Which Actigraphy Dimensions Predict Longitudinal Outcomes in Bipolar Disorders?
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ABSTRACT:
SUBMITTER: Ferrand L
PROVIDER: S-EPMC9027161 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Functional disability is the lead contributor to burden of mental illness. Cognitive deficits frequently limit functional recovery, although whether changes in cognition and disability are longitudinally associated in recent-onset individuals remains unclear. Using a prospective, cohort design, 311 patients were recruited and assessed at baseline. One hundred and sixty-seven patients met eligibility criteria (M=21.5 years old, s.d.=4.8) and returned for follow-up (M=20.6 months later, s.d.=7.8). Two-hundred and thirty participants were included in the final analysis, comprising clinically stable patients with major depression (n=71), bipolar disorder (BD; n=61), schizophrenia-spectrum disorders (n=35) and 63 healthy controls. Neuropsychological functioning and self-rated functional disability were examined using mixed-design, repeated-measures analysis, across diagnoses and cognitive clusters, covarying for relevant confounds. Clinical, neuropsychological and functional changes did not differ between diagnoses (all P>0.05). Three reliable neuropsychological subgroups emerged through cluster analysis, characterized by psychomotor slowing, improved sustained attention, and improved verbal memory. Controlling for diagnosis and changes in residual symptoms, clusters with improved neuropsychological functioning observed greater reductions in functional disability than the psychomotor slowing cluster, which instead demonstrated a worsening in disability (P<0.01). Improved sustained attention was independently associated with greater likelihood of follow-up employment (P<0.01). Diagnosis of BD uniquely predicted both follow-up employment and independent living. Neuropsychological course appears to be independently predictive of subjective and objective functional outcomes. Importantly, cognitive phenotypes may reflect distinct pathophysiologies shared across major psychiatric conditions, and be ideal targets for personalized early intervention.
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Project description:Survival prediction is highly valued in end-of-life care clinical practice, and patient performance status evaluation stands as a predominant component in survival prognostication. While current performance status evaluation tools are limited to their subjective nature, the advent of wearable technology enables continual recordings of patients' activity and has the potential to measure performance status objectively. We hypothesize that wristband actigraphy monitoring devices can predict in-hospital death of end-stage cancer patients during the time of their hospital admissions. The objective of this study was to train and validate a long short-term memory (LSTM) deep-learning prediction model based on activity data of wearable actigraphy devices. The study recruited 60 end-stage cancer patients in a hospice care unit, with 28 deaths and 32 discharged in stable condition at the end of their hospital stay. The standard Karnofsky Performance Status score had an overall prognostic accuracy of 0.83. The LSTM prediction model based on patients' continual actigraphy monitoring had an overall prognostic accuracy of 0.83. Furthermore, the model performance improved with longer input data length up to 48 h. In conclusion, our research suggests the potential feasibility of wristband actigraphy to predict end-of-life admission outcomes in palliative care for end-stage cancer patients. Clinical Trial Registration: The study protocol was registered on ClinicalTrials.gov (ID: NCT04883879).
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Project description:INTRODUCTION:Structural alterations may correlate with symptom severity in psychotic disorders, but the existing literature on this issue is heterogeneous. In addition, it is not known how cortical thickness and cortical surface area correlate with symptom dimensions of psychosis. METHODS:Subjects included 455 individuals with schizophrenia, schizoaffective, or bipolar I disorders. Data were obtained as part of the Bipolar Schizophrenia Network for Intermediate Phenotypes study. Diagnosis was made through the Structured Clinical Interview for DSM-IV. Positive and negative symptom subscales were assessed using the Positive and Negative Syndrome Scale. Structural brain measurements were extracted from T1-weight structural MRIs using FreeSurfer v5.1 and were correlated with symptom subscales using partial correlations. Exploratory factor analysis was also used to identify factors among those regions correlating with symptom subscales. RESULTS:The positive symptom subscale correlated inversely with gray matter volume (GMV) and cortical thickness in frontal and temporal regions, whereas the negative symptom subscale correlated inversely with right frontal cortical surface area. Among regions correlating with the positive subscale, factor analysis identified four factors, including a temporal cortical thickness factor and frontal GMV factor. Among regions correlating with the negative subscale, factor analysis identified a frontal GMV-cortical surface area factor. There was no significant diagnosis by structure interactions with symptom severity. CONCLUSIONS:Structural measures correlate with positive and negative symptom severity in psychotic disorders. Cortical thickness demonstrated more associations with psychopathology than cortical surface area.
