Stochastic modelling of transition dynamic of mixed mood episodes in bipolar disorder

In the present state of health and wellness, mental illness is always deemed less importance compared to other forms of physical illness. In reality, mental illness causes serious multi-dimensional adverse effect to the subject with respect to personal life, social life, as well as financial stability. In the area of mental illness, bipolar disorder is one of the most prominent type which can be triggered by any external stimulation to the subject suffering from this illness. There diagnosis as well as treatment process of bipolar disorder is very much different from other form of illness where the first step of impediment is the correct diagnosis itself. According to the standard body, there are classification of discrete forms of bipolar disorder viz. type-I, type-II, and cyclothymic. Which is characterized by specific mood associated with depression and mania. However, there is no study associated with mixed-mood episode detection which is characterized by combination of various symptoms of bipolar disorder in random, unpredictable, and uncertain manner. Hence, the model contributes to obtain granular information with dynamics of mood transition. The simulated outcome of the proposed system in MATLAB shows that resulting model is capable enough for detection of mixed mood episode precisely

Association between circadian activity rhythms and mood episode relapse in bipolar disorder: a 12-month prospective cohort study

A significant proportion of patients with bipolar disorder experience mood episode relapses. We examined whether circadian activity rhythms were associated with mood episode relapses in patients with bipolar disorder. This prospective cohort study included outpatients with bipolar disorder who participated in a study titled “Association between the Pathology of Bipolar Disorder and Light Exposure in Daily Life (APPLE) cohort study.” The participants’ physical activity was objectively assessed using a wrist-worn accelerometer over 7 consecutive days for the baseline assessment and then at the 12-month follow-up for mood episode relapses. The levels and timing of the circadian activity rhythms were estimated using a cosinor analysis and a nonparametric circadian rhythm analysis. Of the 189 participants, 88 (46%) experienced mood episodes during follow-up. The Cox proportional hazards model adjusting for potential confounders showed that a robust circadian activity rhythm, including midline-estimating statistic of rhythm (MESOR) and amplitude by cosinor analysis and 10 consecutive hours with the highest amplitude values (M10) by the nonparametric circadian rhythm analysis, was significantly associated with a decrease in mood episode relapses (per counts/min, hazard ratio [95% confidence interval]: MESOR, 0.993 [0.988–0.997]; amplitude, 0.994 [0.988–0.999]; and M10, 0.996 [0.993–0.999]). A later timing of the circadian activity rhythm (M10 onset time) was significantly associated with an increase in the depressive episode relapses (per hour; 1.109 [1.001–1.215]). We observed significant associations between circadian activity rhythms and mood episode relapses in bipolar disorder.

Does recurrent catatonia manifest in a similar fashion in all the episodes of mood disorder? A case series with literature review

Catatonia, originally conceptualised by Kahlbaum in 1868, is a neuropsychiatric condition that has been found to occur concomitantly with several organic and psychiatric conditions. Starting from the era of Kraepelin and Bleuler, this condition was faultily linked with schizophrenia alone; however, over time, greater associations have been found between catatonia and mood disorders. Despite the availability of several reports supporting this finding, there is a relative paucity of studies that specifically focus on catatonia to be the first symptom manifestation heralding a subsequent mood episode. In addition, there is scant literature to determine whether there are specific presentations of catatonia that show greater associations with mood disorders and whether these signs and symptoms recur in a stereotypical fashion in the subsequent mood episodes in the lifetime of an individual. We hereby report two cases with a diagnosis of mood disorders (bipolar disorder and recurrent depressive disorder) who had catatonia as the initial symptom not only at presentation but also at subsequent episodes. The report emphasises that recurrent catatonia can be the initial clinical manifestation of an underlying mood episode, which appears otherwise masked behind the catatonic presentation. These catatonic symptoms can be interestingly similar in all the subsequent episodes. A detailed clinical evaluation is thus warranted after catatonia has been duly treated to provide a holistic management.

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 (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.

Recurrence rates in stable bipolar disorder patients after drug discontinuation v. drug maintenance: a systematic review and meta-analysis

Background This random-effects model meta-analysis of double-blind, randomized placebo-controlled trials compared recurrence rates in bipolar disorder (BD) patients between antipsychotic/mood stabilizer discontinuation and maintenance groups. Methods We conducted systematic literature search of Embase, PubMed, and CENTRAL databases without language restriction from inception until 22 May 2020. Independent investigators assessed studies and extracted data. We calculated risk ratios (RRs) and numbers needed to benefit or harm (NNTB/NNTH). Primary outcome was the recurrence rate of any mood episode at 6 months. Secondary outcomes were recurrence rates of depressive episodes and manic/hypomanic/mixed episodes and all-cause discontinuation at 6 months. We also investigated these outcomes at 1, 3, 9, 12, 18, and 24 months. Results We identified 22 studies (n = 5462) receiving aripiprazole, asenapine, divalproex, long-acting injectable (LAI)-aripiprazole, LAI-risperidone, lamotrigine, lithium, olanzapine, paliperidone, or quetiapine. Mean study duration was 64.50 ± 69.35 weeks. The maintenance group demonstrated lower recurrence rates of any mood episode, depressive episodes, and manic/hypomanic/mixed episodes as well as reduced all-cause discontinuation at every observational point. The RRs (95% confidence interval, NNTB/NNTH) of recurrence rate at 6 months were 0.61 (0.54–0.70, 5) for any mood episode, 0.72 (0.60–0.87, 13) for depressive episodes, and 0.45 (0.36–0.57, 6) for manic/hypomanic/mixed episodes. The RR for all-cause discontinuation at 6 months was 0.71 (0.61–0.82, 6). Conclusions Maintaining drug treatment during clinically stable BD prevented recurrence for up to 24 months. Discontinuation of medications for ⩾1 month significantly increased recurrence risk. However, 47.3% of patients who discontinued drugs for 6 months did not experience recurrence.