Depression and Anxiety Among COVID-19 Patients Admitted to a "Red Zone" Intensive Care Unit: Do the Factors of Self-Awareness of Somatic Health, Anxiety, and Depression Contribute to the Course of Sars-Cov-2 Infection?

BACKGROUND: The prevalence of depressive disorders in the general population increased significantly during the COVID-19 pandemic. The aim of this study is to examine the relationship between history of anxiety and depressive disorders and COVID-19 outcome, hospitalization and severity of anxiety and depression, and whether such relationships are explicable by direct impact of the disease. SUBJECTS AND METHODS: We conducted a questionnaire survey among 98 inpatients in the Department of Infectious Diseases of the Clinics of Samara State Medical University. The self-report questionnaire consisted of 120 items, including socio-demographic characteristics of participants, State-Trait Anxiety Inventory, and the Center for Epidemiologic Studies Depression Scale, with items reflecting subjective feelings about the COVID-19 pandemic. We used one-factor analysis of variance to compare between groups for those indicators that conformed to a normal distribution, and the chi-square test (χ2) or Fisher's exact test to analyze group differences in the distribution of categorical variables was used. RESULTS: The mean (SD) total score on the STAI anxiety scale among hospitalized patients (51 (10.1)) significantly exceeded that of the COMET-G control group (44.9 (11.7) (H=22.8, p<0.001). There was a similar difference in the severity of depression as measured by the CES-D scale (23.4 (12.6) versus 18.0 (11.8), H=15.2 and p<0.001). In contrast to the general population, there were no statistically significant differences in anxiety and depression severity in the matched samples 52 subjects fulfilling the criteria of age, gender, and general perception of health condition. CONCLUSIONS: Anxiety and depression scores among ICU (red zone) inpatients significantly exceeded the scores observed in the COMET-G general population group. Our study did not confirm expected relationship between symptoms of anxiety and depression (based on questionnaire response) and the risk of severe course of COVID-19 (e.g. hospitalization) in matched samples, but proved that the factor of self-awareness of health state may be related to the COVID-19 course severity. Future research would benefit from clinical interview of inpatients and follow-up monitoring of affective disorders to specify whether anxiety and particular type of depression (e.g., anxious) are selectively related to the severity of COVID-19 course and risks of affective disorders persistence after somatic recovery. The accumulation of mental disorders with age, and the bidirectional association of mood disorders and infectious diseases should be considered when assessing the risk factors.

The Population Typology of Conspiracy Beliefs About Sars-Cov-2 Origin in Russia Based on Predictive Modelling of COMET-G Study Data: Incoherent Attitude Indicator as a Predisposing Factor for Developing Mental Disturbances.

BACKGROUND: We examined the prevalence and spread of conspiracy beliefs about the origins of the COVID-19 pandemic among representatives of the Russian population. Our study aimed to identify belief clusters and develop predictive models to understand the factors that influence conspiracy beliefs, particularly in the context of how they might evolve in response to socio-political events and cause mental disturbances, thus in relation to specific pathways of the infodemic and psychodemic waves that spread among vulnerable population groups. METHODS: Data respondents to the international COMET-G study living in Russia during pandemic period (n=7,777) were analyzed using descriptive statistics, K-means clustering, and various machine learning models, including gradient boosting. We identified distinct populations depending on predominant beliefs about COVID-19 pandemic origins, and applied game theory (Shapely additive explanations) to determine the most influential variables in predicting cluster membership. RESULTS: Four distinct belief clusters emerged, which we designate as Naturalists, Conspiracists, COVID-Sceptics, and the Incoherent Attitude groups. The Incoherent Attitude cluster constituted 20.8% of the sample, and was particularly associated with mental health signs such as sleep disturbances and the use of psychotropic medications. Internet use and mental health-related factors, as well as the respondents' education level, were key predictors of mental disturbances with mediating effects of the conspiracy views across all clusters. Conspiracy beliefs about COVID-19 origin were highly fluid/variable, often being shaped by external sociopolitical factors rather than objective health data. CONCLUSIONS: The cluster with Incoherent Attitude regarding COVID-pandemic origins, which had an association with psychoticism, showed a greater predisposition for mental health problems, than did the Conspiracist, Naturalist and Sceptic clusters. We suppose that underlying psychoticism bears a relation to their sleep problems and resorting to use of psychotropic medications. These results emphasizes the global health need for implementing target-focused and selective strategies that address public misinformation and promote the adoption of critical thinking skills to mitigate the impact of conspiracy theories, considering the factors of education level and pre-existing mental disorders.

Self-Harm Behavior and Suicidality Among Adolescents in Samara Region.