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Project description:OBJECTIVE:The authors sought to identify and evaluate longitudinal mood trajectories and associated baseline predictors in youths with bipolar disorder. METHOD:A total of 367 outpatient youths (mean age, 12.6 years) with bipolar disorder with at least 4 years of follow-up were included. After intake, participants were interviewed on average 10 times (SD=3.2) over a mean of 93 months (SD=8.3). Youths and parents were interviewed for psychopathology, functioning, treatment, and familial psychopathology and functioning. RESULTS:Latent class growth analysis showed four different longitudinal mood trajectories: "predominantly euthymic" (24.0%), "moderately euthymic" (34.6%), "ill with improving course" (19.1%), and "predominantly ill" (22.3%). Within each class, youths were euthymic on average 84.4%, 47.3%, 42.8%, and 11.5% of the follow-up time, respectively. Multivariate analyses showed that better course was associated with higher age at onset of mood symptoms, less lifetime family history of bipolar disorder and substance abuse, and less history at baseline of severe depression, manic symptoms, suicidality, subsyndromal mood episodes, and sexual abuse. Most of these factors were more noticeable in the "predominantly euthymic" class. The effects of age at onset were attenuated in youths with lower socioeconomic status, and the effects of depression severity were absent in those with the highest socioeconomic status. CONCLUSIONS:A substantial proportion of youths with bipolar disorder, especially those with adolescent onset and the above-noted factors, appear to be euthymic over extended periods. Nonetheless, continued syndromal and subsyndromal mood symptoms in all four classes underscore the need to optimize treatment.
| S-EPMC4164021 | biostudies-literature
Project description:Little longitudinal research has examined progression to more severe bipolar disorders in individuals with "soft" bipolar spectrum conditions. We examine rates and predictors of progression to bipolar I and II diagnoses in a nonpatient sample of college-age participants (n = 201) with high General Behavior Inventory scores and childhood or adolescent onset of "soft" bipolar spectrum disorders followed longitudinally for 4.5 years from the Longitudinal Investigation of Bipolar Spectrum (LIBS) project. Of 57 individuals with initial cyclothymia or bipolar disorder not otherwise specified (BiNOS) diagnoses, 42.1% progressed to a bipolar II diagnosis and 10.5% progressed to a bipolar I diagnosis. Of 144 individuals with initial bipolar II diagnoses, 17.4% progressed to a bipolar I diagnosis. Consistent with hypotheses derived from the clinical literature and the Behavioral Approach System (BAS) model of bipolar disorder, and controlling for relevant variables (length of follow-up, initial depressive and hypomanic symptoms, treatment-seeking, and family history), high BAS sensitivity (especially BAS Fun Seeking) predicted a greater likelihood of progression to bipolar II disorder, whereas early age of onset and high impulsivity predicted a greater likelihood of progression to bipolar I (high BAS sensitivity and Fun-Seeking also predicted progression to bipolar I when family history was not controlled). The interaction of high BAS and high Behavioral Inhibition System (BIS) sensitivities also predicted greater likelihood of progression to bipolar I. We discuss implications of the findings for the bipolar spectrum concept, the BAS model of bipolar disorder, and early intervention efforts.
