Cargando…
Varied performance of picture description task as a screening tool across MCI subtypes
A picture description task is a component of Miro Health’s platform for self-administration of neurobehavioral assessments. Picture description has been used as a screening tool for identification of individuals with Alzheimer’s disease and mild cognitive impairment (MCI), but currently requires in-...
Autores principales: | , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10010512/ https://www.ncbi.nlm.nih.gov/pubmed/36913425 http://dx.doi.org/10.1371/journal.pdig.0000197 |
_version_ | 1784906187682086912 |
---|---|
author | Mefford, Joel A. Zhao, Zilong Heilier, Leah Xu, Man Zhou, Guifeng Mace, Rachel Sloane, Kelly L. Sheppard, Shannon M. Glenn, Shenly |
author_facet | Mefford, Joel A. Zhao, Zilong Heilier, Leah Xu, Man Zhou, Guifeng Mace, Rachel Sloane, Kelly L. Sheppard, Shannon M. Glenn, Shenly |
author_sort | Mefford, Joel A. |
collection | PubMed |
description | A picture description task is a component of Miro Health’s platform for self-administration of neurobehavioral assessments. Picture description has been used as a screening tool for identification of individuals with Alzheimer’s disease and mild cognitive impairment (MCI), but currently requires in-person administration and scoring by someone with access to and familiarity with a scoring rubric. The Miro Health implementation allows broader use of this assessment through self-administration and automated processing, analysis, and scoring to deliver clinically useful quantifications of the users’ speech production, vocal characteristics, and language. Picture description responses were collected from 62 healthy controls (HC), and 33 participants with MCI: 18 with amnestic MCI (aMCI) and 15 with non-amnestic MCI (naMCI). Speech and language features and contrasts between pairs of features were evaluated for differences in their distributions in the participant subgroups. Picture description features were selected and combined using penalized logistic regression to form risk scores for classification of HC versus MCI as well as HC versus specific MCI subtypes. A picture-description based risk score distinguishes MCI and HC with an area under the receiver operator curve (AUROC) of 0.74. When contrasting specific subtypes of MCI and HC, the classifiers have an AUROC of 0.88 for aMCI versus HC and and AUROC of 0.61 for naMCI versus HC. Tests of association of individual features or contrasts of pairs of features with HC versus aMCI identified 20 features with p-values below 5e-3 and False Discovery Rates (FDRs) at or below 0.113, and 61 contrasts with p-values below 5e-4 and FDRs at or below 0.132. Findings suggest that performance of picture description as a screening tool for MCI detection will vary greatly by MCI subtype or by the proportion of various subtypes in an undifferentiated MCI population. |
format | Online Article Text |
id | pubmed-10010512 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-100105122023-03-14 Varied performance of picture description task as a screening tool across MCI subtypes Mefford, Joel A. Zhao, Zilong Heilier, Leah Xu, Man Zhou, Guifeng Mace, Rachel Sloane, Kelly L. Sheppard, Shannon M. Glenn, Shenly PLOS Digit Health Research Article A picture description task is a component of Miro Health’s platform for self-administration of neurobehavioral assessments. Picture description has been used as a screening tool for identification of individuals with Alzheimer’s disease and mild cognitive impairment (MCI), but currently requires in-person administration and scoring by someone with access to and familiarity with a scoring rubric. The Miro Health implementation allows broader use of this assessment through self-administration and automated processing, analysis, and scoring to deliver clinically useful quantifications of the users’ speech production, vocal characteristics, and language. Picture description responses were collected from 62 healthy controls (HC), and 33 participants with MCI: 18 with amnestic MCI (aMCI) and 15 with non-amnestic MCI (naMCI). Speech and language features and contrasts between pairs of features were evaluated for differences in their distributions in the participant subgroups. Picture description features were selected and combined using penalized logistic regression to form risk scores for classification of HC versus MCI as well as HC versus specific MCI subtypes. A picture-description based risk score distinguishes MCI and HC with an area under the receiver operator curve (AUROC) of 0.74. When contrasting specific subtypes of MCI and HC, the classifiers have an AUROC of 0.88 for aMCI versus HC and and AUROC of 0.61 for naMCI versus HC. Tests of association of individual features or contrasts of pairs of features with HC versus aMCI identified 20 features with p-values below 5e-3 and False Discovery Rates (FDRs) at or below 0.113, and 61 contrasts with p-values below 5e-4 and FDRs at or below 0.132. Findings suggest that performance of picture description as a screening tool for MCI detection will vary greatly by MCI subtype or by the proportion of various subtypes in an undifferentiated MCI population. Public Library of Science 2023-03-13 /pmc/articles/PMC10010512/ /pubmed/36913425 http://dx.doi.org/10.1371/journal.pdig.0000197 Text en © 2023 Mefford et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://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 Mefford, Joel A. Zhao, Zilong Heilier, Leah Xu, Man Zhou, Guifeng Mace, Rachel Sloane, Kelly L. Sheppard, Shannon M. Glenn, Shenly Varied performance of picture description task as a screening tool across MCI subtypes |
title | Varied performance of picture description task as a screening tool across MCI subtypes |
title_full | Varied performance of picture description task as a screening tool across MCI subtypes |
title_fullStr | Varied performance of picture description task as a screening tool across MCI subtypes |
title_full_unstemmed | Varied performance of picture description task as a screening tool across MCI subtypes |
title_short | Varied performance of picture description task as a screening tool across MCI subtypes |
title_sort | varied performance of picture description task as a screening tool across mci subtypes |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10010512/ https://www.ncbi.nlm.nih.gov/pubmed/36913425 http://dx.doi.org/10.1371/journal.pdig.0000197 |
work_keys_str_mv | AT meffordjoela variedperformanceofpicturedescriptiontaskasascreeningtoolacrossmcisubtypes AT zhaozilong variedperformanceofpicturedescriptiontaskasascreeningtoolacrossmcisubtypes AT heilierleah variedperformanceofpicturedescriptiontaskasascreeningtoolacrossmcisubtypes AT xuman variedperformanceofpicturedescriptiontaskasascreeningtoolacrossmcisubtypes AT zhouguifeng variedperformanceofpicturedescriptiontaskasascreeningtoolacrossmcisubtypes AT macerachel variedperformanceofpicturedescriptiontaskasascreeningtoolacrossmcisubtypes AT sloanekellyl variedperformanceofpicturedescriptiontaskasascreeningtoolacrossmcisubtypes AT sheppardshannonm variedperformanceofpicturedescriptiontaskasascreeningtoolacrossmcisubtypes AT glennshenly variedperformanceofpicturedescriptiontaskasascreeningtoolacrossmcisubtypes |