Psychiatry Research最新文献_第6页

Pupillary response to blue light as a biomarker of seasonal pattern in Major Depressive Episode: A clinical study using pupillometry 瞳孔对蓝光的反应作为重度抑郁发作季节性模式的生物标志物：一项使用瞳孔测量法的临床研究。

IF 4.2 2区医学 Q1 PSYCHIATRY

Psychiatry Research

Pub Date : 2025-02-01 DOI: 10.1016/j.psychres.2024.116333

Julia Maruani , Lily Vissouze , Marc Hebert , Heloise Rach , Feriel Zehani , Michel Lejoyeux , Patrice Bourgin , Pierre A. Geoffroy

Depressive disorders are characterized by disturbances in light signal processing. More specifically, an alteration of the melanopsin response is suggested. The post-illumination pupillary response (PIPR) to blue light (post-blue PIPR) is increasingly used as a marker of the activity of intrinsically photosensitive melanopsin ganglion cells (ipRGCs). We hypothesized that individuals with Major Depressive Episode (MDE) who exhibited a higher vulnerability to season patterns showed a decreased ability to transmit light signals to the brain. We explored the correlation between the post-blue PIPR and the Global Seasonality Score (GSS) in 21 patients with MDE. The GSS was assessed using the Seasonal Pattern Assessment Questionnaire (SPAQ). The results revealed that decreased relative and absolute post-blue PIPR, suggesting a melanopsinergic hyposensitivity, were associated independently and significantly with higher seasonality in the psychological factor including a greater seasonal variation in sleep duration, mood, energy level and social activity, but were not associated with higher seasonality in the dietary factor (including weight and appetite seasonal variations) or with the severity of anxiety, depression, or sleep disturbances. Interestingly, mediation analyses highlight independent bidirectional effects of high vulnerability to season of psychological factors and decreased ipRGC sensitivity. Post-blue PIPR could be an objective marker of seasonal changes in daylight exposure in patients with MDE. Further research could explore post-blue PIPR as a state or trait biomarker for depressive disorders and the seasonal pattern, and its potential role in predicting therapeutic response to light therapy.

抑郁症的特征是光信号处理受到干扰。更具体地说，是黑视素反应的改变。光照后瞳孔对蓝光的反应（post-blue PIPR）越来越多地被用作内在光敏黑视素神经节细胞（iprgc）活性的标志物。我们假设患有重度抑郁发作（MDE）的个体对季节模式表现出更高的脆弱性，表明向大脑传递光信号的能力下降。我们探讨了21例MDE患者的蓝色后PIPR与全球季节性评分（GSS）之间的相关性。采用季节性模式评估问卷（SPAQ）对GSS进行评估。结果显示，蓝色后PIPR的相对和绝对下降，表明黑素能低敏感性，与心理因素的较高季节性（包括睡眠时间、情绪、能量水平和社交活动的较大季节性变化）独立且显著相关，但与饮食因素的较高季节性（包括体重和食欲的季节性变化）或焦虑、抑郁的严重程度无关。或者睡眠障碍。有趣的是，中介分析强调了对季节心理因素的高易感性和ipRGC敏感性降低的独立双向效应。蓝色后PIPR可能是MDE患者日光照射季节变化的客观标志。进一步的研究可能会探索蓝后PIPR作为抑郁症和季节性模式的状态或特征生物标志物，以及它在预测光疗法治疗反应中的潜在作用。

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引用次数: 0

Developing a simplified measure to predict the risk of autism spectrum disorders: Abbreviating the M-CHAT-R using a machine learning approach in China 开发一种简化的方法来预测自闭症谱系障碍的风险：在中国使用机器学习方法缩写M-CHAT-R。

IF 4.2 2区医学 Q1 PSYCHIATRY

Psychiatry Research

Pub Date : 2025-02-01 DOI: 10.1016/j.psychres.2025.116353

Ning Pan , Lifeng Chen , Bocheng Wu , Fangfang Chen , Jin Chen , Saijun Huang , Cuihua Guo , Jinqing Wu , Yujie Wang , Xian Chen , Shirui Yang , Jin Jing , Xuchu Weng , Lizi Lin , Jiuxing Liang , Xin Wang

Background

Early screening for autism spectrum disorder (ASD) is crucial, yet current assessment tools in Chinese primary child care are limited in efficacy.