| S-EPMC3192298 | biostudies-literature
Project description:BACKGROUND:The current interstitial lung disease (ILD) classification has overlapping clinical presentations and outcomes. Cluster analysis modeling is a valuable tool in identifying distinct clinical phenotypes in heterogeneous diseases. However, this approach has yet to be implemented in ILD. METHODS:Using cluster analysis, novel ILD phenotypes were identified among subjects from a longitudinal ILD cohort, and outcomes were stratified according to phenotypic clusters compared with subgroups according to current American Thoracic Society/European Respiratory Society ILD classification criteria. RESULTS:Among subjects with complete data for baseline variables (N = 770), four clusters were identified. Cluster 1 (ie, younger white obese female subjects) had the highest baseline FVC and diffusion capacity of the lung for carbon monoxide (Dlco). Cluster 2 (ie, younger African-American female subjects with elevated antinuclear antibody titers) had the lowest baseline FVC. Cluster 3 (ie, elderly white male smokers with coexistent emphysema) had intermediate FVC and Dlco. Cluster 4 (ie, elderly white male smokers with severe honeycombing) had the lowest baseline Dlco. Compared with classification according to ILD subgroup, stratification according to phenotypic clusters was associated with significant differences in monthly FVC decline (Cluster 4, -0.30% vs Cluster 2, 0.01%; P < .0001). Stratification by using clusters also independently predicted progression-free survival (P < .001) and transplant-free survival (P < .001). CONCLUSIONS:Among adults with diverse chronic ILDs, cluster analysis using baseline characteristics identified four distinct clinical phenotypes that might better predict meaningful clinical outcomes than current ILD diagnostic criteria.
| S-EPMC5815877 | biostudies-other
Project description:Clinical trials in sickle cell disease (SCD) often focus on health care utilization for painful vaso-occlusive crises (VOCs). However, no objective, quantifiable pain biomarkers exist, pain is not specific to VOCs, health care utilization varies between patients, unreported at-home VOCs likely contribute to long-term outcomes, and patient-reported outcomes are seldom considered. This noninterventional, longitudinal, 6-month study aimed to develop tools to identify VOCs in SCD patients with or without health care utilization. Participants wore an actigraph device, tracking sleep and activity. Patients with SCD used an electronic patient-reported outcome (ePRO) tool to collect data on pain, medication, fatigue, and daily function. Patients self-reported when they experienced VOC pain (VOC day). Biomarkers were collected every 3 weeks (non-VOC). Self-reported VOCs triggered at-home or in-hospital blood collection. The study enrolled 37 participants with SCD; 35 completed the study. Participants reported 114 VOC events and 346 VOC days, of which 62.3% and 78.3%, respectively, were self-treated at home. The ePRO and actigraphy captured end points of pain, functionality, fatigue, activity, and sleep; each was significantly altered on VOC days compared with non-VOC days. Biomarkers collected at home or in the hospital on VOC days were significantly altered compared with non-VOC baseline values, including leukocyte-platelet aggregates, microfluidic-based blood cell adhesion, interleukin-6, C-reactive protein, interleukin-10, tumor necrosis factor-α, and thrombin-antithrombin. The Evaluation of Longitudinal Pain Study in Sickle Cell Disease (ELIPSIS) trial shows the feasibility of accurately monitoring out-of-hospital pain by using patient-reported VOC days as potential end points for clinical trials in SCD; it describes the changes in biomarkers and activity measured by actigraphy that may enable improved identification and assessment of VOCs.
| S-EPMC8057263 | biostudies-literature
Project description:Alterations in activity and connectivity of brain circuits implicated in emotion processing and emotion regulation have been observed during resting-state for different clinical phases of bipolar disorders (BD), but longitudinal investigations across different mood states in the same patients are still rare. Furthermore, measuring dynamics of functional connectivity patterns offers a powerful method to explore changes in the brain's intrinsic functional organization across mood states. We used a novel co-activation pattern (CAP) analysis to explore the dynamics of amygdala connectivity at rest in a cohort of 20 BD patients prospectively followed-up and scanned across distinct mood states: euthymia (20 patients; 39 sessions), depression (12 patients; 18 sessions), or mania/hypomania (14 patients; 18 sessions). We compared them to 41 healthy controls scanned once or twice (55 sessions). We characterized temporal aspects of dynamic fluctuations in amygdala connectivity over the whole brain as a function of current mood. We identified six distinct networks describing amygdala connectivity, among which an interoceptive-sensorimotor CAP exhibited more frequent occurrences during hypomania compared to other mood states, and predicted more severe symptoms of irritability and motor agitation. In contrast, a default-mode CAP exhibited more frequent occurrences during depression compared to other mood states and compared to controls, with a positive association with depression severity. Our results reveal distinctive interactions between amygdala and distributed brain networks in different mood states, and foster research on interoception and default-mode systems especially during the manic and depressive phase, respectively. Our study also demonstrates the benefits of assessing brain dynamics in BD.
