200 - Neuropsychiatric symptoms influence performance of activities of daily living in symptomatic Alzheimer’s Disease

Background:The triad of symptom groups of Alzheimer’s disease (AD) encompasses cognitive impairment (e.g. impaired memory or orientation), neuropsychiatric symptoms like apathy, depressive mood, delusions, hallucinations or anxiety, and functional impairment exclusively in complex activities of dail...

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Veröffentlicht in:International psychogeriatrics 2021-10, Vol.33 (S1), p.5-6
Hauptverfasser: Giannakis, Nikos, Skondra, Maria, Aligianni, Suzanna, Georgiou, Eliza, Prapiadou, Savvina, Lentzari, Iliana, Politis, Antonios, Laskaris, Nikos, Alexopoulos, Panagiotis
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container_issue S1
container_start_page 5
container_title International psychogeriatrics
container_volume 33
creator Giannakis, Nikos
Skondra, Maria
Aligianni, Suzanna
Georgiou, Eliza
Prapiadou, Savvina
Lentzari, Iliana
Politis, Antonios
Laskaris, Nikos
Alexopoulos, Panagiotis
description Background:The triad of symptom groups of Alzheimer’s disease (AD) encompasses cognitive impairment (e.g. impaired memory or orientation), neuropsychiatric symptoms like apathy, depressive mood, delusions, hallucinations or anxiety, and functional impairment exclusively in complex activities of daily living (cADL, e.g. preparing meals, managing finances) in minor neurocognitive disorder due to AD and both in complex and basic ADL (bADL, e.g. dressing, toileting) in major neurocognitive disorder due to AD. These functional impairments are widely thought to be exclusively attributable to the cognitive deficits of the disease. Of note, mounting evidence indicates that neuropsychiatric symptoms are very common in AD and pose a heavy burden to both patients and their caregivers.Research objective:To unravel potential associations between neuropsychiatric symptoms and cADL and bADL in individuals with neurocognitive disorder due to AD by means of machine learning (ML).Methods:The study included 189 cognitively intact older individuals (CI) and 130 with either minor or major neurocognitive disorder due to AD. Neuropsychiatric symptoms were captured with the Neuropsychiatric Inventory (NPI), covering delusions, hallucinations, aggression, depression, anxiety, apathy, elation, disinhibition, irritability, motor disturbance, nighttime behavioural disturbances and appetite disturbances; cognitive function was assessed with the Cognitive Telephone Screening Instrument (COGTEL); The Bristol ADL scale, an informant-rated measure, was employed for tapping performance of ADL. A variety of ML-models was constructed and trained/tested using a 5-fold cross validation, with SMOTE employed as a remedy for class imbalances. In all cases the features had been selected beforehand based on LASSO technique. The dependent variable was either cADL or bADL (after their discretization based on kMeans quantization). Additionally, the modelling of the diagnosis was also attempted within our ML framework.Results:Gradient Boosting models performed superiorly. cADL and bADL levels are predicted based on both deficits in cognitive domains and NPI variables with an accuracy of 82.3% and 84.8% respectively.In addition, diagnosis can be predicted, with an accuracy of 83.5%, based on a model in which NPI and Bristol ADL variables were significant predictors.Conclusions:cADL- and bADL performance in patients with AD is influenced by both cognitive deficits and neuropsychiatric symptoms.
doi_str_mv 10.1017/S1041610221001344
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These functional impairments are widely thought to be exclusively attributable to the cognitive deficits of the disease. Of note, mounting evidence indicates that neuropsychiatric symptoms are very common in AD and pose a heavy burden to both patients and their caregivers.Research objective:To unravel potential associations between neuropsychiatric symptoms and cADL and bADL in individuals with neurocognitive disorder due to AD by means of machine learning (ML).Methods:The study included 189 cognitively intact older individuals (CI) and 130 with either minor or major neurocognitive disorder due to AD. 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Additionally, the modelling of the diagnosis was also attempted within our ML framework.Results:Gradient Boosting models performed superiorly. cADL and bADL levels are predicted based on both deficits in cognitive domains and NPI variables with an accuracy of 82.3% and 84.8% respectively.In addition, diagnosis can be predicted, with an accuracy of 83.5%, based on a model in which NPI and Bristol ADL variables were significant predictors.Conclusions:cADL- and bADL performance in patients with AD is influenced by both cognitive deficits and neuropsychiatric symptoms.