Synthesis of the potent antimalarials calothrixin A and B

A concise synthesis of calothrixins A (1) and B (2) that confirms their assigned structures and affords straightforward synthetic access to them is reported.

Vickybot, a Chatbot for Anxiety-Depressive Symptoms and Work-Related Burnout in Primary Care and Health Care Professionals: Development, Feasibility, and Potential Effectiveness Studies

BACKGROUND

Many people attending primary care (PC) have anxiety-depressive symptoms and work-related burnout compounded by a lack of resources to meet their needs. The COVID-19 pandemic has exacerbated this problem, and digital tools have been proposed as a solution.

OBJECTIVE

We aimed to present the development, feasibility, and potential effectiveness of Vickybot, a chatbot aimed at screening, monitoring, and reducing anxiety-depressive symptoms and work-related burnout, and detecting suicide risk in patients from PC and health care workers.

METHODS

Healthy controls (HCs) tested Vickybot for reliability. For the simulation study, HCs used Vickybot for 2 weeks to simulate different clinical situations. For feasibility and effectiveness study, people consulting PC or health care workers with mental health problems used Vickybot for 1 month. Self-assessments for anxiety (Generalized Anxiety Disorder 7-item) and depression (Patient Health Questionnaire-9) symptoms and work-related burnout (based on the Maslach Burnout Inventory) were administered at baseline and every 2 weeks. Feasibility was determined from both subjective and objective user-engagement indicators (UEIs). Potential effectiveness was measured using paired 2-tailed t tests or Wilcoxon signed-rank test for changes in self-assessment scores.

RESULTS

Overall, 40 HCs tested Vickybot simultaneously, and the data were reliably transmitted and registered. For simulation, 17 HCs (n=13, 76% female; mean age 36.5, SD 9.7 years) received 98.8% of the expected modules. Suicidal alerts were received correctly. For the feasibility and potential effectiveness study, 34 patients (15 from PC and 19 health care workers; 76% [26/34] female; mean age 35.3, SD 10.1 years) completed the first self-assessments, with 100% (34/34) presenting anxiety symptoms, 94% (32/34) depressive symptoms, and 65% (22/34) work-related burnout. In addition, 27% (9/34) of patients completed the second self-assessment after 2 weeks of use. No significant differences were found between the first and second self-assessments for anxiety (t8=1.000; P=.34) or depressive (t8=0.40; P=.70) symptoms. However, work-related burnout scores were moderately reduced (z=-2.07, P=.04, r=0.32). There was a nonsignificant trend toward a greater reduction in anxiety-depressive symptoms and work-related burnout with greater use of the chatbot. Furthermore, 9% (3/34) of patients activated the suicide alert, and the research team promptly intervened with successful outcomes. Vickybot showed high subjective UEI (acceptability, usability, and satisfaction), but low objective UEI (completion, adherence, compliance, and engagement). Vickybot was moderately feasible.

CONCLUSIONS

The chatbot was useful in screening for the presence and severity of anxiety and depressive symptoms, and for detecting suicidal risk. Potential effectiveness was shown to reduce work-related burnout but not anxiety or depressive symptoms. 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 to improve engagement. A consensus on how to report UEIs and validate digital solutions, particularly for chatbots, is required.

Exploring Digital Biomarkers of Illness Activity in Mood Episodes: Hypotheses Generating and Model Development Study

BACKGROUND

Depressive and manic episodes within bipolar disorder (BD) and major depressive disorder (MDD) involve altered mood, sleep, and activity, alongside physiological alterations wearables can capture.

OBJECTIVE

Firstly, we explored whether physiological wearable data could predict (aim 1) the severity of an acute affective episode at the intra-individual level and (aim 2) the polarity of an acute affective episode and euthymia among different individuals. Secondarily, we explored which physiological data were related to prior predictions, generalization across patients, and associations between affective symptoms and physiological data.

