Ignite Creation Date:
2025-12-25 @ 2:27 AM
Ignite Modification Date:
2025-12-31 @ 12:09 PM
Study NCT ID:
NCT04974034
Status:
COMPLETED
Last Update Posted:
2021-07-23
First Post:
2021-07-03
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Movement Disorders Analysis Using a Deep Learning Approach
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D018476', 'term': 'Hypokinesia'}, {'id': 'D010300', 'term': 'Parkinson Disease'}, {'id': 'D020734', 'term': 'Parkinsonian Disorders'}], 'ancestors': [{'id': 'D020820', 'term': 'Dyskinesias'}, {'id': 'D009461', 'term': 'Neurologic Manifestations'}, {'id': 'D009422', 'term': 'Nervous System Diseases'}, {'id': 'D012816', 'term': 'Signs and Symptoms'}, {'id': 'D013568', 'term': 'Pathological Conditions, Signs and Symptoms'}, {'id': 'D001480', 'term': 'Basal Ganglia Diseases'}, {'id': 'D001927', 'term': 'Brain Diseases'}, {'id': 'D002493', 'term': 'Central Nervous System Diseases'}, {'id': 'D009069', 'term': 'Movement Disorders'}, {'id': 'D000080874', 'term': 'Synucleinopathies'}, {'id': 'D019636', 'term': 'Neurodegenerative Diseases'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'RETROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 50}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2019-06-01', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2021-07', 'completionDateStruct': {'date': '2020-12-31', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2021-07-13', 'studyFirstSubmitDate': '2021-07-03', 'studyFirstSubmitQcDate': '2021-07-13', 'lastUpdatePostDateStruct': {'date': '2021-07-23', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2021-07-23', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2020-11-18', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': "Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) part III score", 'timeFrame': '1 day', 'description': "Automatic Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) part III for hand bradykinesia including the three following specific tasks (finger tapping, hand movements and pronation-supination movements of hand).\n\nThe minimum score is 0. The maximum score is 12 Higher scores mean wors outcome"}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Deep Learning', 'Bradykinesia', 'Parkinson Disease'], 'conditions': ['Bradykinesia', 'Parkinson Disease', 'Hypokinesia', 'Akinesia', 'Parkinsonian Syndrome', 'Parkinsonian Disorders']}, 'descriptionModule': {'briefSummary': "Bradykinesia is a key parkinsonian feature yet subjectively assessed by the MDS-UPDRS score, making reproducible measurements and follow-up challenging.\n\nIn a Movement Disorder Unit, the investigators acquired a large database of videos showing parkinsonian patients performing Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) part III protocols.\n\nUsing a Deep Learning approach on these videos, the investigators aimed to develop a tool to compute an objective score of bradykinesia from the three upper limb tests described in the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) part III."}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'samplingMethod': 'PROBABILITY_SAMPLE', 'studyPopulation': 'All patients seen by a neurologist in the department of Neurology at Avicenne Hospital (Bobigny, France) between June 2019 and December 2020 were recorded during MDS-UPDRS examination.\n\nThe investigators also included healthy volunteers on a voluntary basis.', 'healthyVolunteers': True, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Age \\> 18 years\n\nExclusion Criteria:\n\n* Refusal of participation'}, 'identificationModule': {'nctId': 'NCT04974034', 'briefTitle': 'Movement Disorders Analysis Using a Deep Learning Approach', 'organization': {'class': 'OTHER', 'fullName': 'Hospital Avicenne'}, 'officialTitle': 'Movement Disorders Analysis Using a Deep Learning Approach', 'orgStudyIdInfo': {'id': 'CLEA-2019-83'}}, 'contactsLocationsModule': {'locations': [{'zip': '93000', 'city': 'Bobigny', 'state': 'Seine Saint Denis', 'country': 'France', 'facility': 'Hospital Avicenne', 'geoPoint': {'lat': 48.90982, 'lon': 2.45012}}], 'overallOfficials': [{'name': 'Clément Desjardins, MD', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'Hospital Avicenne'}, {'name': 'Bertrand Degos, MD,PhD', 'role': 'STUDY_DIRECTOR', 'affiliation': 'Hospital Avicenne'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'UNDECIDED'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Hospital Avicenne', 'class': 'OTHER'}, 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Neurology Resident', 'investigatorFullName': 'Desjardins Clement', 'investigatorAffiliation': 'Hospital Avicenne'}}}}