Actas espanolas de psiquiatria最新文献

Parkinson's disease (PD) is a degenerative disease of the central nervous system primarily affecting middle-aged and elderly individuals, significantly compromising their quality of life. Neuroinflammation is now recognized as a key feature in the pathogenesis of PD. This study reviews recent advances in the identification of potential biomarkers associated with neuroinflammation in PD and their significance for therapeutic strategies. These findings suggest that inflammatory factors play a pivotal role in PD treatment, and interventions involving anti-inflammatory drugs, physical exercise, and dietary modifications have shown promising results in mitigating disease progression.

Background: Accurate diagnosis and classification of Alzheimer's disease (AD) are crucial for effective treatment and management. Traditional diagnostic models, largely based on binary classification systems, fail to adequately capture the complexities and variations across different stages and subtypes of AD, limiting their clinical utility.

Methods: We developed a deep learning model integrating a dot-product attention mechanism and an innovative labeling system to enhance the diagnosis and classification of AD subtypes and severity levels. This model processed various clinical and demographic data, emphasizing the most relevant features for AD diagnosis. The approach emphasized precision in identifying disease subtypes and predicting their severity through advanced computational techniques that mimic expert clinical decision-making.

Results: Comparative tests against a baseline fully connected neural network demonstrated that our proposed model significantly improved diagnostic accuracy. Our model achieved an accuracy of 83.1% for identifying AD subtypes, compared to 72.9% by the baseline. In severity prediction, our model reached an accuracy of 83.3%, outperforming the baseline (73.5%).

Conclusions: The incorporation of a dot-product attention mechanism and a tailored labeling system in our model significantly enhances the accuracy of diagnosing and classifying AD. This improvement highlights the potential of the model to support personalized treatment strategies and advance precision medicine in neurodegenerative diseases.

Background: Efforts to improve psychiatry training must incorporate residents' assessment of their training. This study sought to collect the opinion of residents about the program that has been in force in Spain since 2008, until the current transition to a new plan.

Methods: The authors conducted an online survey of psychiatry residents in Spain, asking about their formative and working conditions. Based on previous research and the national training programme, it was distributed electronically to resident representatives of the National Board of Psychiatry. This descriptive, cross-sectional study used a mixed-methods (quantitative and qualitative) approach, following standard procedures for data analysis.

Results: A total of 109 residents from 67 training units responded to the survey. The average score for satisfaction with their training was 6.84 (standard deviation (SE) = 2.4; the maximum possible score was 10). Psychotherapy was considered the area with the greatest need for improvement, while the rotations that participants would most like to be extended were child psychiatry and addictions. It was reported that rotation durations established by the national programme were not fulfilled in 38.5% of cases, while the required direct supervision for first-year residents was not fulfilled in 77.1% of cases. Regarding working conditions, 47.7% of the residents reported that they exceeded the maximum working time established by European law.

Conclusions: Psychiatry residents in Spain perceive certain areas of their training as deficient, especially those related to psychotherapy and clinical supervision, and they consider that their working time is excessive. The approval of the new training programme opens up an interesting opportunity for improvement.

Background: Alcohol Use Disorders (AUD), affective disorders, and personality disorders are among the most prevalent mental health conditions observed in individuals exhibiting suicidal behavior, encompassing both completed and attempted suicides. A robust association between AUD and suicidal behavior has been established through retrospective and prospective cohort studies. Research on the relationship between alcohol consumption and self-harm has predominantly focused on Western and high-income countries, whereas approximately one-third of the global population, including half of the world's countries, lacks accessible suicide data. This study aims to present an updated review of empirical evidence regarding the risk of suicide associated with AUD in both developed and developing nations.

Methods: We identified published meta-analyses, reviews, systematic reviews, randomized controlled trials, clinical studies, clinical trials, controlled clinical trials, observational studies, and case reports written in English and published between January 2004 and June 2024. Our search yielded a total of 312 papers. After reviewing titles and abstracts, 232 articles were excluded from the initial records. Following full-text review of the remaining 80 articles, a qualitative synthesis was conducted, highlighting the most representative 41 papers for inclusion in this overview.

Results: Our analysis indicates that alcohol abuse is a significant risk factor for all forms of suicidal behavior. Alcohol consumption functions as both a predisposing and precipitating factor, contributing to maladaptive behaviors in both developing and developed countries. The clinical condition is exacerbated by alcohol use, which in turn increases the risk of suicide.