METHODS

We conducted a prospective exploratory observational study including patients with BD and MDD on acute affective episodes (manic, depressed, and mixed) whose physiological data were recorded using a research-grade wearable (Empatica E4) across 3 consecutive time points (acute, response, and remission of episode). Euthymic patients and healthy controls were recorded during a single session (approximately 48 h). Manic and depressive symptoms were assessed using standardized psychometric scales. Physiological wearable data included the following channels: acceleration (ACC), skin temperature, blood volume pulse, heart rate (HR), and electrodermal activity (EDA). Invalid physiological data were removed using a rule-based filter, and channels were time aligned at 1-second time units and segmented at window lengths of 32 seconds, as best-performing parameters. We developed deep learning predictive models, assessed the channels' individual contribution using permutation feature importance analysis, and computed physiological data to psychometric scales' items normalized mutual information (NMI). We present a novel, fully automated method for the preprocessing and analysis of physiological data from a research-grade wearable device, including a viable supervised learning pipeline for time-series analyses.

RESULTS

Overall, 35 sessions (1512 hours) from 12 patients (manic, depressed, mixed, and euthymic) and 7 healthy controls (mean age 39.7, SD 12.6 years; 6/19, 32% female) were analyzed. The severity of mood episodes was predicted with moderate (62%-85%) accuracies (aim 1), and their polarity with moderate (70%) accuracy (aim 2). The most relevant features for the former tasks were ACC, EDA, and HR. There was a fair agreement in feature importance across classification tasks (Kendall W=0.383). Generalization of the former models on unseen patients was of overall low accuracy, except for the intra-individual models. ACC was associated with "increased motor activity" (NMI>0.55), "insomnia" (NMI=0.6), and "motor inhibition" (NMI=0.75). EDA was associated with "aggressive behavior" (NMI=1.0) and "psychic anxiety" (NMI=0.52).

CONCLUSIONS

Physiological data from wearables show potential to identify mood episodes and specific symptoms of mania and depression quantitatively, both in BD and MDD. Motor activity and stress-related physiological data (EDA and HR) stand out as potential digital biomarkers for predicting mania and depression, respectively. These findings represent a promising pathway toward personalized psychiatry, in which physiological wearable data could allow the early identification and intervention of mood episodes.

Synthesis and biological evaluation of enantiopure thionitrites: the solid-phase synthesis and nitrosation of D-glutathione as a molecular probe

The D-isomer of the naturally-occurring tripeptide glutathione (gamma-L-Glu-L-Cys-Gly, L-GSH) has been synthesised using the Fmoc solid phase peptide synthesis strategy. The D-GSH obtained has been nitrosated to give the D-isomer of the bioactive thionitrite, S-nitroso-L-glutathione. The biological activity of both enantiomers of S-nitrosoglutathione has been studied and compared to the activity of the D- and L-isomers of N-acetyl-S-nitrosopenicillamine (SNAP) and S-nitrosocysteine (CysNO).

Facile metal-assisted hydrolysis of a urethane

Kinetic studies demonstrate that it is possible to achieve large rate enhancements (2 x 10(4)) for the hydrolysis of a urethane group by using metal-bound water or hydroxide as the nucleophile. [reaction: see text]

Systematic review with meta-analysis: neuroimaging in hepatitis C chronic infection

BACKGROUND

Chronic hepatitis C is considered a systemic disease because of extra-hepatic manifestations. Neuroimaging has been employed in hepatitis C virus-infected patients to find in vivo evidence of central nervous system alterations.

AIMS

Systematic review and meta-analysis of neuroimaging research in chronic hepatitis C treatment naive patients, or patients previously treated without sustained viral response, to study structural and functional brain impact of hepatitis C.

METHODS

Using PRISMA guidelines a database search was conducted from inception up until 1 May 2017 for peer-reviewed studies on structural or functional neuroimaging assessment of chronic hepatitis C patients without cirrhosis or encephalopathy, with control group. Meta-analyses were performed when possible.

