Clinical Evaluation of EEG Device for the Triage of Stroke Patients in the Ambulance

NCT ID: NCT06871969

Last Updated: 2025-10-03

Basic Information

• Recruitment Status: RECRUITING
• Clinical Phase: NA
• Total Enrollment: 275 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2025-07-01
• Study Completion Date: 2026-12-31

Brief Summary

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.

To 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.

Detailed Description

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.

HYPOTHESIS:

1. 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.

2. Usability of StrokePointer device is rated as "good" on average by ambulance personnel.

3. StrokePointer is safe to use in an acute care setting.

OBJECTIVE 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.

STUDY DESIGN CROSSROADS-EEG is an investigator-initiated, prospective, multi-centre cohort study.

STUDY POPULATION Adult patients with a suspected stroke, onset of symptoms (or last seen well) <24 hours in the pre-hospital setting.

INTERVENTION 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.

MAIN STUDY END POINTS

• 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.
• Diagnostic accuracy of StrokePointer for LVO stroke among patients with a suspected stroke, as measured with AUC as well as sensitivity and specificity.

Conditions

Ischemic Stroke; Stroke; Cardiovascular Diseases; Vascular Diseases; Central Nervous System Diseases; Brain Diseases; Nervous System Diseases; Cerebrovascular Disease

Study Design

• Allocation Method: NA
• Intervention Model: SINGLE_GROUP
• Primary Study Purpose: DIAGNOSTIC
• Blinding Strategy: NONE

Study Groups

Dry electrode StrokePointer EEG

All patients that are included in the study will undergo a dry electrode electroencephalography (EEG).

Group Type: EXPERIMENTAL

Dry electrode EEG

Intervention Type: DIAGNOSTIC_TEST

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).

StrokePointer 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.

Interventions

Dry electrode EEG

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).

StrokePointer 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.

Intervention Type: DIAGNOSTIC_TEST

Eligibility Criteria

Inclusion Criteria

• Suspected acute stroke as per judgement of the ambulance personnel.
• Age 18 years or older.
• Onset of symptoms (or last seen well) <24 hours.
• Written informed consent by patient or legal representative (deferred).

Exclusion Criteria

• Injuries or infections of the scalp in the area of the electrode headset placement.

• Minimum Eligible Age: 18 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Academisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA)

OTHER

Sponsor Role: lead

Responsible Party

Jonathan Coutinho

MD, PhD, neurologist, Principal Investigator

Responsibility Role: PRINCIPAL_INVESTIGATOR

Locations

Amsterdam University Medical Centers, location AMC

Amsterdam, North Holland, Netherlands

Site Status: RECRUITING

Countries

Netherlands

Facility Contacts

Maud BRC Eurlings, MD

Role: primary

m.b.r.c.eurlings@amsterdamumc.nl

0031 20 566 9111

Jonathan M Coutinho, MD, PhD

Role: backup

j.coutinho@amsterdamumc.nl

0031 20 566 9111

Other Identifiers

NL85665.000.23

Identifier Type: -

Identifier Source: org_study_id