Background & Aims
70% (seventy percent) of stroke survivors report shoulder pain in the acute post- stroke period, and half will go on to develop chronic shoulder pain (hemiplegic shoulder pain or HSP).1-7 Chronic HSP is predictive of lengthened hospitalization, worsened outcomes, decreased quality of life, depression, and physical deconditioning.4,6-10 Evidence points to three physiologic sources of HSP either acting separately or in combination:1,7-8 musculoskeletal lesions; impaired motor control; and altered peripheral and central nervous system activity.1,6-8,11 Because the underlying processes are unclear, 30% of HSP sufferers are left with pain and impairment refractory to any currently available treatments.7 Electroencephalogram (EEG) spatial patterns are recognized biomarkers in many pain conditions,14-22 but are not researched in HSP.
Methods
Stroke survivors with self-reported HSP > 3 months, English or Spanish speaking, underwent 19 electrode EEG and completed self-report pain and interference measures including the Brief Pain Inventory (BPI), PROMIS 8a and 29, and the Pain Vigilance and Awareness Questionnaire (PVAQ). Those with a pre-stroke pain condition were excluded. EEG regions of interest included the standard pain network. Analysis of brain function was completed individually and compared to a database of asymptomatic brains, matched by age, gender, and handedness. Baseline differences were analyzed in amplitude, power, and relative power for delta, theta, alpha, low beta, high beta, gamma, theta/beta ratio, and alpha/beta ratios between the HSP and normal EEG. A Laplacian montage was used to minimize the effect of medications on the EEG. Self-report of the EEG experience was collected using a NRS 0-10 scale and one open text question. Qualitative content analysis was used to code the open text responses.
Results
11 subjects completed the study, 6 of whom were female. The mean age was 60 (range 44 to 70) years. 55% were Black and 36% White. Most frequently reported medical history included hypertension (82%) and high cholesterol (55%). All subjects reported being right-handed. Overall, HSP subjects exhibited an increase in cortical power in the slower frequencies (< 7 HZ), with a concomitant decrease in beta frequencies. However, 33% of our sample presented with an increase in beta power. Connectivity analysis showed disruption within the pain network in all patients. Specifically, reduced power in alpha (8-12 HZ) and reduced beta (15-25 HZ) was consistent among patients. Beta connectivity was most frequently affected with deviances > 3 SD, where alpha was within normal limits in 2 subjects. These two subjects who did not show reduced alpha and/or beta connectivity both had MCA-type strokes. Phase lag is used to estimate connectivity that eliminates volume conduction effects. Phase lag tended to be at least 3 standard deviations slower than a normative database in 88% of our sample. The BPI Severity Scale had a mean of 5 indicating moderate pain, and Intensity Scale a mean of 4.3. All consented subjects completed all study requirements.
Conclusions
Our EEG findings may be unique to HSP patients. The cortex showed overall slowing much like in other types of direct insults to the brain (TBI). One potential mechanism for an increase in power in slow EEG frequencies is a compromise to cerebral blood flow, which then may have an impact on metabolism and neuronal function. The use of EEG to explore biomarkers for HSP has the potential to advance translational medicine by determining unique targets for diagnosis, neuromodulatory interventions, and for medications. EEG biomarker identification for HSP could be widely adopted in clinical testing and health care settings. There is an urgent need to develop non-pharmacological interventions for management of pain and other symptoms. HSP reduces quality of life, and because up to 29% of patients prescribed opioids for chronic pain misuse them, a large percentage of stroke survivors could become statistics in the opioid crisis.
References
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Presenting Author
Deniz Dishman
Poster Authors
Deniz Dishman
PhD, CRNA, NSPM-C
University of Texas Health Science Center at Houston Institute for Stroke and Cerebrovascular Diseas
Lead Author
Tia Lal
MS
Lead Author
Seokhun Kim
PhD
Lead Author
Xiaoqian Jiang
PhD
University of Texas Health Science Center at Houston School of Biomedical Informatics
Lead Author
Charles Green
PhD
University of Texas Health Science Center at Houston Institute for Stroke and Cererovascular Disease
Lead Author
Anjail Sharrief
MD
University of Texas Health Science Center at Houston
Lead Author
Sean Savitz
MD
University of Texas Health Science Center at Houston Institute for Stroke and Cerebrovascular Diseas
Lead Author
Sarah Prinsloo
PhD
MD Anderson Cancer Center
Lead Author
Topics
- Assessment and Diagnosis