6</xref></sup> enquanto a redu&#231;&#227;o na frequ&#234;ncia de interna&#231;&#227;o hospitalar por IC varia de 27 a 39%, principalmente em pacientes em classe funcional III/IV.<sup><xref ref-type="bibr" rid="B7">7</xref> - <xref ref-type="bibr" rid="B9">9</xref></sup></p>
      <p>O TMOI com evid&#234;ncias mais convincentes na IC &#233; o CardioMEMS,<sup><xref ref-type="bibr" rid="B7">7</xref></sup> um dispositivo implantado via percut&#226;nea na art&#233;ria pulmonar, que transmite os valores press&#243;ricos centrais para um servidor seguro e orienta o ajuste nas doses de diur&#233;ticos e vasodilatadores.</p>
    </sec>
    <sec>
      <title><italic>Wearables</italic> na IC: Ferramentas de Monitoramento ou Gadget Eletr&#244;nico?</title>
      <p><italic>Wearables</italic> s&#227;o ferramentas computacionais &#8220;vest&#237;veis&#8221;. Podem ser um rel&#243;gio, uma camisa, uma lente de contato ou um sapato, por exemplo. Esses aparelhos cont&#234;m sensores que podem obter dados em tempo real e transmiti-los para uma nuvem ou para outro dispositivo, permitindo an&#225;lises de uma enorme quantidade de dados, bem como a sua disponibiliza&#231;&#227;o para decis&#245;es diagn&#243;sticas e terap&#234;uticas. Tudo isso &#233; permitido gra&#231;as &#224; evolu&#231;&#227;o da tecnologia de transmiss&#227;o de dados, com o advento do 5G.</p>
      <p>Assim, a Internet das coisas (IoT) realmente se tornar&#225; progressivamente uma realidade em diversos pa&#237;ses. Com a Internet das coisas m&#233;dicas (IoMT), n&#227;o ser&#225; diferente. Com o progressivo barateamento dessas tecnologias, vencendo-se a barreira do custo-efetividade, teremos a oportunidade de testar uma infinidade de <italic>wearables</italic> que poder&#227;o permitir o acesso precoce da equipe de sa&#250;de a dados de telemonitoramento de vari&#225;veis como press&#227;o arterial, pulso, satura&#231;&#227;o de oxig&#234;nio, an&#225;lise postural, queda, frequ&#234;ncia respirat&#243;ria, temperatura, glicemia capilar, entre outros.</p>
      <p>Isso poder&#225; impactar em desfechos clinicamente relevantes, como hospitaliza&#231;&#245;es, custos diretos e indiretos e at&#233; mortalidade, ao mesmo tempo em que se poder&#225; direcionar o manejo dos pacientes com IC para uma medicina de precis&#227;o mais personalizada &#8211; um novo paradigma. Indubitavelmente, h&#225; a necessidade de valida&#231;&#227;o de cada <italic>gadget</italic> que se proponha a trazer estes benef&#237;cios, levando em considera&#231;&#227;o as principais barreiras para sua implementa&#231;&#227;o, mas definitivamente os <italic>wearables</italic> chegaram para ficar.<sup><xref ref-type="bibr" rid="B8">8</xref> , <xref ref-type="bibr" rid="B9">9</xref></sup></p>
    </sec>
    <sec>
      <title>Intelig&#234;ncia Artificial e <italic>Big Data</italic> na IC</title>
      <p>Sistemas computacionais capazes de realizar tarefas que originalmente exigiam atua&#231;&#227;o humana constituem a base da intelig&#234;ncia artificial (IA). Esses sistemas surgiram pela necessidade de interpreta&#231;&#227;o de grande volume de dados ( <italic>big data</italic> ). Os sistemas devem ser capazes de analisar dados simples ou complexos, de forma veloz e com acur&#225;cia, al&#233;m de se adaptarem a eles, sem uma programa&#231;&#227;o est&#225;tica.<sup><xref ref-type="bibr" rid="B10">10</xref></sup> 
 <italic>Machine learning</italic> (ML) e <italic>deep learning</italic> (DL) s&#227;o extens&#245;es da IA. O ML &#233; a pr&#225;tica de usar algoritmos para coletar dados, aprender com eles e ent&#227;o fazer a determina&#231;&#227;o ou predi&#231;&#227;o de alguma coisa, de pessoas ou mesmo de pacientes. Para ser &#250;til e fidedigno, precisa ser constantemente alimentado por dados reais. Al&#233;m disso, o DL, que &#233; o extremo da intera&#231;&#227;o e adapta&#231;&#227;o de aprendizado, pode estabelecer conex&#245;es neurais e diversidade para integrar diferentes bases de dados.<sup><xref ref-type="bibr" rid="B11">11</xref></sup></p>
