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Control charts for monitoring mood stability as a predictor of severe episodes in patients with bipolar disorder
BACKGROUND: Recurrent mood episodes and subsyndromal mood instability cause substantial disability in patients with bipolar disorder. Early identification of mood episodes enabling timely mood stabilization is an important clinical goal. This study investigates the ability of control chart methodolo...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6161980/ https://www.ncbi.nlm.nih.gov/pubmed/29616434 http://dx.doi.org/10.1186/s40345-017-0116-2 |
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author | Vazquez-Montes, Maria D. L. A. Stevens, Richard Perera, Rafael Saunders, Kate Geddes, John R. |
author_facet | Vazquez-Montes, Maria D. L. A. Stevens, Richard Perera, Rafael Saunders, Kate Geddes, John R. |
author_sort | Vazquez-Montes, Maria D. L. A. |
collection | PubMed |
description | BACKGROUND: Recurrent mood episodes and subsyndromal mood instability cause substantial disability in patients with bipolar disorder. Early identification of mood episodes enabling timely mood stabilization is an important clinical goal. This study investigates the ability of control chart methodology to predict manic and/or depressive episodes by applying Shewhart’s control rules to weekly self-reported scores from mania and depression questionnaires. METHODS: Shewhart’s control rules were applied to weekly self-reported scores from the Altman Self-Rating Mania Scale (ASRM) and the Quick Inventory of Depressive Symptomatology—Self-Report (QIDS) collected from 2001 to 2012 as part of the OXTEXT programme. Manic and depressive episodes were defined as an ASRM score ≥ 10 or a QIDS score ≥ 15, respectively. An episode-free run-in period of eight consecutive weeks without an episode of either type was used to calibrate control charts. Shewhart’s rules were then applied to follow-up data. Their sensitivity and positive predictive value for predicting manic or depressive episodes within the next 4 weeks were calculated focusing on the first episode. Secondary analyses varying control chart type, length of episode-free run-in period, time frames to evaluate diagnostic accuracy, thresholds defining either manic or depressive episodes, and missing data methods were performed. RESULTS: Data from 146 participants (37% men) were included. The mean age was 43.4 (SD = 13.3) years. The median follow-up was 10 (IQR 5–40) weeks for mania and 10 (IQR 5–23) weeks for depression. A total of 53 (36%) participants had a manic episode and 67 (46%) had a depressive episode. For manic episodes, the sensitivity and positive predictive value of Shewhart’s control rules were 30% (95% CI 19–45%) and 7% (95% CI 5–9%), and for depressive episodes, 33% (95% CI 22–46%) and 9% (95% CI 6–12%), respectively. Results from secondary analyses were similar to these. CONCLUSIONS: Tele-monitoring with control rules has the potential to predict about one-third of manic or depressive episodes before they occur, at the cost of a high false positive rate. Given the severe consequences of manic and depressive episodes, this trade-off may be desirable. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s40345-017-0116-2) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6161980 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-61619802018-10-12 Control charts for monitoring mood stability as a predictor of severe episodes in patients with bipolar disorder Vazquez-Montes, Maria D. L. A. Stevens, Richard Perera, Rafael Saunders, Kate Geddes, John R. Int J Bipolar Disord Research BACKGROUND: Recurrent mood episodes and subsyndromal mood instability cause substantial disability in patients with bipolar disorder. Early identification of mood episodes enabling timely mood stabilization is an important clinical goal. This study investigates the ability of control chart methodology to predict manic and/or depressive episodes by applying Shewhart’s control rules to weekly self-reported scores from mania and depression questionnaires. METHODS: Shewhart’s control rules were applied to weekly self-reported scores from the Altman Self-Rating Mania Scale (ASRM) and the Quick Inventory of Depressive Symptomatology—Self-Report (QIDS) collected from 2001 to 2012 as part of the OXTEXT programme. Manic and depressive episodes were defined as an ASRM score ≥ 10 or a QIDS score ≥ 15, respectively. An episode-free run-in period of eight consecutive weeks without an episode of either type was used to calibrate control charts. Shewhart’s rules were then applied to follow-up data. Their sensitivity and positive predictive value for predicting manic or depressive episodes within the next 4 weeks were calculated focusing on the first episode. Secondary analyses varying control chart type, length of episode-free run-in period, time frames to evaluate diagnostic accuracy, thresholds defining either manic or depressive episodes, and missing data methods were performed. RESULTS: Data from 146 participants (37% men) were included. The mean age was 43.4 (SD = 13.3) years. The median follow-up was 10 (IQR 5–40) weeks for mania and 10 (IQR 5–23) weeks for depression. A total of 53 (36%) participants had a manic episode and 67 (46%) had a depressive episode. For manic episodes, the sensitivity and positive predictive value of Shewhart’s control rules were 30% (95% CI 19–45%) and 7% (95% CI 5–9%), and for depressive episodes, 33% (95% CI 22–46%) and 9% (95% CI 6–12%), respectively. Results from secondary analyses were similar to these. CONCLUSIONS: Tele-monitoring with control rules has the potential to predict about one-third of manic or depressive episodes before they occur, at the cost of a high false positive rate. Given the severe consequences of manic and depressive episodes, this trade-off may be desirable. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s40345-017-0116-2) contains supplementary material, which is available to authorized users. Springer Berlin Heidelberg 2018-04-04 /pmc/articles/PMC6161980/ /pubmed/29616434 http://dx.doi.org/10.1186/s40345-017-0116-2 Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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. |
spellingShingle | Research Vazquez-Montes, Maria D. L. A. Stevens, Richard Perera, Rafael Saunders, Kate Geddes, John R. Control charts for monitoring mood stability as a predictor of severe episodes in patients with bipolar disorder |
title | Control charts for monitoring mood stability as a predictor of severe episodes in patients with bipolar disorder |
title_full | Control charts for monitoring mood stability as a predictor of severe episodes in patients with bipolar disorder |
title_fullStr | Control charts for monitoring mood stability as a predictor of severe episodes in patients with bipolar disorder |
title_full_unstemmed | Control charts for monitoring mood stability as a predictor of severe episodes in patients with bipolar disorder |
title_short | Control charts for monitoring mood stability as a predictor of severe episodes in patients with bipolar disorder |
title_sort | control charts for monitoring mood stability as a predictor of severe episodes in patients with bipolar disorder |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6161980/ https://www.ncbi.nlm.nih.gov/pubmed/29616434 http://dx.doi.org/10.1186/s40345-017-0116-2 |
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