Objective

This study aims to employ machine learning algorithms to identify key indicators from the 20-item Modified Checklist for Autism in Toddlers, revised (M-CHAT-R) combining with ASD-related sociodemographic and environmental factors, to distinguish ASD from typically developing children.

Methods

Data from our prior validation study of the Chinese M-CHAT-R (August 2016–March 2017, n = 6,049 toddlers) were reviewed. We extracted the 20-item M-CHAT-R data and integrated 17 sociodemographic and environmental risk factors associated with ASD development to strengthen M-CHAT-R's machine learning screening. Five feature selection methods were used to extract subsets from the original set. Six machine learning algorithms were applied to identify the optimal subset distinguishing clinically diagnosed ASD toddlers from typically developing toddlers.

Findings

Nine features were grouped into three subsets: subset 1 contained unanimously recommended items (A1 [Follows point], A3 [Pretend play], A9 [Brings objects to show], A10 [Response to name] and A16 [Gazing following]). Subset 2 added two items (A17 [Gaining parent's attention] and A18 [Understands what is said]), and subset 3 included two more items (A8 [Interest in other children] and child's age). The top-performing algorithm resulted in a seven-item classifier of subset 2 with 92.5 % sensitivity, 90.1 % specificity, and 10.0 % positive predictive value.

Conclusions

Machine learning classifiers effectively differentiate ASD toddlers from typically developing toddlers using a reduced M-CHAT-R item set.

Clinical implications

This highlights the clinical significance of machine learning-optimized models for ASD screening in primary health care centers and broader applications.

背景：自闭症谱系障碍（ASD）的早期筛查至关重要：自闭症谱系障碍（ASD）的早期筛查至关重要，但目前中国基层儿童保健机构使用的评估工具的有效性有限：本研究旨在运用机器学习算法，从20项修订版幼儿自闭症核对表（M-CHAT-R）中识别关键指标，并结合与自闭症相关的社会人口和环境因素，以区分自闭症儿童和发育正常儿童：我们回顾了之前对中文M-CHAT-R的验证研究数据（2016年8月至2017年3月，n = 6049名幼儿）。我们提取了20个项目的M-CHAT-R数据，并整合了17个与ASD发展相关的社会人口和环境风险因素，以加强M-CHAT-R的机器学习筛选。我们使用了五种特征选择方法从原始数据集中提取子集。应用六种机器学习算法来确定最佳子集，以区分临床诊断为 ASD 的幼儿和发育正常的幼儿：九个特征被分为三个子集：子集 1 包含一致推荐的项目（A1 [跟随点]、A3 [假装游戏]、A9 [携带物品展示]、A10 [对名字的反应] 和 A16 [凝视跟随]）。子集 2 增加了两个项目（A17 [引起父母注意] 和 A18 [理解所说的话]），子集 3 增加了两个项目（A8 [对其他孩子感兴趣] 和孩子的年龄）。表现最佳的算法是子集 2 的七项分类器，灵敏度为 92.5%，特异度为 90.1%，阳性预测值为 10.0%：结论：机器学习分类器使用精简的 M-CHAT-R 项目集有效区分了 ASD 学步儿童和典型发育学步儿童：这凸显了机器学习优化模型在初级医疗保健中心和更广泛应用中进行 ASD 筛查的临床意义。

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引用次数: 0

Association between stimulant and non-stimulant ADHD medications and completed suicide in adolescents and adults: A population-based nested case-control study 兴奋剂和非兴奋剂ADHD药物与青少年和成人自杀之间的关系：一项基于人群的巢式病例对照研究。

IF 4.2 2区医学 Q1 PSYCHIATRY

Psychiatry Research

Pub Date : 2025-02-01 DOI: 10.1016/j.psychres.2024.116309

Helen-Maria Vasiliadis , Louis Rochette , Victoria Massamba , Alain Lesage , Elham Rahme , Martin Gignac , Fatoumata Binta Diallo , Alvine Fansi , Samuele Cortese , Carlotta Lunghi

Introduction

ADHD has been linked to an increased risk of completed suicide. The aim of this study was to assess the relationship between ADHD medication use and completed suicide.

Methods

This nested case-control study included individuals aged 12–49 in Quebec, Canada, diagnosed with ADHD and/or dispensed ADHD medication. Suicide cases (n = 472) between 2000 and 2021 were matched with 5 controls each (n = 2360) on date of birth, sex, and continuous public drug insurance coverage for at least 365 days before suicide death (index date). Multivariable conditional logistic regression was used to estimate the association between ADHD medication use and completed suicide. The association between specific ADHD medication types and completed suicide was also assessed.