      <p>A IA, a ML e o DL j&#225; apresentam aplica&#231;&#245;es em estudo para IC, seja como diagn&#243;stico, avalia&#231;&#227;o de progn&#243;stico, TMO ou ainda para selecionar pacientes com maior benef&#237;cio para diversas terapias. Isso pode ser feito, por exemplo, na distin&#231;&#227;o de fen&#243;tipos, alocando pacientes em diferentes perfis de assinatura de doen&#231;a;<sup><xref ref-type="bibr" rid="B12">12</xref></sup> na melhor acur&#225;cia para o diagn&#243;stico de IC aguda em rela&#231;&#227;o ao m&#233;dico;<sup><xref ref-type="bibr" rid="B13">13</xref></sup> e no eventual direcionamento para terapias novas ou j&#225; estabelecidas, como an&#225;lise adicional do ECG basal para identificar paciente melhor respondedor &#224; TRC.<sup><xref ref-type="bibr" rid="B14">14</xref></sup></p>
    </sec>
    <sec>
      <title>Ensino M&#233;dico em IC nos Novos Tempos</title>
      <p>Um dos grandes desafios dos estudos e pesquisa cl&#237;nica &#233; a sua capacidade de traduzi seus resultados cient&#237;ficos para a pr&#225;tica cl&#237;nica. S&#227;o v&#225;rios os fatores envolvidos nesse processo; um importante fator &#233;, particularmente, a capacidade de transmiss&#227;o e aplica&#231;&#227;o efetiva em menor intervalo de tempo desse conhecimento para um maior n&#250;mero de profissionais.</p>
      <p>As mudan&#231;as em ensino m&#233;dico e, consequentemente, no tema IC, passam por uma revolu&#231;&#227;o.<sup><xref ref-type="bibr" rid="B15">15</xref></sup> O que h&#225; pouco tempo se resumia quase que exclusivamente a aulas expositivas, h&#225; anos, atrav&#233;s de t&#233;cnicas de metodologia ativa de ensino e mais recentemente por modelos h&#237;bridos sincr&#244;nicos ou ass&#237;ncronos digitais, o ensino &#233; aperfei&#231;oado, aprimorando o processo de aprendizagem e, consequentemente, o cuidado com o paciente.<sup><xref ref-type="bibr" rid="B16">16</xref></sup></p>
      <p>O modelo atual de ensino deve oferecer o conceito de andragogia,<sup><xref ref-type="bibr" rid="B17">17</xref></sup> associado ao modelo de ensino AGES. Esse modelo engloba a constru&#231;&#227;o de processos expositivos de aprendizagem curtos, que mant&#234;m a aten&#231;&#227;o do expectador ou de alunos, associado &#224; capacidade de gera&#231;&#227;o de motivos intr&#237;nsecos que tragam significado na aprendizagem. Ou seja, envolve emo&#231;&#245;es que possam fortalecer o aprendizado, de forma que este seja constru&#237;do em v&#225;rias etapas ( <italic>Spaced</italic> ). Quando incorporados, todos estes pontos formam uma aprendizagem mais profunda e efetiva, levando ao m&#233;dico e ao profissional de sa&#250;de a possibilidade de adquirir e aplicar na pr&#225;tica os cuidados em IC.<sup><xref ref-type="bibr" rid="B18">18</xref></sup></p>
    </sec>
    <sec>
      <title>Lista de Participantes do Heart Failure Summit Brazil 2020 / Departamento de Insufici&#234;ncia Card&#237;aca - DEIC/SBC</title>
      <p>Aguinaldo Freitas Junior, Andr&#233;ia Biolo, Antonio Carlos Pereira Barretto, Ant&#244;nio Lagoeiro Jorge, Bruno Biselli, Carlos Eduardo Montenegro, Denilson Campos de Albuquerque, Dirceu Rodrigues de Almeida, Edimar Alcides Bocchi, Edval Gomes dos Santos J&#250;nior, Est&#234;v&#227;o Lanna Figueiredo, Evandro Tinoco Mesquita, Fabiana G. Marcondes-Braga, F&#225;bio Fernandes, Fabio Serra Silveira, Felix Jos&#233; Alvarez Ramires, Fernando Atik, Fernando Bacal, Fl&#225;vio de Souza Brito, Germano Emilio Concei&#231;&#227;o Souza, Gustavo Calado de Aguiar Ribeiro, Humberto Villacorta Jr., Jefferson Luis Vieira, Jo&#227;o David de Souza Neto, Jo&#227;o Manoel Rossi Neto, Jos&#233; Albuquerque de Figueiredo