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

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...

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Autores principales: Tieges, Zoë, Stott, David J., Shaw, Robert, Tang, Elaine, Rutter, Lisa-Marie, Nouzova, Eva, Duncan, Nikki, Clarke, Caoimhe, Weir, Christopher J., Assi, Valentina, Ensor, Hannah, Barnett, Jennifer H., Evans, Jonathan, Green, Samantha, Hendry, Kirsty, Thomson, Meigan, McKeever, Jenny, Middleton, Duncan G., Parks, Stuart, Walsh, Tim, Weir, Alexander J., Wilson, Elizabeth, Quasim, Tara, MacLullich, Alasdair M. J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6980392/
https://www.ncbi.nlm.nih.gov/pubmed/31978127
http://dx.doi.org/10.1371/journal.pone.0227471
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author Tieges, Zoë
Stott, David J.
Shaw, Robert
Tang, Elaine
Rutter, Lisa-Marie
Nouzova, Eva
Duncan, Nikki
Clarke, Caoimhe
Weir, Christopher J.
Assi, Valentina
Ensor, Hannah
Barnett, Jennifer H.
Evans, Jonathan
Green, Samantha
Hendry, Kirsty
Thomson, Meigan
McKeever, Jenny
Middleton, Duncan G.
Parks, Stuart
Walsh, Tim
Weir, Alexander J.
Wilson, Elizabeth
Quasim, Tara
MacLullich, Alasdair M. J.
author_facet Tieges, Zoë
Stott, David J.
Shaw, Robert
Tang, Elaine
Rutter, Lisa-Marie
Nouzova, Eva
Duncan, Nikki
Clarke, Caoimhe
Weir, Christopher J.
Assi, Valentina
Ensor, Hannah
Barnett, Jennifer H.
Evans, Jonathan
Green, Samantha
Hendry, Kirsty
Thomson, Meigan
McKeever, Jenny
Middleton, Duncan G.
Parks, Stuart
Walsh, Tim
Weir, Alexander J.
Wilson, Elizabeth
Quasim, Tara
MacLullich, Alasdair M. J.
author_sort Tieges, Zoë
collection PubMed
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.
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spelling pubmed-69803922020-02-07 A smartphone-based test for the assessment of attention deficits in delirium: A case-control diagnostic test accuracy study in older hospitalised patients Tieges, Zoë Stott, David J. Shaw, Robert Tang, Elaine Rutter, Lisa-Marie Nouzova, Eva Duncan, Nikki Clarke, Caoimhe Weir, Christopher J. Assi, Valentina Ensor, Hannah Barnett, Jennifer H. Evans, Jonathan Green, Samantha Hendry, Kirsty Thomson, Meigan McKeever, Jenny Middleton, Duncan G. Parks, Stuart Walsh, Tim Weir, Alexander J. Wilson, Elizabeth Quasim, Tara MacLullich, Alasdair M. J. PLoS One Research Article 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. Public Library of Science 2020-01-24 /pmc/articles/PMC6980392/ /pubmed/31978127 http://dx.doi.org/10.1371/journal.pone.0227471 Text en © 2020 Tieges et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Tieges, Zoë
Stott, David J.
Shaw, Robert
Tang, Elaine
Rutter, Lisa-Marie
Nouzova, Eva
Duncan, Nikki
Clarke, Caoimhe
Weir, Christopher J.
Assi, Valentina
Ensor, Hannah
Barnett, Jennifer H.
Evans, Jonathan
Green, Samantha
Hendry, Kirsty
Thomson, Meigan
McKeever, Jenny
Middleton, Duncan G.
Parks, Stuart
Walsh, Tim
Weir, Alexander J.
Wilson, Elizabeth
Quasim, Tara
MacLullich, Alasdair M. J.
A smartphone-based test for the assessment of attention deficits in delirium: A case-control diagnostic test accuracy study in older hospitalised patients
title A smartphone-based test for the assessment of attention deficits in delirium: A case-control diagnostic test accuracy study in older hospitalised patients
title_full A smartphone-based test for the assessment of attention deficits in delirium: A case-control diagnostic test accuracy study in older hospitalised patients
title_fullStr A smartphone-based test for the assessment of attention deficits in delirium: A case-control diagnostic test accuracy study in older hospitalised patients
title_full_unstemmed A smartphone-based test for the assessment of attention deficits in delirium: A case-control diagnostic test accuracy study in older hospitalised patients
title_short A smartphone-based test for the assessment of attention deficits in delirium: A case-control diagnostic test accuracy study in older hospitalised patients
title_sort smartphone-based test for the assessment of attention deficits in delirium: a case-control diagnostic test accuracy study in older hospitalised patients
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6980392/
https://www.ncbi.nlm.nih.gov/pubmed/31978127
http://dx.doi.org/10.1371/journal.pone.0227471
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