Indirect Assessment of Hyperechogenicity of Substantia Nigra Utilizing Sleep-based Biomarkers
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F24%3APU151024" target="_blank" >RIV/00216305:26220/24:PU151024 - isvavai.cz</a>
Výsledek na webu
<a href="https://doi.org/10.1109/SITA60746.2023.10373593" target="_blank" >https://doi.org/10.1109/SITA60746.2023.10373593</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/SITA60746.2023.10373593" target="_blank" >10.1109/SITA60746.2023.10373593</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Indirect Assessment of Hyperechogenicity of Substantia Nigra Utilizing Sleep-based Biomarkers
Popis výsledku v původním jazyce
Transcranial sonography of the substantia nigra (TCS-SN) may serve as a suitable test for screening groups at a high risk of developing Lewy body diseases (LBDs) such as Parkinson's disease or dementia with Lewy bodies. Although one of the most prominent early markers of these neurodegenerative disorders is the idiopathic rapid eye movement (REM) sleep behavior disorder, the relationship between TCS-SN and sleep alterations has not been fully explored. The aim of this study is to investigate whether sleep-based biomarkers could be used to stratify subjects into three groups with different echogenic areas of the substantia nigra. To achieve this goal, we enrolled 93 participants who underwent TCS-SN and 7-night actigraphy. Additionally, participants completed a sleep diary and the REM sleep behavior disorder screening questionnaire. To assess the severity of pathological echogenicity, we employed a machine learning algorithm utilizing the XGBoost algorithm. The results show that a multimodal assessment of sleep was able to predict the outcomes of TCS-SN with a balanced accuracy of 96 %. Overall, these findings underscore the potential of a comprehensive approach to model the results of TCS-SN and its implications for the prodromal diagnosis of LBDs.
Název v anglickém jazyce
Indirect Assessment of Hyperechogenicity of Substantia Nigra Utilizing Sleep-based Biomarkers
Popis výsledku anglicky
Transcranial sonography of the substantia nigra (TCS-SN) may serve as a suitable test for screening groups at a high risk of developing Lewy body diseases (LBDs) such as Parkinson's disease or dementia with Lewy bodies. Although one of the most prominent early markers of these neurodegenerative disorders is the idiopathic rapid eye movement (REM) sleep behavior disorder, the relationship between TCS-SN and sleep alterations has not been fully explored. The aim of this study is to investigate whether sleep-based biomarkers could be used to stratify subjects into three groups with different echogenic areas of the substantia nigra. To achieve this goal, we enrolled 93 participants who underwent TCS-SN and 7-night actigraphy. Additionally, participants completed a sleep diary and the REM sleep behavior disorder screening questionnaire. To assess the severity of pathological echogenicity, we employed a machine learning algorithm utilizing the XGBoost algorithm. The results show that a multimodal assessment of sleep was able to predict the outcomes of TCS-SN with a balanced accuracy of 96 %. Overall, these findings underscore the potential of a comprehensive approach to model the results of TCS-SN and its implications for the prodromal diagnosis of LBDs.
Klasifikace
Druh
D - Stať ve sborníku
CEP obor
—
OECD FORD obor
30103 - Neurosciences (including psychophysiology)
Návaznosti výsledku
Projekt
Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Ostatní
Rok uplatnění
2024
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název statě ve sborníku
2023 14th International Conference on Intelligent Systems: Theories and Applications (SITA)
ISBN
9798350308211
ISSN
—
e-ISSN
—
Počet stran výsledku
6
Strana od-do
1-6
Název nakladatele
Institute of Electrical and Electronics Engineers Inc.
Místo vydání
Casablanca, Morocco
Místo konání akce
Casablanca
Datum konání akce
22. 11. 2023
Typ akce podle státní příslušnosti
WRD - Celosvětová akce
Kód UT WoS článku
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