Neto, L&#237;dia Ana Zytynski Moura, Livia Adams Goldraich, Lu&#237;s Beck-da- Silva, Lu&#237;s Eduardo Paim Rohde, Luiz Claudio Danzmann, Manoel Fernandes Canesin, Marcelo Bittencourt, Marcelo Westerlund Montera, Marcely Gimenes Bonatto, Marcus Vinicius Sim&#245;es, Maria da Consola&#231;&#227;o Vieira Moreira, Miguel Morita Fernandes da Silva, Monica Samuel Avila, Mucio Tavares de Oliveira Junior, Nadine Clausell, Odilson Marcos Silvestre, Otavio Rizzi Coelho Filho, Pedro Vellosa Schwartzmann, Reinaldo Bulgarelli Bestetti, Ricardo Mourilhe Rocha, Sabrina Bernadez Pereira, Salvador Rassi, Sandrigo Mangini, Silvia Marinho Martins, Silvia Moreira Ayub Ferreira, Victor Sarli Issa.</p>
    </sec>
  </body>
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    <fn-group>
      <fn fn-type="other">
        <p>Carta cient&#237;fica referente ao Heart Failure Summit Brazil 2020 / Departamento de Insufici&#234;ncia Card&#237;aca &#8211; DEIC/SBC</p>
      </fn>
      <fn fn-type="other">
        <p>Vincula&#231;&#227;o Acad&#234;mica</p>
        <p>N&#227;o h&#225; vincula&#231;&#227;o deste estudo a programas de p&#243;s-gradua&#231;&#227;o.</p>
      </fn>
    </fn-group>
    <fn-group>
      <fn fn-type="supported-by">
        <p><bold>Fontes de Financiamento</bold> .O presente estudo n&#227;o teve fontes de financiamento externas.</p>
      </fn>
    </fn-group>
  </back>
  <sub-article article-type="translation" id="TRen" xml:lang="en">
    <front-stub>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Letter</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Emerging Topics in Heart Failure: The Future of Heart Failure: Telemonitoring, Wearables, Artificial Intelligence and Learning in the Post-Pandemic Era</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0003-3778-7153</contrib-id>
          <name>
            <surname>Freitas</surname>
            <given-names>Aguinaldo F</given-names>
            <suffix>Jr</suffix>
          </name>
          <xref ref-type="aff" rid="aff1001">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0002-2924-7328</contrib-id>
          <name>
            <surname>Silveira</surname>
            <given-names>F&#225;bio S.</given-names>
          </name>
          <xref ref-type="aff" rid="aff2001">
            <sup>2</sup>
          </xref>
          <xref ref-type="aff" rid="aff3001">
            <sup>3</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0001-5170-0144</contrib-id>
          <name>
            <surname>Concei&#231;&#227;o-Souza</surname>
            <given-names>Germano E.</given-names>
          </name>
          <xref ref-type="aff" rid="aff4001">
            <sup>4</sup>
          </xref>
          <xref ref-type="aff" rid="aff5001">
            <sup>5</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0001-6014-5533</contrib-id>
          <name>
            <surname>Canesin</surname>
            <given-names>Manoel F.</given-names>
          </name>
          <xref ref-type="aff" rid="aff6001">
            <sup>6</sup>
          </xref>
          <xref ref-type="aff" rid="aff7001">
            <sup>7</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0002-0706-0933</contrib-id>
          <name>
            <surname>Schwartzmann</surname>
            <given-names>Pedro V.</given-names>
          </name>
          <xref ref-type="aff" rid="aff8001">
            <sup>8</sup>
          </xref>
          <xref ref-type="aff" rid="aff9001">
            <sup>9</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0001-7577-8018</contrib-id>
          <name>
            <surname>Bernardez-Pereira</surname>
            <given-names>Sabrina</given-names>
          </name>
          <xref ref-type="aff" rid="aff10001">
            <sup>10</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0002-4488-9601</contrib-id>
          <name>
