Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 1000}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'NOT_YET_RECRUITING', 'startDateStruct': {'date': '2025-06-03', 'type': 'ESTIMATED'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-03', 'completionDateStruct': {'date': '2026-07-01', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2025-04-06', 'studyFirstSubmitDate': '2025-03-27', 'studyFirstSubmitQcDate': '2025-04-06', 'lastUpdatePostDateStruct': {'date': '2025-04-09', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2025-04-09', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2026-06-01', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': "To evaluate the coincidence rate between doctors' independent diagnosis and the diagnosis recommended by the AI system.", 'timeFrame': 'Within 48 hours after the completion of EEG monitoring', 'description': 'The reference standard is the EGG interpreted by 3 clinicians who had attended the uniformly training program and had more than 5 years of experience in diagnosing epilepsy in children.'}], 'secondaryOutcomes': [{'measure': 'To evaluate the diagnostic efficiency of clinicians at two-stage', 'timeFrame': 'Immediately after the end of EEG interpretation', 'description': 'The time taken by physicians to interpret EEG independently and with the aid of AI was measured.'}]}, 'oversightModule': {'isUsExport': False, 'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'conditions': ['Pediatric Epilepsy']}, 'descriptionModule': {'briefSummary': 'A diagnostic accuracy study on Artificial intelligence EEG analysis system assisted doctors to diagnose pediatric epilepsy.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['CHILD', 'ADULT'], 'maximumAge': '18 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'children aged \\< 18 years old with suspected epilepsy who need EEG examination', 'healthyVolunteers': True, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Age \\< 18 years old\n* Children with suspected epilepsy\n\nExclusion Criteria:\n\n* During EEG monitoring, the patients had other serious neurological diseases and mental diseases concurrently\n* Used medication that affect EEG data within 3 weeks, such as sedatives and anti-epileptic medications\n* Substandard data quality, such as data lack of key records, electrode connection discontinuity, insufficient recording time, or the presence of serious artifacts\n* Incomplete or missing data\n* Equipment or operational abnormalities, data for which EEG monitoring has not been performed continuously'}, 'identificationModule': {'nctId': 'NCT06918457', 'briefTitle': 'A Clinical Trial With a Self-controlled, Multicenter, Pediatric EEG Intelligent Analysis System to Assist in Diagnosis', 'organization': {'class': 'OTHER', 'fullName': "Kunming Children's Hospital"}, 'officialTitle': 'A Clinical Trial With a Self-controlled, Multicenter, Pediatric EEG Intelligent Analysis System to Assist in Diagnosis', 'orgStudyIdInfo': {'id': '2024-03-278-K01'}}, 'armsInterventionsModule': {'interventions': [{'name': 'AI EEG analysis system', 'type': 'DIAGNOSTIC_TEST', 'description': 'The first stage, physicians independently diagnose pediatric epilepsy with EEG; the second stage, Artificial intelligence EEG analysis system assisted physicians to diagnose pediatric epilepsy'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': "Kunming Children's Hospital", 'class': 'OTHER'}, 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Professor', 'investigatorFullName': 'Xiaomei Liu', 'investigatorAffiliation': "Kunming Children's Hospital"}}}}