•Fatigue and cognitive impairment are amongst the most common and debilitating symptoms of post-COVID-19 syndrome.•Approximately 1 in 3 individuals experienced fatigue 12 or more weeks following ...COVID-19 diagnosis.•Approximately 1 in 5 individuals exhibited cognitive impairment 12 or more weeks following COVID-19 diagnosis.•There was an elevation in proinflammatory markers and functional impairment in a subset of post-COVID individuals.
COVID-19 is associated with clinically significant symptoms despite resolution of the acute infection (i.e., post-COVID-19 syndrome). Fatigue and cognitive impairment are amongst the most common and debilitating symptoms of post-COVID-19 syndrome.
To quantify the proportion of individuals experiencing fatigue and cognitive impairment 12 or more weeks following COVID-19 diagnosis, and to characterize the inflammatory correlates and functional consequences of post-COVID-19 syndrome.
Systematic searches were conducted without language restrictions from database inception to June 8, 2021 on PubMed/MEDLINE, The Cochrane Library, PsycInfo, Embase, Web of Science, Google/Google Scholar, and select reference lists.
Primary research articles which evaluated individuals at least 12 weeks after confirmed COVID-19 diagnosis and specifically reported on fatigue, cognitive impairment, inflammatory parameters, and/or functional outcomes were selected.
Two reviewers independently extracted published summary data and assessed methodological quality and risk of bias. A meta-analysis of proportions was conducted to pool Freeman-Tukey double arcsine transformed proportions using the random-effects restricted maximum-likelihood model.
The co-primary outcomes were the proportions of individuals reporting fatigue and cognitive impairment, respectively, 12 or more weeks following COVID-19 infection. The secondary outcomes were inflammatory correlates and functional consequences associated with post-COVID-19 syndrome.
The literature search yielded 10,979 studies, and 81 studies were selected for inclusion. The fatigue meta-analysis comprised 68 studies, the cognitive impairment meta-analysis comprised 43 studies, and 48 studies were included in the narrative synthesis. Meta-analysis revealed that the proportion of individuals experiencing fatigue 12 or more weeks following COVID-19 diagnosis was 0.32 (95% CI, 0.27, 0.37; p < 0.001; n = 25,268; I2 = 99.1%). The proportion of individuals exhibiting cognitive impairment was 0.22 (95% CI, 0.17, 0.28; p < 0.001; n = 13,232; I2 = 98.0). Moreover, narrative synthesis revealed elevations in proinflammatory markers and considerable functional impairment in a subset of individuals.
A significant proportion of individuals experience persistent fatigue and/or cognitive impairment following resolution of acute COVID-19. The frequency and debilitating nature of the foregoing symptoms provides the impetus to characterize the underlying neurobiological substrates and how to best treat these phenomena.
PROSPERO (CRD42021256965).
Mood disorders have been recognized by the World Health Organization (WHO) as the leading cause of disability worldwide. Notwithstanding the established efficacy of conventional mood agents, many ...treated individuals continue to remain treatment refractory and/or exhibit clinically significant residual symptoms, cognitive dysfunction, and psychosocial impairment. Therefore, a priority research and clinical agenda is to identify pathophysiological mechanisms subserving mood disorders to improve therapeutic efficacy.
During the past decade, inflammation has been revisited as an important etiologic factor of mood disorders. Therefore, the purpose of this synthetic review is threefold: 1) to review the evidence for an association between inflammation and mood disorders, 2) to discuss potential pathophysiologic mechanisms that may explain this association and 3) to present novel therapeutic options currently being investigated that target the inflammatory–mood pathway.
Accumulating evidence implicates inflammation as a critical mediator in the pathophysiology of mood disorders. Indeed, elevated levels of pro-inflammatory cytokines have been repeatedly demonstrated in both major depressive disorder (MDD) and bipolar disorder (BD) patients. Further, the induction of a pro-inflammatory state in healthy or medically ill subjects induces ‘sickness behavior’ resembling depressive symptomatology.
Potential mechanisms involved include, but are not limited to, direct effects of pro-inflammatory cytokines on monoamine levels, dysregulation of the hypothalamic–pituitary–adrenal (HPA) axis, pathologic microglial cell activation, impaired neuroplasticity and structural and functional brain changes.
Anti-inflammatory agents, such as acetyl-salicylic acid (ASA), celecoxib, anti-TNF-α agents, minocycline, curcumin and omega-3 fatty acids, are being investigated for use in mood disorders. Current evidence shows improved outcomes in mood disorder patients when anti-inflammatory agents are used as an adjunct to conventional therapy; however, further research is needed to establish the therapeutic benefit and appropriate dosage.