RESULTS

The final sample comprised 25 studies (magnetic resonance spectroscopy [N = 12], perfusion weighted imaging [N = 1], positron emission tomography [N = 3], single-photon emission computed tomography [N = 4], functional connectivity in resting state [N = 1], diffusion tensor imaging [N = 2] and structural magnetic resonance imaging [N = 2]). The whole sample was of 509 chronic hepatitis C patients, with an average age of 41.5 years old and mild liver disease. A meta-analysis of magnetic resonance spectroscopy studies showed increased levels of choline/creatine ratio (mean difference [MD] 0.12, 95% confidence interval [CI] 0.06-0.18), creatine (MD 0.85, 95% CI 0.42-1.27) and glutamate plus glutamine (MD 1.67, 95% CI 0.39-2.96) in basal ganglia and increased levels of choline/creatine ratio in centrum semiovale white matter (MD 0.13, 95% CI 0.07-0.19) in chronic hepatitis C patients compared with healthy controls. Photon emission tomography studies meta-analyses did not find significant differences in PK11195 binding potential in cortical and subcortical regions of chronic hepatitis C patients compared with controls. Correlations were observed between various neuroimaging alterations and neurocognitive impairment, fatigue and depressive symptoms in some studies.

CONCLUSIONS

Patients with chronic hepatitis C exhibit cerebral metabolite alterations and structural or functional neuroimaging abnormalities, which sustain the hypothesis of hepatitis C virus involvement in brain disturbances.

Association of chronic inflammation and perceived stress with abnormal functional connectivity in brain areas involved with interoception in hepatitis C patients

BACKGROUND

Sickness behavioral changes elicited by inflammation may become prolonged and dysfunctional in patients with chronic disease, such as chronic hepatitis C (CHC). Neuroimaging studies show that the basal ganglia and insula are sensitive to systemic inflammation.

AIM

To elucidate the clinical and neurobiological aspects of prolonged illnesses in patients with CHC.

METHODS

Thirty-five CHC patients not treated with interferon-α or other antiviral therapy, and 30 control subjects matched for age and sex, were evaluated for perceived stress (perceived stress scale; PSS), depression (PHQ-9), fatigue and irritability through a visual analog scale (VAS), as well as serum levels of interleukin-6 (IL-6), prostaglandin E₂ (PGE₂) and oxidative stress markers. Functional MRI was performed, measuring resting-state functional connectivity using a region-of-interest (seed)-based approach focusing on the bilateral insula, subgenual anterior cingulate cortex and bilateral putamen. Between-group differences in functional connectivity patterns were assessed with two-sample t-tests, while the associations between symptoms, inflammatory markers and functional connectivity patterns were analyzed with multiple regression analyses.

RESULTS

CHC patients had higher PSS, PHQ-9 and VAS scores for fatigue and irritability, as well as increased IL-6 levels, PGE₂ concentrations and antioxidant system activation compared to controls. PSS scores positively correlated with functional connectivity between the right anterior insula and right putamen, whereas PHQ-9 scores correlated with functional connectivity between most of the seeds and the right anterior insula. PGE₂ (positively) and IL-6 (negatively) correlated with functional connectivity between the right anterior insula and right caudate nucleus and between the right ventral putamen and right putamen/globus pallidus. PGE₂ and PSS scores accounted for 46% of the variance in functional connectivity between the anterior insula and putamen.

CONCLUSIONS

CHC patients exhibited increased perceived stress and depressive symptoms, which were associated with changes in inflammatory marker levels and in functional connectivity between the insula and putamen, areas involved in interoceptive integration, emotional awareness, and orientation of motivational state.

