Clinical Trial: Specific Neck Rehabilitation for Unilateral Neck Related Headache and Structural Changes in the Brain

Study Status: Recruiting
Recruit Status: Recruiting
Study Type: Interventional

Official Title: Efficacy of Specific Neck Rehabilitation on Unilateral Neck Related Headache, and Structural Changes of Cerebral Gray and White Matter

Brief Summary: In part 1 of the project clinical efficacy of specific neck rehabilitation will be compared with standard primary health care among patients with cervicogenic headache and study whether fear avoidance beliefs and self-efficacy predict long term neck function and headache frequency superior to active range of neck movement. Part 2 will investigate whether patients with cervicogenic headache have changes in cerebral grey and white matter and in connectivity of the resting state state network, whether these are reversed after effective neck rehabilitation, and correlate to symptom severity and degree of disability.

Detailed Summary:

The project includes two parts:

Part 1: With a longitudinal semicross-over randomized control design (n: 42) the investigators will compare the clinical efficacy of a 6 month specific neck rehabilitation with standard primary health care on patients with cervicogenic headache. The patients will either receive a specific neck rehabilitation program, or 6 month standard primary health care before they cross over to neck rehabilitation.

Sociodemographic and clinical characteristics will be collected before each treatment session and 6 and 12 months later. Whether self-efficacy and fear avoidance beliefs predict 12 month self-reported neck function and headache frequency superior to the active range of neck movement will further be studied.

Part 2: With a non-randomized comparative design the investigators will explore whether there are changes in the cerebral grey and white matter volume and structure measured by volumetric MRi and diffusion tensor imaging (DTI), and whether cerebral connectivity within the default mode network (DMN) are significantly different between patients with cervicogenic headache and healthy controls. Cerebral connectivity will be measured by resting state fMRI (RS-fMRI). Whether the anticipated cerebral changes in volume, structure and connectivity are reversed after specific neck rehabilitation will be tested, and whether these changes correlate to symptom severity and degree of disability

Analyses of MRI scans and clinical characteristics will be performed before each treatment session and 6 months later. Baseline data will be compared with corresponding data from 25 healthy controls not receiving any treatment.

Those who are performing the analyses a
Sponsor: University of Tromso

Current Primary Outcome:

  • Difference of days with headache pr week after specific neck rehabilitation vs standard primary health care [ Time Frame: 6 months after baseline ]
    Two independent group comparison with a numeric variable (scale 0-7)
  • Differences in cerebral grey matter volume in patients with unilateral headache and neck pain vs. healthy controls [ Time Frame: Baseline ]
    Voxel based volumetric analyses of cerebral grey matter


Original Primary Outcome: Same as current

Current Secondary Outcome:

  • Difference in pain intensity after specific neck rehabilitation vs. standard primary health care [ Time Frame: 6 months after baseline ]
    Two independent group comparison with a numeric variable (scale 0-10)
  • Improved neck function after specific neck rehabilitation vs. standard primary health care [ Time Frame: 6 months after baseline ]
    Two independent group comparison with a numeric variable (scale 0-100)
  • Differences in white matter integrity in patients with unilateral headache and neck pain vs. healthy controls [ Time Frame: Baseline ]
    Diffusion tensor imaging with tract based spatial statistics analyses
  • Difference in white matter integrity after specific neck rehabilitation vs standard primary health care [ Time Frame: 6 months after baseline ]
    Diffusion tensor imaging with tract based spatial statistics analyses
  • How four week baseline headache intensity reported by a numeric rating scale is associated with regional cerebral grey matter volume measured by voxel based morphometry in patients with unilateral headache and neck pain. [ Time Frame: Baseline ]
    A linear regression analysis will be performed where the voxel based volumetric measure of cerebral grey matter (VBM) is the dependent variable, and four week baseline headache intensity is independent variable. Baseline headache intensity is based on daily measures during the last 4 weeks and is reported by an electronic diary and numeric rating scale where 0 is no pain and 10 is worst imaginable pain. It is thus considered a continuous measure. Age and gender are included as covariates.
  • How baseline perceived cognitive function predicts volumetric differences of cerebral grey matter in patients with unilateral headache and neck pain [ Time Frame: Baseline ]
    Linear regression analysis of voxel based volumetric measures of grey matter (continuous data) and scores of Everyday Memory Questionnaire (scale 0-8).
  • How baseline active range of neck movement predicts neck function [ Time Frame: 12 months after baseline ]
    A logistic regression analysis on how baseline active range of neck movement (continuous data, degrees of rotation ) predicts a 30% reduction in Neck Disability Index Score (0-50). Co-factors are age, gender, sick-leave.
  • How baseline active range of neck movement predicts headache frequency [ Time Frame: 12 months after baseline ]
    A logistic regression analysis on how baseline active range of neck movement (continuous data, degrees of rotation) predicts a 30% reduction in headache frequency (0-7). Co-factors are age, gender, sick-leave.
  • How baseline self efficacy predicts neck function [ Time Frame: 12 months after baseline ]
    A logistic regression analysis on how baseline General self efficacy scale score (scale 10-40) predicts a 30% reduction in Neck Disability Index Score (0-50). Co-factors are age, gender, sick-leave.
  • How baseline self efficacy predicts headache frequency [ Time Frame: 12 months after baseline ]
    A logistic regression analysis on how baseline General self efficacy scale score (scale 10-40) predicts a 30% reduction in headache frequency (0-7). Co-factors are age, gender, sick-leave.
  • How baseline fear avoidance beliefs for physical activity predict neck function [ Time Frame: 12 months after baseline ]
    A logistic regression analysis on how baseline fear avoidance beliefs score predict a 30% reduction in Neck Disability Index Score (0-50). Co-factors are age, gender, sick-leave.
  • How baseline fear avoidance beliefs for physical activity predict headache frequency [ Time Frame: 12 months after baseline ]
    A logistic regression analysis on how baseline fear avoidance beliefs for physical activity score predict a 30% reduction in headache frequency (0-7). Co-factors are age, gender, education, sick-leave.
  • Difference in intra-network connectivity of the DMN in patients with unilateral headache and neck pain vs. healthy controls. [ Time Frame: Baseline ]
    Baseline RS-fMRI data will be used to compare patients and controls. In multivariate general linear models, the investigators will use DMN and other major cerebral Networks, identified by independent component analysis (ICA), as dependent variables and test whether there are differences in cerebral connectivity between patients and controls. All RS-fMRI analyses will be performed with the GIFT software http://mialab.mrn.org/software/gift/index.html. An ICA procedure in GIFT will be used to identify functional networks. GIFT that has a MatLab based statistical module for general linear modelling (GLM) of RS-fMRI data that will be used for all RS-fMRI analyses.
  • Change of