•Inflammation and mood disorders have a bidirectional interaction.•Cytokines, monoamines, the HPA axis and microglial cells are key players involved.•Anti-inflammatory agents show promise for use in the treatment of mood disorders.
Obesity and mood disorders are highly prevalent and co-morbid. Epidemiological studies have highlighted the public health relevance of this association, insofar as both conditions and its ...co-occurrence are associated with a staggering illness-associated burden. Accumulating evidence indicates that obesity and mood disorders are intrinsically linked and share a series of clinical, neurobiological, genetic and environmental factors. The relationship of these conditions has been described as convergent and bidirectional; and some authors have attempted to describe a specific subtype of mood disorders characterized by a higher incidence of obesity and metabolic problems. However, the nature of this association remains poorly understood. There are significant inconsistencies in the studies evaluating metabolic and mood disorders; and, as a result, several questions persist about the validity and the generalizability of the findings. An important limitation in this area of research is the noteworthy phenotypic and pathophysiological heterogeneity of metabolic and mood disorders. Although clinically useful, categorical classifications in both conditions have limited heuristic value and its use hinders a more comprehensive understanding of the association between metabolic and mood disorders. A recent trend in psychiatry is to move toward a domain specific approach, wherein psychopathology constructs are agnostic to DSM-defined diagnostic categories and, instead, there is an effort to categorize domains based on pathogenic substrates, as proposed by the National Institute of Mental Health (NIMH) Research Domain Criteria Project (RDoC). Moreover, the substrates subserving psychopathology seems to be unspecific and extend into other medical illnesses that share in common brain consequences, which includes metabolic disorders. Overall, accumulating evidence indicates that there is a consistent association of multiple abnormalities in neuropsychological constructs, as well as correspondent brain abnormalities, with broad-based metabolic dysfunction, suggesting, therefore, that the existence of a "metabolic-mood syndrome" is possible. Nonetheless, empirical evidence is necessary to support and develop this concept. Future research should focus on dimensional constructs and employ integrative, multidisciplinary and multimodal approaches.
•Loneliness has been associated with adverse health outcomes, but few studies have evaluated its comparative effects on distinct health outcomes.•A scoping review reveals medium to large effects of ...loneliness on all health outcomes, with the largest effects on mental health outcomes and overall well-being.•Healthcare providers should be adequately trained to perceive and respond to loneliness due to its strong associations with adverse health outcomes.
The primary objective was to evaluate the comparative effects of loneliness on multiple distinct health outcomes. The literature was qualitatively reviewed to identify loneliness risk factors, explore mechanisms, and discuss potential evidence-based interventions for targeting loneliness. 114 identified studies were systematically reviewed and analyzed to examine for associations between loneliness (as measured by the UCLA Loneliness or de Jong Gierveld Loneliness Scales) and one or more health outcome(s). Health outcomes were broadly defined to include measures of mental health (i.e., depression, anxiety, suicidality, general mental health), general health (i.e., overall self-rated health), well-being (i.e., quality of life, life satisfaction), physical health (i.e., functional disability), sleep, and cognition. Loneliness had medium to large effects on all health outcomes, with the largest effects on mental health and overall well-being; however, this result may have been confounded by the breadth of studies exploring the association between loneliness and mental health, as opposed to other health outcomes. A significant effect of gender on the association between loneliness and cognition (i.e., more pronounced in studies with a greater proportion of males) was also observed. The adequate training of health care providers to perceive and respond to loneliness among patients should be prioritized.
•We hypothesized that timely government implementation of stringent measures to reduce COVID-19 transmission would benefit mental health, as evidenced by reduced rates of depressive symptoms.•We ...evaluated data from 33 countries (k=114, N=640,037) in our systematic review (six lower-middle-income countries, nine upper-middle-income countries, and 18 higher-income countries).•Government-imposed stringency and timeliness in response were operationalized using the Oxford COVID-19 Government Response (“Stringency”) Index.•The prevalence of clinically significant depressive symptoms was significantly lower in countries wherein governments implemented stringent policies promptly.•The moderating effect of government response remained significant after including the national frequency of COVID cases at the time of study commencement, Healthcare Access and Quality index, and the inclusion of COVID patients in the study.
The COVID-19 pandemic represents a public health, economic and mental health crisis. We hypothesized that timely government implementation of stringent measures to reduce viral transmission would benefit mental health, as evidenced by reduced rates of depressive symptoms (i.e., Patient Health Questionnaire PHQ-9≥10, PHQ-2≥3).