INTRODUCTION: Self-harm behavior is a significant global concern, with Russia among the countries with high prevalence rates. Adolescents and young adults (15-29 years old) are particularly vulnerable, with suicide being the fourth leading cause of death in this age group. Our objective was to present statistics on suicidality and non-suicidal self-harm behavior (NSSH) among adolescents in the Samara region and to identify psychosocial differences between patients hospitalized for the first time and those hospitalized repeatedly. SUBJECTS AND METHODS: This study is a retrospective chart analysis of adolescents hospitalized due to suicidal ideation or attempts in 2023. Data were collected from hospital records, comprising a diverse sample of adolescents. RESULTS: The sample included 76 adolescents, with a significant gender imbalance, as 84.2% were female. Chronic family conflicts presumably were the most influential factor, rather than family composition. Data on hereditary predisposition were subjective and presumably did not correlate with the number of hospitalizations. Fetal hypoxia was the only notable perinatal pathology. Self-harm behavior was more common in readmissions, while suicidal thoughts were present in similar proportions in both initial and repeat hospitalizations. The main reasons for self-harm behavior were the desire to gain control over life or to relieve emotional pain. Only 2.6% of cases were directly aimed at suicide. CONCLUSIONS: Identified risk factors for suicidal behavior among adolescents included female gender, an unfavorable family environment, and NSSH, which, although not directly suicidal, increased the risk of future suicidal behavior. These factors should be considered in the diagnosis and prevention of suicidal behavior.

Epigenetic Contributors to PTSD: a Comprehensive Review.

BACKGROUND: Post-traumatic stress disorder (PTSD) is a complex condition triggered by traumatic events. The molecular mechanisms underlying PTSD are not fully understood, but epigenetic modifications, particularly DNA methylation, may play a key role. The objective of this review was to identify the most significant epigenetic markers associated with PTSD. MATERIALS AND METHODS: Our search yielded 325 articles, of which 19 met our inclusion criteria for detailed analysis: published between 2018 and 2024, original research, containing molecular-genetic and statistical data, reporting diagnostic verification methods, PTSD as a primary condition, and a sample of at least 40 patients Results: the strongest correlation was found between PTSD and methylation changes in cg17057218, cg22324981, cg04755409 of BDNF, cg05656210, cg12169700, cg20756026 of MAD1L1, HLA-DPA1, HLA-DPB1 (chr6: 33047185 - 33049505) and SPATC1L (chr21: 47604052 - 47605174). The most works on associations of genetic clock with PTSD found significantly increased GrimAge acceleration in patients with PTSD. CONCLUSIONS: Epigenetic modifications, particularly DNA methylation, play a significant role in PTSD pathophysiology. While specific gene methylation changes are associated with PTSD, the link between PTSD and epigenetic aging remains unclear. Variability across studies suggests that trauma type, duration, and genetic factors may influence these epigenetic processes. Further research is essential to fully understand these relationships.

Systematic Review and Meta-Analysis Confirm the Moderate Efficacy of High-Frequency r-TMS in Alzheimer's Disease: Mediating Effects of Anhedonia-Apathy and Add-On Motor-Cognitive Excersizes.

OBJECTIVES: Alzheimer's disease (AD) presents a major global health issue of significant socio-economic impact. Pharmacological treatments for AD have limited efficacy, prompting the exploration of alternative therapies, such as repetitive transcranial magnetic stimulation (rTMS), a promising non-invasive technique to enhance cognitive function in AD patients. Our systematic review and meta-analysis aim to evaluate the efficacy of rTMS in relation to cognitive function in AD patients, identify optimal rTMS stimulation parameters, and understand the underlying neural mechanisms. METHODS: We conducted a comprehensive literature search in PubMed using predefined search terms to identify original research articles investigating the effects of rTMS on cognitive function in AD patients. We selected only randomized controlled trials (RCTs) with sufficient quantitative data for comparing active rTMS to the sham-coil treatment, and then performed a random effects meta-analysis using standardized mean differences (SMDs) to synthesize the effects across studies. RESULTS: The systematic review included 22 studies, among which 14 RCTs met our criteria for meta-analysis. High-frequency rTMS, particularly targeting the dorsolateral prefrontal cortex (DLPFC), evoked significant cognitive improvements in AD patients, with a moderate positive effect size of rTMS on cognitive function (Hedges' g=0.580, 95% CI [0.268, 0.892], p<0.001), albeit with substantial heterogeneity (I²=59%). Funnel plot asymmetry and Egger's test suggested a potential publication bias, but fail-safe N analysis indicated a robust finding. Moreover, anhedonia-apathy symptoms and motor-cognitive exercises mediated the efficacy of tTMS in ameliorating cognitive functioning across several studies. CONCLUSION: rTMS demonstrates moderate efficacy in improving cognitive function in AD-patients, most distinctly with high-frequency rTMS stimulation protocols targeting the DLPFC area. The meta-analysis support rTMS as a viable therapeutic intervention for cognitive enhancement in AD. Future promising research should focus on personalized treatment strategies targeting mediating factors, baseline connectivity patterns, and TMS-induced neuroplasticity in AD.