            <surname>Bestetti</surname>
            <given-names>Reinaldo B.</given-names>
          </name>
          <xref ref-type="aff" rid="aff11001">
            <sup>11</sup>
          </xref>
        </contrib>
      </contrib-group>
      <aff id="aff1001">
        <label>1</label>
        <country country="BR">Brazil</country>
        <institution content-type="original">Hospital das Cl&#237;nicas da Universidade Federal de Goi&#225;s (HC-UFG), Goi&#226;nia, GO - Brazil</institution>
      </aff>
      <aff id="aff2001">
        <label>2</label>
        <country country="BR">Brazil</country>
        <institution content-type="original">Funda&#231;&#227;o Benefic&#234;ncia Hospital de Cirurgia (FBHC-Ebserh), Aracaju, SE - Brazil</institution>
      </aff>
      <aff id="aff3001">
        <label>3</label>
        <country country="BR">Brazil</country>
        <institution content-type="original">Centro de Pesquisa Cl&#237;nica do Cora&#231;&#227;o, Aracaju, SE - Brazil</institution>
      </aff>
      <aff id="aff4001">
        <label>4</label>
        <country country="BR">Brazil</country>
        <institution content-type="original">Hospital Alem&#227;o Oswaldo Cruz, S&#227;o Paulo, SP - Brazil</institution>
      </aff>
      <aff id="aff5001">
        <label>5</label>
        <country country="BR">Brazil</country>
        <institution content-type="original">Hospital Regional de S&#227;o Jos&#233; dos Campos, S&#227;o Jos&#233; dos Campos, SP - Brazil</institution>
      </aff>
      <aff id="aff6001">
        <label>6</label>
        <country country="BR">Brazil</country>
        <institution content-type="original">Hospital Universit&#225;rio - Universidade Estadual de Londrina (HU-UEL), Londrina, PR - Brazil</institution>
      </aff>
      <aff id="aff7001">
        <label>7</label>
        <country country="BR">Brazil</country>
        <institution content-type="original">ACTIVE - Metodologias Ativas de Ensino, S&#227;o Paulo, SP - Brazil</institution>
      </aff>
      <aff id="aff8001">
        <label>8</label>
        <country country="BR">Brazil</country>
        <institution content-type="original">Hospital Unimed Ribeir&#227;o Preto, Ribeir&#227;o Preto, SP - Brazil</institution>
      </aff>
      <aff id="aff9001">
        <label>9</label>
        <country country="BR">Brazil</country>
        <institution content-type="original">Centro Avan&#231;ado de Pesquisa, Ensino e Diagn&#243;stico (Caped), Ribeir&#227;o Preto, SP - Brazil</institution>
      </aff>
      <aff id="aff10001">
        <label>10</label>
        <country country="BR">Brazil</country>
        <institution content-type="original">Hospital de Cora&#231;&#227;o (HCor), S&#227;o Paulo, SP - Brazil</institution>
      </aff>
      <aff id="aff11001">
        <label>11</label>
        <country country="BR">Brazil</country>
        <institution content-type="original">Departamento de Medicina, Universidade de Ribeir&#227;o Preto (Unaerp), Ribeir&#227;o Preto, SP &#8211; Brazil</institution>
      </aff>
      <author-notes>
        <corresp id="c01001"><bold>Mailing Address: Reinaldo B Bestetti</bold> &#8226; Universidade de Ribeir&#227;o Preto, Curso de Medicina - Av. Costabile Romano, 2201. Postal Code 14096-900, Ribeir&#227;o Preto, SP &#8211; Brazil E-mail rbestetti44@gmail.com</corresp>
        <fn fn-type="con">
          <p>Author Contributions</p>
          <p>Writing of the manuscript: Freitas Jr. AF, Silveira FS, Concei&#231;&#227;o-Souza GE, Canesin MF, Schwartzmann PV, Bernardez-Pereira S, Bestetti RB; Critical revision of the manuscript for intellectual content: Bernardez-Pereira S, Bestetti RB.</p>
        </fn>
        <fn fn-type="conflict">
          <p>Potential Conflict of Interest</p>
          <p>No potential conflict of interest relevant to this article was reported.</p>
        </fn>
