Outcome
Type |
Measure |
Description |
Time frame |
Safety issue |
Primary |
One or more novel AI-based EEG algorithms based on dry electrode EEG-data with optimal diagnostic accuracy for LVO-a |
One or more novel artificial intelligence (AI) based electroencephalography (EEG) algorithms (the AI-STROKE algorithms) with maximal diagnostic accuracy to identify patients with an large vessel occlusion of the anterior circulation (LVO-a) in a population of patients with suspected acute ischemic stroke. For each patient a single dry electrode electroencephalography (EEG) will be performed and the presence or absence of an LVO-a will be assessed based on CT angiography data acquired at the emergency department. |
EEG-data for development of the algorithm will be recorded within 24 hours after onset of symptoms or last seen well |
|
Secondary |
AUC of the AI-STROKE algorithms for diagnosis of LVO-a |
Area under the receiver operating characteristic curve (AUC) of the AI-STROKE algorithms based on ambulant electroencephalography (EEG) for diagnosis of large vessel occlusion of the anterior circulation (LVO-a) in suspected acute ischemic stroke patients in the prehospital setting. For each patient a single dry electrode electroencephalography (EEG) will be performed and the presence or absence of an LVO-a will be assessed based on CT angiography data acquired at the emergency department. |
EEG-data for development of the algorithm will be recorded within 24 hours after onset of symptoms or last seen well |
|
Secondary |
Sensitivity of the AI-STROKE algorithms for diagnosis of LVO-a |
Sensitivity of the AI-STROKE algorithms based on ambulant electroencephalography (EEG) for diagnosis of large vessel occlusion of the anterior circulation (LVO-a) in suspected acute ischemic stroke patients in the prehospital setting. For each patient a single dry electrode electroencephalography (EEG) will be performed and the presence or absence of an LVO-a will be assessed based on CT angiography data acquired at the emergency department. |
EEG-data for development of the algorithm will be recorded within 24 hours after onset of symptoms or last seen well |
|
Secondary |
Specificity of the AI-STROKE algorithms for diagnosis of LVO-a |
Specificity of the AI-STROKE algorithms based on ambulant electroencephalography (EEG) for diagnosis of large vessel occlusion of the anterior circulation (LVO-a) in suspected acute ischemic stroke patients in the prehospital setting. For each patient a single dry electrode electroencephalography (EEG) will be performed and the presence or absence of an LVO-a will be assessed based on CT angiography data acquired at the emergency department. |
EEG-data for development of the algorithm will be recorded within 24 hours after onset of symptoms or last seen well |
|
Secondary |
PPV of the AI-STROKE algorithms for diagnosis of LVO-a |
Positive predictive value (PPV) of the AI-STROKE algorithms based on ambulant electroencephalography (EEG) for diagnosis of large vessel occlusion of the anterior circulation (LVO-a) in suspected acute ischemic stroke patients in the prehospital setting. For each patient a single dry electrode electroencephalography (EEG) will be performed and the presence or absence of an LVO-a will be assessed based on CT angiography data acquired at the emergency department. |
EEG-data for development of the algorithm will be recorded within 24 hours after onset of symptoms or last seen well |
|
Secondary |
NPV of the AI-STROKE algorithms for diagnosis of LVO-a |
Negative predictive value (NPV) of the AI-STROKE algorithms based on ambulant electroencephalography (EEG) for diagnosis of large vessel occlusion of the anterior circulation (LVO-a) in suspected acute ischemic stroke patients in the prehospital setting. For each patient a single dry electrode electroencephalography (EEG) will be performed and the presence or absence of an LVO-a will be assessed based on CT angiography data acquired at the emergency department. |
EEG-data for development of the algorithm will be recorded within 24 hours after onset of symptoms or last seen well |
|
Secondary |
AUC of existing EEG algorithms for diagnosis of LVO-a |
Area under the receiver operating characteristic curve (AUC) of existing electroencephalography (EEG) algorithms based on ambulant EEG for diagnosis of large vessel occlusion of the anterior circulation (LVO-a) in suspected acute ischemic stroke patients in the prehospital setting. For each patient a single dry electrode electroencephalography (EEG) will be performed and the presence or absence of an LVO-a will be assessed based on CT angiography data acquired at the emergency department. |
EEG-data for development of the algorithm will be recorded within 24 hours after onset of symptoms or last seen well |
|
Secondary |
Sensitivity of existing EEG algorithms for diagnosis of LVO-a |
Sensitivity of existing electroencephalography (EEG) algorithms based on ambulant EEG for diagnosis of large vessel occlusion of the anterior circulation (LVO-a) in suspected acute ischemic stroke patients in the prehospital setting. For each patient a single dry electrode electroencephalography (EEG) will be performed and the presence or absence of an LVO-a will be assessed based on CT angiography data acquired at the emergency department. |
EEG-data for development of the algorithm will be recorded within 24 hours after onset of symptoms or last seen well |
|
Secondary |
Specificity of existing EEG algorithms for diagnosis of LVO-a |
