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OpenTrials
Completed

NCT Number: NCT04585451

Expanded Development of a Medical Device Utilizing an EEG-Based Algorithm for the Objective Quantification of Pain

PainQx is conducting a study to collect electroencephalography (EEG) data from 250 people with chronic pain and 50 healthy controls in order to develop algorithms that will objectively assess the level of pain a person is experiencing.

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Key information

Conditions

Chronic Pain Neurologic Manifestations Pain Pathological Conditions, Signs and Symptoms Signs and Symptoms

Age range

18 year–85 year

Sex eligibility

All sexes

Study type

Observational

Primary location

Panorama Orthopedics & Spine Center, Golden, Colorado, United States

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Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Male and female chronic pain patients
  • Patients between the ages of 18-85 years
  • Patients exhibiting the presence of symptoms in excess of 3 months duration
  • Patients suffering from neuropathic (e.g., lower back pain), osteoarthritis, or muscular skeletal pain
  • Patients with evidence of pathology related to the painful condition on which diagnosis was made (e.g., results of imaging or diagnostic pain code)

Patients with NRS pain scores across the full range (1-10) at the time of testing Inclusion Criteria, Normal (no-pain) Group

o Subjects will be included with no history of pain with a duration of greater than 3 months, and no report of pain at the time of testing (or within 3 months of testing)

Exclusion criteria

  • Patients with medically diagnosed psychotic illness
  • Patients with medically diagnosed drug or alcohol dependence in the past 12 months
  • Patients with a medical history of head injury with loss of consciousness and amnesia (within the last 2 years)
  • Patients with skull abnormalities that preclude the proper placement of the electrodes for the EEG data acquisition
  • Patients who have a spinal cord stimulator, or other implantable devices
  • Patients for whom the source of pain at the time of the evaluation is associated with: neurological disorders (multiple sclerosis, Parkinson, dementia), diabetes, migraines, or those with reflex / sympathetic dystrophy disorder/complex regional pain syndrome, fibromyalgia, or visceral pain

Note: This does not exclude patients who suffer from these disorders if the current source of pain is not due to the disorder. For example, patients with diabetes are NOT excluded, but patients whose pain at the time of the evaluation is a result of diabetic neuropathy are excluded. Similarly, patients with a history of migraines but for whom a migraine is not the current source of pain at the time of the evaluation are NOT excluded.

  • Patients with cancer
  • Patients on workers compensation or disability
  • Patient on anticonvulsant medication
  • Patients who have a history of seizures

Treatment and study plan

ALGOS System

Diagnostic Test

A Quantitative Electroencephalography (QEEG) based pain biomarker assessment that scales with patient reported Numeric Rating Scale (NRS)

Primary outcomes

  1. Area Under the Curve of Classification Versus Patient Self Report of Pain vs no Pain State

    Time frame: Self-reported pain using average of NRS value at the start and end of EEG collection, and classification based on 15 minutes of EEG collection.

    This measure is the performance of the classification of pain vs no pain compared to the patient self-report in the form of Numerical Rating Scale (NRS). The primary outcome measure is Area Under the Curve (AUC), derived from the Receiver Operating Characteristic (ROC) curve, a standard metric of performance for binary classifiers. AUC is a numeric quantity ranging from 0 to 1, where the value of 1 indicates perfect separation, while 0.5 represents zero separation. AUC represents a fundamental expression of classifier separation performance without the complexity of threshold selection. (NRS 0 vs 1-10)

  2. Sensitivity of Classification Versus Patient Self Report of Pain vs no Pain State

    Time frame: Self-reported pain using average of NRS value at the start and end of EEG collection, and classification based on 15 minutes of EEG collection.

    Sensitivity, or true positive rate is the probability of a positive result in the true chronic pain patients. This measure is calculated by dividing true positives by the summation of true positives and false negatives. (NRS 0 vs 1-10)

  3. Specificity of Classification Versus Patient Self Report of Pain vs no Pain State

    Time frame: Self-reported pain using average of NRS value at the start and end of EEG collection, and classification based on 15 minutes of EEG collection.

    Specificity, or true negative rate is the probability of a negative result in the true healthy control patients. This measure is calculated by dividing true negatives by the summation of true negatives and false positives. (NRS 0 vs 1-10)

Secondary outcomes

  1. Area Under the Curve of Classification Versus Patient Self Report of no/Mild Pain vs Moderate/Severe Pain State

    Time frame: Self-reported pain using average of NRS value at the start and end of EEG collection, and classification based on 15 minutes of EEG collection.

    This measure is the performance of the classification of No/Mild vs Moderate/Severe pain compared to the patient self-report in the form of Numerical Rating Scale (NRS). The outcome measure is Area Under the Curve (AUC), derived from the Receiver Operating Characteristic (ROC) curve, a standard metric of performance for binary classifiers. AUC is a numeric quantity ranging from 0 to 1, where the value of 1 indicates perfect separation (the classifier is correct on every subject), while 0.5 represents zero separation (no better than guessing). AUC represents a fundamental expression of classifier separation performance without the complexity of threshold selection. (NRS 0-3.5 vs 4-10)

  2. Area Under the Curve of Classification Versus Patient Self Report of no, Mild, or Moderate Pain vs Severe Pain State

    Time frame: Self-reported pain using average of NRS value at the start and end of EEG collection, and classification based on 15 minutes of EEG collection.

    This measure is the performance of the classification of No/Mild/Moderate vs Severe pain compared to the patient self-report in the form of Numerical Rating Scale (NRS). The outcome measure is Area Under the Curve (AUC), derived from the Receiver Operating Characteristic (ROC) curve, a standard metric of performance for binary classifiers. AUC is a numeric quantity ranging from 0 to 1, where the value of 1 indicates perfect separation (the classifier is correct on every subject), while 0.5 represents zero separation (no better than guessing). AUC represents a fundamental expression of classifier separation performance without the complexity of threshold selection. (NRS 0-6.5 vs 7-10)

Sponsors and collaborators

Lead sponsor

PainQx, Inc

Industry

Collaborators

  • National Institute on Drug Abuse (NIDA)

Registry information

Important dates

Study start
2020
Primary completion
2022
Study completion
2022
First posted
Oct 14, 2020
Registry last updated
May 6, 2023

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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