A smartphone-based test for the assessment of attention deficits in delirium: a case-control diagnostic test accuracy study in older hospitalised patients

Zoe Tieges*, David J. Stott, Robert Shaw, Elaine Tang, Lisa-Marie Rutter, Eva Nouzova, Nikki Duncan, Caoimhe Clarke, Christopher J. Weir, Valentina Assi, Hannah Ensor, Jennifer H. Barnett, Jonathan Evans, Samantha Green, Kirsty Hendry, Meigan Thomson, Jenny McKeever, Duncan G. Middleton, Stuart Parks, Tim WalshAlexander J. Weir, Elizabeth Wilson, Tara Quasim, Alasdair M.J. MacLullich

*Corresponding author for this work

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Delirium is a common and serious acute neuropsychiatric syndrome which is often missed in routine clinical care. Inattention is the core cognitive feature. Diagnostic test accuracy (including cut-points) of a smartphone Delirium App (DelApp) for assessing attention deficits was assessed in older hospital inpatients.

This was a case-control study of hospitalised patients aged ≥65 years with delirium (with or without pre-existing cognitive impairment), who were compared to patients with dementia without delirium, and patients without cognitive impairment. Reference standard delirium assessment, which included a neuropsychological test battery, was based on Diagnostic and Statistical Manual of Mental Disorders-5 criteria. A separate blinded assessor administered the DelApp arousal assessment (score 0–4) and attention task (0–6) yielding an overall score of 0 to 10 (lower scores indicate poorer performance). Analyses included receiver operating characteristic curves and sensitivity and specificity. Optimal cut-points for delirium detection were determined using Youden’s index.

A total of 187 patients were recruited, mean age 83.8 (range 67–98) years, 152 (81%) women; n = 61 with delirium; n = 61 with dementia without delirium; and n = 65 without cognitive impairment. Patients with delirium performed poorly on the DelApp (median score = 4/10; inter-quartile range 3.0, 5.5) compared to patients with dementia (9.0; 5.5, 10.0) and those without cognitive impairment (10.0; 10.0, 10.0). Area under the curve for detecting delirium was 0.89 (95% Confidence Interval 0.84, 0.94). At an optimal cut-point of ≤8, sensitivity was 91.7% (84.7%, 98.7%) and specificity 74.2% (66.5%, 81.9%) for discriminating delirium from the other groups. Specificity was 68.3% (56.6%, 80.1%) for discriminating delirium from dementia (cut-point ≤6).

Patients with delirium (with or without pre-existing cognitive impairment) perform poorly on the DelApp compared to patients with dementia and those without cognitive impairment. A cut-point of ≤8/10 is suggested as having optimal sensitivity and specificity. The DelApp is a promising tool for assessment of attention deficits associated with delirium in older hospitalised adults, many of whom have prior cognitive impairment, and should be further validated in representative patient cohorts.
Original languageEnglish
Article numbere0227471
Pages (from-to)e0227471
Number of pages15
JournalPLoS ONE
Issue number1
Publication statusPublished - 24 Jan 2020


  • DelApp
  • delirium
  • smartphones
  • diagnostic tests
  • hospitalised patients

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • General
  • Biochemistry, Genetics and Molecular Biology(all)


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