Conclusions: Further research is essential to develop targeted psychological and pharmacological interventions aimed at preventing and treating these conditions, with the goal of reducing the risk of suicidal behavior associated with AUD. In developing countries, integrating public health and clinical strategies is crucial for effectively addressing suicide prevention.

Objective: To explore the relationship between Career Decision-Making Self-Efficacy and maladjustment among psychiatric nursing students.

Method: The results of baseline data, Mental Health Knowledge Questionnaire, Career Decision-Making Self-Efficacy scale and Clinical Practice Maladjustment Questionnaire of psychiatric nursing students from January 2022 to August 2023 were obtained from our hospital, and the correlation of scores was examined through Pearson correlation analysis. The factors affecting psychiatric nursing students' maladjustment were analyzed through logistic regression analysis.

Results: A total of 286 psychiatric nursing students were included in this study. The total score of all students of Mental Health Law Knowledge Questionnaire score was 21.30 ± 5.28, the total score of Career Decision-Making Self-Efficacy scale was 132.90 ± 13.36 and the total score of Clinical Practice Maladjustment Questionnaire was 102.85 ± 9.81. Positive correlations were found among the Mental Health Knowledge Questionnaire score and the Career Decision-Making Self-Efficacy scale and Clinical Practice Maladjustment Questionnaire (r = 0.550, 0.602, p < 0.05). Similarly, a positive correlation was found between the Career Decision-Making Self-Efficacy scale and Clinical Practice Maladjustment Questionnaire (r = 0.639, p < 0.05). Personality, school performance, Mental Health Knowledge Questionnaire score and Career Decision-Making Self-Efficacy Scale score were the main factors affecting clinical practice inadaptability of psychiatric nursing students, and the odds ratio (OR) values were higher than 1.

Conclusion: Psychiatric nursing students experienced maladjustment during clinical practice, and Career Decision-Making Self-Efficacy was the main influencing factor.

This editorial explores the dynamic psychiatric research field by focusing on interdisciplinary approaches to understand the complexity of mental disorders by placing particular emphasis on schizophrenia. It highlights the need to integrate findings from diverse scientific disciplines, such as neuroscience, computational modeling and genomics, to unravel the multifaceted nature of these conditions. The potential of interdisciplinary research to transform our knowledge and the treatment of psychiatric disorders is underscored by moving beyond traditional models and developing more nuanced frameworks to more effectively address these complexities. Thus by combining perspectives from different fields, significant advancements are expected in the diagnosis, treatment and prevention of mental disorders like schizophrenia, and will open new research and clinical practice avenues in psychiatry.

Background: Acute ischemic stroke (AIS) is a prevalent and challenging neurological condition associated with high mortality and morbidity rates. This study aimed to evaluate the therapeutic efficacy of repetitive transcranial magnetic stimulation (rTMS) combined with ginkgo diterpene lactone meglumine injection (GDLMI) on cognitive and neurological function recovery in patients with AIS.

Methods: A total of 120 patients with AIS, admitted between January 2021 and January 2022, received rTMS combined with GDLMI after admission. Their cognitive and neurological functions were assessed using the Chinese version of the Montreal Cognitive Assessment (MoCA) and the National Institute of Health Stroke Scale (NIHSS) respectively before and after treatment. Additionally, serum levels of lipoprotein-associated phospholipase A2 (Lp-PLA2) and ischemia-modified albumin (IMA) were quantified. Statistical analyses were performed to elucidate potential correlations between Lp-PLA2 and IMA levels and clinical outcomes.

Results: After treatment, patients with AIS exhibited significantly improved cognitive and neurological functions, increased MoCA score and decreased NIHSS score compared to those before treatment (p < 0.05). A linear correlation was observed between Lp-PLA2 and IMA levels and the recovery of cognitive function in AIS patients (r = -0.892/-0.764, p < 0.05). Before and after factor adjustment, Lp-PLA2 and IMA were identified as independent influencing factors for the efficiency in cognitive function recovery (p < 0.05). Similarly, Lp-PLA2 and IMA levels were linearly correlated with the recovery of neurological function in AIS patients (r = -0.887/-0.796, p < 0.05). Lp-PLA2 combined with IMA performed better than Lp-PLA2 or IMA alone in predicting the efficiency of rTMS plus GDLMI in promoting the cognitive and neurological function recovery (p < 0.05).

Conclusions: rTMS combined with GDLMI can contribute to the cognitive and neurological function recovery in patients with AIS. Serum levels of Lp-PLA2 and IMA could serve as independent influencing factors for the efficiency in promoting cognitive and neurological function recovery.

