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Data-driven monitoring in patients on left ventricular assist device support.
Numan, Lieke; Moazeni, Mehran; Oerlemans, Marish I F J; Aarts, Emmeke; Van Der Kaaij, Niels P; Asselbergs, Folkert W; Van Laake, Linda W.
Afiliação
  • Numan L; Department of Cardiology, University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, 3584 CX, Utrecht, the Netherlands.
  • Moazeni M; Department of Methodology and Statistics, Utrecht University, Heidelberglaan 8, 3584 CS, Utrecht, the Netherlands.
  • Oerlemans MIFJ; Department of Cardiology, University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, 3584 CX, Utrecht, the Netherlands.
  • Aarts E; Department of Methodology and Statistics, Utrecht University, Heidelberglaan 8, 3584 CS, Utrecht, the Netherlands.
  • Van Der Kaaij NP; Department of Cardiothoracic Surgery, University Medical Centre Utrecht, Utrecht University, Utrecht, The Netherlands.
  • Asselbergs FW; Department of Cardiology, University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, 3584 CX, Utrecht, the Netherlands.
  • Van Laake LW; Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, Gower Street, WC1E 6BT, London, UK.
Expert Rev Med Devices ; 19(9): 677-685, 2022 Sep.
Article em En | MEDLINE | ID: mdl-36285341
INTRODUCTION: Despite an increasing population of patients supported with a left ventricular assist device (LVAD), it remains a complex therapy, and patients are frequently admitted. Therefore, a strict follow-up including frequent hospital visits, patient self-management and telemonitoring is needed. AREAS COVERED: The current review describes the principles of LVADs, the possibilities of (tele)monitoring using noninvasive and invasive devices. Furthermore, possibilities, challenges, and future perspectives in this emerging field are discussed. EXPERT OPINION: Several studies described initial experiences on telemonitoring in LVAD patients, using mobile phone applications to collect clinical data and pump data. This may replace frequent hospital visits in near future. In addition, algorithms were developed aiming to early detect pump thrombosis or driveline infections. Since not all complications are reflected by pump parameters, data from different sources should be combined to detect a broader spectrum of complications in an early stage. We need to focus on the development of sophisticated but understandable algorithms and infrastructure combining different data sources, while addressing essential aspects such as data safety, privacy, and cost-effectiveness.
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Texto completo: 1 Temas: ECOS / Aspectos_gerais Bases de dados: MEDLINE Assunto principal: Trombose / Coração Auxiliar / Insuficiência Cardíaca Limite: Humans Idioma: En Revista: Expert Rev Med Devices Assunto da revista: DIAGNOSTICO POR IMAGEM / TERAPEUTICA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Holanda

Texto completo: 1 Temas: ECOS / Aspectos_gerais Bases de dados: MEDLINE Assunto principal: Trombose / Coração Auxiliar / Insuficiência Cardíaca Limite: Humans Idioma: En Revista: Expert Rev Med Devices Assunto da revista: DIAGNOSTICO POR IMAGEM / TERAPEUTICA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Holanda