Risk Assessment Suicidality Scale (RASS)-Based On-Line Calculator Targeting Early Prevention of Suicides in General Population: from COMET-G Study Results Towards Integration of the Screening Tool into Routine Clinical Practice.

BACKGROUND: Suicide is a major global health concern, particularly among young people. This study evaluates an online suicide risk calculator based on the Risk Assessment of Suicidality Scale (RASS), which is designed to enhance accessibility and early detection of suicide risk. METHODS: The study involved 444 participants who completed the RASS via an online calculator. Results were compared with data from the COMET-G study's Russian sample (n=7572). Descriptive statistics, correlation analysis, and two-way ANOVA were used to analyze the data. RESULTS: The mean age of participants was 22.71 years (SD=7.94). The mean total RASS standardized score was 837.7 (SD=297.8). There was a significant negative correlation between age and RASS scores (r=-0.463, p<0.0001). The online calculator sample showed significantly higher RASS scores compared to the COMET-G sample, with 71% of online users scoring above the 90th percentile of the COMET-G sample. CONCLUSION: Our study demonstrated the advantage of the on-line suicidality risk calculator based on the RASS scale as a sensitive tool in detecting suicidal behaviours and measuring the severity of suicidality risks, offering a capability for broad reach and immediate assessment during clinical conversation between doctor and patient. Moreover, the RASS on-line psychometric instrument, when being freely distributed among the general population over internet sources, enabled to attract vulnerable groups of respondents with significantly higher suicidality risks. Future research should focus on integrating such tools into comprehensive suicide prevention programs and developing appropriate follow-up monitoring strategies for high risk-cases.

Visual Snow Syndrome Prevalence Among Young Adults in the Russian Federation: a Research Perspective.

BACKGROUND: Visual snow syndrome (VSS) is a poorly understood neurological condition of unclear etiology, characterized by visual and non-visual symptoms that reduce quality of life. The objective of our study was to estimate the prevalence of young adults with visual snow in Russia. MATERIALS AND METHODS: We conducted an online survey among 1,177 respondents over the age of 18 residing in Russia. The questionnaire was based on MIDAS, HIT-6, ICHD-3, GAD-7, CES-D. RESULTS: A total of 1085 individuals, divided into three groups: 48 participants with Visual Snow Syndrome (VSS), 36 participants with visual snow symptoms (VS), and 1001 participants without visual snow (control group). Tinnitus (p<0.001) and paresthesia (p<0.001) were more common in participants with VSS compared to the control group. VSS group also reported mood disorders more frequently than those in the other groups (29.2% VSS, 13.9% VS, 7.0% control, p<0.001). Additionally, VSS group exhibited more elevated anxiety levels on the GAD-7 scale compared to the other groups (p=0.005), suggesting a weak association between anxiety and VSS. CONCLUSIONS: Diagnosed migraine, tinnitus, concentration problems, paresthesia, and verified psychiatric conditions were significantly more prevalent in the VSS group in our study. Tinnitus was significantly more frequent in the VS group. Diagnosed conditions across all ICD-10 classes were more frequently identified in the VSS group, with the strongest associations (moderate) found with ICD-10 codes: F80-F89 and F60-F69. Additionally ICD-10 codes F30-F39 were more frequently found in the VS group compared to the control group. Our study revealed that nearly all individuals with VSS in our sample (89.6%) had experienced symptoms for as long as they can remember. The prevalence of VS symptoms in Russia is 7.7% (6.2-9.3%) and VSS is 4.4% (3.2-5.7%).

Virtual Reality (VR) Device with Integrated Biofeedback Sensors (ReViSide) to Cope with Emotional Burnout State Among Employees Experiencing Stress at Workplace: Problem Overview and Action Plan.

