Predicting Post-surgery Discharge Time in Pediatric Patients Using Machine Learning.

Journal: Translational medicine @ UniSa
Published Date: Jul 18, 2024

Abstract

BACKGROUND: Prolonged hospital stays after pediatric surgeries, such as tonsillectomy and adenoidectomy, pose significant concerns regarding cost and patient care. Dissecting the determinants of extended hospitalization is crucial for optimizing postoperative care and resource allocation.

Authors

  • Marco Cascella
    Department of Medicine, Surgery and Dentistry, University of Salerno, 84081, Baronissi, Italy.
  • Cosimo Guerra
    Department of Medicine, Surgery and Dentistry, 'Scuola Medica Salernitana' University of Salerno, 84081, Baronissi, Italy.
  • Atanas G Atanasov
    Institute of Genetics and Animal Biotechnology of the Polish Academy of Sciences, Jastrzebiec, 05-552, Magdalenka, Poland.
  • Maria G Calevo
    Epidemiology and Biostatistics Unit, Scientific Direction, IRCCS Istituto Giannina Gaslini, Genoa, Italy.
  • Ornella Piazza
    Anesthesia and Pain Medicine, Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", University of Salerno, Baronissi, 84081, Italy.
  • Alessandro Vittori
    Department of Anesthesia and Critical Care, ARCO ROMA, Ospedale Pediatrico Bambino Gesù IRCCS, Piazza S. Onofrio 4, 00165, Rome, Italy.
  • Alessandro Simonini
    Pediatric Anesthesia and Intensive Care Unit AOU delle Marche, Salesi Children's Hospital, 60121, Ancona, Italy.

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