The network structure of core depressive symptom-domains in major depressive disorder following antidepressant treatment: a randomized clinical trial

重性抑郁障碍 依西酞普兰 精神病理学 心情 心理学 抗抑郁药 随机对照试验 临床心理学 精神科 医学 内科学 焦虑
作者
Marcelo T. Berlim,Stéphane Richard‐Devantoy,Nicole Rodrigues dos Santos,Gustavo Turecki
出处
期刊:Psychological Medicine [Cambridge University Press]
卷期号:51 (14): 2399-2413 被引量:62
标识
DOI:10.1017/s0033291720001002
摘要

BACKGROUND: Network analysis (NA) conceptualizes psychiatric disorders as complex dynamic systems of mutually interacting symptoms. Major depressive disorder (MDD) is a heterogeneous clinical condition, and very few studies to date have assessed putative changes in its psychopathological network structure in response to antidepressant (AD) treatment. METHODS: In this randomized trial with adult depressed outpatients (n = 151), we estimated Gaussian graphical models among nine core MDD symptom-domains before and after 8 weeks of treatment with either escitalopram or desvenlafaxine. Networks were examined with the measures of cross-sectional and longitudinal structure and connectivity, centrality and predictability as well as stability and accuracy. RESULTS: At baseline, the most connected MDD symptom-domains were fatigue-cognitive disturbance, whereas at week 8 they were depressed mood-suicidality. Overall, the most central MDD symptom-domains at baseline and week 8 were, respectively, fatigue and depressed mood; in contrast, the most peripheral symptom-domain across both timepoints was appetite/weight disturbance. Furthermore, the psychopathological network at week 8 was significantly more interconnected than at baseline, and they were also structurally dissimilar. CONCLUSION: Our findings highlight the utility of focusing on the dynamic interaction between depressive symptoms to better understand how the treatment with ADs unfolds over time. In addition, depressed mood, fatigue, and cognitive/psychomotor disturbance seem to be central MDD symptoms that may be viable targets for novel, focused therapeutic interventions.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
内向的冬易的应助被yy采纳,获得10
刚刚
QII关注了科研通微信公众号
刚刚
cyu发布了新的文献求助10
刚刚
鲤鱼一一完成签到,获得积分10
1秒前
masirui的应助被珊珊采纳,获得10
1秒前
小张完成签到,获得积分10
1秒前
天天快乐的应助被LC采纳,获得10
1秒前
pear完成签到,获得积分10
2秒前
2秒前
3秒前
吴佳鑫完成签到,获得积分10
3秒前
Patrick完成签到,获得积分10
3秒前
3秒前
3秒前
追寻澜完成签到,获得积分10
3秒前
长弓诘完成签到 ,获得积分10
4秒前
xiaoju完成签到,获得积分20
4秒前
wcp完成签到,获得积分10
4秒前
Garrett完成签到 ,获得积分10
4秒前
于湘完成签到,获得积分10
4秒前
sxqt完成签到,获得积分10
5秒前
HC发布了新的文献求助10
6秒前
无尽夏完成签到,获得积分10
6秒前
6秒前
蓝天的应助被酷炫的致远采纳,获得10
7秒前
zhangz完成签到,获得积分10
7秒前
7秒前
自由123完成签到,获得积分10
8秒前
阔达的海完成签到,获得积分10
8秒前
8秒前
冤家Gg完成签到,获得积分10
9秒前
JinFFyy完成签到,获得积分10
9秒前
正直的的白羊完成签到 ,获得积分10
9秒前
狸追完成签到,获得积分10
9秒前
伊瑟儿的应助被木木采纳,获得10
9秒前
10秒前
英姑的应助被谢张璞采纳,获得10
10秒前
10秒前
等待的小笼包完成签到,获得积分10
10秒前
corn发布了新的文献求助10
11秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Encyclopedia of Modern Artificial Intelligence 1000
Особенности технологий и методов информационно-психологических войн СССР с Великобританией и США в период 1939-1953 гг 1000
Das Matthäusevangelium: Kapitel 1:1–17 1000
IRTSD: Open-Source Data and Toolset for Electromagnetic Transient Analysis of Disturbances and IBR Control Malfunctions in Transmission Systems 1000
Challenging Attachment Theory 600
Analyses de reconnaissances de dettes passées devant les échevins d'Ypres (1249-1291) 600
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 工程类 有机化学 化学工程 生物化学 物理 复合材料 内科学 催化作用 光电子学 人工智能 细胞生物学 无机化学 物理化学 数学
热门帖子
关注 科研通微信公众号,转发送积分 8136921
求助须知:如何正确求助?哪些是违规求助? 9537941
关于积分的说明 21626827
捐赠科研通 7720678
什么是DOI,文献DOI怎么找? 3420109
关于科研通互助平台的介绍 2545494
邀请新用户注册赠送积分活动 2461921