INTRODUCTION: In this study we examine the issue of employee burnout, caused by long-term exposure to workplace stressors, considering its complex phenomenology in the context of contemporary psychological and psychiatric views. Towards the development of innovative technologies to correct burnout in the context of psychosocial rehabilitation, we present our study protocol involving the ReViSide virtual reality (VR) and biofeedback intervention, including monitoring of respiratory rates and EEG rhythms. METHODS: The randomized controlled trial protocol includes adult participants aged 18 to 65 years (n=140) who exhibit emotional burnout in the workplace. The intervention group will undergo a course of VR correction (ReViSide), while the control group receives a standard psychocorrection. The primary endpoint will be level of emotional burnout to the Maslach Burnout Inventory (MBI). We shall also assess anxiety, depression, asthenia and subjective improvement in condition using validated scales (HADS, HARS, HDRS, VAS-A, PGI-C). RESULTS: We shall test our hypothesis that the VR-correction group will show significant improvements in MBI scores, particularly in emotional exhaustion, depersonalization, and personal accomplishment, compared to the control group. Secondary outcome measures are likewise expected to demonstrate more prominent improvements in the VR group, correlating with the magnitude of burnout reduction to MBI. Analysis of EEG data may reveal changes in alpha rhythm patterns during VR sessions, potentially correlating with reduced distress levels. CONCLUSIONS: We designed this study to test the integration of an interdisciplinary approach for treating burnout, highlighting the ReViSide technology. Confirming the efficacy of this approach for psychosocial rehabilitation targeting burnout states among employees should improve their stress resilience, daily motivation, and work productivity in the context of the modern high working pressure environment and demanding corporate culture.

Virtual Reality / Augmented Reality (VR/AR) Approach to Develop Social and Communication Skills in Children and Adolescents with Autism Spectrum Disorders Without Intellectual Impairment.

BACKGROUND: Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder that affects a significant proportion of the world's population, particularly children and adolescents. The sensory processing issues can be an evidence-based target for therapeutic/corrective interventions by controlling the intensity and targeted replacement of maladaptive sensory stimuli with neutral stimuli using virtual reality or augmented reality. SUBJECTS AND METHODS: We searched for articles on Pubmed. The search query included ((VR or virtual reality) or (AR or augmented reality)) and (children or adolescents) and (ASD or autism spectrum disorder or autism). RESULTS: Our criteria were met by 25 articles. 19 articles used VR, 5 articles used AR and 1 article used MR. Most interventions offer children and adolescents with ASD individualized tasks. Immersive VR games developed collaborative skills. Other systems encourage and teach directed facial gaze. Evaluation of the effectiveness of learning in VR/AR environment is carried out by means of different scales, qualitative analysis of surveys, questionnaires and interviews, studying the number and duration of eye contacts between the participant and the avatar. It should be noted that almost all studies were conducted on small samples, so their results allow us to draw only preliminary conclusions about the effectiveness of VR /AR. CONCLUSIONS: The following key areas of VR/AR technologies for children and adolescents with high-functioning ASD can be identified: communicating with an avatar, including answering its questions, tracking the child's gaze and encouraging the child to look at the face, placing it in social situations close to real life, practicing common everyday situations, learning to recognize emotions. A VR/AR-based therapy approach may help children with autism spectrum disorder without cognitive impairment to develop higher levels of adaptation in terms of social and communication skills. However, more research is needed to evaluate the effectiveness of different methods.

Arterial vascular complications predictive score in extrasystolic arrhythmia "EX-prognosis".

BACKGROUND: The aim of this study was the creation of an optimal model for predicting arterial vascular complications in patients with extrasystolic arrhythmia. METHODS: A single-center prospective study was performed with involving 634 patients with supraventricular or ventricular extrasystoles (ES) of 700 or more per 24 hours. The control group consisted of 106 people with ES less than 700 per 24 hours. The main and control groups were initially equivalent in anthropometric criteria and concomitant pathology. The list of examinations included laboratory methods (including lipid profile, coagulograms), as well as instrumental studies (transthoracic and/or transesophageal echocardiography (EchoCG), Doppler ultrasound of the brachiocephalic arteries and arteries of the lower extremities, 24-hours ECG monitoring, according to the indications - computed tomography or magnetic resonance imaging of the brain, coronary angiography, stress echocardiography. Prospective observation of patients performed for 1 year after the initial examination. Combined end points: development of arterial vascular complications - stroke, myocardial infarction, distal arterial embolism of other locations. We studied the data on identified complications. Next, we built models for predicting complications in various ways: Decision Tree; Bootstrap Forest; Boosted Tree; Neural Boosted; Support Vector Machines; Fit Stepwise; Nominal Logistic; Generalized Regression Lasso; Generalized Regression Forward Selection; Generalized Regression Pruned Forward Selection; Generalized Regression Elastic Net; Generalized Regression Ridge. To assess the quality of the models and compare them we used cross-validation with 30 replications. RESULTS: The highest profit values with minimal values of false positive results were obtained for the Bootstrap Forest model. Basing on this model, we created arterial vascular complications predictive score in extrasystolic arrhythmia "EX-prognosis" that included the following parameters: atheroma type III in carotid arteries - 3 points; age 69+ years old - 2 points; ES appearing before transmitral blood flow peak in cardiac cycle 700 and more per 24 hours - 1 point; carotid arteries stenosis, non-significant - 1 point. If total number is 3 and more points, the risk of arterial vascular complications within 1 year is high. CONCLUSIONS: We recommend to use the scale "EX-prognosis" in the clinical practice. For a quick assessment of the total risk, it is optimal to implement the risk14.exe program - calculator - developed by us for a personal computer, based on this scale.