Results

After controlling for potential confounders, no significant association was found between ADHD medication use and completed suicide in the overall sample, in individuals aged 12–24 and 25 to 49 years, and those with a prior ADHD physician diagnosis. No significant differences were found when comparing the use of non-stimulants only (aOR 1.27; 95 % CI: 0.62, 2.63), stimulants and non-stimulants (aOR 1.01; 95 % CI: 0.33, 3.08), and ADHD consultation without medication (aOR 0.94; 95 % CI: 0.69, 1.28) against stimulant-only use.

Conclusion

Both stimulants and non-stimulants were not associated with the risk of completed suicide. These findings can inform clinical decision-making.

导读：ADHD与自杀风险增加有关。本研究的目的是评估ADHD药物使用与自杀之间的关系。方法：这项巢式病例对照研究包括加拿大魁北克12-49岁的个体，诊断为ADHD和/或分配了ADHD药物。2000年至2021年间的自杀病例（n = 472）与5名对照（n = 2360）进行匹配，对照包括出生日期、性别和自杀死亡前至少365天（索引日期）持续的公共药物保险。使用多变量条件逻辑回归来估计ADHD药物使用与自杀之间的关系。还评估了特定ADHD药物类型与自杀之间的关系。结果：在控制了潜在的混杂因素后，在整个样本中，在12-24岁和25 - 49岁的个体中，以及之前有ADHD医生诊断的个体中，没有发现ADHD药物使用与完成自杀之间的显著关联。当只比较非兴奋剂的使用时，没有发现显著差异(aOR 1.27；95% CI: 0.62, 2.63)，兴奋剂和非兴奋剂(aOR 1.01；95% CI: 0.33, 3.08)，以及无药物治疗的ADHD咨询(aOR 0.94；95% CI: 0.69, 1.28)。结论：兴奋剂和非兴奋剂均与自杀风险无关。这些发现可以为临床决策提供参考。

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引用次数: 0

Gaps in psychiatric care before and after the COVID-19 pandemic among patients with depression using electronic health records 使用电子健康记录对 COVID-19 大流行前后的抑郁症患者进行精神病护理的差距。

IF 4.2 2区医学 Q1 PSYCHIATRY

Psychiatry Research

Pub Date : 2025-02-01 DOI: 10.1016/j.psychres.2025.116354

Catherine K. Ettman , Carly Lupton Brantner , Elena Badillo Goicoechea , Priya Dohlman , Grace V. Ringlein , Jason Straub , Sazal Sthapit , Ramin Mojtabai , Stanislav Spivak , Michael Albert , Fernando S. Goes , Elizabeth A. Stuart , Peter P. Zandi

The COVID-19 pandemic caused disruption to health services. It is unclear if there were inequalities in the continuity of mental health care in the years around the COVID-19 pandemic. We used electronic health records (EHR) to detect mental health care gaps of more than six months in psychiatric appointments across demographic and socioeconomic characteristics among patients with depression. The analysis included patients with depression who were seen at one of two mental health clinics every year of 2018, 2019, 2021, and 2022 (n = 783 patients). First, we found that the odds of mental health care gaps significantly decreased in the post-pandemic period (2021–2022) relative to the pre-pandemic period (2018–2019). Second, in the pre-pandemic period, patients who lived in areas in the highest tertile of deprivation had greater odds of gaps in mental health care relative to those in the lowest tertile (aOR: 2.18 [95 % CI: 1.02, 4.68]). Males had higher odds of gaps in care than females in the post-pandemic period (aOR: 2.22 [1.13, 4.37]) and the pooled pre- and post-pandemic study period (aOR: 1.58 [1.04, 2.40]). Third, interactions between patient characteristics and time were not significant, suggesting that the change in the odds of gaps of mental health care before relative to after the COVID-19 pandemic did not differ significantly based on patient characteristics. Overall, gaps in care decreased in the post-pandemic period relative to the pre-pandemic period among almost all patient groups.

