Machine learning-based prediction of circuit clotting during pediatric continuous kidney replacement therapy sessions.

Journal: Pediatric nephrology (Berlin, Germany)
Published Date:

Abstract

BACKGROUND: Continuous kidney replacement therapy (CKRT) is commonly used for managing acute kidney injury (AKI) in critically ill pediatric patients. However, unexpected circuit clotting remains a frequent complication, resulting in therapy interruptions, blood loss, and increased clinical workload. Timely prediction of clotting could enhance circuit management and patient outcomes.

Authors

  • Emanuele Buccione
    Health Local Authority3 of Pescara, Pescara, Italy. emanuele.buccione@ausl.pe.it.
  • Davide Passaro
    Sapienza University of Rome, Universita Degli Studi Di Roma La Sapienza, Rome, Italy.
  • Luca Tardella
    Sapienza University of Rome, Universita Degli Studi Di Roma La Sapienza, Rome, Italy.
  • Marina Maffeo
    Meyer Children's Hospital, IRCCS, Florence, Italy.
  • Brigida Tedesco
    Meyer Children's Hospital, IRCCS, Florence, Italy.
  • Denise Colosimo
    Meyer Children's Hospital, IRCCS, Florence, Italy.
  • Zaccaria Ricci
    Meyer Children's Hospital, IRCCS, Florence, Italy.

Keywords

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