(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]
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
利莫里亚发布了新的文献求助10
刚刚
刚刚
1秒前
量子星尘发布了新的文献求助10
1秒前
田様应助路途采纳,获得10
1秒前
1秒前
量子星尘发布了新的文献求助10
2秒前
苹果完成签到 ,获得积分10
4秒前
乐乐发布了新的文献求助10
5秒前
李健应助流水不争先采纳,获得10
5秒前
6秒前
6秒前
陆登完成签到 ,获得积分20
7秒前
7秒前
8秒前
10秒前
10秒前
无花果应助呆萌听兰采纳,获得10
12秒前
12秒前
13秒前
我是老大应助李嘉诚采纳,获得10
14秒前
何海发布了新的文献求助10
14秒前
15秒前
量子星尘发布了新的文献求助10
15秒前
上官若男应助霸气的思柔采纳,获得10
16秒前
16秒前
小徐要上学完成签到,获得积分10
16秒前
彬彬发布了新的文献求助10
17秒前
bsf123完成签到,获得积分10
19秒前
云阿柔发布了新的文献求助10
19秒前
jjkktt发布了新的文献求助10
19秒前
19秒前
无限豪英发布了新的文献求助10
20秒前
lin完成签到 ,获得积分10
20秒前
00928完成签到,获得积分10
20秒前
123完成签到,获得积分10
21秒前
22秒前
雪白微笑发布了新的文献求助10
22秒前
23秒前
酷炫的蓝关注了科研通微信公众号
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
Binary Alloy Phase Diagrams, 2nd Edition 8000
Comprehensive Methanol Science Production, Applications, and Emerging Technologies 2000
Building Quantum Computers 800
Translanguaging in Action in English-Medium Classrooms: A Resource Book for Teachers 700
Exosomes Pipeline Insight, 2025 500
Red Book: 2024–2027 Report of the Committee on Infectious Diseases 500
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5656283
求助须知:如何正确求助?哪些是违规求助? 4802765
关于积分的说明 15075386
捐赠科研通 4814578
什么是DOI,文献DOI怎么找? 2575843
邀请新用户注册赠送积分活动 1531182
关于科研通互助平台的介绍 1489776