Background: Diagnosing psychiatric disorders following craniocerebral trauma primarily depends on clinical symptoms and neuropsychological evaluation, which can be subjective and limited. This study aimed to investigate the diagnostic value of serum matrix metalloproteinase-9 (MMP-9), S100 calcium-binding protein β (S100-β), and glial fibrillary acidic protein (GFAP) in post-traumatic mental disorders.

Methods: A retrospective analysis was conducted on 108 patients with craniocerebral trauma admitted to Wenzhou Hospital of Integrated Traditional Chinese and Western Medicine between January 2021 and December 2023. Patients were categorized into a post-traumatic mental disorder group (n = 68) and a simple craniocerebral trauma group (n = 40) according to whether they had mental disorders. Serum MMP-9, S100-β, and GFAP levels were measured using enzyme-linked immunosorbent assay (ELISA) and compared between the two groups. Logistic multivariate regression identified risk factors for post-traumatic mental disorders, while receiver operating characteristic (ROC) curve analysis assessed the predictive value of the biomarkers. Spearman correlation analysis examined the relationship between serum biomarkers and the presence of post-traumatic mental disorders.

Results: Serum levels of MMP-9, S100-β, and GFAP were significantly elevated in the post-traumatic mental disorder group compared to the simple traumatic brain injury group (p < 0.001). Logistic regression revealed that craniocerebral injury severity, family satisfaction, and serum levels of S100-β and GFAP were significant risk factors for post-traumatic mental disorders (p < 0.05). The areas under the ROC curve for MMP-9, S100-β, and GFAP were 0.768, 0.937, and 0.904, respectively. Spearman correlation analysis showed that serum MMP-9, S100-β and GFAP were significantly positively correlated with the incidence of post-traumatic mental disorders (p < 0.001).

Conclusion: The levels of MMP-9, S100-β and GFAP were abnormal in the serum of patients with craniocerebral trauma. These biomarkers hold significant diagnostic value in patients with post-traumatic stress disorder.

Background: The COVID-19 pandemic was a global public health crisis with an unparalleled impact worldwide, presenting a significant challenge for both physical and mental health. The main objective of this study was to analyze the risk of depression during the COVID-19 pandemic and how this was affected by sociodemographic factors, pandemic fatigue, risk perception, trust in institutions, and perceived self-efficacy.

Methods: A cross-sectional study was conducted in the Region of Murcia through two online surveys completed by 1000 people in June 2021 (Round 1) and March 2022 (Round 2). Risk of depression was measured using the 5-item World Health Organization Well-Being Index (WHO-5) questionnaire, and descriptive, bivariate, and multivariate regression analyses were performed to identify factors associated with the risk of depression.

Results: In Round 1, 35.2% of the sample presented a risk of depression, which increased to 39.1% in Round 2. Those at greater risk were women, individuals with lower socioeconomic status, those with less family support, lower trust in institutions, higher perceived risk of contracting the disease, and higher levels of pandemic fatigue.

Conclusions: Identifying vulnerable populations facing mental health issues can help the authorities and institutions that are responsible for managing public health crises to develop and implement inclusive strategies and interventions tailored to the population's needs.

Background: The increasingly fast development of mobile health technologies holds significant value for individuals dealing with mental health conditions. However, inadequate consideration of patients' preferences and expectations undermines real-world outcomes, including sustained adherence. Driven by the belief that specific characteristics, such as youth and higher education, of individuals with obsessive-compulsive disorder make them suitable for digital adoption, we investigated mHealth-related desirability factors within this patient group.

Methods: Fifty-one conveniently selected adults with obsessive-compulsive disorder filled in a self-report questionnaire about symptom self-management preferences, with an emphasis on assessing mobile health options and perceptions of patient-centeredness.

Results: The smartphone phone app emerged as the top choice of most of the sample for receiving information about symptom status (82.4%), obtaining general information about obsessive-compulsive disorder (74.5%), and symptom self-registration (66.7%), with no significant effect of sex or living location. Although only 23.5% of participants were using a health-related app, most expressed interest in using it for receiving symptom management tips (98.1%), medical advice (94.2%), symptom evolution updates (90.2%), lifestyle information (92.2%), medication tracking (88.2%) and short symptom self-reports (90.2%). Median expectations regarding mobile health's impact on patient-centeredness, satisfaction, and adherence were positive or very positive.

Conclusions: Our data confirm that individuals with obsessive-compulsive disorder exhibit strong inclinations and optimistic expectations toward technology-based solutions. We highlight some of the preferences within this patient group, which can inform the design of practical, real-world applications.