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DeltaScan for the Assessment of Acute Encephalopathy and Delirium in ICU and non-ICU Patients, a Prospective Cross-Sectional Multicenter Validation Study: Fienke L. Ditzel, MD. e-mail: [email protected]

  • Fienke L. Ditzel*
  • , Suzanne C.A. Hut
  • , Mark van den Boogaard
  • , Michel Boonstra
  • , Frans S.S. Leijten
  • , Evert Jan Wils
  • , Tim van Nesselrooij
  • , Marjan Kromkamp
  • , Paul J.T. Rood
  • , Christian Röder
  • , Paul F. Bouvy
  • , Michiel Coesmans
  • , Robert Jan Osse
  • , Monica Pop-Purceleanu
  • , Edwin van Dellen
  • , Jaap W.M. Krulder
  • , Koen Milisen
  • , Richard Faaij
  • , Ariël M. Vondeling
  • , Ad M. Kamper
  • Barbara C. van Munster, Annemarieke de Jonghe, Marian A.M. Winters, Jeanette van der Ploeg, Sanneke van der Zwaag, Dineke H.L. Koek, Clara A.C. Drenth-van Maanen, Albertus Beishuizen, Deirdre M. van den Bos, Wiepke Cahn, Ewoud Schuit, Arjen J.C. Slooter
*Corresponding author for this work
  • Utrecht University
  • Radboud University Medical Center
  • HAN University of Applied Sciences
  • Vrije Universiteit Brussel
  • KU Leuven
  • University Hospitals Leuven
  • Diakonessenhuis Utrecht
  • Isala Clinics
  • University Medical Centre Groningen
  • Alzheimer Center Groningen (BCM)
  • Tergooi Ziekenhuis
  • Medisch Spectrum Twente

Research output: Contribution to journalArticleAcademicpeer-review

10 Citations (Scopus)
75 Downloads (Pure)

Abstract

Objectives: To measure the diagnostic accuracy of DeltaScan: a portable real-time brain state monitor for identifying delirium, a manifestation of acute encephalopathy (AE) detectable by polymorphic delta activity (PDA) in single-channel electroencephalograms (EEGs). Design: Prospective cross-sectional study. Setting: Six Intensive Care Units (ICU's) and 17 non-ICU departments, including a psychiatric department across 10 Dutch hospitals. Participants: 494 patients, median age 75 (IQR:64-87), 53% male, 46% in ICUs, 29% delirious. Measurements: DeltaScan recorded 4-minute EEGs, using an algorithm to select the first 96 seconds of artifact-free data for PDA detection. This algorithm was trained and calibrated on two independent datasets. Methods: Initial validation of the algorithm for AE involved comparing its output with an expert EEG panel's visual inspection. The primary objective was to assess DeltaScan's accuracy in identifying delirium against a delirium expert panel's consensus. Results: DeltaScan had a 99% success rate, rejecting 6 of the 494 EEG's due to artifacts. Performance showed and an Area Under the Receiver Operating Characteristic Curve (AUC) of 0.86 (95% CI: 0.83-0.90) for AE (sensitivity: 0.75, 95%CI=0.68-0.81, specificity: 0.87 95%CI=0.83-0.91. The AUC was 0.71 for delirium (95%CI=0.66-0.75, sensitivity: 0.61 95%CI=0.52-0.69, specificity: 72, 95%CI=0.67-0.77). Our validation aim was an NPV for delirium above 0.80 which proved to be 0.82 (95%CI: 0.77-0.86). Among 84 non-delirious psychiatric patients, DeltaScan differentiated delirium from other disorders with a 94% (95%CI: 87-98%) specificity. Conclusions: DeltaScan can diagnose AE at bedside and shows a clear relationship with clinical delirium. Further research is required to explore its role in predicting delirium-related outcomes.

Original languageEnglish
Pages (from-to)1093-1104
Number of pages12
JournalAmerican Journal of Geriatric Psychiatry
Volume32
Issue number9
DOIs
Publication statusPublished - Sept 2024

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Publisher Copyright: © 2023 The Authors

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This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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