MedTrace Logo

Logistic Regression and Elastic Net Regularization for the Diagnosis of Fibromyalgia

NCT04088747 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 81

Last updated 2019-09-17

No results posted yet for this study

Summary

This study will utilize ultrasound image texture variables to construct an elastic net regularized, logistic regression model to differentiate between healthy and Fibromyalgia patients. The collected ultrasound data will be from participants who are healthy, and from participants who have Fibromyalgia. The predicted performance accuracy of the diagnostic model will be validated and this will confirm or deny the hypothesis that differentiation between the two cohorts is possible.

Conditions

  • Fibromyalgia

Interventions

DIAGNOSTIC_TEST

Ultrasound Imaging

B-mode ultrasound pictures of the upper Trapezius were collected from both left and right sides.

Sponsors & Collaborators

  • Toronto Rehabilitation Institute

    lead OTHER

Principal Investigators

  • Dinesh Kumbhare, MD,PhD · Toronto Rehabilitation Institute

Eligibility

Min Age
20 Years
Max Age
65 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2018-09-01
Primary Completion
2019-09-06
Completion
2019-09-06

Countries

  • Canada

Study Locations

More Related Trials

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT04088747 on ClinicalTrials.gov