Cognitive impairment, anxiety, depression, fatigue, and dependence in instrumental activities of daily living (ADL) are common after stroke; however, little is known about how these outcomes may differ following treatment with endovascular clot retrieval (ECR), intravenous tissue plasminogen activator (t-PA), or conservative management.

Patients were recruited after acute treatment and invited to participate in an outcome assessment 90–120 days post-stroke. The assessment included a cognitive test battery and several questionnaires. The COVID-19 pandemic led to significant disruptions in recruitment and data collection, and the t-PA and conservative management groups were combined into a standard medical care (SMC) group.

Sixty-two participants were included in the study (ECR = 31, SMC = 31). Mean age was 66.5 (20–86) years, and 35 (56.5%) participants were male. Participants treated with ECR had significantly higher National Institutes of Health Stroke Scale scores at presentation and significantly lower education. After adjusting for stroke severity, premorbid intellectual ability, and age, treatment with ECR was associated with significantly better performances on measures of cognitive screening, visual working memory, and verbal learning and memory. Participants treated with ECR also experienced less fatigue and were more likely to achieve independence in basic and instrumental ADLs. Despite this, cognitive impairment and fatigue were still common among participants treated with ECR and anxiety and depression symptoms were experienced similarly by both groups.

Cognitive impairment and fatigue were less common but still prevalent following treatment with ECR. This has important practical implications for stroke rehabilitation, and routine assessment of cognition, emotion, and fatigue is recommended for all stroke survivors regardless of stroke treatment and functional outcome.

Stress and depression have a reciprocal relationship, but the neural underpinnings of this reciprocity are unclear. We investigated neuroimaging phenotypes that facilitate the reciprocity between stress and depressive symptoms.

In total, 22 195 participants (52.0% females) from the population-based UK Biobank study completed two visits (initial visit: 2006–2010, age = 55.0 ± 7.5 [40–70] years; second visit: 2014–2019; age = 62.7 ± 7.5 [44–80] years). Structural equation modeling was used to examine the longitudinal relationship between self-report stressful life events (SLEs) and depressive symptoms. Cross-sectional data were used to examine the overlap between neuroimaging correlates of SLEs and depressive symptoms on the second visit among 138 multimodal imaging phenotypes.

Longitudinal data were consistent with significant bidirectional causal relationship between SLEs and depressive symptoms. In cross-sectional analyses, SLEs were significantly associated with lower bilateral nucleus accumbal volume and lower fractional anisotropy of the forceps major. Depressive symptoms were significantly associated with extensive white matter hyperintensities, thinner cortex, lower subcortical volume, and white matter microstructural deficits, mainly in corticostriatal-limbic structures. Lower bilateral nucleus accumbal volume were the only imaging phenotypes with overlapping effects of depressive symptoms and SLEs (B = −0.032 to −0.023, p = 0.006–0.034). Depressive symptoms and SLEs significantly partially mediated the effects of each other on left and right nucleus accumbens volume (proportion of effects mediated = 12.7–14.3%, p < 0.001−p = 0.008). For the left nucleus accumbens, post-hoc seed-based analysis showed lower resting-state functional connectivity with the left orbitofrontal cortex (cluster size = 83 voxels, p = 5.4 × 10−5) in participants with high v. no SLEs.

The nucleus accumbens may play a key role in the reciprocity between stress and depressive symptoms.

The purpose of the research project is to analyze the long-term evolution of obsessive-compulsive disorder (OCD) from of a study of a cohort of patients prospectively followed over a period ranging from 5 to 20 years, treated for according to therapeutic guidelines mediating serotonin reuptake inhibitors (IRS) and drug enhancers (antipsychotics) and cognitive behavioral therapy and evaluated in a standardized manner.

To assess the long-term course of Obsessive-Compulsive Disorder (OCD) in a cohort of patients treated according to current clinical guidelines; to analyse possible prognostic factors associated with the long-term course of the disorder including clinical and sociodemographic variables, as well as genetic and neuroimaging biomarkers, and their interaction, and finally to study neuroanatomical and functional cerebral connectivity changes after 15 years of treatment in a subsample of patients.

