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Ambulatory Detection of Isolated Rapid‐Eye‐Movement Sleep Behavior Disorder Combining Actigraphy and Questionnaire

BACKGROUND: Isolated rapid‐eye‐movement sleep behavior disorder (iRBD) is in most cases a prodrome of neurodegenerative synucleinopathies, affecting 1% to 2% of middle‐aged and older adults; however, accurate ambulatory diagnostic methods are not available. Questionnaires lack specificity in nonclin...

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Autores principales: Brink‐Kjaer, Andreas, Gupta, Niraj, Marin, Eric, Zitser, Jennifer, Sum‐Ping, Oliver, Hekmat, Anahid, Bueno, Flavia, Cahuas, Ana, Langston, James, Jennum, Poul, Sorensen, Helge B.D., Mignot, Emmanuel, During, Emmanuel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10092688/
https://www.ncbi.nlm.nih.gov/pubmed/36258659
http://dx.doi.org/10.1002/mds.29249
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author Brink‐Kjaer, Andreas
Gupta, Niraj
Marin, Eric
Zitser, Jennifer
Sum‐Ping, Oliver
Hekmat, Anahid
Bueno, Flavia
Cahuas, Ana
Langston, James
Jennum, Poul
Sorensen, Helge B.D.
Mignot, Emmanuel
During, Emmanuel
author_facet Brink‐Kjaer, Andreas
Gupta, Niraj
Marin, Eric
Zitser, Jennifer
Sum‐Ping, Oliver
Hekmat, Anahid
Bueno, Flavia
Cahuas, Ana
Langston, James
Jennum, Poul
Sorensen, Helge B.D.
Mignot, Emmanuel
During, Emmanuel
author_sort Brink‐Kjaer, Andreas
collection PubMed
description BACKGROUND: Isolated rapid‐eye‐movement sleep behavior disorder (iRBD) is in most cases a prodrome of neurodegenerative synucleinopathies, affecting 1% to 2% of middle‐aged and older adults; however, accurate ambulatory diagnostic methods are not available. Questionnaires lack specificity in nonclinical populations. Wrist actigraphy can detect characteristic features in individuals with RBD; however, high‐frequency actigraphy has been rarely used. OBJECTIVE: The aim was to develop a machine learning classifier using high‐frequency (1‐second resolution) actigraphy and a short patient survey for detecting iRBD with high accuracy and precision. METHODS: The method involved analysis of home actigraphy data (for seven nights and more) and a nine‐item questionnaire (RBD Innsbruck inventory and three synucleinopathy prodromes of subjective hyposmia, constipation, and orthostatic dizziness) in a data set comprising 42 patients with iRBD, 21 sleep clinic patients with other sleep disorders, and 21 community controls. RESULTS: The actigraphy classifier achieved 95.2% (95% confidence interval [CI]: 88.3–98.7) sensitivity and 90.9% (95% CI: 82.1–95.8) precision. The questionnaire classifier achieved 90.6% accuracy and 92.7% precision, exceeding the performance of the Innsbruck RBD Inventory and prodromal questionnaire alone. Concordant predictions between actigraphy and questionnaire reached a specificity and precision of 100% (95% CI: 95.7–100.0) with 88.1% sensitivity (95% CI: 79.2–94.1) and outperformed any combination of actigraphy and a single question on RBD or prodromal symptoms. CONCLUSIONS: Actigraphy detected iRBD with high accuracy in a mixed clinical and community cohort. This cost‐effective fully remote procedure can be used to diagnose iRBD in specialty outpatient settings and has potential for large‐scale screening of iRBD in the general population. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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spelling pubmed-100926882023-04-13 Ambulatory Detection of Isolated Rapid‐Eye‐Movement Sleep Behavior Disorder Combining Actigraphy and Questionnaire Brink‐Kjaer, Andreas Gupta, Niraj Marin, Eric Zitser, Jennifer Sum‐Ping, Oliver Hekmat, Anahid Bueno, Flavia Cahuas, Ana Langston, James Jennum, Poul Sorensen, Helge B.D. Mignot, Emmanuel During, Emmanuel Mov Disord Research Articles BACKGROUND: Isolated rapid‐eye‐movement sleep behavior disorder (iRBD) is in most cases a prodrome of neurodegenerative synucleinopathies, affecting 1% to 2% of middle‐aged and older adults; however, accurate ambulatory diagnostic methods are not available. Questionnaires lack specificity in nonclinical populations. Wrist actigraphy can detect characteristic features in individuals with RBD; however, high‐frequency actigraphy has been rarely used. OBJECTIVE: The aim was to develop a machine learning classifier using high‐frequency (1‐second resolution) actigraphy and a short patient survey for detecting iRBD with high accuracy and precision. METHODS: The method involved analysis of home actigraphy data (for seven nights and more) and a nine‐item questionnaire (RBD Innsbruck inventory and three synucleinopathy prodromes of subjective hyposmia, constipation, and orthostatic dizziness) in a data set comprising 42 patients with iRBD, 21 sleep clinic patients with other sleep disorders, and 21 community controls. RESULTS: The actigraphy classifier achieved 95.2% (95% confidence interval [CI]: 88.3–98.7) sensitivity and 90.9% (95% CI: 82.1–95.8) precision. The questionnaire classifier achieved 90.6% accuracy and 92.7% precision, exceeding the performance of the Innsbruck RBD Inventory and prodromal questionnaire alone. Concordant predictions between actigraphy and questionnaire reached a specificity and precision of 100% (95% CI: 95.7–100.0) with 88.1% sensitivity (95% CI: 79.2–94.1) and outperformed any combination of actigraphy and a single question on RBD or prodromal symptoms. CONCLUSIONS: Actigraphy detected iRBD with high accuracy in a mixed clinical and community cohort. This cost‐effective fully remote procedure can be used to diagnose iRBD in specialty outpatient settings and has potential for large‐scale screening of iRBD in the general population. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. John Wiley & Sons, Inc. 2022-10-18 2023-01 /pmc/articles/PMC10092688/ /pubmed/36258659 http://dx.doi.org/10.1002/mds.29249 Text en © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Research Articles
Brink‐Kjaer, Andreas
Gupta, Niraj
Marin, Eric
Zitser, Jennifer
Sum‐Ping, Oliver
Hekmat, Anahid
Bueno, Flavia
Cahuas, Ana
Langston, James
Jennum, Poul
Sorensen, Helge B.D.
Mignot, Emmanuel
During, Emmanuel
Ambulatory Detection of Isolated Rapid‐Eye‐Movement Sleep Behavior Disorder Combining Actigraphy and Questionnaire
title Ambulatory Detection of Isolated Rapid‐Eye‐Movement Sleep Behavior Disorder Combining Actigraphy and Questionnaire
title_full Ambulatory Detection of Isolated Rapid‐Eye‐Movement Sleep Behavior Disorder Combining Actigraphy and Questionnaire
title_fullStr Ambulatory Detection of Isolated Rapid‐Eye‐Movement Sleep Behavior Disorder Combining Actigraphy and Questionnaire
title_full_unstemmed Ambulatory Detection of Isolated Rapid‐Eye‐Movement Sleep Behavior Disorder Combining Actigraphy and Questionnaire
title_short Ambulatory Detection of Isolated Rapid‐Eye‐Movement Sleep Behavior Disorder Combining Actigraphy and Questionnaire
title_sort ambulatory detection of isolated rapid‐eye‐movement sleep behavior disorder combining actigraphy and questionnaire
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10092688/
https://www.ncbi.nlm.nih.gov/pubmed/36258659
http://dx.doi.org/10.1002/mds.29249
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