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Common and Specific Information From Neuroimaging and Smartphone (MS-CSI)

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ClinicalTrials.gov Identifier: NCT05482906
Recruitment Status : Not yet recruiting
First Posted : August 1, 2022
Last Update Posted : August 1, 2022
Sponsor:
Collaborator:
Rennes University Hospital
Information provided by (Responsible Party):
Nantes University Hospital

Brief Summary:
Gait alteration is frequent in MS and limitation in walking ability is a major concern in MS patients. Umanit and LMJL (Nantes university) has developed a device call egait to assess walking ability in individuals (eg MS patients).

Condition or disease Intervention/treatment
Multiple Sclerosis Other: eGait

Detailed Description:
This device consists in a commercialized IMU sensor (MetaMotionR Sensor, Mbientilab) worn at the right hip, a smartphone app and dedicated algorithm/mathematical model to extract raw sensor data and calculate individual gait pattern (IGP). This IGP consists of a curve, based on quaternion and representing the rotation recorded by the IMU during an average gait cycle. Pursue previous works conducted on (IGP to assess) gait alteration in MS by adding (to IGP) new information from MRI.

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Study Type : Observational
Estimated Enrollment : 100 participants
Observational Model: Other
Time Perspective: Prospective
Official Title: Individual Gait Pattern and MRI Lesion Load to Quantify Gait Impairment in MS: A Cross Sectional Study.
Estimated Study Start Date : September 1, 2022
Estimated Primary Completion Date : November 1, 2024
Estimated Study Completion Date : November 1, 2024



Intervention Details:
  • Other: eGait
    IMU sensor (as part of eGait device) worn at the hip during T25FW
    Other Name: Wearable sensor


Primary Outcome Measures :
  1. Clustering analyze based on IGP [ Time Frame: At the inclusion ]
    IGP consists of a curve, based on quaternion and representing the rotation recorded by the IMU during an average gait cycle (0-1).

  2. Clustering analyze based on EDSS score [ Time Frame: At the inclusion ]
    EDSS is an ordinal scale measuring disability and ranging from 0 (normal examination) to 10 (death due to MS) in a 0,5-point increments from score 1.

  3. Clustering analyze based on MRI lesion load [ Time Frame: At the inclusion ]
    MRI characteristics are spinal and extraspinal lesion volumes.


Secondary Outcome Measures :
  1. Correlation with disability [ Time Frame: At the inclusion ]
    Correlation of IGP obtained during a walk of 25 feet with Expanded Disability Status Scale (EDSS). EDSS is an ordinal scale measuring disability and ranging from 0 (normal examination) to 10 (death due to MS) in a 0,5-point increments from score 1. Here EDSS of 0 to 2 inclusive defined as mild, 2,5 to 4 inclusive as moderate and EFDSS of 4,5 to 6 inclusive defined as severe

  2. Correlation with MRI lesion load [ Time Frame: At the inclusion ]
    Add lesion load (Spinal and extraspinal lesion volume) from MRI to previous correlation.

  3. Building a predictive model for lesion load involving in walk ability from IGP [ Time Frame: At the inclusion ]
    Root mean square error between observed and lesion load predicted by the model, calculated by cross-validation.

  4. Building a predictive model for group belonging from group established in main outcome based on IGP [ Time Frame: At the inclusion ]
    Multiclass accuracy between real and predict group, calculated by cross-validation



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Ages Eligible for Study:   18 Years and older   (Adult, Older Adult)
Sexes Eligible for Study:   All
Sampling Method:   Non-Probability Sample
Study Population
MS patients cohort followed at Nantes university hospital or Rennes university hospital (OFSEP HD cohort)
Criteria

Inclusion Criteria :

  • Diagnosis of MS based on McDonald criteria (including Relapsing-remitting and progressive MS)
  • Over 18 years old /age greater than 18 years
  • Patients followed at Nantes university hospital or Rennes university hospital
  • Last known EDSS before inclusion ranging from 0 to 6 inclusive/EDSS of 0 to 6 inclusive, prior inclusion
  • No relapse within 3 months
  • With a Medullar MRI planed as part as usual care
  • Affiliated person or beneficiary of a social security scheme

Exclusion Criteria :

  • Bilateral aid needed to walk
  • Women who are pregnant
  • Patient having expressed their opposition
  • Patient under guardianship or security measure

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT05482906


Contacts
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Contact: David LAPLAUD, PHD 33 2 40 16 52 00 david.laplaud@chu-nantes.fr

Locations
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France
Nantes University Hospital
Nantes, Loire-Atlantique, France, 44093
Sponsors and Collaborators
Nantes University Hospital
Rennes University Hospital
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Responsible Party: Nantes University Hospital
ClinicalTrials.gov Identifier: NCT05482906    
Other Study ID Numbers: RC20_0203
First Posted: August 1, 2022    Key Record Dates
Last Update Posted: August 1, 2022
Last Verified: July 2022
Individual Participant Data (IPD) Sharing Statement:
Plan to Share IPD: No

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Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No
Keywords provided by Nantes University Hospital:
Wearable sensor
Gait
MRI
Additional relevant MeSH terms:
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Multiple Sclerosis
Demyelinating Autoimmune Diseases, CNS
Autoimmune Diseases of the Nervous System
Nervous System Diseases
Demyelinating Diseases
Autoimmune Diseases
Immune System Diseases