(264) Altered Brain Network Topology in Chronic Low Back Pain Patients on Prescription Opioid Analgesics

医学 慢性疼痛 类阿片 药方 麻醉 拓扑(电路) 物理疗法 药理学 内科学 受体 数学 组合数学
作者
Behnaz Jarrahi,Sean Mackey
出处
期刊:The Journal of Pain [Elsevier BV]
卷期号:20 (4): S40-S40
标识
DOI:10.1016/j.jpain.2019.01.186
摘要

Opioid prescribing for chronic pain conditions such as Chronic Low Back Pain (CLBP) in the United States has increased substantially in the past two decades. However, the effects of opioid analgesics on the brain network topology in CLBP remains unknown. The present study therefore provides the first test of the hypothesis that opioid status impacts the activity of the whole-brain network using graph theory methods. Resting state fMRI data were collected on a 3T scanner from 10 CLBP patients on long-term opioid regimens (CLBP+; 5 males, mean age ± SD = 48.5 ± 14.8 years) and 10 matched opioid-naive CLBP patients (CLBP-, 5 males, mean age ± SD = 43.6 ± 12.6 years) according to a protocol approved by the Stanford IRB. Following image quality assurance in MRIQC, and preprocessing in SPM12, we performed graph theoretical network analysis using CONN toolbox. For each participant, global network efficiency — a graph theory measure for integrative capacity of complex systems, was calculated and correlated with individual differences in sensory pain scores from Short Form McGill Pain Questionnaire (SF-MPQ). We focused on global efficiency as it reflects effective information transfer (i.e., small-worldness) within a network of nodes (i.e., regions of interests) and edges (i.e., correlation). Results revealed that the global efficiency values were positively correlated with pain in CLBP- but not in CLBP+ (r = 0.49 vs r = - 0.06, p = 0.05). This suggests that as sensory dimension of the pain intensity increased, CLBP- exhibited more efficient information transfer across a network of brain regions, including the core nodes of the salience network (anterior insula), frontoparietal central executive network (dorsolateral prefrontal cortices), and bilateral sensorimotor networks. Follow up studies with larger sample size are required to corroborate these observations and to formulate appropriate strategies for opioid prescribing guidelines, accordingly. Supported by NIH P01AT006651, and NIH T32DA035165.

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
汝桢发布了新的文献求助10
刚刚
万能图书馆应助thezwt采纳,获得10
1秒前
zengji完成签到,获得积分10
1秒前
reck发布了新的文献求助10
2秒前
诚心的水杯完成签到 ,获得积分10
2秒前
3秒前
ZOE应助ying777采纳,获得30
4秒前
小蘑菇应助ybk666采纳,获得10
4秒前
Tk完成签到,获得积分20
5秒前
我服有点黑完成签到,获得积分10
5秒前
烟雨江南完成签到,获得积分10
5秒前
zyj发布了新的文献求助10
5秒前
阔达的傲芙完成签到,获得积分10
7秒前
RT完成签到,获得积分10
7秒前
河里的星发布了新的文献求助10
8秒前
ying777完成签到,获得积分10
8秒前
8秒前
9秒前
10秒前
清秀的凌柏完成签到,获得积分20
10秒前
642463016完成签到,获得积分10
11秒前
打打应助oliverrrr采纳,获得10
12秒前
12秒前
eternity136发布了新的文献求助10
12秒前
愤怒的树叶完成签到,获得积分10
12秒前
lli完成签到,获得积分10
13秒前
小马甲应助hhha采纳,获得10
14秒前
正直听白发布了新的文献求助10
14秒前
15秒前
太阳当空照完成签到,获得积分10
15秒前
ybk666发布了新的文献求助10
15秒前
鲤鱼羊完成签到,获得积分10
16秒前
Jundy发布了新的文献求助10
17秒前
20秒前
asdfghjkl发布了新的文献求助10
20秒前
上官若男应助河里的星采纳,获得10
20秒前
黎明前完成签到,获得积分10
21秒前
21秒前
23秒前
24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
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
Picture this! Including first nations fiction picture books in school library collections 1500
Instituting Science: The Cultural Production of Scientific Disciplines 666
Signals, Systems, and Signal Processing 610
The Organization of knowledge in modern America, 1860-1920 / 600
Unlocking Chemical Thinking: Reimagining Chemistry Teaching and Learning 555
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6360136
求助须知:如何正确求助?哪些是违规求助? 8174206
关于积分的说明 17216738
捐赠科研通 5414961
什么是DOI,文献DOI怎么找? 2865731
邀请新用户注册赠送积分活动 1843049
关于科研通互助平台的介绍 1691244