Development and feasibility of a smartphone-based test for the objective detection and monitoring of attention impairments in delirium in the ICU

J Crit Care. 2018 Dec:48:104-111. doi: 10.1016/j.jcrc.2018.08.019. Epub 2018 Aug 21.

Abstract

Purpose: Delirium in the ICU is under-diagnosed. We evaluated feasibility and performance of a novel smartphone-based test for objectively detecting inattention in delirium.

Material and methods: DelApp-ICU combines a behavioural assessment and an attention task, whereby participants follow simple commands and count serially presented circles (score range 0-12, lower scores indicating worse performance). We assessed feasibility through staff interviews. Then we performed a preliminary case-control study in patients with and without delirium (ascertained with the Confusion Assessment Method for the ICU) who underwent the DelApp-ICU on up to 4 days.

Results: Forty-six patients (median age = 57.5 years, range 18-83) were assessed 89 times in total (N's = 46, 29, 10 and 4 for subsequent assessments; 33.7% delirious). DelApp-ICU scores were lower in delirium (N = 20; median = 0.5, Inter-Quartile Range (IQR) = 0-4.75) compared to no delirium (N = 26, median = 12, IQR = 8-12) on days 1, 2 and 3 (p < 0.001, p < 0.001 and p < 0.05, respectively). A DelApp-ICU score ≤6 was 100% sensitive and 96% specific to delirium on day 1. Positive and Negative Predictive Values were 91% and 100%, respectively. DelApp-ICU scores were responsive to changes in CAM-ICU status.

Conclusions: DelApp-ICU shows promise for assessing inattention and delirium in ICU patients, including longitudinally monitoring deficits and providing a metric of delirium severity.

Keywords: Arousal; Attention Impairments; Case-Control Study; Cognitive Assessment; Delirium; Smartphone.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Attention* / physiology
  • Case-Control Studies
  • Delirium / diagnosis*
  • Delirium / physiopathology
  • Delirium / psychology*
  • Feasibility Studies
  • Female
  • Humans
  • Intensive Care Units
  • Male
  • Middle Aged
  • Mobile Applications*
  • Program Development
  • Smartphone*