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Anticipating manic and depressive transitions in patients with bipolar disorder using early warning signals
BACKGROUND: In bipolar disorder treatment, accurate episode prediction is paramount but remains difficult. A novel idiographic approach to prediction is to monitor generic early warning signals (EWS), which may manifest in symptom dynamics. EWS could thus form personalized alerts in clinical care. T...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8994809/ https://www.ncbi.nlm.nih.gov/pubmed/35397076 http://dx.doi.org/10.1186/s40345-022-00258-4 |
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author | Bos, Fionneke M. Schreuder, Marieke J. George, Sandip V. Doornbos, Bennard Bruggeman, Richard van der Krieke, Lian Haarman, Bartholomeus C. M. Wichers, Marieke Snippe, Evelien |
author_facet | Bos, Fionneke M. Schreuder, Marieke J. George, Sandip V. Doornbos, Bennard Bruggeman, Richard van der Krieke, Lian Haarman, Bartholomeus C. M. Wichers, Marieke Snippe, Evelien |
author_sort | Bos, Fionneke M. |
collection | PubMed |
description | BACKGROUND: In bipolar disorder treatment, accurate episode prediction is paramount but remains difficult. A novel idiographic approach to prediction is to monitor generic early warning signals (EWS), which may manifest in symptom dynamics. EWS could thus form personalized alerts in clinical care. The present study investigated whether EWS can anticipate manic and depressive transitions in individual patients with bipolar disorder. METHODS: Twenty bipolar type I/II patients (with ≥ 2 episodes in the previous year) participated in ecological momentary assessment (EMA), completing five questionnaires a day for four months (Mean = 491 observations per person). Transitions were determined by weekly completed questionnaires on depressive (Quick Inventory for Depressive Symptomatology Self-Report) and manic (Altman Self-Rating Mania Scale) symptoms. EWS (rises in autocorrelation at lag-1 and standard deviation) were calculated in moving windows over 17 affective and symptomatic EMA states. Positive and negative predictive values were calculated to determine clinical utility. RESULTS: Eleven patients reported 1–2 transitions. The presence of EWS increased the probability of impending depressive and manic transitions from 32-36% to 46–48% (autocorrelation) and 29–41% (standard deviation). However, the absence of EWS could not be taken as a sign that no transition would occur in the near future. The momentary states that indicated nearby transitions most accurately (predictive values: 65–100%) were full of ideas, worry, and agitation. Large individual differences in the utility of EWS were found. CONCLUSIONS: EWS show theoretical promise in anticipating manic and depressive transitions in bipolar disorder, but the level of false positives and negatives, as well as the heterogeneity within and between individuals and preprocessing methods currently limit clinical utility. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40345-022-00258-4. |
format | Online Article Text |
id | pubmed-8994809 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-89948092022-04-22 Anticipating manic and depressive transitions in patients with bipolar disorder using early warning signals Bos, Fionneke M. Schreuder, Marieke J. George, Sandip V. Doornbos, Bennard Bruggeman, Richard van der Krieke, Lian Haarman, Bartholomeus C. M. Wichers, Marieke Snippe, Evelien Int J Bipolar Disord Research BACKGROUND: In bipolar disorder treatment, accurate episode prediction is paramount but remains difficult. A novel idiographic approach to prediction is to monitor generic early warning signals (EWS), which may manifest in symptom dynamics. EWS could thus form personalized alerts in clinical care. The present study investigated whether EWS can anticipate manic and depressive transitions in individual patients with bipolar disorder. METHODS: Twenty bipolar type I/II patients (with ≥ 2 episodes in the previous year) participated in ecological momentary assessment (EMA), completing five questionnaires a day for four months (Mean = 491 observations per person). Transitions were determined by weekly completed questionnaires on depressive (Quick Inventory for Depressive Symptomatology Self-Report) and manic (Altman Self-Rating Mania Scale) symptoms. EWS (rises in autocorrelation at lag-1 and standard deviation) were calculated in moving windows over 17 affective and symptomatic EMA states. Positive and negative predictive values were calculated to determine clinical utility. RESULTS: Eleven patients reported 1–2 transitions. The presence of EWS increased the probability of impending depressive and manic transitions from 32-36% to 46–48% (autocorrelation) and 29–41% (standard deviation). However, the absence of EWS could not be taken as a sign that no transition would occur in the near future. The momentary states that indicated nearby transitions most accurately (predictive values: 65–100%) were full of ideas, worry, and agitation. Large individual differences in the utility of EWS were found. CONCLUSIONS: EWS show theoretical promise in anticipating manic and depressive transitions in bipolar disorder, but the level of false positives and negatives, as well as the heterogeneity within and between individuals and preprocessing methods currently limit clinical utility. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40345-022-00258-4. Springer Berlin Heidelberg 2022-04-09 /pmc/articles/PMC8994809/ /pubmed/35397076 http://dx.doi.org/10.1186/s40345-022-00258-4 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Research Bos, Fionneke M. Schreuder, Marieke J. George, Sandip V. Doornbos, Bennard Bruggeman, Richard van der Krieke, Lian Haarman, Bartholomeus C. M. Wichers, Marieke Snippe, Evelien Anticipating manic and depressive transitions in patients with bipolar disorder using early warning signals |
title | Anticipating manic and depressive transitions in patients with bipolar disorder using early warning signals |
title_full | Anticipating manic and depressive transitions in patients with bipolar disorder using early warning signals |
title_fullStr | Anticipating manic and depressive transitions in patients with bipolar disorder using early warning signals |
title_full_unstemmed | Anticipating manic and depressive transitions in patients with bipolar disorder using early warning signals |
title_short | Anticipating manic and depressive transitions in patients with bipolar disorder using early warning signals |
title_sort | anticipating manic and depressive transitions in patients with bipolar disorder using early warning signals |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8994809/ https://www.ncbi.nlm.nih.gov/pubmed/35397076 http://dx.doi.org/10.1186/s40345-022-00258-4 |
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