Objective Measurement of Pain Using the Algometer

NCT ID: NCT02325284

Last Updated: 2017-04-12

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Total Enrollment

20 participants

Study Classification

OBSERVATIONAL

Study Start Date

2014-09-30

Study Completion Date

2016-12-31

Brief Summary

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The development of tools for assessment and management of pain in newborns and children is a high priority and represents a significant unmet need. The inadequate treatment of pain and the overuse of analgesics can cause harmful consequences for neonates, infants, and children. To accomplish successful pain management in children one must first objectively assess pain. Thus, to address these critical issues with pain management, the Human Algometer and methods are under development by Drs. Julia Finkel and Zena Quezado, Pain Medicine Program (SZI) at Children's National Medical Center.

Detailed Description

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It is generally recognized that pain assessment and management in newborns and children is an unmet need. According to the American Medical Association, "The pediatric population is at risk of inadequate pain management, with age-related factors affecting pain management in children. Children are often given minimal or no analgesia for procedures that would routinely be treated aggressively in adults. Although much is now known about pain management in children, it has not been widely or effectively translated into routine clinical practice."1 Although some clinically validated methods exist (e.g. CRIES, PPIP, Faces, etc.), no "gold standard" of pain assessment has been adopted in clinical practice. All are hindered by ambiguous behavioral correlates to the pain stimuli standards as well as the subjective variability inherent in both clinical and parent evaluators 2.

Other apparatus/methods for pain assessment suffer from similar shortcomings. For example, pain tolerance threshold (PTT) and current perception threshold (CPT) determinations both rely on verbal response from a patient. Those determinations are subjective and semi-quantitative and use electrical stimulation to directly excite both large and small diameter sensory nerve fibers. The CPT determination represents the minimum amount of a potentially noxious electrical stimulus that can be perceived, while the PTT determination represents the maximum amount of noxious electrical stimulation that can be tolerated when used as a clinical diagnostic tool. Thus, PTT depends on a subject's verbal response and requires patient exposure to aversive electrical stimulation, which causes both undesirable discomfort but also elicits the affective component of pain.

Therefore, the development of tools for assessment and management of pain in newborns and children is a high priority and represents a significant unmet medical need. Both inadequately treated pain or over administration of analgesics can have deleterious physiologic consequences for neonates, infants and children. While a number of methods are in use, no "gold standard" for pain assessment exists. (Anand 2007) To accomplish meaningful pain management in children one must first be able to objectively assess pain, particularly in patients who are (1) non-verbal (e.g. neonates, infants), (2) lacking understanding and adequate verbalization skills (e.g. young children, developmentally disabled individuals) and (3) patients with compromising neuropathic clinical presentations. To address these critical issues with pain management, the Human Algometer and method are under development by Drs. Finkel and Quezado from the Pain Medicine Program at the Sheikh Zayed Institute. In brief, this device integrates a neurospecific neurostimulation of sensory nerve fibers involved in pain response and near infra-red spectroscopy (NIRS) signal acquisition derived from pain related hemodynamic changes in the somatosensory cortex. The device has the ability to collect data on the NIRS response in the cerebral cortex to noxious stimulation provided by the neurostimulation component. Signal processing of data from this trial and subsequent trials will result in (1) the detection and optimization of a NIRS signal specific to increased neuronal blood flow over the somatosensory cortex (nociceptive response) and the frontal cortex (affective component). The individual neurostimulatory and NIRS signal acquisition components integrated into this novel device are based in part or whole on previously FDA approved devices from Neurotron, Inc. and Covidien plc (former Somanetics INVOS ™) respectively.

Conditions

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Healthy

Study Design

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Observational Model Type

CASE_ONLY

Study Time Perspective

PROSPECTIVE

Study Groups

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Healthy adults

Pressure Algometer Testing

Intervention Type DEVICE

Interventions

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Pressure Algometer Testing

Intervention Type DEVICE

Other Intervention Names

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Wagner FPIX 50™ digital pressure algometer.

Eligibility Criteria

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Inclusion Criteria

* the subject 18-65 years of age.
* the subject is a healthy adult with significant ongoing medical conditions
* the subject is willing to remain at the research site for the duration of the study session.
* the subject is willing and able to provide written informed consent to study participation.

Exclusion Criteria

* the subject has consumed alcohol within the last 12 hours prior to testing
* subject has pain at the time of testing anywhere in the body
Minimum Eligible Age

18 Years

Maximum Eligible Age

65 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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CoolCad Electronics, LLC; University of Maryland Engineering

UNKNOWN

Sponsor Role collaborator

Julia Finkel

OTHER

Sponsor Role lead

Responsible Party

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Julia Finkel

MD

Responsibility Role SPONSOR_INVESTIGATOR

Locations

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Children's National Medical Center

Washington D.C., District of Columbia, United States

Site Status

Countries

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United States

Other Identifiers

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Algometer/Phase 1 pilot study

Identifier Type: -

Identifier Source: org_study_id

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