Patients with fibromyalgia display two different clinical profiles based on their GABAergic EEG markers: Preliminary results

可视模拟标度 焦虑 纤维肌痛 脑电图 神经病理性疼痛 萧条(经济学) 医学 伤害 心情 病态的 慢性疼痛 内科学 听力学 物理疗法 物理医学与康复 心理学 麻醉 精神科 受体 经济 宏观经济学
作者
Christian Mancini,Corentin A. Wicht,Michaël Mouthon,Stephan J. Goetz,Joëlle Nsimire Chabwine
出处
期刊:Journal of the Neurological Sciences [Elsevier BV]
卷期号:405: 92-92
标识
DOI:10.1016/j.jns.2019.10.390
摘要

Mechanisms undelying chronic pain in fibromyalgia are still unknown and most treatments remain unsuccessful. A neurotransmission-based approach could contribute to further understand this disease and better tailor therapeutic strategies. Previous data showed decreased GABAergic electroencephalographic (EEG) markers correlated chronic neuropathic pain intensity. This study measured β global spectral power (GPS) as a GABAergic marker, using a 20-minute high-density (64 electrodes, BIOSEMI) resting-state EEG recording, in addition to pain intensity and components (Visual Analog Scale (VAS)/10, emotional and sensory items of the MacGill Pain Questionnaire Short-Form (MPQe and MPQs)/10), and mood disturbance (anxiety and depression scores of the Hospital Anxiety and Depression (HAD) scale (HADa and HADd)) in 7 fibromyalgia patients (FibroP, ~60 y, females). Data analysis was perfomed using MATLAB and SPSS (mean(SD)). Two distinct groups emerged from EEG data: G1, similar to previous data (n=3), displayed two β peaks (16 Hz, -2.6 (4) dB and 25 Hz, -5.8(1.1) dB) whereas G2 (n=4) showed one unique peak (20 Hz, (-4.7(4.1) dB). Pain and mood scores tent to be worse in G2 than in G1: higher VAS (7.1(0.9) vs 2.8(2.5)), MPQe (6 (2.8) vs 1.5(0.4)) and MPQs (6.6(0.9) vs 2.9(0.4)); pathological HADd (11.8(2.8) vs 5(5)) and HADa (8.5(3) vs 5 (5)), higher neuropathic component (DN4=8(0) vs 3(1)). Overall, G2 FibroP display more pathological clinical conditions than G1 coinciding with more remarkable (so far qualitative) changes in GABAergic neurotransmission. These preliminary data, if confirmed, suggest GABAergic markers as potential criterion for differenciation between sub-classes of FibroP with potential use for analgesic strategies.
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