A smartphone-based test for the assessment of attention deficits in delirium: A case-control diagnostic test accuracy study in older hospitalised patients
Creators: name: Tieges, Zoë
name: Stott, David J.
name: Shaw, Robert
name: Tang, Elaine
name: Rutter, Lisa-Marie
name: Nouzova, Eva
name: Duncan, Nikki
name: Clarke, Caoimhe
name: Weir, Christopher J.
name: Assi, Valentina
name: Ensor, Hannah
name: Barnett, Jennifer H.
name: Evans, Jonathan
name: Green, Samantha
name: Hendry, Kirsty
name: Thomson, Meigan
name: McKeever, Jenny
name: Middleton, Duncan G.
name: Parks, Stuart
name: Walsh, Tim
name: Weir, Alexander J.
name: Wilson, Elizabeth
name: Quasim, Tara
name: MacLullich, Alasdair M. J.
Publisher: name: Apollo - University of Cambridge Repository
Year: 2020
Subjects: subject: Research Article
subject: Biology and life sciences
subject: Medicine and health sciences
subject: Social sciences
subject: FOS: Social sciences
subject: FOS: Social sciences
subject: Research and analysis methods
subject: Engineering and technology
subject: FOS: Engineering and technology
subject: FOS: Engineering and technology

description: Background: 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. Methods: 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. Results: 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). Conclusion: 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.