</description><identifier>ISSN: 1041-6102</identifier><identifier>EISSN: 1741-203X</identifier><identifier>DOI: 10.1017/S1041610221001344</identifier><language>eng</language><publisher>Cambridge, UK: Cambridge University Press</publisher><subject>Activities of daily living ; Alzheimer's disease ; Apathy ; Caregivers ; Cognitive functioning ; Cognitive impairment ; Cognitive-behavioral factors ; Delusions ; Dementia ; Disinhibition ; Dressing ; Functional impairment ; Hallucinations ; Irritability ; Live Free/Oral Communications ; Meals ; Medical diagnosis ; Medical screening ; Mental depression ; Neurocognition ; Neuropsychiatric symptoms ; Older people ; Symptoms</subject><ispartof>International psychogeriatrics, 2021-10, Vol.33 (S1), p.5-6</ispartof><rights>International Psychogeriatric Association 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c2054-7285504ed05832416457c31aaff4175ca689325db55178fa2511e6db9aef351f3</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.cambridge.org/core/product/identifier/S1041610221001344/type/journal_article$$EHTML$$P50$$Gcambridge$$H</linktohtml><link.rule.ids>164,314,780,784,12846,27924,27925,30999,55628</link.rule.ids></links><search><creatorcontrib>Giannakis, Nikos</creatorcontrib><creatorcontrib>Skondra, Maria</creatorcontrib><creatorcontrib>Aligianni, Suzanna</creatorcontrib><creatorcontrib>Georgiou, Eliza</creatorcontrib><creatorcontrib>Prapiadou, Savvina</creatorcontrib><creatorcontrib>Lentzari, Iliana</creatorcontrib><creatorcontrib>Politis, Antonios</creatorcontrib><creatorcontrib>Laskaris, Nikos</creatorcontrib><creatorcontrib>Alexopoulos, Panagiotis</creatorcontrib><title>200 - Neuropsychiatric symptoms influence performance of activities of daily living in symptomatic Alzheimer’s Disease</title><title>International psychogeriatrics</title><addtitle>Int. 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Psychogeriatr</addtitle><date>2021-10</date><risdate>2021</risdate><volume>33</volume><issue>S1</issue><spage>5</spage><epage>6</epage><pages>5-6</pages><issn>1041-6102</issn><eissn>1741-203X</eissn><abstract>Background:The triad of symptom groups of Alzheimer’s disease (AD) encompasses cognitive impairment (e.g. impaired memory or orientation), neuropsychiatric symptoms like apathy, depressive mood, delusions, hallucinations or anxiety, and functional impairment exclusively in complex activities of daily living (cADL, e.g. preparing meals, managing finances) in minor neurocognitive disorder due to AD and both in complex and basic ADL (bADL, e.g. dressing, toileting) in major neurocognitive disorder due to AD. These functional impairments are widely thought to be exclusively attributable to the cognitive deficits of the disease. Of note, mounting evidence indicates that neuropsychiatric symptoms are very common in AD and pose a heavy burden to both patients and their caregivers.Research objective:To unravel potential associations between neuropsychiatric symptoms and cADL and bADL in individuals with neurocognitive disorder due to AD by means of machine learning (ML).Methods:The study included 189 cognitively intact older individuals (CI) and 130 with either minor or major neurocognitive disorder due to AD. Neuropsychiatric symptoms were captured with the Neuropsychiatric Inventory (NPI), covering delusions, hallucinations, aggression, depression, anxiety, apathy, elation, disinhibition, irritability, motor disturbance, nighttime behavioural disturbances and appetite disturbances; cognitive function was assessed with the Cognitive Telephone Screening Instrument (COGTEL); The Bristol ADL scale, an informant-rated measure, was employed for tapping performance of ADL. A variety of ML-models was constructed and trained/tested using a 5-fold cross validation, with SMOTE employed as a remedy for class imbalances. In all cases the features had been selected beforehand based on LASSO technique. The dependent variable was either cADL or bADL (after their discretization based on kMeans quantization). Additionally, the modelling of the diagnosis was also attempted within our ML framework.Results:Gradient Boosting models performed superiorly. cADL and bADL levels are predicted based on both deficits in cognitive domains and NPI variables with an accuracy of 82.3% and 84.8% respectively.In addition, diagnosis can be predicted, with an accuracy of 83.5%, based on a model in which NPI and Bristol ADL variables were significant predictors.Conclusions:cADL- and bADL performance in patients with AD is influenced by both cognitive deficits and neuropsychiatric symptoms.</abstract><cop>Cambridge, UK</cop><pub>Cambridge University Press</pub><doi>10.1017/S1041610221001344</doi><tpages>2</tpages><oa>free_for_read</oa></addata></record>
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subjects Activities of daily living
Alzheimer's disease
Apathy
Caregivers
Cognitive functioning
Cognitive impairment
Cognitive-behavioral factors
Delusions
Dementia
Disinhibition
Dressing
Functional impairment
Hallucinations
Irritability
Live Free/Oral Communications
Meals
Medical diagnosis
Medical screening
Mental depression
Neurocognition
Neuropsychiatric symptoms
Older people
Symptoms
title 200 - Neuropsychiatric symptoms influence performance of activities of daily living in symptomatic Alzheimer’s Disease
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