Neuronetwork Approach in the Early Diagnosis of Depression.

BACKGROUND: Depression is a common mental illness, with around 280 million people suffering from depression worldwide. At present, the main way to quantify the severity of depression is through psychometric scales, which entail subjectivity on the part of both patient and clinician. In the last few years, deep (machine) learning is emerging as a more objective approach for measuring depression severity. We now investigate how neural networks might serve for the early diagnosis of depression. SUBJECTS AND METHODS: We searched Medline (Pubmed) for articles published up to June 1, 2023. The search term included Depression AND Diagnostics AND Artificial Intelligence. We did not search for depression studies of machine learning other than neural networks, and selected only those papers attesting to diagnosis or screening for depression. RESULTS: Fifty-four papers met our criteria, among which 14 using facial expression recordings, 14 using EEG, 5 using fMRI, and 5 using audio speech recording analysis, whereas 6 used multimodality approach, two were the text analysis studies, and 8 used other methods. CONCLUSIONS: Research methodologies include both audio and video recordings of clinical interviews, task performance, including their subsequent conversion into text, and resting state studies (EEG, MRI, fMRI). Convolutional neural networks (CNN), including 3D-CNN and 2D-CNN, can obtain diagnostic data from the videos of the facial area. Deep learning in relation to EEG signals is the most commonly used CNN. fMRI approaches use graph convolutional networks and 3D-CNN with voxel connectivity, whereas the text analyses use CNNs, including LSTM (long/short-term memory). Audio recordings are analyzed by a hybrid CNN and support vector machine model. Neural networks are used to analyze biomaterials, gait, polysomnography, ECG, data from wrist wearable devices, and present illness history records. Multimodality studies analyze the fusion of audio features with visual and textual features using LSTM and CNN architectures, a temporal convolutional network, or a recurrent neural network. The accuracy of different hybrid and multimodality models is 78-99%, relative to the standard clinical diagnoses.

G.T. MSRS On-Line Calculator Targeting the Early Diagnosis of Mixed Affective States: the Multicenter Study Project Design on the Approbation and Validity of the Three Language Versions of the Rating Scale.

BACKGROUND: Mixed affective states (MS) are often misdiagnosed by the clinicians and lead to the inappropriate treatment strategies contributing to the severe forms, poor outcome with higher rates of comorbid conditions and worse remission quality in affective and bipolar disorders, as well as to a decreased psychosocial functioning of these patients. The development of reliable tools for the MS assessments or so called the phenomenon of mixity in affective disorders, is still an unmet need of psychiatric research and clinical practice. In this paper, we present PC program "Multilingual IBM-PC on-line calculator for early diagnosis of the mixed affective states" based on the Giuseppe Tavormina Mixed States Rating Scale (G.T. MSRS) (Russian, English, Italian language versions) created by the ICERN group using programming language JavaScript, working for such operation systems (OS) as Windows, Linux, MacOs, Android, iOS, and aims to contribute to the accurate assessment of the presence and severity of the mixed states among affective disorders. SUBJECTS AND METHODS: The G.T. Mixed States Rating Scale on-line calculator consists of 11 items which evaluate various aspects of MS in patients with major depression, bipolar or recurrent depressive disorder. A total score is automatically calculated, considering the type of affective temperament according to the Akiskal's and Tavormina's schemas, thus, the specific sub-groups of MS are differentiated based on the ranges: Medium-light (2-6), Medium (7-12), and High (13-19) Mixity level. The study will enroll 330 participants during two (three months follow-up) visits (110 native speakers in each of the three languages) of both genders aged from 18 till 55 y.o. with the diagnoses of depressive episodes, major depression, bipolar or recurrent depressive disorder according to the DSM-5 criteria. Assessments will be provided by the two investigators (second one will be blinded to the G.T. MSRS results obtained by the first researcher), based on the use of DSM-5 clinical interview, Young Mania Rating Scale, Montgomery-Åsberg Depression Rating Scale, Clinical Global Impression - Severity scale (CGI-S), Clinical Global Impression - Improvement scale (CGI-I), Patient Global Impression of Change (PGIC). RESULTS: The study will assess the agreement between the diagnostic category/clinical impression and the on-line G.T. MSRS calculator use results, its test-retest reliability, and diagnosis stability for further assessment of the on-line G.T. MSRS calculator validity and clinical utility. Secondary variables will evaluate internal reliability and such statistical analyses as Cronbach's alpha, Cohen's Kappa, biserial correction, and agreement between initial and follow-up diagnoses. CONCLUSIONS: Current multicenter validation study of the on-line G.T. MSRS calculator will enhance the understanding of the mixity phenomenon and its clinical implication, aiming to improve the treatment strategies to manage the course of mental disorder, quality of life and psychosocial functioning in patients with affective (bipolar) disorders, accompanied by MS, and a clinical recommendation for the routine administration of the user-friendly on-line G.T. MSRS version in clinical practice.

