Ignite Creation Date:
2025-12-24 @ 10:48 PM
Ignite Modification Date:
2025-12-30 @ 10:24 PM
Study NCT ID:
NCT06871969
Status:
RECRUITING
Last Update Posted:
2025-10-03
First Post:
2025-02-27
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Clinical Evaluation of EEG Device for the Triage of Stroke Patients in the Ambulance
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D000083242', 'term': 'Ischemic Stroke'}, {'id': 'D020521', 'term': 'Stroke'}, {'id': 'D002318', 'term': 'Cardiovascular Diseases'}, {'id': 'D014652', 'term': 'Vascular Diseases'}, {'id': 'D002493', 'term': 'Central Nervous System Diseases'}, {'id': 'D001927', 'term': 'Brain Diseases'}, {'id': 'D009422', 'term': 'Nervous System Diseases'}, {'id': 'D002561', 'term': 'Cerebrovascular Disorders'}]}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'NA', 'maskingInfo': {'masking': 'NONE'}, 'primaryPurpose': 'DIAGNOSTIC', 'interventionModel': 'SINGLE_GROUP'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 275}}, 'statusModule': {'overallStatus': 'RECRUITING', 'startDateStruct': {'date': '2025-07-01', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-09', 'completionDateStruct': {'date': '2026-12', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2025-09-30', 'studyFirstSubmitDate': '2025-02-27', 'studyFirstSubmitQcDate': '2025-03-06', 'lastUpdatePostDateStruct': {'date': '2025-10-03', 'type': 'ESTIMATED'}, 'studyFirstPostDateStruct': {'date': '2025-03-12', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2026-12', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Data quality of StrokePointer', 'timeFrame': 'EEG-data for analysis will be recorded within 24 hours after onset of symptoms or last seen well.', 'description': 'Proportion of patients with a technically successful EEG dataset: at least 20 seconds of usable EEG (at least 3 electrodes with good skin-electrode quality on either side, no movement artifacts, no muscle artifacts) within a measurement time of 3 minutes.'}, {'measure': 'Diagnostic accuracy of StrokePointer for LVO stroke', 'timeFrame': 'EEG-data for analysis will be recorded within 24 hours after onset of symptoms or last seen well.', 'description': 'Diagnostic accuracy of StrokePointer for LVO stroke among patients with a suspected stroke, as measured with Area under the curve (AUC) as well as sensitivity and specificity'}], 'secondaryOutcomes': [{'measure': 'Predictive value of StrokePointer in identifying LVO stroke', 'timeFrame': 'EEG-data for analysis will be recorded within 24 hours after onset of symptoms or last seen well.', 'description': 'Positive and negative predictive value of StrokePointer in identifying LVO stroke'}, {'measure': 'User friendliness', 'timeFrame': 'EEG-data for analysis will be recorded within 24 hours after onset of symptoms or last seen well.', 'description': 'User-friendliness rating of StrokePointer by ambulance personnel and researchers: (1) after the training 80% of the users should be able to start StrokePointer and start measuring EEG-data within 120s. (2) Interviewed users score (a) usability of StrokePointer hardware on average as "makkelijk" (easy) or better, (b) StrokePointer software on average as "duidelijk" (clear) or better.'}, {'measure': 'Incidence of serious adverse device-related events (Safety of StrokePointer)', 'timeFrame': 'EEG-data for analysis will be recorded within 24 hours after onset of symptoms or last seen well.', 'description': 'Provided that the device is being used in line with the intended use, there are no occurrences of serious adverse device-related events in the study.'}, {'measure': 'Incidence of skin reactions (Safety of StrokePointer)', 'timeFrame': 'EEG-data for analysis will be recorded within 24 hours after onset of symptoms or last seen well.', 'description': 'Number of patients with an (allergic) skin reaction observed at the site of the electrode.'}, {'measure': 'Diagnostic accuracy for identifying LVO stroke subgroups', 'timeFrame': 'EEG-data for analysis will be recorded within 24 hours after onset of symptoms or last seen well.', 'description': 'Diagnostic accuracy for identifying LVO stroke within the following subgroups: sex (men vs. women) and age (above vs. below 60), as measured with sensitivity and specificity.'}, {'measure': 'Discriminative power of StrokePointer', 'timeFrame': 'EEG-data for analysis will be recorded within 24 hours after onset of symptoms or last seen well.', 'description': 'Discriminative power of StrokePointer for ischemic stroke vs stroke mimic as measured with Area under the curve (AUC) as well as sensitivity and specificity.'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'conditions': ['Ischemic Stroke', 'Stroke', 'Cardiovascular Diseases', 'Vascular Diseases', 'Central Nervous System Diseases', 'Brain Diseases', 'Nervous System Diseases', 'Cerebrovascular Disease']}, 'descriptionModule': {'briefSummary': 'Endovascular thrombectomy (EVT) is the standard treatment for large vessel occlusion (LVO) strokes, but it can only be performed in specialized hospitals. Since ambulance personnel cannot determine if a patient is eligible for EVT, 54% of LVO stroke patients are initially taken to non-EVT-capable hospitals, resulting in an average delay of 1 hour in time-to-EVT in the Netherlands. To reduce this delay, it is crucial for ambulance personnel to identify potential LVO stroke patients and directly transport them to EVT-capable hospitals. Dry electrode electroencephalography (EEG) has shown high diagnostic accuracy for detecting LVO strokes, but in 32% of patients, the EEG signal quality was too poor to analyze.