COVID-19大流行造成卫生服务中断。目前尚不清楚在COVID-19大流行期间，精神卫生保健的连续性是否存在不平等。我们使用电子健康记录（EHR）来检测抑郁症患者在人口统计学和社会经济特征方面超过6个月的精神科预约的精神卫生保健差距。该分析包括2018年、2019年、2021年和2022年每年在两家心理健康诊所之一就诊的抑郁症患者（n = 783名患者）。首先，我们发现，与大流行前（2018-2019）相比，大流行后（2021-2022）出现精神卫生保健缺口的几率显著下降。其次，在大流行前时期，生活在最贫困地区的患者与生活在最贫困地区的患者相比，在精神卫生保健方面存在差距的几率更大（比值比：2.18 [95% CI: 1.02, 4.68]）。在大流行后时期（aOR: 2.22[1.13, 4.37]）和大流行前后综合研究期间（aOR: 1.58[1.04, 2.40]），男性在护理方面的差距高于女性。第三，患者特征与时间之间的相互作用不显著，这表明在COVID-19大流行之前相对于之后的精神卫生保健差距的赔率变化在患者特征上没有显着差异。总体而言，与大流行前相比，几乎所有患者群体在大流行后期间的护理差距都有所缩小。

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引用次数: 0

Peripheral inflammatory and metabolic markers as potential biomarkers in treatment-resistant schizophrenia: Insights from a Qatari Cohort 外周炎症和代谢标志物作为治疗难治性精神分裂症的潜在生物标志物：来自卡塔尔队列的见解。

IF 4.2 2区医学 Q1 PSYCHIATRY

Psychiatry Research

Pub Date : 2025-02-01 DOI: 10.1016/j.psychres.2024.116307

Mohamed Adil Shah Khoodoruth , Tarteel Hussain , Sami Ouanes , Nuzhah Widaad Chut-kai Khoodoruth , Adel Hmissi , Samuel L. Lachica Jr , Mustafa Nissar Bankur , Abdul Waheed Khan , Mohamad Samir Makki , Yasser Saeed Khan , James Currie , Majid Alabdullah , Farhan Mohammad

Schizophrenia presents significant diagnostic and treatment challenges, particularly in distinguishing between treatment-resistant (TRS) and non-treatment-resistant schizophrenia (NTRS). This cross-sectional study analyzed routine laboratory parameters as potential biomarkers to differentiate TRS, NTRS, and healthy individuals within a Qatari cohort. The study included 31 TRS and 38 NTRS patients diagnosed with schizophrenia, alongside 30 control subjects from the Qatar Biobank. Key measurements included complete blood count, lipid panel, HbA1c, and ferritin levels. Our findings indicated elevated body mass index (BMI) and triglyceride (TG) levels in both patient groups compared to controls. The NTRS group also showed higher HbA1c levels. Variations in inflammatory markers were noted, with the NTRS group exhibiting a higher platelet/lymphocyte ratio (PLR). Multivariate analysis highlighted significant differences in platelet count, mean platelet volume (MPV), TG, HbA1c, BMI, neutrophil/lymphocyte ratio (NLR), monocyte/lymphocyte ratio (MLR), and ferritin among the groups. Linear regression analysis revealed that MLR and clozapine treatment were significantly correlated with the severity of schizophrenia symptoms. The Random Forest model, a supervised machine learning algorithm, efficiently differentiated between cases and controls and between TRS and NTRS, with accuracies of 86.87 % and 88.41 %, respectively. However, removing PANSS scores notably decreased the model's diagnostic effectiveness. These results suggest that accessible peripheral laboratory parameters can serve as useful biomarkers for schizophrenia, potentially aiding in the early identification of TRS, enhancing personalized treatment strategies, and contributing to precision psychiatry. Future longitudinal studies are necessary to confirm these findings and further explore the role of inflammation in schizophrenia pathophysiology and treatment response.

