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Ensemble machine learning classification of daily living abilities among older people with HIV

BACKGROUND: clinically relevant methods to identify individuals at risk for impaired daily living abilities secondary to neurocognitive impairment (ADLs) remain elusive. This is especially true for complex clinical conditions such as HIV-Associated Neurocognitive Disorders (HAND). The aim of this st...

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Autores principales: Paul, Robert, Tsuei, Torie, Cho, Kyu, Belden, Andrew, Milanini, Benedetta, Bolzenius, Jacob, Javandel, Shireen, McBride, Joseph, Cysique, Lucette, Lesinski, Samantha, Valcour, Victor
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8129893/
https://www.ncbi.nlm.nih.gov/pubmed/34027327
http://dx.doi.org/10.1016/j.eclinm.2021.100845
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author Paul, Robert
Tsuei, Torie
Cho, Kyu
Belden, Andrew
Milanini, Benedetta
Bolzenius, Jacob
Javandel, Shireen
McBride, Joseph
Cysique, Lucette
Lesinski, Samantha
Valcour, Victor
author_facet Paul, Robert
Tsuei, Torie
Cho, Kyu
Belden, Andrew
Milanini, Benedetta
Bolzenius, Jacob
Javandel, Shireen
McBride, Joseph
Cysique, Lucette
Lesinski, Samantha
Valcour, Victor
author_sort Paul, Robert
collection PubMed
description BACKGROUND: clinically relevant methods to identify individuals at risk for impaired daily living abilities secondary to neurocognitive impairment (ADLs) remain elusive. This is especially true for complex clinical conditions such as HIV-Associated Neurocognitive Disorders (HAND). The aim of this study was to identify novel and modifiable factors that have potential to improve diagnostic accuracy of ADL risk, with the long-term goal of guiding future interventions to minimize ADL disruption. METHODS: study participants included 79 people with HIV (PWH; mean age = 63; range = 55–80) enrolled in neuroHIV studies at University California San Francisco (UCSF) between 2016 and 2019. All participants were virally suppressed and exhibited objective evidence of neurocognitive impairment. ADL status was defined as either normative (n = 39) or at risk (n = 40) based on a task-based protocol. Gradient boosted multivariate regression (GBM) was employed to identify the combination of variables that differentiated ADL subgroup classification. Predictor variables included demographic factors, HIV disease severity indices, brain white matter integrity quantified using diffusion tensor imaging, cognitive test performance, and health co-morbidities. Model performance was examined using average Area Under the Curve (AUC) with repeated five-fold cross validation. FINDINGS: the univariate GBM yielded an average AUC of 83% using Wide Range Achievement test 4 (WRAT-4) reading score, self-reported thought confusion and difficulty reading, radial diffusivity (RD) in the left external capsule, fractional anisotropy (FA) in the left cingulate gyrus, and Stroop performance. The model allowing for two-way interactions modestly improved classification performance (AUC of 88%) and revealed synergies between race, reading ability, cognitive performance, and neuroimaging metrics in the genu and uncinate fasciculus. Conversion of Neuropsychological Assessment Battery Daily Living Module (NAB-DLM) performance from raw scores into T scores amplified differences between White and non-White study participants. INTERPRETATION: demographic and sociocultural factors are critical determinants of ADL risk status among older PWH who meet diagnostic criteria for neurocognitive impairment. Task-based ADL assessment that relies heavily on reading proficiency may artificially inflate the frequency/severity of ADL impairment among diverse clinical populations. Culturally relevant measures of ADL status are needed for individuals with acquired neurocognitive disorders, including HAND.
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spelling pubmed-81298932021-05-21 Ensemble machine learning classification of daily living abilities among older people with HIV Paul, Robert Tsuei, Torie Cho, Kyu Belden, Andrew Milanini, Benedetta Bolzenius, Jacob Javandel, Shireen McBride, Joseph Cysique, Lucette Lesinski, Samantha Valcour, Victor EClinicalMedicine Research Paper BACKGROUND: clinically relevant methods to identify individuals at risk for impaired daily living abilities secondary to neurocognitive impairment (ADLs) remain elusive. This is especially true for complex clinical conditions such as HIV-Associated Neurocognitive Disorders (HAND). The aim of this study was to identify novel and modifiable factors that have potential to improve diagnostic accuracy of ADL risk, with the long-term goal of guiding future interventions to minimize ADL disruption. METHODS: study participants included 79 people with HIV (PWH; mean age = 63; range = 55–80) enrolled in neuroHIV studies at University California San Francisco (UCSF) between 2016 and 2019. All participants were virally suppressed and exhibited objective evidence of neurocognitive impairment. ADL status was defined as either normative (n = 39) or at risk (n = 40) based on a task-based protocol. Gradient boosted multivariate regression (GBM) was employed to identify the combination of variables that differentiated ADL subgroup classification. Predictor variables included demographic factors, HIV disease severity indices, brain white matter integrity quantified using diffusion tensor imaging, cognitive test performance, and health co-morbidities. Model performance was examined using average Area Under the Curve (AUC) with repeated five-fold cross validation. FINDINGS: the univariate GBM yielded an average AUC of 83% using Wide Range Achievement test 4 (WRAT-4) reading score, self-reported thought confusion and difficulty reading, radial diffusivity (RD) in the left external capsule, fractional anisotropy (FA) in the left cingulate gyrus, and Stroop performance. The model allowing for two-way interactions modestly improved classification performance (AUC of 88%) and revealed synergies between race, reading ability, cognitive performance, and neuroimaging metrics in the genu and uncinate fasciculus. Conversion of Neuropsychological Assessment Battery Daily Living Module (NAB-DLM) performance from raw scores into T scores amplified differences between White and non-White study participants. INTERPRETATION: demographic and sociocultural factors are critical determinants of ADL risk status among older PWH who meet diagnostic criteria for neurocognitive impairment. Task-based ADL assessment that relies heavily on reading proficiency may artificially inflate the frequency/severity of ADL impairment among diverse clinical populations. Culturally relevant measures of ADL status are needed for individuals with acquired neurocognitive disorders, including HAND. Elsevier 2021-05-07 /pmc/articles/PMC8129893/ /pubmed/34027327 http://dx.doi.org/10.1016/j.eclinm.2021.100845 Text en © 2021 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Paper
Paul, Robert
Tsuei, Torie
Cho, Kyu
Belden, Andrew
Milanini, Benedetta
Bolzenius, Jacob
Javandel, Shireen
McBride, Joseph
Cysique, Lucette
Lesinski, Samantha
Valcour, Victor
Ensemble machine learning classification of daily living abilities among older people with HIV
title Ensemble machine learning classification of daily living abilities among older people with HIV
title_full Ensemble machine learning classification of daily living abilities among older people with HIV
title_fullStr Ensemble machine learning classification of daily living abilities among older people with HIV
title_full_unstemmed Ensemble machine learning classification of daily living abilities among older people with HIV
title_short Ensemble machine learning classification of daily living abilities among older people with HIV
title_sort ensemble machine learning classification of daily living abilities among older people with hiv
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8129893/
https://www.ncbi.nlm.nih.gov/pubmed/34027327
http://dx.doi.org/10.1016/j.eclinm.2021.100845
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