Prospective, descriptive, and observational study of a cohort of OCD patients, receiving treatment at the Department of Psychiatry of Hospital de Bellvitge since 1998, according to a standardized protocol. Follow-up period ranges from 5 (n=423), to 10 (n= 247) and 15 years (123). Baseline clinical and sociodemographic assessment, long-term evolution and information on treatments provided are available for the whole sample. Data on whole exome sequencing is available for 300 of the patients included in the cohort and baseline structural neuroimaging and cerebral functional connectivity has been analysed in 168 subjects. To expand the analysis of genetic biomarkers, we propose the study of de novo variants through exome analysis of 50 trios (patient and both parents) selected among those subjects that have reached 15 years of follow-up (25 trios with patients within the “long-term remission” group and 25 trios with patients with chronic OCD). De novo variants detected in the trio analysis will be replicated in the rest of the sample. A structural and resting state MRI will be obtained in a subsample of 100 patients recruited among those who have completed a minimum follow-up period of 15 years, to assess cerebral changes associated with the long-term course of the disorder.

in the current moment the recruitment period of the study has ended and all the data is being statistically analysed in order to provide solid results in a short period of time.

The identification of those factors associated with an increased risk of chronic disease is an element essential to offer personalized treatment to our patients and improve their prognosis, emphasizing the intensive use of those therapeutic strategies for which we can predict a better response and modifying to the extent of, if possible, environmental factors or factors of access to treatment that contribute to perpetuate obsessive symptoms.

None Declared

Antidepressants (AD) are one of the most prescribed pharmacological treatments in developed countries. AD efficacy is well-proven in anxiety, depressive and other mental disorders, but their use is also common in individuals without psychiatric health conditions. Indeed, recent evidence reported an increase in AD prescription over the latest years. Concern has been raised on the overuse of AD in several countries, and societal policies and national guidelines have been developed to regulate their use in the general population.

Several factor might be used to explain this increase, including the more safety profile of new AD classes (i.e. SSRI, or vortioxetine) compared to old AD, a possible overall increase in the incidence of depressive and anxiety disorders, or their inappropriate prescription in mild conditions which could be managed without pharmacological treatment as first-step option in primary care (PC).

Explore AD prescription patterns in relation to mental health diagnoses and identify the most relevant factors involved in PC health systems. Understanding the variables influencing AD prescription would allow designing strategies and guidelines to make appropriate use of this pharmacological group in PC. As part of the PRESTO project (www.prestoclinic.cat), here we investigated the changes in frequency and the variables associated with AD prescription in a population-representative sample of people attending PC between 2010 –2019 in Catalonia, Spain.

We retrieved AD prescription, sociodemographic, and health-related data using individual electronic health records from a population-representative sample (N=947.698) attending PC between 2010-2019. Prescription of AD was calculated using DHD (Defined Daily Doses per 1,000 inhabitants/day). We compared cumulative changes in DHD with cumulative changes in diagnoses with an indication for AD during the study period. We used Poisson regression to examine sociodemographic and health-related variables associated with AD prescription.

Both AD prescription and mental health diagnoses with an indication for AD gradually increased. At the end of the study period, DHD of AD prescriptions and mental health diagnoses with an indication for AD reached cumulative increases of 404% and 49% respectively. Female sex (incidence rate ratio (IRR)= 2.83), older age (IRR = 25.43), and lower socio-economic status (IRR= 1.35) were significantly associated with increased risk of being prescribed an AD.

Our results from a large and representative cohort of patients confirm a steady increase of AD prescriptions that is not explained by a parallel increase in mental health diagnoses with an indication for AD. A trend on AD off-label and over-prescriptions in the PC system in Catalonia can be inferred from this dissociation.

M. Gonzalez: None Declared, G. anmella Grant / Research support from: received CME-related honoraria, or consulting fees from Janssen-Cilag, Lundbeck, Lundbeck/Otsuka, and Angelini, with no financial or other relationship relevant to the subject of this article, E. vieta Grant / Research support from: received research support from or served as consultant, adviser or speaker for AB-Biotics, Abbott, Abbvie, Adamed, Angelini, Biogen, Celon, Dainippon Sumitomo Pharma, Ferrer, Gedeon Richter, GH Research, Glaxo SmithKline, Janssen, Lundbeck, Organon, Otsuka, Rovi, Sage pharmaceuticals, Sanofi-Aventis, Shire, Sunovion, Takeda, and Viatris, out of the submitted work, M. Primé-Tous: None Declared, X. Segú: None Declared, A. Mas: None Declared, D. Hidalgo Grant / Research support from: received CME-related honoraria or adviser from Abbott, Angelini, Janssen-Cilag and Ethypharm with no financial or other relationship relevant to the subject of this article.

A significant proportion of people attending Primary Care (PC) have anxiety-depressive symptoms and work-related burnout and there is a lack of resources to attend them. The COVID-19 pandemic has worsened this problem, particularly affecting healthcare workers, and digital tools have been proposed as a workaround.

We present the development, feasibility and effectiveness studies of chatbot (Vickybot) aimed at screening, monitoring, and reducing anxiety-depressive symptoms and work-related burnout in PC patients and healthcare workers.