精神分裂症提出了重大的诊断和治疗挑战，特别是在区分治疗耐药（TRS）和非治疗耐药精神分裂症（NTRS）方面。本横断面研究分析了卡塔尔队列中常规实验室参数作为区分TRS、NTRS和健康个体的潜在生物标志物。该研究包括31名被诊断为精神分裂症的TRS和38名NTRS患者，以及来自卡塔尔生物银行的30名对照受试者。主要测量指标包括全血细胞计数、血脂、糖化血红蛋白和铁蛋白水平。我们的研究结果表明，与对照组相比，两组患者的体重指数（BMI）和甘油三酯（TG）水平均有所升高。NTRS组的HbA1c水平也较高。注意到炎症标志物的变化，NTRS组表现出更高的血小板/淋巴细胞比率（PLR）。多因素分析显示各组间血小板计数、平均血小板体积（MPV）、TG、HbA1c、BMI、中性粒细胞/淋巴细胞比值（NLR）、单核细胞/淋巴细胞比值（MLR）和铁蛋白均存在显著差异。线性回归分析显示，MLR和氯氮平治疗与精神分裂症症状严重程度显著相关。随机森林模型是一种有监督的机器学习算法，可以有效地区分病例和对照，TRS和NTRS，准确率分别为86.87%和88.41%。然而，去除PANSS评分显著降低了模型的诊断有效性。这些结果表明，可获得的外围实验室参数可以作为精神分裂症的有用生物标志物，可能有助于早期识别TRS，增强个性化治疗策略，并有助于精确精神病学。未来有必要进行纵向研究来证实这些发现，并进一步探索炎症在精神分裂症病理生理和治疗反应中的作用。

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引用次数: 0

Safety outcomes of ketamine for treatment-resistant depression in clinical settings and development of the ketamine side effect tool-revised (KSET-R) 氯胺酮治疗难治性抑郁症的临床安全性结局和氯胺酮副作用工具修订（KSET-R）的发展。

IF 4.2 2区医学 Q1 PSYCHIATRY

Psychiatry Research

Pub Date : 2025-02-01 DOI: 10.1016/j.psychres.2024.116334

Adam Bayes , Thanh Vinh Cao , Ana Rita Barreiros , Clara Massaneda-Tuneu , Vanessa Dong , Nicollette Thornton , Nicholas Glozier , Laura Beesley , Dalia Moreno , Verònica Gálvez-Ortiz , Brooke Short , Donel Martin , Colleen Loo

Background

Ketamine and its derivates (e.g. esketamine) are increasingly used in clinical settings for treatment-resistant depression (TRD). Ketamine can give rise to acute, cumulative and longer-term side effects (SEs) across a treatment course. The Ketamine Side Effect Tool (KSET) examines adverse effects though its length has affected feasibility for use in clinical settings.

Objective

To estimate the frequency of ketamine SEs occurring in real-world settings using the KSET, additional validated scales and laboratory measures. Utilising this naturalistic data, to develop a shorter, more feasible and validated tool (KSET-Revised; KSET-R).

Methods

Retrospective patient and safety data from three outpatient services were collected which included KSET symptom questions, standardised scales and laboratory measures. We calculated frequency of SEs occurring intra-session, intersession and at follow-up. Revision of the KSET included removal of items based on a priori criteria. Construct and concurrent validity were examined by comparison of specific KSET items and the overall tolerability rating with standardised scales.

Results

Descriptive statistics including SE frequencies are reported and the KSET-R is detailed: a shorter tool with construct and concurrent validity for specific items, along with the overall tolerability rating.

Limitations

small sample size for follow-up data; predominantly subcutaneous racemic and intranasal esketamine analysed - other routes and formulations not examined; and subjective not objective cognition measured.

Conclusions

Naturalistic data gives an estimate of frequency of ketamine SEs within session, between sessions and at follow-up. The KSET-R has improved feasibility and clinical utility and is recommended for use in clinical practice where ketamine is prescribed.

背景：氯胺酮及其衍生物（如艾氯胺酮）越来越多地用于临床治疗难治性抑郁症（TRD）。氯胺酮在整个治疗过程中会产生急性、累积和长期的副作用（se）。氯胺酮副作用工具（KSET）检查不良反应，尽管其长度影响了在临床环境中使用的可行性。目的：利用KSET、额外的有效量表和实验室测量来估计氯胺酮se在现实环境中发生的频率。利用这些自然数据，开发一种更短、更可行和更有效的工具(KSET-Revised；KSET-R)。方法：回顾性收集三个门诊的患者和安全性数据，包括KSET症状问题、标准化量表和实验室测量。我们计算了会话内、会话间和随访时SEs发生的频率。KSET的修订包括根据先验标准删除项目。通过比较特定的KSET项目和标准化量表的总体耐受性评分来检验结构效度和并发效度。结果：描述性统计包括SE频率的报告和详细的KSET-R：一个较短的工具，具有特定项目的结构和并发效度，以及总体耐受性评级。局限性：随访资料样本量小；主要分析皮下消旋和鼻内艾氯胺酮——其他途径和配方未检查；主观认知而非客观认知。结论：自然数据给出了治疗期间、治疗之间和随访时氯胺酮se的频率估计。KSET-R提高了可行性和临床效用，建议在开氯胺酮处方的临床实践中使用。

