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Neurologic Signatures of Chronic Pain Disorders

Neurologic Signatures of Chronic Pain Disorders

Status
Completed
Phases
Phase 4
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT02747940
Enrollment
200
Registered
2016-04-22
Start date
2015-12-31
Completion date
Unknown
Last updated
2020-11-02

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Chronic Migraine, Chronic Pain, Fibromyalgia

Brief summary

Brain signatures as objective measures of acute pain have been characterized with functional magnetic resonance image and machine learning technology. As compared to acute pain, chronic pain leads to greater socioeconomic burden. However, measures for chronic pain remain subjective and suboptimal, and the brain signatures for chronic pain are largely unknown. Chronic migraine and fibromyalgia are two prototypes primary chronic pain disorders with high disability and intractability with prevalence of around 2% for both diseases. These two chronic pain disorders have shared clinical presentations (abnormal pain sensitivity, mood and sleep disorders), pathophysiology (central sensitization) and medical treatment (anti-depressants), despite different body parts are involved (head vs. whole body). The present integrated project aims to characterize both common and disease-specific brain signatures of chronic pain by investigating these two chronic pain disorders. Our findings may shed some light on the key mechanisms of pain chronification, and may pave the way for the optimization of diagnosis and prognostication, as well as formulation of personalized medicine in chronic pain, so as to improve life quality of these patients and to reduce socioeconomic loss. The present project includes three interdisciplinary sub-projects (plus one animal study, not listed here): A: Clinical studies for chronic migraine and fibromyalgia: endophenotypes and pain chronification B: Functional neuroimaging of chronic pain: multimodal quantitative analysis of brain connectomes C. Data stream mining technology for multimodal physiological signals of chronic pain: real-time tracking and clinical correlation The specific aims of the present projects include: 1. Identification of common and disease-specific brain signatures for chronic pain (sub-projects A, B, C) 2. Investigation of clinical indicators with predictive values by machine learning analysis of big data (sub-projects A, B, C) 3. Elucidation of the specific anatomical structures or neural networks underpinning pain chronification based on clinical neuroimaging (sub-projects A, B) In this 1st-year pilot study of the 4-year longitudinal study, we will establish experimental platforms for each sub-project, start to recruit participants and perform endophenotyping, as well as have a preliminary integration for sub-projects A, B and C.

Interventions

DRUGflunarizine and/or pregabalin

Sponsors

Ministry of Science and Technology of the People´s Republic of China
CollaboratorOTHER_GOV
Taipei Veterans General Hospital, Taiwan
Lead SponsorOTHER_GOV

Study design

Allocation
NON_RANDOMIZED
Intervention model
PARALLEL
Primary purpose
BASIC_SCIENCE
Masking
NONE

Eligibility

Sex/Gender
ALL
Age
20 Years to 70 Years
Healthy volunteers
Yes

Inclusion criteria

* Control: devoid of any systemic or neurological diseases * Chronic migraine: by ICHD-III (International Classification of Headache Disorder) criteria * Fibromyalgia: by ACR (American College of Rheumatology) 2010 criteria

Exclusion criteria

* history of major systemic illness, including uncontrolled hypertension, diabetes, chronic renal insufficiency, autoimmune diseases or malignancies * history of neurological disorders which might affect sensation such as previous stroke or peripheral neuropathy * history of substance abuse (except painkillers) * heavy smokers (with a daily consumption \>20 cigarettes) * pregnancy or lactation * any contraindication for magnetic resonance imaging (MRI) * and any obvious infection or inflammation over a period of at least 1 month before the study.

Design outcomes

Primary

MeasureTime frameDescription
clinical improvement after treatment (1) headache/pain intensity [NRS, numeric rating scale]4 monthsclinical improvement (headache/pain intensity) after treatment unit: NRS (numeric rating scale, 0-10) analysis: comparing the mean headache/pain intensity in each month after treatment (M1/M2/M3/M4) to that before treatment (M-1)
clinical improvement after treatment (2) headache/pain frequency [attacks per month]4 monthsclinical improvement (headache/pain frequency) after treatment unit: attacks per month analysis: comparing the mean headache/pain frequency in each month after treatment (M1/M2/M3/M4) to that before treatment (M-1)
clinical improvement after treatment (3) headache/pain duration [hours per day]4 monthsclinical improvement (headache/pain duration) after treatment unit: hours/day analysis: comparing the mean headache/pain duration (hours/day) in each month after treatment (M1/M2/M3/M4) to that before treatment (M-1)

Secondary

MeasureTime frameDescription
EEG change after treatment4 monthsLinear and nonlinear analysis of EEG before and after treatment * Three EEG session will be arranged. The first one is done before treatment, and the 2nd/3rd one will be done after a 2-month/4-month treatment course, respectively. * The EEG analyses include linear (eg: power spectrum, coherence, functional connectivity) analyses as well as non-linear (eg: entropy) analyses.
sensory and pain threshold change after treatment2 monthsUsing quantitative sensory testing (QST) to evaluate the sensory and pain threshold before and after treatment * Three QST session will be arranged. The first one is done before treatment, and the 2nd/3rd one will be done after a 2-month/4-month treatment course, respectively. * Equipment: electric von Fray filaments * unit: gram
Autonomic function change after treatment2 monthsUsing heart rate variability (HRV) to evaluate autonomic function before and after treatment * Three HRV session will be arranged. The first one is done before treatment, and the 2nd/3rd one will be done after a 2-month/4-month treatment course, respectively. * The HRV analyses include time-domain (eg: mean heart rate and its variation, mean R-R interval and its variation), and also frequency domain analysis (eg: power spectrum)

Countries

Taiwan

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 25, 2026