      </author-notes>
      <kwd-group xml:lang="en">
        <kwd>Telemonitoring</kwd>
        <kwd>Artificial Intelligence</kwd>
        <kwd>Heart Failure</kwd>
        <kwd>Learning</kwd>
      </kwd-group>
    </front-stub>
    <body>
      <sec>
        <title>Telemonitoring in Heart Failure and Remote Management</title>
        <p>Telemonitoring consists of monitoring and remote support for chronic heart failure (HF) patients. Telemonitoring can be non-invasive or invasive. Non-invasive telemonitoring includes telephone calls, periodic guidance through instructional material, control and monitoring of body weight, video calls and teleconsultations.<sup><xref ref-type="bibr" rid="B1">1</xref> , <xref ref-type="bibr" rid="B2">2</xref></sup> Invasive telemonitoring involves implantable devices that transmit hemodynamic and intrathoracic impedance data to a remote server.<sup><xref ref-type="bibr" rid="B3">3</xref> , <xref ref-type="bibr" rid="B4">4</xref></sup></p>
        <p>Clinical trials of non-invasive telemonitoring often show conflicting results. However, meta-analyses of observational and randomized studies on invasive and non-invasive telemonitoring have shown that they have a positive impact on HF prognosis. The reduction in overall mortality in HF patients can vary from 19 to 31% with invasive or non-invasive telemonitoring,<sup><xref ref-type="bibr" rid="B5">5</xref> , <xref ref-type="bibr" rid="B6">6</xref></sup> while reduction in the frequency of hospitalization for HF varies from 27 to 39%, mainly in functional class III/IV patients.<sup><xref ref-type="bibr" rid="B7">7</xref> - <xref ref-type="bibr" rid="B9">9</xref></sup></p>
        <p>Among invasive telemonitoring systems, CardioMEMS<sup><xref ref-type="bibr" rid="B7">7</xref></sup> has the most convincing evidence in HF. This device is implanted percutaneously in the pulmonary artery and transmits central blood pressure values to a secure server, guiding adjustments in diuretic and vasodilator dosage.</p>
      </sec>
      <sec>
        <title>Wearables in HF: Monitoring Tools or More Electronic Gadgets?</title>
        <p>Wearables are computational tools that can be worn on the body. They could be a watch, a shirt, a contact lens, or a shoe, for example. These devices contain sensors that obtain real-time data and transmit it to a cloud or another device, allowing analysis of an enormous amount of data, as well as facilitating diagnostic and therapeutic decision making. All of this has been made possible by the evolution of data transmission technology, particularly the advent of 5G networks.</p>
        <p>Thus, the Internet of things will eventually become a reality in a number of countries. The Internet of medical things will be no different. The progressive cheapening of these technologies will overcome the cost-effectiveness barrier, and we will have the opportunity to test a multitude of wearables that can provide the health team with early access to telemonitoring data for variables such as blood pressure, pulse, blood oxygen, postural analysis, fall, respiratory rate, temperature, capillary blood glucose, etc.</p>
        <p>This could have an impact on clinically relevant outcomes, such as hospitalizations, direct and indirect costs and even mortality. At the same time, the management of HF patients can be directed towards more personalized precision medicine - a new paradigm. Despite the fact that each gadget promising such benefits must undoubtedly be validated (considering the main barriers to its implementation), it seems clear that wearables are here to stay.<sup><xref ref-type="bibr" rid="B8">8</xref> , <xref ref-type="bibr" rid="B9">9</xref></sup></p>
      </sec>
      <sec>
        <title>Artificial Intelligence and Big Data in HF</title>