Toward an Integrated Model of Pathological Personality Traits: Common Hierarchical Structure of the PID-5 and the DAPP-BQ

A dimensional classification seems to be the next move in the personality disorders field. However, it is not clear whether there is one dimensional model or many, or whether the currently available dimensional instruments measure the same traits. To help clarify these issues, the authors administered the Personality Inventory for DSM-5 (PID-5) and the Dimensional Assessment of Personality Pathology (DAPP-BQ) to 414 psychiatric outpatients. Factor analyses showed that a common hierarchical structure underlies both instruments, even if each one measures slightly different aspects of it. Disattenuated correlations indicated that, at the lower order level, two thirds of the PID-5 and DAPP-BQ facets measure essentially the same traits, although the pairings were not exactly as predicted. Among higher order domains, only PID Negative Affectivity and Detachment converged unambiguously with DAPP Emotional Dysregulation and Inhibition. Overall, the PID-5 and the DAPP-BQ reflect, with small divergences, one and the same structure of pathological personality traits.

Development and assessment of an active strategy for the implementation of a collaborative care approach for depression in primary care (the INDI·i project)

Background

Primary care is the principal clinical setting for the management of depression. However, significant shortcomings have been detected in its diagnosis and clinical management, as well as in patient outcomes. We developed the INDI collaborative care model to improve the management of depression in primary care. This intervention has been favorably evaluated in terms of clinical efficacy and cost-effectiveness in a clinical trial. Our aim is to bring this intervention from the scientific context into clinical practice.

Methods

Objective: To test for the feasibility and impact of a strategy for implementing the INDI model for depression in primary care.

Design: A quasi-experiment conducted in primary care. Several areas will be established to implement the new program and other, comparable areas will serve as control group. The study constitutes the preliminary phase preceding generalization of the model in the Catalan public healthcare system.

Participants: The target population of the intervention are patients with major depression. The implementation strategy will also involve healthcare professionals, primary care centers, as well as management departments and the healthcare organization itself in the geographical areas where the study will be conducted: Camp de Tarragona and Vallès Occidental (Catalonia).

Intervention: The INDI model is a program for improving the management of depression involving clinical, instructional, and organizational interventions including the participation of nurses as care managers, the efficacy and efficiency of which has been proven in a clinical trial. We will design an active implementation strategy for this model based on the PARIHS (Promoting Action on Research Implementation in Health Services) framework.

Measures: Qualitative and quantitative measures will be used to evaluate variables related to the successful implementation of the model: acceptability, utility, penetration, sustainability, and clinical impact.

Discussion

This project tests the transferability of a healthcare intervention supported by scientific research to clinical practice. If implementation is successful in this experimental phase, we will use the information and experience obtained to propose and plan the generalization of the INDI model for depression in the Catalan healthcare system. We expect the program to benefit patients, the healthcare system, and society.

Trial registration

ClinicalTrials.gov identifier: NCT03285659; Registered 12th September, 2017.

[A computerised clinical decision-support system for the management of depression in Primary Care]

A pesar de su relevancia clínica y de su importancia como problema de salud pública existen importantes deficiencias en el abordaje de la depresión. Las guías clínicas basadas en la evidencia son útiles para mejorar los procesos y los resultados clínicos, y para facilitar su implementación se ha ensayado su transformación en sistemas informatizados de apoyo a las decisiones clínicas. En este artículo se describen los fundamentos y principales características de una nueva guía clínica informatizada para el manejo de la depresión mayor desarrollada en el sistema sanitario público de Cataluña. Esta herramienta ayuda al clínico a establecer diagnósticos de depresión fiables y precisos, a elegir el tratamiento idóneo a priori según las características de la enfermedad y del propio paciente, y enfatiza en la importancia de un seguimiento sistemático para evaluar la evolución clínica y adecuar las intervenciones terapéuticas a las necesidades del paciente en cada momento.

Chronic hepatitis C, depression and gender: a state of art

Purpose

– The purpose of this paper is to provide a comprehensive overview of the current knowledge regarding chronic hepatitis C (CHC) infection, antiviral therapy, depression, and gender.