\n\nTo address this issue, TrianecT developed StrokePointer, a portable EEG-based triage device designed to collect and analyze EEG data in patients with suspected acute stroke. The objective of this study is to validate the effectiveness and safety of StrokePointer in detecting LVO stroke among patients with a suspected stroke in the pre-hospital setting.', 'detailedDescription': 'RATIONALE Endovascular thrombectomy (EVT) is the standard treatment for large vessel occlusion (LVO) stroke. However, EVT can only be performed in specialized hospitals and its effect on functional outcome rapidly decreases with passing time (time = brain). Since ambulance personnel cannot determine whether a patient has a stroke that is eligible for EVT, 54% of patients with an LVO stroke are primarily presented at a non-EVT capable hospital. These patients then require interhospital transfer, resulting in average delay in time-to-EVT of 1 hour in the Netherlands. Therefore, providing ambulance personnel with tools to identify patients with a possible LVO stroke in the ambulance, allowing direct transport to an EVT capable hospital, is much needed. Dry electrode electroencephalography (EEG) has shown to have a high diagnostic accuracy for LVO stroke detection among patients with a suspected stroke (area under the receiving operating curve \\[AUC\\]: 0.91). However, in 32% of patients EEG signal quality was too poor to analyse. A new portable EEG-based triage device (StrokePointer) has been developed by TrianecT with the aim to collect and analyse EEG data in patients suspected of acute stroke. In this study, we intend to validate the safety and effectiveness of the device.\n\nHYPOTHESIS:\n\n1. StrokePointer device can measure EEG data of sufficient quality in \\>85% of patients, and has a good diagnostic accuracy (AUC\\>0.8) for LVO stroke detection in the pre-hospital setting.\n2. Usability of StrokePointer device is rated as "good" on average by ambulance personnel.\n3. StrokePointer is safe to use in an acute care setting.\n\nOBJECTIVE Primary objective is to validate the data quality and diagnostic accuracy of StrokePointer to detect LVO stroke among patients with a suspected stroke in the pre-hospital setting.\n\nSTUDY DESIGN CROSSROADS-EEG is an investigator-initiated, prospective, multi-centre cohort study.\n\nSTUDY POPULATION Adult patients with a suspected stroke, onset of symptoms (or last seen well) \\<24 hours in the pre-hospital setting.\n\nINTERVENTION A single measurement with a dry electrode headset EEG (approximately 2 minutes recording duration) will be performed in each patient. Clinical and radiological data will be collected. EEG data will be acquired with the improved TrianecT EEG device, StrokePointer.\n\nMAIN STUDY END POINTS\n\n* Proportion of patients with a technically successful EEG dataset: at least 20 seconds of usable EEG (at least 3 electrodes with good skin-electrode quality on either side, no movement artifacts, no muscle artifacts) within a measurement time of 3 minutes.\n* Diagnostic accuracy of StrokePointer for LVO stroke among patients with a suspected stroke, as measured with AUC as well as sensitivity and specificity.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Suspected acute stroke as per judgement of the ambulance personnel.\n* Age 18 years or older.\n* Onset of symptoms (or last seen well) \\<24 hours.\n* Written informed consent by patient or legal representative (deferred).\n\nExclusion Criteria:\n\n\\- Injuries or infections of the scalp in the area of the electrode headset placement.'}, 'identificationModule': {'nctId': 'NCT06871969', 'acronym': 'CROSSROADS-EEG', 'briefTitle': 'Clinical Evaluation of EEG Device for the Triage of Stroke Patients in the Ambulance', 'organization': {'class': 'OTHER', 'fullName': 'Academisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA)'}, 'officialTitle': 'Clinical Evaluation of Pre-hospital Stroke Triage Devices - Electroencephalography', 'orgStudyIdInfo': {'id': 'NL85665.000.23'}}, 'armsInterventionsModule': {'armGroups': [{'type': 'EXPERIMENTAL', 'label': 'Dry electrode StrokePointer EEG', 'description': 'All patients that are included in the study will undergo a dry electrode electroencephalography (EEG).', 'interventionNames': ['Diagnostic Test: Dry electrode EEG']}], 'interventions': [{'name': 'Dry electrode EEG', 'type': 'DIAGNOSTIC_TEST', 'description': 'A single dry electrode electroencephalography (EEG) will be performed in each patient that is included in this study. EEG data will be acquired with Strokepointer (TrianecT B.V., Utrecht, The Netherlands).\n\nStrokePointer is a portable EEG acquisition and analysis device. The device consists of three parts: (1) StrokePointer headset with dry electrodes to measure EEG data, (2) Portable StrokePointer suitcase that contains a mobile computing device (Android phone), CE-marked (IIa) EEG amplifier and storage compartments and (3) Software to acquire, analyse and upload EEG data.', 'armGroupLabels': ['Dry electrode StrokePointer EEG']}]}, 'contactsLocationsModule': {'locations': [{'zip': '1105AZ', 'city': 'Amsterdam', 'state': 'North Holland', 'status': 'RECRUITING', 'country': 'Netherlands', 'contacts': [{'name': 'Maud BRC Eurlings, MD', 'role': 'CONTACT', 'email': 'm.b.r.c.eurlings@amsterdamumc.nl', 'phone': '0031 20 566 9111'}, {'name': 'Jonathan M Coutinho, MD, PhD', 'role': 'CONTACT', 'email': 'j.coutinho@amsterdamumc.nl', 'phone': '0031 20 566 9111'}, {'name': 'Jonathan M Coutinho, MD, PhD', 'role': 'PRINCIPAL_INVESTIGATOR'}], 'facility': 'Amsterdam University Medical Centers, location AMC', 'geoPoint': {'lat': 52.37403, 'lon': 4.88969}}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Academisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA)', 'class': 'OTHER'}, 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'MD, PhD, neurologist, Principal Investigator', 'investigatorFullName': 'Jonathan Coutinho', 'investigatorAffiliation': 'Academisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA)'}}}}