Stability of the diagnosis of seasonal affective disorder in a long-term prospective study

Psychiatric emergency department visits during the coronavirus disease-2019 pandemic

Background

Previous research has demonstrated the negative impact of the coronavirus disease-2019 (COVID-19) pandemic on mental health.

Aims

To examine changes in the Chinese psychiatric emergency department (PED) visits for mental health crises that occurred during the pandemic.

Methods

Before and during the COVID-19 pandemic, PED visit counts from the largest psychiatric hospital in China between 2018 and 2020 were investigated. Electronic medical records of 2020 PED visits were extracted during the COVID-19 pandemic period and compared for the same period of 2018 and 2019.

Results

Overall, PED visits per year increased from 1,767 in 2018 to 2210 (an increase of 25.1%) in 2019 and 2,648 (an increase of 49.9%) in 2020. Compared with 2 years before the epidemic, during the COVID-19 pandemic, the proportion of PED visits among patients with stress disorders, sleep disorders, and anxiety disorders increased significantly. In terms of the distribution of demographic characteristics, age shows a younger trend, while the gender difference is not significant.

Conclusion

These findings suggest that PED care-seeking increases during the COVID-19 pandemic, highlighting the need to integrate mental health services for patients with stress, sleep, anxiety, and obsessive-compulsive disorders during public health crises.

Severe psychiatric disorders and general medical comorbidities: inflammation-related mechanisms and therapeutic opportunities

Individuals with severe psychiatric disorders, such as mood disorders and schizophrenia, are at increased risk of developing other medical conditions, especially cardiovascular and metabolic diseases. These medical conditions are underdiagnosed and undertreated in these patients contributing to their increased morbidity and mortality. The basis for this increased comorbidity is not well understood, possibly reflecting shared risks factors (e.g. lifestyle risk factors), shared biological mechanisms and/or reciprocal interactions. Among overlapping pathophysiological mechanisms, inflammation and related factors, such as dysbiosis and insulin resistance, stand out. Besides underlying the association between psychiatric disorders and cardiometabolic diseases, these mechanisms provide several potential therapeutic targets.

Predictability of Seasonal Mood Fluctuations Based on Self-Report Questionnaires and EEG Biomarkers in a Non-clinical Sample

Induced by decreasing light, people affected by seasonal mood fluctuations may suffer from low energy, have low interest in activities, experience changes in weight, insomnia, difficulties in concentration, depression, and suicidal thoughts. Few studies have been conducted in search for biological predictors of seasonal mood fluctuations in the brain, such as EEG oscillations. A sample of 64 participants was examined with questionnaires and electroencephalography in summer. In winter, a follow-up survey was recorded and participants were grouped into those with at least mild (N = 18) and at least moderate (N = 11) mood decline and those without self-reported depressive symptoms both in summer and in winter (N = 46). A support vector machine was trained to predict mood decline by either EEG biomarkers alone, questionnaire data from baseline alone, or a combination of the two. Leave-one-out-cross validation with lasso regularization was used with logistic regression to fit a model. The accuracy for classification for at least mild/moderate mood decline was 77/82% for questionnaire data, 72/82% for EEG alone, and 81/86% for EEG combined with questionnaire data. Self-report data was more conclusive than EEG biomarkers recorded in summer for prediction of worsening of depressive symptoms in winter but it is advantageous to combine EEG with psychological assessment to boost predictive performance.

A new approach for seasonal pattern: is it related to bipolarity dimension? Findings from an Italian multicenter study

OBJECTIVE

The aims of this study were to assess the impact of seasonal pattern on several clinical dimensions in inpatients with a current major depressive episode and to evaluate clinical differences between unipolar and bipolar depression according to seasonal pattern.

METHODS

Study participants were 300 patients affected by major depressive disorder (MDD) or bipolar disorder (BD) currently experiencing a major depressive episode (MDE) and were recruited at three University Medical Centres in Italy. All study subjects completed several evaluation scales for depressive and hypomanic symptoms, quality of life and functioning, impulsiveness, and seasonal pattern.