Peripheral Blood Mononuclear Cell-Related Biomarkers in Schizophrenia.

INTRODUCTION: Schizophrenia is a severe mental illness causing significant impairment in personal, family, social, educational, occupational, and other important areas of life. While there is no widely accepted endophenotype, peripheral blood cells may serve as an accessible model of intracellular changes in schizophrenia. METHODS: We reviewed the literature on the query "peripheral blood mononuclear cells AND schizophrenia" in Medline (Pubmed), selecting studies that searched for specific biomarkers of schizophrenia. We considered both diagnostic biomarkers and biomarkers of therapeutic response, specific schizophrenia disorders or differential diagnostic biomarkers. RESULTS: We retrieved 41 articles matching the search criteria, among which were studies that considered changes in the production of pro-inflammatory and anti-inflammatory markers, proteins, receptors, enzyme activity, and gene expression as potential biomarkers. CONCLUSION: Approaches analysing a biological axis or a group of related biomarkers may hold the greatest promise for identifying schizophrenia. In addition, pharmacological status, smoking status, inflammatory markers and glucose metabolites, the presence of comorbidities should be considered. Certain biomarkers, while not specific for the diagnosis of schizophrenia, may indicate the prognosis and effectiveness of treatment in the established diagnosis.

Post-COVID Neuropsychiatric Complications in Children and Adolescents: a Study Design for Early Diagnosis and Treatment Using Innovative Technologies.

BACKGROUND: The COVID-19 pandemic has had significant impacts on the child and adolescent population, with long-term consequences for physical health, socio-psychological well-being, and cognitive development, which require further investigation. We herein describe a study design protocol for recognizing neuropsychiatric complications associated with pediatric COVID-19, and for developing effective prevention and treatment strategies grounded on the evidence-based findings. METHODS: The study includes two cohorts, each with 163 participants, aged from 7 to 18 years old, and matched by gender. One cohort consisted of individuals with a history of COVID-19, while the other group presents those without such a history. We undertake comprehensive assessments, including neuropsychiatric evaluations, blood tests, and validated questionnaires completed by parents/guardians and by the children themselves. The data analysis is based on machine learning techniques to develop predictive models for COVID-19-associated neuropsychiatric complications in children and adolescents. RESULTS: The first model is focused on a binary classification to distinguish participants with and without a history of COVID-19. The second model clusters significant indicators of clinical dynamics during the follow-up observation period, including the persistence of COVID-19 related somatic and neuropsychiatric symptoms over time. The third model manages the predictors of discrete trajectories in the dynamics of post-COVID-19 states, tailored for personalized prediction modeling of affective, behavioral, cognitive, disturbances (academic/school performance), and somatic symptoms of the long COVID. CONCLUSIONS: The current protocol outlines a comprehensive study design aiming to bring a better understanding of COVID-19-associated neuropsychiatric complications in a population of children and adolescents, and to create a mobile phone-based applications for the diagnosis and treatment of affective, cognitive, and behavioral conditions. The study will inform about the improved management of preventive and personalized care strategies for pediatric COVID-19 patients. Study results support the development of engaging and age-appropriate mobile technologies addressing the needs of this vulnerable population group.

Comparison of Anxiety and Depression Rates in Russian Health Care Professionals in 2020 and 2023.

