1
|
Halabi R, Mulsant BH, Alda M, DeShaw A, Hintze A, Husain MI, O'Donovan C, Patterson R, Ortiz A. Not missing at random: Missing data are associated with clinical status and trajectories in an electronic monitoring longitudinal study of bipolar disorder. J Psychiatr Res 2024; 174:326-331. [PMID: 38692162 DOI: 10.1016/j.jpsychires.2024.04.036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/20/2024] [Revised: 04/11/2024] [Accepted: 04/18/2024] [Indexed: 05/03/2024]
Abstract
There is limited information on the association between participants' clinical status or trajectories and missing data in electronic monitoring studies of bipolar disorder (BD). We collected self-ratings scales and sensor data in 145 adults with BD. Using a new metric, Missing Data Ratio (MDR), we assessed missing self-rating data and sensor data monitoring activity and sleep. Missing data were lowest for participants in the midst of a depressive episode, intermediate for participants with subsyndromal symptoms, and highest for participants who were euthymic. Over a mean ± SD follow-up of 246 ± 181 days, missing data remained unchanged for participants whose clinical status did not change throughout the study (i.e., those who entered the study in a depressive episode and did not improve, or those who entered the study euthymic and remained euthymic). Conversely, when participants' clinical status changed during the study (e.g., those who entered the study euthymic and experienced the occurrence of a depressive episode), missing data for self-rating scales increased, but not for sensor data. Overall missing data were associated with participants' clinical status and its changes, suggesting that these are not missing at random.
Collapse
Affiliation(s)
- Ramzi Halabi
- Campbell Family Research Institute, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada
| | - Benoit H Mulsant
- Campbell Family Research Institute, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada; Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Martin Alda
- Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia, Canada; National Institute of Mental Health, Klecany, Czech Republic
| | | | - Arend Hintze
- Department of MicroData Analytics, Dalarna University, Sweden
| | - Muhammad I Husain
- Campbell Family Research Institute, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada; Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Claire O'Donovan
- Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Rachel Patterson
- Campbell Family Research Institute, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada
| | - Abigail Ortiz
- Campbell Family Research Institute, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada; Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.
| |
Collapse
|
2
|
Strejilevich S, Samamé C, Marengo E, Godoy A, Smith J, Camino S, Oppel M, Sobrero M, López Escalona L. Can we predict a "tsunami"? Symptomatic and syndromal density, mood instability and treatment intensity in people with bipolar disorders under a strict and long lockdown. J Affect Disord 2024; 351:827-832. [PMID: 38341152 DOI: 10.1016/j.jad.2024.02.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 07/18/2023] [Accepted: 02/06/2024] [Indexed: 02/12/2024]
Abstract
BACKGROUND Converging evidence supports the involvement of circadian rhythm disturbances in the course and morbidity of bipolar disorders (BD). During 2020, lockdown measures were introduced worldwide to contain the health crisis caused by the COVID-19 pandemic. As a result, chronobiological rhythms were critically disrupted and illness outcomes were expected to worsen. The current study aimed to explore changes in morbidity among BD patients living under lockdown. METHODS Ninety BD outpatients under naturalistic treatment conditions were followed from March to September 2020 using a mood chart technique. Different treatment and illness variables, including mood instability, were assessed and compared with the outcomes obtained during the same 28-week period in 2019. RESULTS For most clinical variables, no significant differences were observed between time periods. A slight decrease was found in symptom intensity (from 15.19 ± 20.62 to 10.34 ± 15.79, FDR-adjusted p = 0.04) and in the number of depressive episodes (from 0.39 ± 0.74 to 0.22 ± 0.63, FDR-adjusted p = 0.03), whereas the intensity of pharmacological treatment remained unchanged. Previous illness course predicted mood outcomes during the confinement. LIMITATIONS Follow-up periods were relatively short. Further, actigraphy or other methods capable of ensuring significant changes in physical activity were not used. CONCLUSIONS In line with other studies, our findings show no worsening in the clinical morbidity of BD patients during lockdown. This conspicuous contrast between our initial predictions and the observed findings highlights the fact that we are still far from being able to provide accurate predictive models for BD.
Collapse
Affiliation(s)
- Sergio Strejilevich
- ÁREA, Asistencia e Investigación en Trastornos del Ánimo, Buenos Aires, Argentina.