User-centered development strategies were adopted. Main functions included self-assessments, psychological modules, and emergency alerts. (1) Simulation: HCs used Vickybot for 2 weeks to simulate different possible clinical situations and evaluated their experience. (3) Feasibility and effectiveness study: People consulting PC or healthcare workers with mental health problems were offered to use Vickybot for one month. Self-assessments for anxiety (GAD-7) and depression (PHQ-9) symptoms, and work-related burnout (based on the Maslach Burnout Inventory) were administered at baseline and every two weeks. Feasibility was determined based on the combination of both subjective and objective user-engagement Indicators (UEIs). Effectiveness was measured using paired t-tests as the change in self-assessment scores.

(1) Simulation: 17 HCs (73% female; mean age=36.5±9.7) simulated different clinical situations. 98.8% of the expected modules were recommended according to each simulation. Suicidal alerts were correctly activated and received by the research team. (2) Feasibility and effectiveness study: 34 patients (15 from PC and 19 healthcare workers; 77% female; mean age=35.3±10.1) completed the first self-assessments, with 34 (100%) presenting anxiety symptoms, 32 (94%) depressive symptoms, and 22 (64.7%) work-related burnout. Nine (26.5%) patients completed the second self-assessments after 2-weeks of use. No significant differences were found for anxiety [t(8) = 1.000, p = 0.347] or depressive [t(8) = 0.400, p = 0.700] symptoms, but work-related burnout was significantly reduced [t(8) = 2.874, p = 0.021] between the means of the first and second self-assessments. Vickybot showed high subjective-UEIs, but low objective-UEIs (completion, adherence, compliance, and engagement).

The chatbot proved to be useful in screening the presence and severity of anxiety and depressive symptoms, in reducing work-related burnout, and in detecting suicidal risk. Subjective perceptions of use contrasted with low objective-use metrics. Our results are promising, but suggest the need to adapt and enhance the smartphone-based solution in order to improve engagement. Consensus on how to report UEIs and validate digital solutions, especially for chatbots, are required.

None Declared

Virtual reality exposure therapy (VRET) is a treatment in a virtual environment based on the representation of a patient’s disease in virtual reality. VRET means getting used to a specific situation by intentionally facing the patient’s fearful situation based on the ‘exposure technique.’ By repeatedly exposing the patient to a fearful situation, in the end, inducing the intensity of fear to decrease without avoiding the situation. Virtual reality exposure therapy (VRET) was initially used to treat phobias, anxiety disorders, and stress. It has been proven to be an effective psychotherapy method mainly focusing on acrophobia, flight phobia, arachnophobia, social phobia, and post-traumatic stress disorder (PTSD).

Virtual reality exposure therapy (VRET) is used to treat phobias, anxiety disorders, and stress. The virtual reality treatment system can reproduce virtual scenes with the environment modified or removed, and can familiarize patients with such environments. This study aims to verify the degree of improvement of the symptoms of panic disorder by conducting VRET that we have made considering the degree of gradual exposure to the panic disorder group and the control group.

A total of 60 subjects were included in this study, including 43 patients with panic disorder and 17 control group. Subjects were systematically exposed to specific situations over five steps. We checked the heart rate, body temperature, EEG and symptoms before and after exposure using the following assessment instruments; Subjective Units of Discomfort (SUD), Anxiety Sensitivity Index (ASI), Panic Disorder Severity Scale. Repeated measures ANOVA was performed separately for presence, SUDS (distress) scores, and PDSS across time points.

In the patient group, the program proved to be effective as the sensitivity to anxiety decreased significantly after the VR program (F=3.570, p<0.05). Among the subcategories of ASI, the fear of anxiety symptoms showed statistical significance between sessions (F=3.883, p<0.05) and in the interaction between group and time (F=4.585, p<0.01). The study confirmed the effectiveness of the VR program in situations that mainly induce panic attacks in patients diagnosed with panic disorder (elevator riding, driving a car, driving a car in a tunnel, driving a car in rain). The program effect was significant through repeated measurement ANOVA for each variable of EEG (Alpha, Beta, Delta, Gamma, Theta) (F=3.249, p<0.01).

VRET is the process of gradually being exposed to fear stimuli, deliberately confronting and experiencing a fear situation, and learning that nothing dangerous will happen. Even if the patient experiences bodily sensations that are the subject of fear, they can reduce their fear of bodily sensations by repeatedly confirming that they are safe and getting used to them.

None Declared

Mood episodes in bipolar disorder (BD) are still identified with subjective retrospective reports and scales. Digital biomarkers, such as actigraphy, heart rate variability, or ElectroDermal activity (EDA) have demonstrated their potential to objectively capture illness activity.