Design/methodology/approach

– CHC and its treatment options were reviewed examining their relationship with depression and gender.

Findings

– CHC is a high prevalent chronic infection worldwide, being similar in men and women. However, the infection shows many gender differences in terms of innate response, genetic variability (i.e. IL-28B), route of transmission (i.e. intravenous drug use), disease progression (i.e. fibrosis), lifetime period (i.e. pregnancy), and risk factors (i.e. HIV). Both the hepatitis C infection and antiviral treatment (especially when using the pro-inflammatory cytokine interferon α), are highly associated with depression, where female gender constitutes a risk factor. It seems that the new direct-acting antiviral combinations produce fewer neuropsychiatric side effects. In fact, the presence of depression at baseline is no longer a limitation for the initiation of antiviral treatment. Antidepressant drugs have been recommended as current depression and prophylactic treatment in risk subgroups. However, caution should be exercised due to the risk of drug-drug interactions with some antiviral drugs. Women should be counselled prenatal, during and after pregnancy, taking into account the clinical situation, and the available evidence of the risks and benefits of antiviral and antidepressant treatments. Multidisciplinary approach shows cost-efficacy results.

Originality/value

– The paper clarifies the complex management of CHC therapy and the importance of individualizing treatment. The results also underline the need for an integrated multidisciplinary approach.

Improvement of sexuality after hepatitis C cure with direct acting antivirals

Despite rarely assessed, sexuality is a relevant domain in Quality of Life. We prospectively evaluated the impact of direct-acting antiviral therapy on sexuality in a cohort of 186 patients with chronic hepatitis C (HCV). Sexual dysfunction was assessed by validated scales CSFQ-14/CSFQ-VAS at baseline and one year after treatment finalization. Median age was 55 years and 87% had mild liver disease. Basal prevalence of sexual dysfunction (62%) and fear of HCV transmission (25%) were high. After HCV cure, both sexual dysfunction prevalence and CSFQ-VAS improved (P = .058 and P < .01, respectively), and fear of HCV transmission dropped to 16% (P = .02). These changes were especially relevant in young men (<55), where sexual dysfunction decreased from 48.6% to 29.7% (P = .04) and among non-depressed patients in whom sexual dysfunction decreased from 54.6% to 47% (P < .01). Age and major depression remained as independent factors of sexual dysfunction persistence after HCV cure. Our data suggest that HCV eradication is associated with an improvement in sexuality, in those patients without depression.

Efficacy of an active implementation process of a computerized CPG of major depression disorder in primary care

Introduction

The application of scientific evidence in clinical practice management of Major Depressive Disorder (MDD) is complex. Generally, the usual dissemination process and implementation of Clinical Practice Guidelines (CPG) induce modest changes. A computerized version of a Clinical Practice Guideline for Major Depression (e-CPG-MD) has been integrated in Electronic Clinical Records of Primary Care in Catalonia (Spain). It offers an opportunity to improve clinical results. The design allows access to precise help in the visit itself, improving diagnosis, treatment and follow-up.

Objectives

To evaluate the effects of a multifaceted implementation process of e-CPG-MD, analysing their use and changes in MDD diagnosis.

Methods

A cluster randomized clinical trial was performed in 10 primary care centers (PCC) in Barcelona. In five of ten centers, a multifaceted implementation process of the e-CPG-MD was developed during 6 month. The active process includes: interactive training program, regular feedback audit, educational outreach visits and periodic reminders.

Results

The multifaceted implementation of e-CPG-MD was associated with a significant increase in use during the first 6 months (4.1% + 3.1% vs. 52.7% + 7.3%, P < 0.001). In the active centers, the MD diagnosis increased significantly (rate quotient = 1.56, P < 0.001) and the proportion of moderate and severe MD increased (13.6% vs 41.1%, P = 0.002).

Conclusions

A multifaceted implementation method of e-CPG-MD increased significantly its use in active centers at 6 months. Diagnosis of MDD and the proportion of moderate and severe cases also increased significantly.