| | - Cecilia Samamé
- Departamento de Psicología, Universidad Católica del Uruguay, Montevideo, Uruguay
| | - Eliana Marengo
- ÁREA, Asistencia e Investigación en Trastornos del Ánimo, Buenos Aires, Argentina
| | - Antonella Godoy
- ÁREA, Asistencia e Investigación en Trastornos del Ánimo, Buenos Aires, Argentina
| | - José Smith
- ÁREA, Asistencia e Investigación en Trastornos del Ánimo, Buenos Aires, Argentina
| | - Sebastián Camino
- ÁREA, Asistencia e Investigación en Trastornos del Ánimo, Buenos Aires, Argentina
| | - Melany Oppel
- ÁREA, Asistencia e Investigación en Trastornos del Ánimo, Buenos Aires, Argentina
| | - Martina Sobrero
- ÁREA, Asistencia e Investigación en Trastornos del Ánimo, Buenos Aires, Argentina
| | | |
Collapse
|
3
|
Guo YB, Jiao Q, Zhang XT, Xiao Q, Wu Z, Cao WF, Cui D, Yu GH, Dou RH, Su LY, Lu GM. Increased regional Hurst exponent reflects response inhibition related neural complexity alterations in pediatric bipolar disorder patients during an emotional Go-Nogo task. Cereb Cortex 2024; 34:bhad442. [PMID: 38031362 PMCID: PMC10793568 DOI: 10.1093/cercor/bhad442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Revised: 10/28/2023] [Accepted: 10/30/2023] [Indexed: 12/01/2023] Open
Abstract
Fractal patterns have been shown to change in resting- and task-state blood oxygen level-dependent signals in bipolar disorder patients. However, fractal characteristics of brain blood oxygen level-dependent signals when responding to external emotional stimuli in pediatric bipolar disorder remain unclear. Blood oxygen level-dependent signals of 20 PBD-I patients and 17 age- and sex-matched healthy controls were extracted while performing an emotional Go-Nogo task. Neural responses relevant to the task and Hurst exponent of the blood oxygen level-dependent signals were assessed. Correlations between clinical indices and Hurst exponent were estimated. Significantly increased activations were found in regions covering the frontal lobe, parietal lobe, temporal lobe, insula, and subcortical nuclei in PBD-I patients compared to healthy controls in contrast of emotional versus neutral distractors. PBD-I patients exhibited higher Hurst exponent in regions that involved in action control, such as superior frontal gyrus, inferior frontal gyrus, inferior temporal gyrus, and insula, with Hurst exponent of frontal orbital gyrus correlated with onset age. The present study exhibited overactivation, increased self-similarity and decreased complexity in cortical regions during emotional Go-Nogo task in patients relative to healthy controls, which provides evidence of an altered emotional modulation of cognitive control in pediatric bipolar disorder patients. Hurst exponent may be a fractal biomarker of neural activity in pediatric bipolar disorder.
Collapse
Affiliation(s)
- Yi-Bing Guo
- School of Radiology, Shandong First Medical University and Shandong Academy of Medical Sciences, Tai’an 271000, China
- Brain and Mind Center, The University of Sydney, Sydney, NSW 2008, Australia
| | - Qing Jiao
- School of Radiology, Shandong First Medical University and Shandong Academy of Medical Sciences, Tai’an 271000, China
| | - Xiao-Tong Zhang
- School of Radiology, Shandong First Medical University and Shandong Academy of Medical Sciences, Tai’an 271000, China
| | - Qian Xiao
- Mental Health Centre of Xiangya Hospital, Central South University, Changsha 410083, China
| | - Zhou Wu
- School of Psychology, Nanjing Normal University, Nanjing 210097, China
| | - Wei-Fang Cao
- School of Radiology, Shandong First Medical University and Shandong Academy of Medical Sciences, Tai’an 271000, China
| | - Dong Cui
- School of Radiology, Shandong First Medical University and Shandong Academy of Medical Sciences, Tai’an 271000, China
| | - Guang-Hui Yu
- School of Radiology, Shandong First Medical University and Shandong Academy of Medical Sciences, Tai’an 271000, China
| | - Ru-Hai Dou
- School of Radiology, Shandong First Medical University and Shandong Academy of Medical Sciences, Tai’an 271000, China
| | - Lin-Yan Su
- Mental Health Institute of the Second Xiangya Hospital, Central South University, Changsha 410083, China
| | - Guang-Ming Lu
- Department of Medical Imaging, Jinling Hospital, Clinical School of Medical College, Nanjing University, Nanjing 210023, China
| |
Collapse
|
4
|
Qian Y, Solano MJ, Kreindler D. Grouping of mood symptoms by time series dynamics. J Affect Disord 2022; 309:186-192. [PMID: 35461820 DOI: 10.1016/j.jad.2022.04.117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Revised: 03/12/2022] [Accepted: 04/16/2022] [Indexed: 11/30/2022]
Abstract
BACKGROUND Understanding how symptoms of mood disorders vary over time in relation to each other is potentially valuable for diagnosis and predicting episodes of illness. In this paper, we characterize the degree of similarity of time series of different mood disorder symptoms. METHODS We collected 32,215 mood disorder symptom questionnaires, administered twice-daily over 18 months to (n = 19) subjects with rapidly cycling bipolar disorder and (n = 20) healthy control subjects, using visual analog scales to rate 11 sets of symptom severity ratings plus a control item. We used Dynamic Time Warping to calculate similarity ratings between all within-subject pairs of severity ratings followed by Exploratory Factor Analysis (EFA) to identify latent factors of symptom time series across all subjects. RESULTS Two latent factors were identified: one with depression and anxiety; and a second, with concentration, energy, irritability, fatigue, appetite, euphoria/elation and overall mood. Restlessness, racing thoughts, and the control item (daily hours of daylight) did not cluster with any of the others. LIMITATIONS Limited sample size dictated that we pool bipolar and healthy patients and use an iterative EFA procedure. CONCLUSION This analysis suggests that, in a pooled sample of individuals with bipolar disorder and in healthy controls, severity ratings of overall depression and overall anxiety vary jointly as one dynamic factor, while some but not all other DSM mood symptoms vary jointly along with overall mood rating as a second dynamic factor. Further investigation may determine if these findings can simplify subjective symptom reporting in mood-monitoring studies.