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引用次数: 0

Association between autism diagnosis rates and adolescent depression: A population-based study in Sweden 自闭症诊断率与青少年抑郁症之间的关系：瑞典的一项基于人群的研究。

IF 4.2 2区医学 Q1 PSYCHIATRY

Psychiatry Research

Pub Date : 2025-02-01 DOI: 10.1016/j.psychres.2024.116341

Adrian E. Desai Boström , Peter Andersson , Lee E. Wachtel , Håkan Jarbin , Jussi Jokinen , Johan Lundberg

Introduction

The association between increasing diagnosis rates of autism-related disorders (ASD-R) in Swedish regions and diagnosis rates of major depressive disorders (MDD) in adolescents remains unexplored.

Methods

Following STROBE guidelines, this pre-registered (https://osf.io/duvq7) observational study, utilizing registry data from 2008 to 2022 across the 21 Swedish regions, employed a generalized linear mixed model (GLMM) to analyze the association between ASD-R (ICD-10: F84) and MDD diagnosis rates (ICD-10: F32) in 15–19 year olds, with registered primary diagnoses considered. The GLMM included psychiatric care affiliation rates (PCAR) as fixed effects and variations across years and regions as random intercepts. The model incorporated bipolar disorder (BD) rates and the male-to-female ratio of ASD-R diagnoses when justified. Separate models were created for combined sexes, males, and females.

Results

A significant inverse relationship was observed between ASD-R and MDD diagnosis rates across all sex groups. In the combined-sex model, the mean ratio was 0.40 (P = 0.003), while the sex-specific models showed ratios of 0.28 for males (P < 0.001) and 0.37 for females (P = 0.017). All ratios were significantly below 1, indicating a negative association between ASD-R and MDD diagnosis rates.

Conclusions

The study's observational nature limits causal inferences, but findings reveal that higher primary diagnosis rates of ASD-R correlate with lower primary diagnosis rates of MDD in adolescents of both sexes, although more pronounced in males. These results highlight the importance of further research on the relationship between ASD-R and MDD diagnosis rates, emphasizing the need for prospective, longitudinal, and individualized register data that include both primary and co-diagnoses.

瑞典地区自闭症相关障碍（ASD-R）诊断率上升与青少年重度抑郁症（MDD）诊断率之间的关系仍未得到研究。方法：遵循STROBE指南，这项预注册（https://osf.io/duvq7）观察性研究，利用2008年至2022年瑞典21个地区的注册数据，采用广义线性混合模型（GLMM）分析15-19岁儿童ASD-R （ICD-10: F84）和MDD诊断率（ICD-10: F32）之间的关系，并考虑已登记的原发性诊断。GLMM将精神科护理隶属率（PCAR）作为固定效应，将不同年份和地区的变化作为随机截距。该模型结合了双相情感障碍（BD）的发病率和男性与女性的ASD-R诊断比例。分别为男女组合创建了不同的模型。结果：在所有性别组中，ASD-R和MDD诊断率呈显著负相关。在混合性别模型中，平均比率为0.40 (P = 0.003)，而性别特异性模型显示男性的比率为0.28 (P < 0.001)，女性的比率为0.37 （P = 0.017）。所有比值均显著低于1，表明ASD-R与MDD诊断率呈负相关。结论：该研究的观察性质限制了因果推断，但研究结果显示，在男女青少年中，较高的ASD-R初级诊断率与较低的MDD初级诊断率相关，尽管在男性中更为明显。这些结果强调了进一步研究ASD-R和MDD诊断率之间关系的重要性，强调需要前瞻性、纵向和个性化的登记数据，包括原发性和合并诊断。

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引用次数: 0

Multilayer network instability underlying persistent auditory verbal hallucinations in schizophrenia 精神分裂症患者持续性听觉言语幻觉的多层网络不稳定性。

IF 4.2 2区医学 Q1 PSYCHIATRY

Psychiatry Research

Pub Date : 2025-02-01 DOI: 10.1016/j.psychres.2024.116351

Jinguang Li , Jingqi He , Honghong Ren , Zongchang Li , Xiaoqian Ma , Liu Yuan , Lijun Ouyang , Chunwang Li , Xiaogang Chen , Ying He , Jinsong Tang

Background

Auditory verbal hallucinations (AVHs) in schizophrenia (SCZ) are linked to brain network abnormalities. Resting-state fMRI studies often assume stable networks during scans, yet dynamic changes related to AVHs are not well understood.

