Detection of Small Fiber Neuropathy Using Skin Properties

NCT ID: NCT04759443

Last Updated: 2025-02-06

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

RECRUITING

Total Enrollment

400 participants

Study Classification

OBSERVATIONAL

Study Start Date

2021-07-01

Study Completion Date

2027-02-01

Brief Summary

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Small fiber neuropathy affects millions of peoples worldwide. The neuropathy is causing disabling burning pain and dysautonomia such as dizziness with standing, brain fog, fatigue, constipation, too much or too little sweating. The detection of nerve damage is complicated and not widely available; it requires either skin biopsy or specialized equipment and training. This project utilizes the mathematical processing of skin pictures for the purpose to extract the statistical features related to loss of small fibers. This approach can improve the availability of diagnosis of small fiber neuropathy.

Detailed Description

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Small fiber neuropathy, including cardiovascular diabetic neuropathy, affects millions of peoples worldwide. The neuropathy is causing disabling burning pain and dysautonomia such as dizziness with standing, brain fog, fatigue, constipation, urinary problems and cold or hot intolerance. Early and accurate diagnosis of neuropathy is essential for correct treatment. Available diagnostic methods are either invasive such as skin biopsy or available only in few specialized centers. This project addresses the limited availability of small fiber neuropathy detection.

The project utilizes utilize specialized image processing of skin pictures for the purpose to extract the statistical features that are related to loss of small fibers. The accuracy of the diagnosis verified using skin biopsies.

This approach can improve the availability of diagnosis of small fiber neuropathy.

Conditions

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Small Fiber Neuropathy

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Interventions

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Image processing of skin

Image processing will be used to extract skin features that correlate with loss of small skin fibers.

Intervention Type OTHER

Eligibility Criteria

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Inclusion Criteria

* Patients with age 18 year or older
* Patients that sign the informed consent form to participate in this study
* Patients completed the autonomic testing with skin biopsies

Exclusion Criteria

* Patients with significant hairs at the legs that will cover the skin
* Any dermatological disorder that can affect the skin composition
* The use of skin lotion
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Brigham and Women's Hospital

OTHER

Sponsor Role lead

Responsible Party

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Peter Novak

Director, Autonomic Laboratory

Responsibility Role PRINCIPAL_INVESTIGATOR

Locations

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Brigham and Women's Faulkner Hospital

Boston, Massachusetts, United States

Site Status RECRUITING

Countries

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United States

Central Contacts

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Peter Novak, MD

Role: CONTACT

617-732-7432

Facility Contacts

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Peter Novak, MD

Role: primary

Other Identifiers

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2021P000410

Identifier Type: -

Identifier Source: org_study_id

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