Disclosure of interest

The authors have not supplied their declaration of competing interest.

PRimary carE digital Support ToOl in mental health (PRESTO): Design, development and study protocols

BACKGROUND

About 30-50% of Primary Care (PC) users in Spain suffer mental health problems, mostly mild to moderate anxious and depressive symptoms, which account for 2% of Spain's total Gross domestic product and 50% of the costs associated to all mental disorders. Mobile health tools have demonstrated to cost-effectively reduce anxious and depressive symptoms while machine learning (ML) techniques have shown to accurately detect severe cases. The main aim of this project is to develop a comprehensive ML digital support platform (PRESTO) to cost-effectively screen, assess, triage, and provide personalized treatments for anxious and depressive symptoms in PC.

METHODS

The project will be carried out in 3 complementary phases: First, a ML predictive severity model will be built based on all the cases referred to the PC mental health support programme during the last 5 years in Catalonia. Simultaneously, a smartphone app to monitor and deliver psychological interventions for anxiety and depressive symptoms will be developed and tested in a clinical trial. Finally, the ML models and the app will be integrated in a comprehensive decision-support platform (PRESTO) which will triage and assign to each patient a specific intervention based on individual personal and clinical characteristics. The effectiveness of PRESTO to reduce waiting times in receiving mental healthcare will be tested in a stepped-wedge cluster randomized controlled trial in 5 PC centres.

DISCUSSION

PRESTO will offer timely and personalized cost-effective mental health treatment to people with mild to moderate anxious and depressive symptoms. This will result in a reduction of the burden of mental health problems in PC and on society as a whole.

TRIAL REGISTRATION

The project and their clinical trials were registered in Clinical Trials.gov: NCT04559360 (September 2020).

High S100B Levels Predict Antidepressant Response in Patients With Major Depression Even When Considering Inflammatory and Metabolic Markers

BACKGROUND

The relationship between antidepressant response and glial, inflammatory, and metabolic markers is poorly understood in depression. This study assessed the ability of biological markers to predict antidepressant response in major depressive disorder (MDD).

METHODS

We included 31 MDD outpatients treated with escitalopram or sertraline for 8 consecutive weeks. The Montgomery-Åsberg Depression Rating Scale (MADRS) was administered at baseline and at week 4 and 8 of treatment. Concomitantly, blood samples were collected for the determination of serum S100B, C-reactive protein (CRP), and high-density lipoprotein cholesterol (HDL)-C levels. Treatment response was defined as ≥50% improvement in the MADRS score from baseline to either week 4 or 8. Variables associated with treatment response were included in a linear regression model as predictors of treatment response.

RESULTS

Twenty-seven patients (87%) completed 8 weeks of treatment; 74% and 63% were responders at week 4 and 8, respectively. High S100B and low HDL-C levels at baseline were associated with better treatment response at both time points. Low CRP levels were correlated with better response at week 4. Multivariate analysis showed that high baseline S100B levels and low baseline HDL-C levels were good predictors of treatment response at week 4 (R2 = 0.457, P = .001), while S100B was at week 8 (R2 = 0.239, P = .011). Importantly, baseline S100B and HDL-C levels were not associated with depression severity and did not change over time with clinical improvement.

CONCLUSIONS

Serum S100B levels appear to be a useful biomarker of antidepressant response in MDD even when considering inflammatory and metabolic markers.

Antidepressants overuse in primary care: Prescription trends between 2010 and 2019 in Catalonia

INTRODUCTION

There has been an increase in the prescription of antidepressants (AD) in primary care (PC). However, it is unclear whether this was explained by a rise in diagnoses with an indication for AD. We investigated the changes in frequency and the variables associated with AD prescription in Catalonia, Spain.

METHODS

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 and 2019. Prescription of AD was calculated using DHD (Defined Daily Doses per 1000 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.

RESULTS

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.