BACKGROUND: The COVID-19 pandemic had a significant impact on the mental health of medical personnel worldwide, leading to increased levels of anxiety and depression. This study aimed to compare anxiety and depression levels among healthcare workers during the initial wave of the pandemic in April-May 2020 and the post-pandemic period in January-May 2023 in Russia. METHODS: Data from two similar surveys conducted during the respective periods were combined, and a case-control matching approach was used to ensure compatibility between the two samples. The Hospital Anxiety and Depression Scale (HADS) was used to assess anxiety and depression levels. RESULTS: The mean total score for Anxiety subscale in 2020 was 4.126 (SD = 3.042), and in 2023 it increased to 6.632 (SD = 4.132) (F=20.751, df (1, 172), p<0.001, η2p=0.108). Similarly, the mean total score for Depression subscale increased from 3.253 (SD = 2.616) in 2020 to 4.115 (SD = 2.939) in 2023 (F=4.177, df (1, 172), p=0.043, η2p=0.024). The proportion of healthcare workers with higher-than-normal levels of anxiety increased from 16.09% in 2020 to 39.08% in 2023, whereas the effect size for depression remained negligible. The increase in anxiety severity was contrary to previous longitudinal studies showing a decrease in anxiety and depression levels after an initial increase during the pandemic. CONCLUSION: The increase in anxiety and depression levels in healthcare workers in 2023 may be attributed to other factors like "special military operation" in Ukraine, sanctions, and announcement of partial mobilization in September 2022. These factors could be perceived as more serious adverse factors, leading to increased anxiety levels.

Neurological and Psychiatric Aspects of Biological Markers for the Provision of Medical Care to Patients with Spinal Muscular Atrophy 5q.

BACKGROUND: Spinal muscular atrophy (SMA) is a rare genetic disorder, in which, for the common childhood onset forms, loss of function of the SMA 5q gene leads to disability and death before adulthood. Symptomatic treatment focusses on respiratory and nutritional support, and physical therapy, but there is little consideration of psychiatric manifestations of SMA. The aim of this study was to explore blood biomarker levels, electromyography (EMG) data, and clinical manifestations, including psychiatric impairments, in patients with SMA 5q. Our objectives were twofold: First, to assess the clinical relevance of standard biomarkers, i.e., creatinine, creatine kinase (CK), and lactate dehydrogenase (LDH) levels, and second, to obtain data supporting the development of an effective prognostic algorithm for the course of this disease. RESULTS: We analyzed retrospective data from 112 medical records of 58 registered patients (2008-2022) with SMA. At the time of last registration, the 58 patients had a mean age 38.4 years [13.68; 55.0], of whom 32 (52%) were female. The subgroup of 21 pediatric patients had a mean age 12.32 years [6.57; 13.93], of whom 14 (24%) were girls. The ICD-10 diagnoses were as follows: G12.0 (n=7, 12%, children), G12.1 (n=14, 24% children; n=29, 50% adults), G12.8 (n=6, 10% adults), G12.9 (n=2, 1% adults). The archival data on psychiatric status indicated emotional lability (n=6, 10.3%), fatigue (n=10, 17.2%), and tearfulness (n=3, 5.2%) in some patients. There were no significant subgroup differences in serum creatinine and CK levels, but there were significant differences in LDH levels between the G12.0, G12.1, G12.8, and G12.9 subgroups. Among the serum biomarkers, only LDH levels showed significant differences among the subgroups of SMA 5q patients; higher levels in the G12.1, G12.8, and G12.9 groups compared to the G12.0 (infantile) group related to age, weight, gender, and level of physical activity. Data on psychiatric status were insufficient to identify group differences and associations with biomarker levels. Likewise, longitudinal data on repeat hospitalizations did not indicate associations with biomarker levels. CONCLUSIONS: Creatinine, CK, and LDH levels were insufficient for monitoring and predicting the course of SMA. Further prospective research is needed to elaborate the weak relationships between CK levels, the dynamics of the clinical presentation, and therapeutic interventions, and to investigate psychiatric co-morbidities in SMA 5q patients.

Dietary Patterns as Modifiable Risk Factors for Depression: a Narrative Review.

BACKGROUND: The role of nutrition in treating clinical depression has been widely discussed. Unhealthy lifestyle patterns, like lack of physical activity, junk food consumption, and irregular sleep patterns are common in depressed patients. Considering the mental and physical side-effects, the daily nutrition of these patients seems to be a plausible option for reducing depressive symptoms and enhancing treatment results. METHODS: A PubMed search was done for meta-analyses published from January 2018 to June 2023 with the query: (diet) AND (psychiatric disorder) AND (depression). We selected meta-analyses that met specific criteria like including the entire diet or specific diet patterns and having depression or depressive symptoms as a primary or secondary outcome. RESULTS: Out of 28 papers found, the 9 meta-analyses, selected for review, revealed different types of correlation between dietary patterns and the symptoms of depression and anxiety. Healthy diets were associated with higher intake of fruits, vegetables, nuts, and lower intake of pro-inflammatory food items like processed meats and trans fats. Adherence to such diets showed a negative association with incident depression in cross-sectional and longitudinal studies. A diet mostly including ultra-processed foods was associated with higher odds of depressive and anxiety symptoms. Women were found to be more susceptible than men both in developing the depressive symptoms with unhealthy diet and in reducing the symptoms of depression and anxiety with improvement of diet quality. Statistically significant improvement in symptoms of depression and anxiety in both sexes was observed in study groups assigned for individual consultations of a dietician and a psychotherapist when compared with group sessions or general recommendations. CONCLUSIONS: Research on the correlation of healthy dietary patterns and symptoms of depression and anxiety has mainly focused on non-clinical populations. The evidence supports an inverse association between healthy eating habits and symptoms of depression. Further research should be encouraged on the eating habits of clinically depressed individuals and the underlying physiological mechanisms of uncontrolled food intake.