        <p>Computer systems capable of carrying out tasks that originally required human performance are the basis of artificial intelligence. These systems were developed out of the need to interpret &#8216;big data&#8217;. Systems must be able to quickly and accurately analyze simple or complex data, as well as adapt to the data without static programming.<sup><xref ref-type="bibr" rid="B10">10</xref></sup> Machine learning and deep learning are extensions of artificial intelligence. Machine learning uses algorithms to collect data, learn from them and then make predictions about things or even patients. To be useful and reliable, machine learning systems must be constantly fed real data. In addition, deep learning, which is the vanguard of interaction and adaptive learning, can involve neural connections and diversity to integrate different databases.<sup><xref ref-type="bibr" rid="B11">11</xref></sup></p>
        <p>Artificial intelligence, machine learning and deep learning applications are already being studied for HF with respect to diagnosis, prognosis assessment, telemonitoring or even the selection of patients with the greatest projected benefit from various therapies. This can occur, for example, by distinguishing phenotypes, allocating patients with different disease profiles;<sup><xref ref-type="bibr" rid="B12">12</xref></sup> by determining the best acute HF diagnostic accuracy in relation to the doctor;<sup><xref ref-type="bibr" rid="B13">13</xref></sup> and by targeting new or already established therapies, such as additional analysis of baseline electrocardiograms to identify the best patients for cardiac-resynchronization therapy.<sup><xref ref-type="bibr" rid="B14">14</xref></sup></p>
      </sec>
      <sec>
        <title>Medical Education About HF in These New Times</title>
        <p>One of the greatest challenges for studies and clinical research is translating scientific results into clinical practice. Although there are several factors involved in this process, one particularly important factor is the ability to effectively transmit and apply knowledge to the greatest number of professionals in the least possible time.</p>
        <p>Medical education and, consequently, the subject of HF, are undergoing a revolution.<sup><xref ref-type="bibr" rid="B15">15</xref></sup> For a long time, HF had been reduced almost exclusively to expository classes. However, in recent years, active teaching methodologies and synchronous hybrid models or digital asynchronous models have improved the teaching and learning process and, consequently, patient care.<sup><xref ref-type="bibr" rid="B16">16</xref></sup></p>
        <p>The current teaching model must offer the concept of andragogy,<sup><xref ref-type="bibr" rid="B17">17</xref></sup> which is associated with the AGES teaching model. This model involves short expository learning processes, which maintain viewer/student attention, and produces intrinsic motives that bring meaning to learning. That is, it involves emotions that can strengthen learning, so that learning is spaced over several stages. When incorporated, these approaches lead to more profound and effective learning, enabling doctors and health professionals to absorb and apply the best HF care practices.</p>
      </sec>
    </body>
    <back>
      <fn-group>
        <fn fn-type="other">
          <p>Research letter related to Heart Failure Summit Brazil 2020 / Heart Failure Department - Brazilian Society of Cardiology</p>
        </fn>
        <fn fn-type="other">
          <p>Study Association</p>
          <p>This study is not associated with any thesis or dissertation work.</p>
        </fn>
      </fn-group>
      <fn-group>
        <fn fn-type="supported-by">
          <p><bold>Sources of Funding</bold> .There were no external funding sources for this study.</p>
        </fn>
      </fn-group>
    </back>
  </sub-article>
</article>