CONCLUSIONS

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.

Differentiating Abnormal, Normal, and Ideal Personality Profiles in Multidimensional Spaces

Abstract: Current dimensional taxonomies of personality disorder (PD) establish that intense traits do not suffice to diagnose a disorder, and additional constructs reflecting dysfunction are required. However, traits appear able to predict maladaptation by themselves, which might avoid duplications and simplify diagnosis. On the other hand, if trait-based diagnoses are feasible, it is the whole personality profile that should be considered, rather than individual traits. This takes us into multidimensional spaces, which have their own particular – but poorly understood – logic. The present study examines how profile-level differences between normal and disordered subjects can be used for diagnosis. The Dimensional Assessment of Personality Pathology – Basic Questionnaire (DAPP-BQ) and the Personality Inventory for DSM-5 (PID-5) were administered to a community and a clinical sample each (total n = 1,925 and 3,543 respectively). Intense traits proved to be common in the general population, so empirically-based thresholds are indispensable not to take as abnormal what is at most unideal. Profile-level parameters such as Euclidean and Mahalanobis distances outperformed individual traits in predicting mental problems and equaled the performance of published measures of dysfunction or severity. Personality profiles can play a more central role in identifying disorders than is currently acknowledged, provided that adequate metrics are used.

Predictors of Metabolic Syndrome in Severe Mental Disorders

Aims:

To assess the potential factors related to the development of metabolic syndrome (MS) in patients with chronic mental disorders.

Method:

Descriptive, cross-sectional study; sample: 140 outpatients with schizophrenia or affective disorders attended for more than 2 years. Dependent variable: metabolic syndrome (Adult Treatment Panel III diagnostic criteria). Independent variables: age, gender, syndromic diagnosis, main treatment, duration of treatment, Global Functioning, type of diet, sedentarism, alcohol consumption, smoking, Primary Care monitoring.

Results:

43.6% of patients who had an unhealthy diet showed MS, whereas only 25.6% of those patients that followed healthy food habits met criteria for MS (p< 0.05, chi square; OR=1.23, 95% CI =1.01-1.5). Logistic regression identifies type of diet and GAF scores as the only predictive variables for MS. Bivariant analysis confirms previous data concerning the relationship between age and MS, and shows a negative relationship between alcohol consumption and Body Mass Index, and between alcohol and fasting plasma glucose, particularly among young women.

Conclusion:

The lack of a well-balanced dietetic habit appears to be an essential factor in the development of metabolic syndrome. for its prevention, educational programs addressed to patients with severe mental disorders should focus on healthy diet. A sum of effects of age, diet, central adiposity, estrogenic balance and moderate alcohol consumption might argue for the rest of our results.

Results of the Implementation of a Spanish Computerized Guideline for Depression in Primary Care

A new computerized CPG for Major Depression (e-CPG-MD) was integrated in electronic medical records of primary care in a 7 million population in Catalonia (Spain). An integrated design allows precise access in each patient visit, improving diagnosis, treatment and follow-up. It facilitates an evaluation of suicide risk in depressed patients.

Objective

To evaluate the effects of a multifactor process of implementation of the e-CPG MD, analyzing its use and the key clinical outcomes.

Methods

A cluster randomized clinical trial was performed in 10 primary care centers (PCC) in Barcelona. In five of ten centers a multifaceted implementation process of the e-CPG-MD was developed during 6 month. The others five PCCs received only an usual diffusion. The multifaceted process includes an establishment of local implementation teams, an interactive training program, regular feedback audits, educational outreach visits and periodic reminders.

Results

At six month, a greater proportion of new MD patients from active PCCs were included in the e- CPG-DEP (4.1% + 3.1% vs. 52.7% + 7.3%, p < 0.001); the incidence of MD diagnostics of Major Depression increased significantly (rate quotient = 1.56, p < 0.001) and the proportion of cases with moderate and severe MD too (13.6% vs 41.1%, p = 0.002).