The systematic review herein (PROSPERO CRD42020200647) evaluated to what extent differences in government-imposed stringency and timeliness of response to COVID-19 moderate the prevalence of depressive symptoms across 33 countries (k=114, N=640,037). We included data from six lower-middle-income countries, nine upper-middle-income countries, and 18 higher-income countries. Government-imposed stringency and timeliness in response were operationalized using the Oxford COVID-19 Government Response (“Stringency”) Index.
The overall proportion of study participants with clinically significant depressive symptoms was 21.39% (95% CI 19.37–23.47). The prevalence of clinically significant depressive symptoms was significantly lower in countries wherein governments implemented stringent policies promptly. The moderating effect of government response remained significant after including the national frequency of COVID cases at the time of study commencement, Healthcare Access and Quality index, and the inclusion of COVID patients in the study.
Factors that may have confounded our results include, for example, differences in lockdown duration, lack of study participant and outcome assessor blinding, and retrospective assessment of depressive symptom severity.
Governments that enacted stringent measures to contain the spread of COVID-19 benefited not only the physical, but also the mental health of their population.
Type 2 Diabetes Mellitus (T2DM) and Major Depressive Disorder (MDD) are leading causes of disability worldwide. Indeed, both are costly and burdensome diseases at both individual and socio-economic ...levels. Notably, there are similar pathophysiological elements, which might explain the overlap in phenotypic symptoms and the high rate of comorbidity. Brain insulin resistance is a shared metabolic abnormality amongst many individuals with T2DM and MDD. Patients with either or both diseases often exhibit disturbances in cognition and mood, as well as the presence of anhedonia-like symptoms. However, individuals with T2DM with high glycemic control have reduced cognitive and depressive symptom burden. Based on this evidence, it is possible that repurposing therapies approved for treating insulin resistance may be useful in treating cognitive and anhedonia symptoms in depression. The objective of this review is to discuss the relationship between brain insulin resistance and depression, as well as possible disease modifying therapeutic agents targeting insulin signalling.
Abstract Objective Comprehensively review studies evaluating factors associated with adherence to treatment in bipolar disorder (BD), as well as the results of interventions developed to enhance ...adherence in this population. Methods The following search engines were consulted: PubMed, Scielo, LILACS and PsycINFO. The keywords used were “Bipolar Disorder”, “Factor”, “Adherence”, “Nonadherence”, “Compliance” and “Intervention”. In addition, references list of selected studies were consulted searching for relevant articles. Results Adherence has been defined in various ways, with some considering adherence vs. nonadherence, and other including a “partial” adherence measure. In addition, methods to assess adherence differ for each study. Several factors were related to poor adherence, including patient-related factors (e.g. younger age, male gender, low level of education, alcohol and drugs comorbidity), disorder-related factors (e.g. younger age of onset, severity of BD, insight and lack of awareness of illness) and treatment-related factors (e.g. side effects of medications, effectiveness). To improve adherence, the main recommendations are to provide customized interventions focusing on the underlying causes of nonadherence, strong therapeutic alliance and different modalities based on psychoeducation. Conclusion Our results indicate that nonadherence is a multicausal phenomenon and strategies to prevent and approaches them must include enhanced therapeutic alliance, flexible topics, early intervention, group setting, and psychoeducation. Limitations Different definitions and measures of adherence in the literature currently moderate the generalization of the findings in this review. Further studies are necessary regarding factors of adherence in BD and interventions to improve it, especially on social factors like stigma and family.
Bipolar disorders are a complex group of severe and chronic disorders that includes bipolar I disorder, defined by the presence of a syndromal, manic episode, and bipolar II disorder, defined by the ...presence of a syndromal, hypomanic episode and a major depressive episode. Bipolar disorders substantially reduce psychosocial functioning and are associated with a loss of approximately 10–20 potential years of life. The mortality gap between populations with bipolar disorders and the general population is principally a result of excess deaths from cardiovascular disease and suicide. Bipolar disorder has a high heritability (approximately 70%). Bipolar disorders share genetic risk alleles with other mental and medical disorders. Bipolar I has a closer genetic association with schizophrenia relative to bipolar II, which has a closer genetic association with major depressive disorder. Although the pathogenesis of bipolar disorders is unknown, implicated processes include disturbances in neuronal-glial plasticity, monoaminergic signalling, inflammatory homoeostasis, cellular metabolic pathways, and mitochondrial function. The high prevalence of childhood maltreatment in people with bipolar disorders and the association between childhood maltreatment and a more complex presentation of bipolar disorder (eg, one including suicidality) highlight the role of adverse environmental exposures on the presentation of bipolar disorders. Although mania defines bipolar I disorder, depressive episodes and symptoms dominate the longitudinal course of, and disproportionately account for morbidity and mortality in, bipolar disorders. Lithium is the gold standard mood-stabilising agent for the treatment of people with bipolar disorders, and has antimanic, antidepressant, and anti-suicide effects. Although antipsychotics are effective in treating mania, few antipsychotics have proven to be effective in bipolar depression. Divalproex and carbamazepine are effective in the treatment of acute mania and lamotrigine is effective at treating and preventing bipolar depression. Antidepressants are widely prescribed for bipolar disorders despite a paucity of compelling evidence for their short-term or long-term efficacy. Moreover, antidepressant prescription in bipolar disorder is associated, in many cases, with mood destabilisation, especially during maintenance treatment. Unfortunately, effective pharmacological treatments for bipolar disorders are not universally available, particularly in low-income and middle-income countries. Targeting medical and psychiatric comorbidity, integrating adjunctive psychosocial treatments, and involving caregivers have been shown to improve health outcomes for people with bipolar disorders. The aim of this Seminar, which is intended mainly for primary care physicians, is to provide an overview of diagnostic, pathogenetic, and treatment considerations in bipolar disorders. Towards the foregoing aim, we review and synthesise evidence on the epidemiology, mechanisms, screening, and treatment of bipolar disorders.