Collapse
Affiliation(s)
- Yuxin Qian
- Applied Mathematics Program, University of California Los Angeles, Los Angeles, California, USA
| | - Maria José Solano
- Mathematics and Computer Science Program, McGill University, Montreal, Quebec, Canada
| | - David Kreindler
- Division of Child and Youth Mental Health, Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada, M5T 1R8; Centre for Mobile Computing in Mental Health, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada, M4N 3M5; Division of Youth Psychiatry, Department of Psychiatry, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada, M4N 3M5.
| |
Collapse
|
5
|
Ortiz A, Hintze A, Burnett R, Gonzalez-Torres C, Unger S, Yang D, Miao J, Alda M, Mulsant BH. Identifying patient-specific behaviors to understand illness trajectories and predict relapses in bipolar disorder using passive sensing and deep anomaly detection: protocol for a contactless cohort study. BMC Psychiatry 2022; 22:288. [PMID: 35459150 PMCID: PMC9026652 DOI: 10.1186/s12888-022-03923-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Accepted: 04/07/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Predictive models for mental disorders or behaviors (e.g., suicide) have been successfully developed at the level of populations, yet current demographic and clinical variables are neither sensitive nor specific enough for making individual clinical predictions. Forecasting episodes of illness is particularly relevant in bipolar disorder (BD), a mood disorder with high recurrence, disability, and suicide rates. Thus, to understand the dynamic changes involved in episode generation in BD, we propose to extract and interpret individual illness trajectories and patterns suggestive of relapse using passive sensing, nonlinear techniques, and deep anomaly detection. Here we describe the study we have designed to test this hypothesis and the rationale for its design. METHOD This is a protocol for a contactless cohort study in 200 adult BD patients. Participants will be followed for up to 2 years during which they will be monitored continuously using passive sensing, a wearable that collects multimodal physiological (heart rate variability) and objective (sleep, activity) data. Participants will complete (i) a comprehensive baseline assessment; (ii) weekly assessments; (iii) daily assessments using electronic rating scales. Data will be analyzed using nonlinear techniques and deep anomaly detection to forecast episodes of illness. DISCUSSION This proposed contactless, large cohort study aims to obtain and combine high-dimensional, multimodal physiological, objective, and subjective data. Our work, by conceptualizing mood as a dynamic property of biological systems, will demonstrate the feasibility of incorporating individual variability in a model informing clinical trajectories and predicting relapse in BD.
Collapse
Affiliation(s)
- Abigail Ortiz
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada.
- Centre for Addiction and Mental Health (CAMH), 100 Stokes St., Rm 4229, Toronto, ON, Canada.
| | - Arend Hintze
- Department of Computer Science, Dalarna University, Dalarna, Sweden
| | - Rachael Burnett
- Centre for Addiction and Mental Health (CAMH), 100 Stokes St., Rm 4229, Toronto, ON, Canada
| | - Christina Gonzalez-Torres
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
- Centre for Addiction and Mental Health (CAMH), 100 Stokes St., Rm 4229, Toronto, ON, Canada
| | - Samantha Unger
- Centre for Addiction and Mental Health (CAMH), 100 Stokes St., Rm 4229, Toronto, ON, Canada
| | - Dandan Yang
- Centre for Addiction and Mental Health (CAMH), 100 Stokes St., Rm 4229, Toronto, ON, Canada
- Department of Pharmacology, University of Toronto, Toronto, Ontario, Canada
| | - Jingshan Miao
- Centre for Addiction and Mental Health (CAMH), 100 Stokes St., Rm 4229, Toronto, ON, Canada
- Department of Pharmacology, University of Toronto, Toronto, Ontario, Canada
| | - Martin Alda
- Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia, Canada
- National Institute of Mental Health, Klecany, Czech Republic
| | - Benoit H Mulsant
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
- Centre for Addiction and Mental Health (CAMH), 100 Stokes St., Rm 4229, Toronto, ON, Canada
| |
Collapse
|