Methods

We analyzed resting-state fMRI data from 60 SCZ patients with persistent AVHs (p-AVHs), 39 SCZ patients without AVHs (n-AVHs), and 59 healthy controls (HCs), matched for demographics. Using graph theory, we constructed a time-varying modular structure of brain networks, focusing on multilayer modularity. Network switching rates at global, subnetwork, and nodal levels were compared across groups and related to AVH severity.

Results

SCZ groups had higher switching rates in the subcortical network compared to HCs. Increased switching was found in two thalamic nodes for both patient groups. The p-AVH group showed lower switching rates in the default mode network (DMN) and two superior frontal gyrus nodes compared to HC and n-AVH groups. DMN switching rates negatively correlated with AVH severity in the p-AVH group.

Conclusions

Dynamic changes in brain networks, especially lower DMN and frontal region switching rates, may contribute to the development and persistence of AVHs in SCZ.

背景：精神分裂症（SCZ）患者的言语幻听（AVHs）与大脑网络异常有关。静息状态fMRI研究通常假设扫描期间的网络稳定，但与avh相关的动态变化尚未得到很好的理解。方法：我们分析了60例伴有持续性AVHs （p-AVHs）的SCZ患者、39例无AVHs （n-AVHs）的SCZ患者和59例健康对照（hc）的静息状态fMRI数据，这些数据在人口统计学上是匹配的。利用图论构造了一个时变的脑网络模块结构，重点研究了多层模块结构。在全局、子网和节点水平上比较各组之间的网络切换率，并与AVH严重程度相关。结果：与hc组相比，SCZ组皮质下网络的转换率更高。两组患者均发现两个丘脑节点的开关增加。与HC和n-AVH组相比，p-AVH组在默认模式网络（DMN）和两个额上回节点的切换率较低。在p-AVH组，DMN转换率与AVH严重程度呈负相关。结论：脑网络的动态变化，特别是DMN和额叶区转换率的降低，可能是SCZ中AVHs发生和持续的原因。

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引用次数: 0

Alcohol and substance use differentially impact suicidal ideation in a longitudinal cohort of bipolar disorder 在双相情感障碍纵向队列中，酒精和物质使用对自杀意念的影响存在差异。

IF 4.2 2区医学 Q1 PSYCHIATRY

Psychiatry Research

Pub Date : 2025-02-01 DOI: 10.1016/j.psychres.2025.116357

Julia L. Smith, Melvin G. McInnis, Sarah H. Sperry

Background

Across bipolar disorders (BSDs), alcohol and substance use and suicidal ideation (SI) contribute to increased rates of morbidity and mortality. The goal of the present study was to investigate temporal relationships between the intensity/frequency (I/F) of use and impairment related to alcohol and substance use and SI in a longitudinal BSD cohort.

Methods

Participants with BDI (n=565), BDII (n=162), and BD NOS (n=61) were included (median enrollment=72 months). Alcohol and substance use were measured using a modified version of the AUDIT administered every 6 months. SI was measured every 2 months using item 9 from the PHQ-9. Linear mixed effects models tested concurrent associations and Dynamic Structural Equation Models tested prospective associations between alcohol and substance use I/F and impairment with SI.

Results

Cocaine I/F and alcohol and substance use impairment were concurrently associated with SI. When a person had more frequent and intense cannabis use compared to average, they had higher SI at the next timepoint. When individuals experienced more alcohol and substance use impairment than average, they had higher SI at the next timepoint.

Conclusions

I/F of cannabis use and alcohol and substance use impairment appear to lead to future increases in SI for those with BSDs.

