Stroke, cerebrovascular accident Stroke
Conditions
Interventions
The StrokePointer shEEG device, with electroencephalography electrodes below the hairline for detection of stroke
Sponsors
Amsterdam UMC
Eligibility
Age
18 Years to 99 Years
Inclusion criteria
Inclusion criteria: In order to be eligible to participate in this study, all subjects must meet the following criterion: - Age of 18 years or older - Written informed consent Furthermore, suspected stroke patients must meet all of the following criteria: - Suspected stroke as per judgement of the ambulance personnel or a confirmed LVO stroke - Onset of symptoms or last seen well <24 hours before shEEG data acquisition
Exclusion criteria
Exclusion criteria: - Skin defect or active infection of the scalp in the area of electrode placement
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| A shEEG-based AI-algorithm with optimal diagnostic accuracy for the detection of LVO stroke of the anterior circulation among patients with a suspected stroke. The final diagnosis of all patients will be established by an adjudication committee, which will consist of a vascular neurologist and neuroradiologist, and will be based on available clinical and imaging data. For the purpose of the study, an LVO stoke is defined as an occlusion of: - Intracranial part of the internal carotid artery (ICA) - First segment or proximal part of the second segment of the middle cerebral artery (M1 and proximal M2, respectively) - First segment of the anterior cerebral artery (A1) | — |
Secondary
| Measure | Time frame |
|---|---|
| The secondary study endpoints include: - The user-friendliness rating of the StrokePointer shEEG device by ambulance personnel in terms of EEG recording preparation time, usability of the StrokePointer shEEG patch (scored as XX ) and usability of the StrokePointer shEEG software (scored as XX) - Safety assessment of the StrokePointer shEEG device, i.e. the number of serious adverse device-related events and the number of healthy subjects and patients with an (allergic) skin reaction observed at the placement area of the shEEG patch - The proportion of suspected stroke patients with a technically successful shEEG dataset, i.e. at least 10 seconds of shEEG data with no to minimal artifacts, in the ER and prehospital setting - The diagnostic accuracy of existing EEG-based algorithms and the newly developed shEEG-based AI-algorithm for LVO stroke detection among patients with a suspected stroke, as measured with AUC as well as sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) - The diagnostic accuracy of existing shEEG-based algorithms and newly developed shEEG-based AI-algorithms for the detection of LVO stroke of the posterior circulation, intracerebral hemorrhage, transient ischemic attack and stroke mimics, as measured with AUC as well as sensitivity, specificity, PPV and NPV - The diagnostic accuracy of existing EEG-based algorithms in combination with clinical scales for LVO stroke detection among patients with a suspected stroke, as measured with AUC as well as sensitivity, specificity, PPV and NPV - Differences between shEEG electrodes and conventional EEG electrodes in signal quality, noise level and power spectral density | — |
Countries
Netherlands
Contacts
Public ContactM.J. Spaaks
Amsterdam UMC
Outcome results
None listed