Conclusions

A multifaceted implementation method of an e-CPG-MD increased significantly its uses, the registered incidence of MD and improved the capacity of recognizing severity. Further analysis is necessary in order to determine the impact on clinical outcomes.

Disclosure of interest

The authors have not supplied their declaration of competing interest.

The impact of the Catalonia Suicide Risk Code (CSRC) in a tertiary hospital: Reduction in hospitalizations and emergency room visits for any reason but not for suicide attempt

INTRODUCTION

Suicide attempts represent a public health concern. The objective of this study is to describe the clinical characteristics of patients visiting an emergency room for a suicide attempt and included in a suicide prevention program, the Catalonia Suicide Risk Code (CSRC), particularly focusing on the follow-up evaluations.

MATERIALS AND METHODS

The CSRC program is divided in 3 phases: (1) alert and activation, (2) proactive telephone and face-to-face follow-up and (3) comprehensive preventive health monitoring. This is the analysis of the sample of patients attempting or intending suicide who were seen at a tertiary hospital in Barcelona, and their 1-year follow-up outcome.

RESULTS

Three hundred and sixty-five patients were included. In 15% of the cases, there was no previous psychiatric history but in the majority of cases, a previous psychiatric diagnosis was present. The most common type of suicide attempt was by drug overdose (84%). Up to 66.6% of the patients attended the scheduled follow-up visit in the CSRC program. A significant reduction in the proportion of patients visiting the emergency room for any reason (but not specifically for a suicide attempt) and being hospitalized in the first semester in comparison with the second six months after the CSRC activation (30.1% versus 19.9%, p=0.006; 14.1% versus 5.8%, p=0.002) was observed.

CONCLUSIONS

The clinical risk factors and the findings of the CSRC helped in the characterization of suicide attempters. The CSRC may contribute to reduce hospitalizations and the use of mental health care resources, at least in the short-term.

Automated Speech Analysis in Bipolar Disorder: The CALIBER Study Protocol and Preliminary Results

Background: Bipolar disorder (BD) involves significant mood and energy shifts reflected in speech patterns. Detecting these patterns is crucial for diagnosis and monitoring, currently assessed subjectively. Advances in natural language processing offer opportunities to objectively analyze them. Aims: To (i) correlate speech features with manic-depressive symptom severity in BD, (ii) develop predictive models for diagnostic and treatment outcomes, and (iii) determine the most relevant speech features and tasks for these analyses. Methods: This naturalistic, observational study involved longitudinal audio recordings of BD patients at euthymia, during acute manic/depressive phases, and after-response. Patients participated in clinical evaluations, cognitive tasks, standard text readings, and storytelling. After automatic diarization and transcription, speech features, including acoustics, content, formal aspects, and emotionality, will be extracted. Statistical analyses will (i) correlate speech features with clinical scales, (ii) use lasso logistic regression to develop predictive models, and (iii) identify relevant speech features. Results: Audio recordings from 76 patients (24 manic, 21 depressed, 31 euthymic) were collected. The mean age was 46.0 ± 14.4 years, with 63.2% female. The mean YMRS score for manic patients was 22.9 ± 7.1, reducing to 5.3 ± 5.3 post-response. Depressed patients had a mean HDRS-17 score of 17.1 ± 4.4, decreasing to 3.3 ± 2.8 post-response. Euthymic patients had mean YMRS and HDRS-17 scores of 0.97 ± 1.4 and 3.9 ± 2.9, respectively. Following data pre-processing, including noise reduction and feature extraction, comprehensive statistical analyses will be conducted to explore correlations and develop predictive models. Conclusions: Automated speech analysis in BD could provide objective markers for psychopathological alterations, improving diagnosis, monitoring, and response prediction. This technology could identify subtle alterations, signaling early signs of relapse. Establishing standardized protocols is crucial for creating a global speech cohort, fostering collaboration, and advancing BD understanding.