背景：在双相情感障碍（bsd）中，酒精和物质使用以及自杀意念（SI）导致发病率和死亡率增加。本研究的目的是在纵向BSD队列中调查使用强度/频率（I/F）与酒精和物质使用和SI相关的损害之间的时间关系。方法：纳入BDI （n=565）、BDII （n=162）和bdnos （n=61）患者（中位入组时间为72个月）。使用每6个月一次的修订版审计来测量酒精和物质使用情况。使用PHQ-9中的第9项每2个月测量一次SI。线性混合效应模型测试了并发关联，动态结构方程模型测试了酒精和物质使用I/F和SI损伤之间的前瞻性关联。结果：可卡因I/F、酒精和物质使用障碍与SI同时相关。当一个人使用大麻的频率和强度高于平均水平时，他们在下一个时间点的SI更高。当个体经历比平均水平更多的酒精和物质使用障碍时，他们在下一个时间点的SI更高。结论：大麻使用、酒精和物质使用障碍的I/F似乎会导致bsd患者未来SI的增加。

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引用次数: 0

SARS-CoV-2 infection and COVID-19 outcomes across mental disorders and the role of sex: A register-based study from Catalonia 精神障碍中的SARS-CoV-2感染和COVID-19结果以及性别的作用：来自加泰罗尼亚的一项基于登记册的研究

IF 4.2 2区医学 Q1 PSYCHIATRY

Psychiatry Research

Pub Date : 2025-02-01 DOI: 10.1016/j.psychres.2024.116325

Anna Monistrol-Mula , Iago Giné-Vázquez , Giulia Caggiu , Claudia Conflitti , Katalin Gemes , Irwin Hecker , Roberto Mediavilla , Matteo Monzio Compagnoni , Irene Pinucci , Jutta Stoffers-Winterling , Anke B. Witteveen , Pierre Smith , Henrik Walter , Jose Luis Ayuso-Mateos , Maria Melchior , Ellenor Mittendorfer-Rutz , Marit Sijbrandij , Josep Maria Haro , Mireia Felez-Nobrega

Introduction

This study investigated the risk of SARS-CoV-2 infection and severe COVID-19 outcomes among different mental health diagnoses and the role of sex in these associations.

Methods

Using electronic records from Catalonia, we identified adults receiving mental health care from 2017–2019 with diagnoses of non-affective psychosis (NAP), bipolar disorder (BD), depressive disorder (DEP), stress-related disorders, neurotic/somatoform disorders (NSD), and substance misuse (SUB) (exposed). The outcomes assessed were SARS-CoV-2 infection, COVID-19 hospitalization, and COVID-19-related death, compared to matched individuals without these mental disorders (unexposed). Adjusted logistic regression analyses were conducted.

Results

785,378 adults were included (70.3% < 65 years old; 57.1% women). Compared to unexposed, those with NAP, BD, DEP, and SUB had a lower risk of SARS-CoV-2 infection, while those with NSD had an increased risk. Infected individuals with DEP, NSD, and SUB had a lower risk of hospitalization but a higher risk of COVID-19-related death. Higher COVID-19-related death was also observed in individuals with NAP and BD. Sex-stratified analysis revealed that women with NSD were especially vulnerable to infection, and women with DEP and NSD had a higher risk of COVID-19-related death.

Conclusions

These findings emphasize the need for tailored public health strategies to reduce excess mortality risk among individuals with certain mental disorders, while accounting for sex differences.

前言：本研究调查了不同心理健康诊断中SARS-CoV-2感染风险和严重COVID-19结局的关系，以及性别在这些关联中的作用。方法：使用来自加泰罗尼亚的电子记录，我们确定了2017-2019年接受精神卫生保健的成年人，诊断为非情感性精神病（NAP）、双相情感障碍（BD）、抑郁症（DEP）、压力相关障碍、神经症/躯体形式障碍（NSD）和物质滥用（SUB）（暴露）。评估的结果是与没有这些精神障碍的匹配个体（未暴露）相比，SARS-CoV-2感染、COVID-19住院和COVID-19相关死亡。进行调整后的logistic回归分析。结果：纳入785,378名成人(70.3% < 65岁；57.1%的女性)。与未暴露者相比，NAP、BD、DEP和SUB患者感染SARS-CoV-2的风险较低，而NSD患者的风险较高。DEP、NSD和SUB感染者住院的风险较低，但与covid -19相关的死亡风险较高。NAP和BD患者的covid -19相关死亡率也较高。性别分层分析显示，患有NSD的女性特别容易受到感染，而患有DEP和NSD的女性与covid -19相关死亡的风险更高。结论：这些发现强调，在考虑性别差异的同时，需要制定量身定制的公共卫生策略，以降低某些精神障碍患者的超额死亡风险。

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引用次数: 0