RESULTS

Several differences between BD with and without seasonal pattern, MDD with and without seasonal pattern but in particular between BD and MDD with seasonal pattern were found. Patients with MDE with seasonal pattern had more frequently received a longitudinal diagnosis of BD.

CONCLUSIONS

A large number of patients with BD and seasonal pattern, but also a considerable number of patients with MDD and seasonal pattern, endorsed manic items during a current MDE. Seasonal pattern should be associated with a concept of bipolarity in mood disorders and not only related to bipolar disorder. A correct identification of seasonal patterns may lead to the implementation of personalised pharmacological treatment approaches.KEY POINTSHigh prevalence of mixed features in mood disorders with seasonal pattern, supporting the need for a dimensional approach to major depressive disorder and bipolar disorder.Significant percentage of patients with a primary diagnosis of major depressive disorder had seasonal pattern.Significant percentage of patients with a primary diagnosis of major depressive disorder reported (hypo)manic symptomatology.

The darkness and the light: diurnal rodent models for seasonal affective disorder

The development of animal models is a critical step for exploring the underlying pathophysiological mechanisms of major affective disorders and for evaluating potential therapeutic approaches. Although most neuropsychiatric research is performed on nocturnal rodents, differences in how diurnal and nocturnal animals respond to changing photoperiods, combined with a possible link between circadian rhythm disruption and affective disorders, has led to a call for the development of diurnal animal models. The need for diurnal models is most clear for seasonal affective disorder (SAD), a widespread recurrent depressive disorder that is linked to exposure to short photoperiods. Here, we briefly review what is known regarding the etiology of SAD and then examine progress in developing appropriate diurnal rodent models. Although circadian disruption is often invoked as a key contributor to SAD, a mechanistic understanding of how misalignment between endogenous circadian physiology and daily environmental rhythms affects mood is lacking. Diurnal rodents show promise as models of SAD, as changes in affective-like behaviors are induced in response to short photoperiods or dim-light conditions, and symptoms can be ameliorated by brief exposure to intervals of bright light coincident with activity onset. One exciting avenue of research involves the orexinergic system, which regulates functions that are disturbed in SAD, including sleep cycles, the reward system, feeding behavior, monoaminergic neurotransmission and hippocampal neurogenesis. However, although diurnal models make intuitive sense for the study of SAD and are more likely to mimic circadian disruption, their utility is currently hampered by a lack of genomic resources needed for the molecular interrogation of potential mechanisms.

Cross-sectional and within-subject seasonality and regularity of hospitalizations: A population study in mood disorders and schizophrenia

BACKGROUND

Seasonal peaks in hospitalizations for mood disorders and schizophrenia are well recognized and often replicated. The within-subject tendency to experience illness episodes in the same season, that is, seasonal course, is much less established, as certain individuals may temporarily meet criteria for seasonal course purely by chance.

AIMS

In this population, prospective cohort study, we investigated whether between and within-subject seasonal patterns of hospitalizations occurred more frequently than would be expected by chance.

METHODS

Using a compulsory, standardized national register of hospitalizations, we analyzed all admissions for mood disorders and schizophrenia in the Czech Republic between 1994 and 2013. We used bootstrap tests to compare the observed numbers of (a) participants with seasonal/regular course and (b) hospitalizations in individual months against empirical distributions obtained by simulations.

RESULTS

Among 87 184 participants, we found uneven distribution of hospitalizations, with hospitalization peaks for depression in April and November (X² (11) = 363.66, P < .001), for mania in August (X² (11) = 50.36, P < .001) and for schizophrenia in June (X² (11) = 70.34, P < .001). Significantly more participants than would be expected by chance, had two subsequent rehospitalizations in the same 90 days in different years (7.36%, bootstrap P < .01) or after a regular, but non-seasonal interval (6.07%, bootstrap P < .001). The proportion of participants with two consecutive hospitalizations in the same season was below chance level (7.06%).

CONCLUSIONS

Psychiatric hospitalizations were unevenly distributed throughout the year (cross-sectional seasonality), with evidence for regularity, but not seasonality of hospitalizations within subjects. Our data do not support the validity of seasonal pattern specifier. Season may be a general risk factor, which increases the risk of hospitalizations across psychiatric participants.

