Chronic Pain Clinical Trial
Official title:
Neurologic Signatures of Chronic Pain Disorders
NCT number | NCT02747940 |
Other study ID # | 2015-10-001BC2015-11-001AC002B |
Secondary ID | |
Status | Completed |
Phase | Phase 4 |
First received | |
Last updated | |
Start date | December 2015 |
Verified date | October 2020 |
Source | Taipei Veterans General Hospital, Taiwan |
Contact | n/a |
Is FDA regulated | No |
Health authority | |
Study type | Interventional |
"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.
Status | Completed |
Enrollment | 200 |
Est. completion date | |
Est. primary completion date | December 2019 |
Accepts healthy volunteers | Accepts Healthy Volunteers |
Gender | All |
Age group | 20 Years to 70 Years |
Eligibility | 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. |
Country | Name | City | State |
---|---|---|---|
Taiwan | Headache Center, Teipei Veterans General Hospital | Taipei |
Lead Sponsor | Collaborator |
---|---|
Taipei Veterans General Hospital, Taiwan | Ministry of Science and Technology, R.O.C. |
Taiwan,
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | clinical improvement after treatment (1) headache/pain intensity [NRS, numeric rating scale] | clinical 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) | 4 months | |
Primary | clinical improvement after treatment (2) headache/pain frequency [attacks per month] | clinical 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) | 4 months | |
Primary | clinical improvement after treatment (3) headache/pain duration [hours per day] | clinical 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) | 4 months | |
Secondary | EEG change after treatment | Linear 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. |
4 months | |
Secondary | sensory and pain threshold change after treatment | Using 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 |
2 months | |
Secondary | Autonomic function change after treatment | Using 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) |
2 months |
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