•Mood disorders could have metabolic manifestations as part of the psychiatric syndrome.•Diet interventions present a unique and potentially useful treatment avenue for mood disorders.•Preliminary ...data suggest a potential role for ketogenic diet in the treatment of mood disorders.
Despite significant advances in pharmacological and non-pharmacological treatments, mood disorders remain a significant source of mental capital loss, with high rates of treatment resistance, requiring a coordinated effort in investigation and development of efficient, tolerable and accessible novel interventions. Ketogenic diet (KD) is a low-carb diet that substantially changes the energetic matrix of the body including the brain. It has been established as an effective anticonvulsant treatment, and more recently, the role of KD for mental disorders has been explored. Ketogenic diet has profound effects in multiple targets implicated in the pathophysiology of mood disorders, including but not limited to, glutamate/GABA transmission, monoamine levels, mitochondrial function and biogenesis, neurotrophism, oxidative stress, insulin dysfunction and inflammation. Preclinical studies, case reports and case series have demonstrated antidepressant and mood stabilizing effects of KD, however, to date, no clinical trials for depression or bipolar disorder have been conducted. Because of its potential pleiotropic benefits, KD should be considered as a promising intervention in research in mood disorder therapeutics, especially in treatment resistant presentations.
•We surveyed the use of machine learning to inform predictive models in mood disorders.•We include studies that use machine learning algorithms to identify predictors of therapeutic outcomes in ...uni/bipolar depression.•Classification algorithms informed by neuroimaging, phenomenological, and genetic data were able to predict therapeutic outcomes with an overall accuracy of 0.82.•Predictive models integrating multiple data types performed better when compared to models with single lower-dimension data types (p <0.01).•Machine learning provides opportunity to parse clinical heterogeneity and characterize moderators of disease risk and trajectory.
No previous study has comprehensively reviewed the application of machine learning algorithms in mood disorders populations. Herein, we qualitatively and quantitatively evaluate previous studies of machine learning-devised models that predict therapeutic outcomes in mood disorders populations.
We searched Ovid MEDLINE/PubMed from inception to February 8, 2018 for relevant studies that included adults with bipolar or unipolar depression; assessed therapeutic outcomes with a pharmacological, neuromodulatory, or manual-based psychotherapeutic intervention for depression; applied a machine learning algorithm; and reported predictors of therapeutic response. A random-effects meta-analysis of proportions and meta-regression analyses were conducted.
We identified 639 records: 75 full-text publications were assessed for eligibility; 26 studies (n=17,499) and 20 studies (n=6325) were included in qualitative and quantitative review, respectively. Classification algorithms were able to predict therapeutic outcomes with an overall accuracy of 0.82 (95% confidence interval CI of 0.77, 0.87). Pooled estimates of classification accuracy were significantly greater (p < 0.01) in models informed by multiple data types (e.g., composite of phenomenological patient features and neuroimaging or peripheral gene expression data; pooled proportion 95% CI = 0.930.86, 0.97) when compared to models with lower-dimension data types (pooledproportion=0.680.62,0.74to0.850.81,0.88).
Most studies were retrospective; differences in machine learning algorithms and their implementation (e.g., cross-validation, hyperparameter tuning); cannot infer importance of individual variables fed into learning algorithm.
Machine learning algorithms provide a powerful conceptual and analytic framework capable of integrating multiple data types and sources. An integrative approach may more effectively model neurobiological components as functional modules of pathophysiology embedded within the complex, social dynamics that influence the phenomenology of mental disorders.
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