Can Electroencephalography (EEG) Identify the Different Dimensions of Pain in Fibromyalgia?

NCT ID: NCT05962658

Last Updated: 2023-08-01

Basic Information

• Recruitment Status: COMPLETED
• Total Enrollment: 21 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2021-04-01
• Study Completion Date: 2022-12-31

Brief Summary

Studies with quantitative electroencephalogram (qEEG) in people with fibromyalgia showed the existence of distinct patterns of brain electrical activity when compared to healthy individuals. Such dysfunctional patterns may be correlated to clinical symptoms of the syndrome as chronic pain and emotional disorders (depression and anxiety). As chronic pain can be considered a multidimensional symptom, its evaluation should consider beyond others, two main dimensions: the sensitive-discriminative dimension and the affective-motivational dimension. Previous studies have been describing distinct brain areas as neural substrates for processing such dimensions of pain. Thus, the identification of electrophysiological biomarkers (i.e., as qEEG measures) allowing to perform an evaluation between dysfunctional patterns of brain electrical activity and different dimensions of pain seems to be a promising path in the search for a better understanding of the syndrome as well as for more individualized and effective therapeutic approaches. Our objective was to investigate whether dysfunctional patterns of brain electrical activity in frontal and central areas of people with fibromyalgia are differently related to dimensions of pain (sensory-discriminative and affective-motivational) and to emotional disorders (depression and anxiety).

Detailed Description

The study was a pilot study with a cross-sectional and exploratory design carried out from 2020 to 2022. A quantitative electroencephalographic analysis was performed with women with Fibromyalgia and pain-free individuals as a control group, matched for gender and age. The sample was not probabilistic and recruitment occurred in a random manner. All volunteers were recruited from reference services in the state of Pernambuco, referred from other centers as well as through announcements in digital media.

Procedures All procedures were conducted respecting the Declaration of Helsinki (1964) and approved by the local ethical committee. Before clinical and sociodemographic evaluation, all volunteers signed a written informed consent, including all information regarding the risks and benefits of their participation in the study. During the study, all individuals with fibromyalgia were instructed not to change their medication use as well as eating habits. Clinical assessments and qEEG data acquisition took place in one single visit to the laboratory lasting around two hours. After signing the written informed consent, all volunteers were taken to an isolated room to perform an EEG evaluation. Then, they underwent sociodemographic and clinical assessments (only individuals with fibromyalgia).

EEG data acquisition and processing For each volunteer, signals were recorded using digital EEG equipment for 120 seconds in an isolated room - without any communication with the external environment - with volunteers rested, seated in a comfortable chair, and with closed eyes. Signal recording was performed through 19 Ag/AgCl electrodes positioned on the scalp following the predetermined points of the international 10-20 system of electroencephalography and, always maintaining a maximum impedance of 10 kΩ. Additionally, a ground electrode was positioned on the lateral third of the right clavicle, while two reference electrodes were positioned on the region of the right and left mastoid processes. A sampling rate for recording the 500 Hz signal was captured by the NeuronSpectrum signal amplifier and recorded by the Neuron-Spectrum/NET omega software. Additionally, the high-pass (0.5 Hz), low-pass (35 Hz), and notch (60Hz; suitable for 220V mains) filters were applied during data acquisition and processing.

Then, the collected data were pre-processed using the EEGLab toolbox in MATLAB® version R2014a software for Windows. In addition, an Independent Component analysis was performed using the Independent Components Analysis (ICA) algorithm to separate the components related to biological artifacts. The rejection of these components was done through the Multiple Artefact Rejection Algorithm (MARA) considering a 50% cutoff point. For time-frequency analysis of the relative spectral power for each epoch, the fast Fourrier transform method was used. The dominant frequency in each patient was identified in the following points of the international 10-20 EEG system: F3, F4, Fz, F7, F8 (frontal area), and C3, C4, Cz (central area) during rest. Spectral power density assessment was also performed, for each frequency band, considering the following bands: delta (0,5 a ≤ 4 Hz); theta ( > 4 a ≤ 8 Hz); alpha (> 8 a ≤13 Hz) e beta (> 13 a ≤ 30 Hz). For relative spectral power distribution calculations, the absolute spectral power of each frequency band was divided by the total power of all bands present in the 0.5-35Hz.

Conditions

Fibromyalgia

Study Design

• Observational Model Type: OTHER
• Study Time Perspective: CROSS_SECTIONAL

Study Groups

Fibromyalgia

Our sample consisted of 11 women with fibromyalgia enrolled according to the criteria of the American College of Rheumatology (ACR). Participants were underwent to clinical and electrophysiological assessments using the McGill Pain Questionnaire, the Hospital Anxiety and Depression Scale, and qEEG in frontal (F3, F4, Fz, F7, F8) and central (C3, C4,Cz) areas. qEEG data was collected with patients in resting eyes-closed: the relative spectral power of the frequency bands delta, theta, alpha and beta was evaluated.

qEEG

Intervention Type: OTHER

qEEG data was collected with patients and healthy individuals in resting eyes-closed: the relative spectral power of the frequency bands delta, theta, alpha and beta was evaluated.

Healthy individuals

A control group was enrolled and data was collected from healthy subjects to confirm different patterns of cortical electrical activity in people with fibromyalgia. For that, self-declared healthy and pain-free individuals, matched by gender and age with the women with fibromyalgia included in the sample were recruited through advertising in digital media.

qEEG

Intervention Type: OTHER

qEEG data was collected with patients and healthy individuals in resting eyes-closed: the relative spectral power of the frequency bands delta, theta, alpha and beta was evaluated.

Interventions

qEEG

qEEG data was collected with patients and healthy individuals in resting eyes-closed: the relative spectral power of the frequency bands delta, theta, alpha and beta was evaluated.

Intervention Type: OTHER

Eligibility Criteria

Inclusion Criteria

• widespread pain index (WPI) ≥ 7;
• symptom severity scale (SS) = 5;
• WPI between 4-6 and (iv) SS ≥ 9;
• generalized pain, as defined as pain in at least 4 regions of the body;
• having been diagnosed with fibromyalgia at least three months ago.

Exclusion Criteria

• autoimmune or inflammatory diseases that cause pain, such as rheumatoid arthritis, systemic lupus erythematosus, or inflammatory bowel disease;
• history of neurological or psychotic disorders;
• cognitive impairment that prevents the conduct of study procedures;
• patients with a history of abusive use of alcohol or other illicit drugs;
• patients who have any contraindication for the use of the qEEG (excessive seborrhoea, scalp infection or pediculosis).

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 60 Years
• Eligible Sex: FEMALE
• Accepts Healthy Volunteers: Yes

Sponsors

Universidade Federal de Pernambuco

OTHER

Sponsor Role: lead

Responsible Party

Kátia Monte-Silva

Principal Investigator

Responsibility Role: PRINCIPAL_INVESTIGATOR

Principal Investigators

Kátia Monte-Silva, PhD

Role: PRINCIPAL_INVESTIGATOR

PI

Locations

Applied Neuroscience Laboratory

Recife, Pernambuco, Brazil

Countries

Brazil

References

Diniz L, Carneiro M, Fonseca A, Shirahige L, Brito R, Melo L, Melo D, Austregesilo M, Piscitelli D, Monte-Silva K. Can electroencephalography (EEG) identify the different dimensions of pain in fibromyalgia? A pilot study. BMC Musculoskelet Disord. 2024 Sep 3;25(1):705. doi: 10.1186/s12891-024-07824-0.

Reference Type: DERIVED

PMID: 39227893 (View on PubMed)

Other Identifiers

Fibro

Identifier Type: -

Identifier Source: org_study_id