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

• Main Authors: Zoë 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 Walsh, Alexander J Weir, Elizabeth Wilson, Tara Quasim, Alasdair M J MacLullich
• Format: Article
• Language: English
• Published: Public Library of Science (PLoS) 2020-01-01
• Series: PLoS ONE
• Online Access: https://doi.org/10.1371/journal.pone.0227471

<h4>Background</h4>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.<h4>Methods</h4>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.<h4>Results</h4>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).<h4>Conclusion</h4>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.