Evaluation of the Polygenic Risk Score for Alzheimer's Disease in Russian Patients with Dementia Using a Low-Density Hydrogel Oligonucleotide Microarray.

The polygenic risk score (PRS), together with the ɛ4 allele of the APOE gene (APOE-ɛ4), has shown high potential for Alzheimer's disease (AD) risk prediction. The aim of this study was to validate the model of polygenic risk in Russian patients with dementia. A microarray-based assay was developed to identify 21 markers of polygenic risk and ɛ alleles of the APOE gene. This case-control study included 348 dementia patients and 519 cognitively normal volunteers. Cerebrospinal fluid (CSF) amyloid-ß (Aß) and tau protein levels were assessed in 57 dementia patients. PRS and APOE-ɛ4 were significant genetic risk factors for dementia. Adjusted for APOE-ɛ4, individuals with PRS corresponding to the fourth quartile had an increased risk of dementia compared to the first quartile (OR 1.85; p-value 0.002). The area under the curve (AUC) was 0.559 for the PRS model only, and the inclusion of APOE-ɛ4 improved the AUC to 0.604. PRS was positively correlated with tTau and pTau181 and inversely correlated with Aß42/Aß40 ratio. Carriers of APOE-ɛ4 had higher levels of tTau and pTau181 and lower levels of Aß42 and Aß42/Aß40. The developed assay can be part of a strategy for assessing individuals for AD risk, with the purpose of assisting primary preventive interventions.

Are subjective language complaints in memory clinic patients informative?

To diagnose mild cognitive impairment, it is crucial to understand whether subjective cognitive complaints reflect objective cognitive deficits. This question has mostly been investigated in the memory domain, with mixed results. Our study was one of the first to address it for language. Participants were 55-to-93-year-old memory clinic patients (n = 163). They filled in a questionnaire about subjective language and memory complaints and performed two language tasks (naming-by-definition and sentence comprehension). Greater language complaints were associated with two language measures, thus showing a moderate value in predicting language performance. Greater relative severity of language versus memory complaints was a better predictor, associated with three language performance measures. Surprisingly, greater memory complaints were associated with better naming, probably due to anosognosia in further disease progression or personality-related factors. Our findings highlight the importance of relative complaint severity across domains and, clinically, call for developing self-assessment questionnaires asking specific questions about multiple cognitive functions.

Alteration of Blood Immune Biomarkers in MCI Patients with Different APOE Genotypes after Cognitive Training: A 1 Year Follow-Up Cohort Study.

Many studies aim to detect the early phase of dementia. One of the major ways to achieve this is to identify corresponding biomarkers, particularly immune blood biomarkers. The objective of this study was to identify such biomarkers in patients with mild cognitive impairment (MCI) in an experiment that included cognitive training. A group of patients with MCI diagnoses over the age of 65 participated in the study (n = 136). Measurements of cognitive functions (using the Mini-Mental State Examination scale and Montreal Cognitive Assessment) and determination of 27 serum biomarkers were performed twice: on the first visit and on the second visit, one year after the cognitive training. APOE genotypes were also determined. Concentrations of EGF (F = 17; p = 0.00007), Eotaxin (F = 7.17; p = 0.008), GRO (F = 13.42; p = 0.0004), IL-8 (F = 8.16; p = 0.005), MCP-1 (F = 13.46; p = 0.0001) and MDC (F = 5.93; p = 0.016) increased after the cognitive training in MCI patients. All these parameters except IL-8 demonstrated a weak correlation with other immune parameters and were poorly represented in the principal component analysis. Differences in concentrations of IP-10, FGF-2, TGFa and VEGF in patients with MCI were associated with APOE genotype. Therefore, the study identified several immune blood biomarkers that could potentially be associated with changes in cognitive function.