Prevalence of seasonal depression in a prospective cohort study

The prevalence of autumn/winter seasonality in depression has been documented in the longitudinal Zurich cohort study by five comprehensive diagnostic interviews at intervals over more than 20 years (N = 499). Repeated winter major depressive episodes (MDE-unipolar + bipolar) showed a prevalence of 3.44% (5× more women than men), whereas MDE with a single winter episode was much higher (9.96%). A total of 7.52% suffered from autumn/winter seasonality in major and minor depressive mood states. The clinical interviews revealed novel findings: high comorbidity of Social Anxiety Disorder and Agoraphobia within the repeated seasonal MDE group, high incidence of classic diurnal variation of mood (with evening improvement), as well as a high rate of oversensitivity to light, noise, or smell. Nearly twice as many of these individuals as in the other MDE groups manifested the syndrome of atypical depression (DSM-V), which supports the prior description of seasonal affective disorder (SAD) as presenting primarily atypical symptoms (which include hypersomnia and increase in appetite and weight). This long-term database of regular structured interviews provides important confirmation of SAD as a valid diagnosis, predominantly found in women, and with atypical vegetative symptoms.

Relationship between family history of alcohol problems and different clusters of depressive symptoms

Objectives:

Major depressive disorder (MDD) is a multifactorial syndrome with significant interactions between genetic and environmental factors. This study specifically investigates the association between family history of alcohol problems (FHAP) and family history of depression (FHD), and how these relate to different clusters of depressive symptoms.

Methods:

Correlations between FHAP and FHD and different clusters of the Beck Depression Inventory (BDI) were studied. We sampled 333 employees from a general hospital who had been receiving a psychiatric consultation between 2005 and 2012. Analysis of variance (ANOVA) and Analysis of covariance (ANCOVA) models were conducted to explore these correlations.

Results:

There was a significant positive correlation between FHAP and BDI affective score. This result remained significant even after the adjustment for other variables considered as important factors for MDD, such as gender, age, marital status, education, ethnic group and FHD. More specifically, FHAP was correlated with dissatisfaction and episodes of crying among the affective symptoms. FHAP showed no statistical difference in any of the other clusters score or in the BDI total score. Moreover, as expected, we found a correlation between FHD and BDI total score and Somatic and Cognitive clusters.

Conclusion:

FHAP should be routinely investigated in individuals presenting with depressive symptoms. This is especially important in cases presenting with dissatisfaction and episodes of crying in patients who do not endorse criteria for MDD. Due to study limitations, the findings require replication by neurobiological, epidemiological and clinical studies.

Seasonality of antidepressant prescriptions and sick leaves

The aim of the present study was to estimate the number of patients with a seasonal prescription pattern of antidepressants, which might be taken as a surrogate marker for medicated patients with seasonal affective disorder (SAD). Furthermore, we examined the time course of sick leaves for patients with seasonal and non-seasonal prescriptions of antidepressants. A retrospective analysis of prescription data of all patients insured by the Sickness Fund Burgenland (BGKK) between 2005 and 2016 was performed. Patients with treatment initiation of an antidepressant in the last and first quarter of the year for at least two consecutive years were selected (SAD-med). Patients with continuation treatment in the third quarter and patients with initiation of antidepressant medication in the second and third quarter of the year were excluded. The mean yearly prescription rate for antidepressants was 9.6% in the insured population. 3.0% of patients treated with antidepressants and 0.9% of insured cases satisfied the definition of SAD-med. The mean number of yearly sick leave days was similar for SAD-med patients and those with non-seasonal prescriptions. Time series analysis showed that sick leaves in SAD-med were influenced by seasonal fluctuations for several years after the first antidepressant prescription. Our study sheds light on antidepressant prescription and sick leave patterns in the general population. Compared to the prevalence of SAD, the estimated rate of SAD-med is substantial. Sick leaves appear to be closely linked to antidepressant prescriptions, and show a characteristic time course before and after the initial prescription.