To identify physiological digital signatures of illness activity during acute episodes of BD compared to euthymia and healthy controls (HC) using a novel wearable device (Empatica´s E4).

A pragmatic exploratory study. The sample will include 3 independent groups totalizing 60 individuals: 36 BD inpatients admitted due to severe acute episodes of mania (N=12), depression (N=12), and mixed features (N=12), will wear the E4-device at four timepoints: the acute phase (T0), treatment response (T1), symptoms remission (T2) and during euthymia (T3; outpatient follow-up). 12 BD euthymic outpatients and 12 HC will be asked to wear the E4-device once. Data pre-processing included average downsampling, channel time-alignment in 2D segments, 3D-array stacking of segments, and random shuffling for training/validation sets. Finally, machine learning algorithms will be applied.

A total of 10 patients and 5 HC have been recruited so far. The preliminary results follow the first differences between the physiological digital biomarkers between manic and depressive episodes. 3 fully connected layers with 32 hidden units, ectified linear activation function (ReLU) activation, 25% dropout rate, significantly differentiated a manic from a depressive episode at different timepoints (T0, T1, T2).

New wearables technologies might provide objective decision-support parameters based on digital signatures of symptoms that would allow tailored treatments and early identification of symptoms.

No significant relationships.

Neuroimaging findings have reported aberrant functional connectivity in brain regions involved reward system in individuals with anorexia nervosa (AN) altering hedonic processing over food. Likewise, endocannabinoids such as Anandamide (AEA) and 2-Arachidonoylglycerol (2-AG) have been involved in rewarding aspects of food intake.

To identify nucleus accumbens (NAcc) functional connectivity with whole-brain comparing between individuals with AN and controls. Furthermore, in a sub-study, to explore the interaction between NAcc functional connectivity and peripheral AEA and 2-AG levels.

A total of 60 adult women (18 to 56 years of age) took part in the present study. Twenty-six individuals belonged to the AN group (BMI<18) and 34 to the HC group (BMI=18-24.99). All participants underwent functional magnetic resonance in resting-state, and blood samples were obtained in fasting.

Negative functional connectivity was observed in the AN group compared with the control group between the NAcc and the cerebellum (pFWE<.001), between the NAcc and the insula (pFWE<.001), between the NAcc and the supramarginal gyrus (pFWE=.019), and between the NAcc and the postcentral gyrus (pFWE=.010). Analyses exploring the association between NAcc functional connectivity and peripheral endocannabinoids levels displayed altered NAcc-cerebellum functional connectivity was negatively associated with peripheral 2-AG levels in the AN group (r= -.553; p=.011).

Understanding the interaction between the reward system and peripheral endocannabinoids in patients with AN could contribute to better elucidate the pathophysiology of this disorder. Future studies will need to further investigate the clinical and therapeutic implications of these findings in patients with AN.

No significant relationships.

People with serious mental illness (SMI) experience higher mortality partially attributable to higher long-term condition (LTC) prevalence. However, little is known about multiple LTCs (MLTCs) clustering in this population.

People from South London with SMI and two or more existing LTCs aged 18+ at diagnosis were included using linked primary and mental healthcare records, 2012–2020. Latent class analysis (LCA) determined MLTC classes and multinominal logistic regression examined associations between demographic/clinical characteristics and latent class membership.

The sample included 1924 patients (mean (s.d.) age 48.2 (17.3) years). Five latent classes were identified: ‘substance related’ (24.9%), ‘atopic’ (24.2%), ‘pure affective’ (30.4%), ‘cardiovascular’ (14.1%), and ‘complex multimorbidity’ (6.4%). Patients had on average 7–9 LTCs in each cluster. Males were at increased odds of MLTCs in all four clusters, compared to the ‘pure affective’. Compared to the largest cluster (‘pure affective’), the ‘substance related’ and the ‘atopic’ clusters were younger [odds ratios (OR) per year increase 0.99 (95% CI 0.98–1.00) and 0.96 (0.95–0.97) respectively], and the ‘cardiovascular’ and ‘complex multimorbidity’ clusters were older (ORs 1.09 (1.07–1.10) and 1.16 (1.14–1.18) respectively). The ‘substance related’ cluster was more likely to be White, the ‘cardiovascular’ cluster more likely to be Black (compared to White; OR 1.75, 95% CI 1.10–2.79), and both more likely to have schizophrenia, compared to other clusters.

The current study identified five latent class MLTC clusters among patients with SMI. An integrated care model for treating MLTCs in this population is recommended to improve multimorbidity care.