Predicting adverse long-term neurocognitive outcomes after pediatric intensive care unit admission.

Journal: Computer methods and programs in biomedicine
Published Date: Apr 10, 2024

Abstract

BACKGROUND AND OBJECTIVE: Critically ill children may suffer from impaired neurocognitive functions years after ICU (intensive care unit) discharge. To assess neurocognitive functions, these children are subjected to a fixed sequence of tests. Undergoing all tests is, however, arduous for former pediatric ICU patients, resulting in interrupted evaluations where several neurocognitive deficiencies remain undetected. As a solution, we propose using machine learning to predict the optimal order of tests for each child, reducing the number of tests required to identify the most severe neurocognitive deficiencies.

Authors

  • Felipe Kenji Nakano
    KU Leuven, Campus KULAK - Department of Public Health and Primary Care, Etienne Sabbelaan 53, Kortrijk, 8500, Belgium. felipekenji.nakano@kuleuven.be.
  • Karolijn Dulfer
    Intensive Care Unit, Department of Paediatrics and Paediatric Surgery, Erasmus Medical Centre, Sophia Children's Hospital, Doctor Molewaterplein 40, Rotterdam, 3015 GD, the Netherlands.
  • Ilse Vanhorebeek
    Clinical Division and Laboratory of Intensive Care Medicine, Department of Cellular and Molecular Medicine, UZ Herestraat 49, Leuven, 3000, Belgium.
  • Pieter J Wouters
    Clinical Division and Laboratory of Intensive Care Medicine, Department of Cellular and Molecular Medicine, UZ Herestraat 49, Leuven, 3000, Belgium.
  • Sascha C Verbruggen
    Intensive Care Unit, Department of Paediatrics and Paediatric Surgery, Erasmus Medical Centre, Sophia Children's Hospital, Doctor Molewaterplein 40, Rotterdam, 3015 GD, the Netherlands.
  • Koen F Joosten
    Intensive Care Unit, Department of Paediatrics and Paediatric Surgery, Erasmus Medical Centre, Sophia Children's Hospital, Doctor Molewaterplein 40, Rotterdam, 3015 GD, the Netherlands.
  • Fabian Güiza Grandas
    Clinical Division and Laboratory of Intensive Care Medicine, Department of Cellular and Molecular Medicine, UZ Herestraat 49, Leuven, 3000, Belgium.
  • Celine Vens
    Department of Computer Science, KU Leuven, Leuven, Belgium.
  • Greet Van den Berghe
    Clinical Division and Laboratory of Intensive Care Medicine, Academic Department of Cellular and Molecular Medicine, KU Leuven, Herestraat 49, B-3000, Leuven, Belgium.

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