| S-EPMC8280117 | biostudies-literature
Project description:BackgroundWrist-worn actigraphy can objectively measure sleep, and has advantages over self-report, particularly for people with Bipolar Disorder (BD) for whom self-reports might be influenced by affect. Clinically useful data reduction approaches are needed to explore these complex data.MethodsWe created a composite score of sleep metrics in BD based on 51 BD and 80 healthy comparison (HC) participants. Subjects wore an actigraph for up to 14 consecutive 24-h periods, and we assessed total sleep time (TST), wake after sleep onset (WASO), percent sleep (PS), and number of awakenings (NA). We focused on participants who had at least 5 nights of actigraphy data. We computed z-scores for within-person means of sleep measures for BD subjects versus HCs, which were averaged to create a composite measure. We correlated this composite with participant characteristics, and used LASSO regression to identify sleep measures best explaining variability in identified correlates.ResultsSleep measures and the composite did not differ between BDs and HCs; however, there was considerable variability in z-scores among those with BD. In BDs, the composite score was higher in women (t(49) = 2.28, p = 0.027) and those who were employed (t(34) = 2.34, p = 0.025), and positively correlated with medication load (r = 0.41, p = 0.003) while negatively correlated with Young Mania Rating Scale (YMRS; r = -0.35, p = 0.030). In LASSO regression, TST and NA best explained medication load while PS best explained employment and YMRS.ConclusionWhile a composite score of sleep metrics may provide useful information about sleep quality globally, our findings suggest that selection of theory-driven sleep measures may be more clinically meaningful.
| S-EPMC8722119 | biostudies-literature
Project description:BACKGROUND:The concept of misperception of sleep refers to the estimated discrepancy between subjective and objective measures of sleep. This has been assessed only in a few prior studies in individuals with Bipolar Disorder (BD) as compared to Healthy Controls (HC) and with mixed results. METHODS:We assessed a sample of 133 euthymic individuals with BD and 63 HC for retrospective subjective (Pittsburgh Sleep Quality Index) and objective (21 days of actigraphy recording) measures of total sleep time, sleep latency and sleep efficiency. We first investigated the correlations between these subjective and objective measures in the two groups. We then compared individuals with BD and HC for the absolute values of the differences between subjective and objective sleep parameters, used as a proxy of the magnitude of misperception of sleep. Finally, we undertook regression analyses to assess associations between clinical groups, core demographics, clinical factors and misperception of sleep. RESULTS:The correlation coefficients between subjective and objective measures of sleep did not differ between groups (total sleep time: rho?=?.539 in BD and rho?=?.584 in HC; sleep latency: rho?=?.190 in BD and rho?=?.125 in HC; sleep efficiency: rho?=?.166 in BD and rho?=?.222 in HC). Individuals with BD did not differ from HC in the magnitude of misperception of total sleep time, sleep latency nor sleep efficiency. Individuals with BD type 1 misperceived their sleep efficiency significantly more than individuals with BD type 2, with no further difference between BD type 1 and BD type 2 regarding sleep latency and sleep duration misperceptions. Three factors (age, symptoms of obstructive sleep apnea, and mild depressive symptoms), were the main contributors to the magnitude of misperception of sleep. CONCLUSIONS:Misperception of sleep was not associated with a diagnosis of BD. In this sample, mild depressive symptoms, older age, or symptoms of obstructive sleep apnea may be related to greater sleep misperception. In that case, the reliability of subjective measures may decrease as the misperception of sleep increases. This study may help guide clinicians in selecting the best approach for assessing sleep (objective versus subjective measures) in individuals with BD.
| S-EPMC7677419 | biostudies-literature