Specificity of existing electroencephalography (EEG) algorithms based on ambulant EEG for diagnosis of large vessel occlusion of the anterior circulation (LVO-a) in suspected acute ischemic stroke patients in the prehospital setting. For each patient a single dry electrode electroencephalography (EEG) will be performed and the presence or absence of an LVO-a will be assessed based on CT angiography data acquired at the emergency department. |
EEG-data for development of the algorithm will be recorded within 24 hours after onset of symptoms or last seen well |
|
Secondary |
PPV of existing EEG algorithms for diagnosis of LVO-a |
Positive predictive value (PPV) of existing electroencephalography (EEG) algorithms based on ambulant EEG for diagnosis of large vessel occlusion of the anterior circulation (LVO-a) in suspected acute ischemic stroke patients in the prehospital setting. For each patient a single dry electrode electroencephalography (EEG) will be performed and the presence or absence of an LVO-a will be assessed based on CT angiography data acquired at the emergency department. |
EEG-data for development of the algorithm will be recorded within 24 hours after onset of symptoms or last seen well |
|
Secondary |
NPV of existing EEG algorithms for diagnosis of LVO-a |
Negative predictive value (NPV) of existing electroencephalography (EEG) algorithms based on ambulant EEG for diagnosis of large vessel occlusion of the anterior circulation (LVO-a) in suspected acute ischemic stroke patients in the prehospital setting. For each patient a single dry electrode electroencephalography (EEG) will be performed and the presence or absence of an LVO-a will be assessed based on CT angiography data acquired at the emergency department. |
EEG-data for development of the algorithm will be recorded within 24 hours after onset of symptoms or last seen well |
|
Secondary |
AUC of existing and newly developed EEG algorithms for detection of LVO-p, intracerebral hemorrhage, transient ischemic attack, and stroke mimics |
Area under the receiver operating characteristic curve (AUC) of existing and newly developed electroencephalography (EEG) algorithms based on ambulant EEG for detection of an large vessel occlusion of the posterior circulation (LVO-p), intracerebral hemorrhage, transient ischemic attack, and stroke mimics. |
EEG-data for development of the algorithm will be recorded within 24 hours after onset of symptoms or last seen well |
|
Secondary |
Sensitivity of existing and newly developed EEG algorithms for detection of LVO-p, intracerebral hemorrhage, transient ischemic attack, and stroke mimics |
Sensitivity of existing and newly developed electroencephalography (EEG) algorithms based on ambulant EEG for detection of an large vessel occlusion of the posterior circulation (LVO-p), intracerebral hemorrhage, transient ischemic attack, and stroke mimics. |
EEG-data for development of the algorithm will be recorded within 24 hours after onset of symptoms or last seen well |
|
Secondary |
Specificity of existing and newly developed EEG algorithms for detection of LVO-p, intracerebral hemorrhage, transient ischemic attack, and stroke mimics |
Specificity of existing and newly developed electroencephalography (EEG) algorithms based on ambulant EEG for detection of an large vessel occlusion of the posterior circulation (LVO-p), intracerebral hemorrhage, transient ischemic attack, and stroke mimics. |
EEG-data for development of the algorithm will be recorded within 24 hours after onset of symptoms or last seen well |
|
Secondary |
PPV of existing and newly developed EEG algorithms for detection of LVO-p, intracerebral hemorrhage, transient ischemic attack, and stroke mimics |
Positive predictive value (PPV) of existing and newly developed electroencephalography (EEG) algorithms based on ambulant EEG for detection of an large vessel occlusion of the posterior circulation (LVO-p), intracerebral hemorrhage, transient ischemic attack, and stroke mimics. |
EEG-data for development of the algorithm will be recorded within 24 hours after onset of symptoms or last seen well |
|
Secondary |
NPV of existing and newly developed EEG algorithms for detection of LVO-p, intracerebral hemorrhage, transient ischemic attack, and stroke mimics |
Negative predictive value (NPV) of existing and newly developed electroencephalography (EEG) algorithms based on ambulant EEG for detection of an large vessel occlusion of the posterior circulation (LVO-p), intracerebral hemorrhage, transient ischemic attack, and stroke mimics. |
EEG-data for development of the algorithm will be recorded within 24 hours after onset of symptoms or last seen well |
|
Secondary |
Technical feasibility of performing ambulant EEGs in the prehospital setting |
Assessing whether it is technically possible for paramedics to perform ambulant electroencephalography (EEG) in patients with a suspected AIS in the prehospital setting. |
Feedback on technical issues by the paramedic that performs the EEG and by the EEG-expert, will be collected directly at arrival in the emergency department (within 24 hours after the patient is included in the study) |
|
Secondary |
Logistical feasibility of performing ambulant EEGs in the prehospital setting |
Assessing whether it is logistically possible for paramedics to perform ambulant electroencephalography (EEG) in patients with a suspected AIS in the prehospital setting. |
Feedback on logistical issues by the paramedic that performs the EEG, will be collected directly at arrival in the emergency department (within 24 hours after the patient is included in the study) |
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