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Efficacy of early warning signals and spectral periodicity for predicting transitions in bipolar patients: An actigraphy study
Early-warning signals (EWS) have been successfully employed to predict transitions in research fields such as biology, ecology, and psychiatry. The predictive properties of EWS might aid in foreseeing transitions in mood episodes (i.e. recurrent episodes of mania and depression) in bipolar disorder...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8184978/ https://www.ncbi.nlm.nih.gov/pubmed/34099627 http://dx.doi.org/10.1038/s41398-021-01465-w |
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author | Kunkels, Yoram K. Riese, Harriëtte Knapen, Stefan E. Riemersma - van der Lek, Rixt F. George, Sandip V. van Roon, Arie M. Schoevers, Robert A. Wichers, Marieke |
author_facet | Kunkels, Yoram K. Riese, Harriëtte Knapen, Stefan E. Riemersma - van der Lek, Rixt F. George, Sandip V. van Roon, Arie M. Schoevers, Robert A. Wichers, Marieke |
author_sort | Kunkels, Yoram K. |
collection | PubMed |
description | Early-warning signals (EWS) have been successfully employed to predict transitions in research fields such as biology, ecology, and psychiatry. The predictive properties of EWS might aid in foreseeing transitions in mood episodes (i.e. recurrent episodes of mania and depression) in bipolar disorder (BD) patients. We analyzed actigraphy data assessed during normal daily life to investigate the feasibility of using EWS to predict mood transitions in bipolar patients. Actigraphy data of 15 patients diagnosed with BD Type I collected continuously for 180 days were used. Our final sample included eight patients that experienced a mood episode, three manic episodes and five depressed episodes. Actigraphy data derived generic EWS (variance and kurtosis) and context-driven EWS (autocorrelation at lag-720) were used to determine if these were associated to upcoming bipolar episodes. Spectral analysis was used to predict changes in the periodicity of the sleep/wake cycle. The study procedures were pre-registered. Results indicated that in seven out of eight patients at least one of the EWS did show a significant change-up till four weeks before episode onset. For the generic EWS the direction of change was always in the expected direction, whereas for the context-driven EWS the observed effect was often in the direction opposite of what was expected. The actigraphy data derived EWS and spectral analysis showed promise for the prediction of upcoming transitions in mood episodes in bipolar patients. Further studies into false positive rates are suggested to improve effectiveness for EWS to identify upcoming bipolar episode onsets. |
format | Online Article Text |
id | pubmed-8184978 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-81849782021-06-11 Efficacy of early warning signals and spectral periodicity for predicting transitions in bipolar patients: An actigraphy study Kunkels, Yoram K. Riese, Harriëtte Knapen, Stefan E. Riemersma - van der Lek, Rixt F. George, Sandip V. van Roon, Arie M. Schoevers, Robert A. Wichers, Marieke Transl Psychiatry Article Early-warning signals (EWS) have been successfully employed to predict transitions in research fields such as biology, ecology, and psychiatry. The predictive properties of EWS might aid in foreseeing transitions in mood episodes (i.e. recurrent episodes of mania and depression) in bipolar disorder (BD) patients. We analyzed actigraphy data assessed during normal daily life to investigate the feasibility of using EWS to predict mood transitions in bipolar patients. Actigraphy data of 15 patients diagnosed with BD Type I collected continuously for 180 days were used. Our final sample included eight patients that experienced a mood episode, three manic episodes and five depressed episodes. Actigraphy data derived generic EWS (variance and kurtosis) and context-driven EWS (autocorrelation at lag-720) were used to determine if these were associated to upcoming bipolar episodes. Spectral analysis was used to predict changes in the periodicity of the sleep/wake cycle. The study procedures were pre-registered. Results indicated that in seven out of eight patients at least one of the EWS did show a significant change-up till four weeks before episode onset. For the generic EWS the direction of change was always in the expected direction, whereas for the context-driven EWS the observed effect was often in the direction opposite of what was expected. The actigraphy data derived EWS and spectral analysis showed promise for the prediction of upcoming transitions in mood episodes in bipolar patients. Further studies into false positive rates are suggested to improve effectiveness for EWS to identify upcoming bipolar episode onsets. Nature Publishing Group UK 2021-06-07 /pmc/articles/PMC8184978/ /pubmed/34099627 http://dx.doi.org/10.1038/s41398-021-01465-w Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Kunkels, Yoram K. Riese, Harriëtte Knapen, Stefan E. Riemersma - van der Lek, Rixt F. George, Sandip V. van Roon, Arie M. Schoevers, Robert A. Wichers, Marieke Efficacy of early warning signals and spectral periodicity for predicting transitions in bipolar patients: An actigraphy study |
title | Efficacy of early warning signals and spectral periodicity for predicting transitions in bipolar patients: An actigraphy study |
title_full | Efficacy of early warning signals and spectral periodicity for predicting transitions in bipolar patients: An actigraphy study |
title_fullStr | Efficacy of early warning signals and spectral periodicity for predicting transitions in bipolar patients: An actigraphy study |
title_full_unstemmed | Efficacy of early warning signals and spectral periodicity for predicting transitions in bipolar patients: An actigraphy study |
title_short | Efficacy of early warning signals and spectral periodicity for predicting transitions in bipolar patients: An actigraphy study |
title_sort | efficacy of early warning signals and spectral periodicity for predicting transitions in bipolar patients: an actigraphy study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8184978/ https://www.ncbi.nlm.nih.gov/pubmed/34099627 http://dx.doi.org/10.1038/s41398-021-01465-w |
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