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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...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley & Sons, Inc.
2022
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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. |
format | Online Article Text |
id | pubmed-10092688 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley & Sons, Inc. |
record_format | MEDLINE/PubMed |
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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