Disparities by Socioeconomic Status and Diagnosis of Dementia in the Prescribing of Antipsychotics in a Real-World Data Population Over 60 Years of Age.

Background: Antipsychotics are widely used in the elderly due to the high prevalence of neuropsychiatric associated with dementia.

Objective: To analyze potential disparities in antipsychotic use in the general population of Gipuzkoa by socioeconomic status (SES) and diagnosis of Alzheimer's disease and related dementia (ADRD) adjusting for somatic and psychiatric comorbidities, age, and sex.

Methods: A retrospective observational study was carried out in all the 221,777 individuals over 60 years of age (Gipuzkoa, Spain) to collect diagnosis of ADRD, the Charlson Comorbidity Index, and psychiatric comorbidities considering all primary, outpatient, emergency and inpatient care episodes and first- and second-generation antipsychotics, and sociodemographic variables, namely, age, sex, SES and living in a nursing home.

Mindfulness-based cognitive therapy neurobiology in treatment-resistant obsessive-compulsive disorder: A domain-related resting-state networks approach.

Mindfulness-based cognitive therapy (MBCT) stands out as a promising augmentation psychological therapy for patients with obsessive-compulsive disorder (OCD). To identify potential predictive and response biomarkers, this study examines the relationship between clinical domains and resting-state network connectivity in OCD patients undergoing a 3-month MBCT programme. Twelve OCD patients underwent two resting-state functional magnetic resonance imaging sessions at baseline and after the MBCT programme.

Comorbidity and household income as mediators of gender inequalities in dementia risk: a real-world data population study.

Background: Low household income (HI), comorbidities and female sex are associated with an increased risk of dementia. The aim of this study was to measure the mediating effect of comorbidity and HI on the excess risk due to gender in relation to the incidence and prevalence of dementia in the general population.

Methods: A retrospective and observational study using real-world data analysed all people over 60 who were registered with the Basque Health Service in Gipuzkoa.

Sex differences in clinical response to deep brain stimulation in resistant obsessive-compulsive disorder.

Introduction: Deep brain stimulation (DBS) is an effective alternative to treat severe refractory obsessive-compulsive disorder (OCD), although little is known on factors predicting response. The objective of this study was to explore potential sex differences in the pattern of response to DBS in OCD patients.

Methods: We conducted a prospective observational study in 25 patients with severe resistant OCD.

Areas of interest and sentiment analysis towards second generation antipsychotics, lithium and mood stabilizing anticonvulsants: Unsupervised analysis using Twitter.

Background: Severe mental disorders like Schizophrenia and related psychotic disorders (SRD) or Bipolar Disorder (BD) require pharmacological treatment for relapse prevention and quality of life improvement. Yet, treatment adherence is a challenge, partly due to patients' attitudes and beliefs towards their medication. Social media listening offers insights into patient experiences and preferences, particularly in severe mental disorders.

Excess healthcare costs of mental disorders in children, adolescents and young adults in the Basque population registry adjusted for socioeconomic status and sex.

Background: Mental illnesses account for a considerable proportion of the global burden of disease. Economic evaluation of public policies and interventions aimed at mental health is crucial to inform decisions and improve the provision of healthcare services, but experts highlight that nowadays the cost implications of mental illness are not properly quantified. The objective was to measure the costs of excess use of all healthcare services by 1- to 30-year-olds in the Basque population as a function of whether or not they had a mental disorder diagnosis.

Budget impact analysis of the use of Souvenaid in patients with prodromal Alzheimer's Disease in Spain.

Introduction: The effectiveness, safety, and cost-effectiveness of the use of Souvenaid for Alzheimer's disease (AD) have been previously evidenced. To complete the economic analysis, there is a need to assess whether society can afford it. The objective of this study was to carry out a budget impact analysis of the use of Souvenaid in Spain under the conditions of the LipiDidiet clinical trial from a societal perspective.

Estimation of the epidemiology of dementia and associated neuropsychiatric symptoms by applying machine learning to real-world data.

Introduction: Incidence rates of dementia-related neuropsychiatric symptoms (NPS) are not known and this hampers the assessment of their population burden. The objective of this study was to obtain an approximate estimate of the population incidence and prevalence of both dementia and NPS.

Methods: Given the dynamic nature of the population with dementia, a retrospective study was conducted within the database of the Basque Health Service (real-world data) at the beginning and end of 2019.

Long-term comparative effectiveness of deep brain stimulation in severe obsessive-compulsive disorder.

Background: Twenty years after the first use of Deep Brain Stimulation (DBS) in obsessive-compulsive disorder (OCD), our knowledge of the long-term effects of this therapeutic option remains very limited.

Objective: Our study aims to assess the long-term effectiveness and tolerability of DBS in OCD patients and to look for possible predictors of long-term response to this treatment.

Methods: We studied the course of 25 patients with severe refractory OCD treated with DBS over an average follow-up period of 6.

Viability Study of Machine Learning-Based Prediction of COVID-19 Pandemic Impact in Obsessive-Compulsive Disorder Patients.

Background: Machine learning modeling can provide valuable support in different areas of mental health, because it enables to make rapid predictions and therefore support the decision making, based on valuable data. However, few studies have applied this method to predict symptoms' worsening, based on sociodemographic, contextual, and clinical data. Thus, we applied machine learning techniques to identify predictors of symptomatologic changes in a Spanish cohort of OCD patients during the initial phase of the COVID-19 pandemic.

Deep brain stimulation for obsessive-compulsive disorder: A systematic review of worldwide experience after 20 years.

Background: Twenty years after its first use in a patient with obsessive-compulsive disorder (OCD), the results confirm that deep brain stimulation (DBS) is a promising therapy for patients with severe and resistant forms of the disorder. Nevertheless, many unknowns remain, including the optimal anatomical targets, the best stimulation parameters, the long-term (LT) effects of the therapy, and the clinical or biological factors associated with response. This systematic review of the articles published to date on DBS for OCD assesses the short and LT efficacy of the therapy and seeks to identify predictors of response.

Estimation of the epidemiology of dementia and associated neuropsychiatric symptoms by applying machine learning to real-world data.

Introduction: Incidence rates of dementia-related neuropsychiatric symptoms (NPS) are not known and this hampers the assessment of their population burden. The objective of this study was to obtain an approximate estimate of the population incidence and prevalence of both dementia and NPS.

Methods: Given the dynamic nature of the population with dementia, a retrospective study was conducted within the database of the Basque Health Service (real-world data) at the beginning and end of 2019.

[Cost-effectiveness analysis of sofosbuvir-simeprevir regimens for chronic hepatitis C genotype 1 patients with advanced fibrosis].

Background And Objective: The aim of this study was to measure the cost-effectiveness of the treatment with simeprevir and sofosbuvir in chronic hepatitis C genotype 1 patients with F3-F4 levels of fibrosis, according to the results of the COSMOS trial.

Material And Methods: A Markov model was used to estimate the costs and clinical outcomes from the start of therapy. In the model, the progression was simulated alongside the different health states of the chronic liver disease associated with chronic hepatitis C using whole life as time-horizon.