    Original Secondary Outcome:

    • Difference in pain intensity after specific neck rehabilitation vs. standard primary health care [ Time Frame: 6 months after baseline ]
      Two independent group comparison with a numeric variable (scale 0-10)
    • Improved neck function after specific neck rehabilitation vs. standard primary health care [ Time Frame: 6 months after baseline ]
      Two independent group comparison with a numeric variable (scale 0-100)
    • Differences in white matter integrity in patients with unilateral headache and neck pain vs. healthy controls [ Time Frame: Baseline ]
      Diffusion tensor imaging with tract based spatial statistics analyses
    • Difference in white matter integrity after specific neck rehabilitation vs standard primary health care [ Time Frame: 6 months after baseline ]
      Diffusion tensor imaging with tract based spatial statistics analyses
    • How four week baseline headache intensity reported by a numeric rating scale is associated with regional cerebral grey matter volume measured by voxel based morphometry in patients with unilateral headache and neck pain. [ Time Frame: Baseline ]
      We will perform a linear regression analysis where the voxel based volumetric measure of cerebral grey matter (VBM) is the dependent variable, and four week baseline headache intensity is independent variable. Baseline headache intensity is based on daily measures during the last 4 weeks and is reported by an electronic diary and numeric rating scale where 0 is no pain and 10 is worst imaginable pain. It is thus considered a continuous measure. Age and gender are included as covariates.
    • How baseline perceived cognitive function predicts volumetric differences of cerebral grey matter in patients with unilateral headache and neck pain [ Time Frame: Baseline ]
      Linear regression analysis of voxel based volumetric measures of grey matter (continuous data) and scores of Everyday Memory Questionnaire (scale 0-8).
    • How baseline active range of neck movement predicts neck function [ Time Frame: 12 months after baseline ]
      A logistic regression analysis on how baseline active range of neck movement (continuous data, degrees of rotation ) predicts a 30% reduction in Neck Disability Index Score (0-50). Co-factors are age, gender, sick-leave.
    • How baseline active range of neck movement predicts headache frequency [ Time Frame: 12 months after baseline ]
      A logistic regression analysis on how baseline active range of neck movement (continuous data, degrees of rotation) predicts a 30% reduction in headache frequency (0-7). Co-factors are age, gender, sick-leave.
    • How baseline self efficacy predicts neck function [ Time Frame: 12 months after baseline ]
      A logistic regression analysis on how baseline General self efficacy scale score (scale 10-40) predicts a 30% reduction in Neck Disability Index Score (0-50). Co-factors are age, gender, sick-leave.
    • How baseline self efficacy predicts headache frequency [ Time Frame: 12 months after baseline ]
      A logistic regression analysis on how baseline General self efficacy scale score (scale 10-40) predicts a 30% reduction in headache frequency (0-7). Co-factors are age, gender, sick-leave.
    • How baseline fear avoidance beliefs for physical activity predict neck function [ Time Frame: 12 months after baseline ]
      A logistic regression analysis on how baseline fear avoidance beliefs score predict a 30% reduction in Neck Disability Index Score (0-50). Co-factors are age, gender, sick-leave.
    • How baseline fear avoidance beliefs for physical activity predict headache frequency [ Time Frame: 12 months after baseline ]
      A logistic regression analysis on how baseline fear avoidance beliefs for physical activity score predict a 30% reduction in headache frequency (0-7). Co-factors are age, gender, education, sick-leave.
    • Difference in intra-network connectivity of the DMN in patients with unilateral headache and neck pain vs. healthy controls. [ Time Frame: Baseline ]
      Baseline RS-fMRI data will be used to compare patients and controls. By multivariate general linear models, we will use the DMN and other major cerebral networks identified by independent component analysis (ICA) as dependent variables and test whether there are differences in cerebral connectivity between patients and controls. All RS-fMRI analyses will be performed with the GIFT software http://mialab.mrn.org/software/gift/index.html. We will use an ICA procedure in GIFT to identify functional networks. GIFT that has a MatLab based statistical module for general linear modelling (GLM) of RS-fMRI data that will be used for all RS-fMRI analyses.
    • Change of DMN connectivit

      Information By: University of Tromso

      Dates:
      Date Received: January 14, 2016
      Date Started: October 2016
      Date Completion: September 2019
      Last Updated: October 28, 2016
      Last Verified: October 2016