Monitoring Neurological Deterioration in Anaesthetised Patients With Electroencephalogram (EEG)
Monitoring Neurological Deterioration in Anaesthetised Patients With Electroencephalogram (EEG)
The incidence of perioperative stroke in the non-cardiac, non-vascular, non-neurological high
 risk surgical population is 2%. It is higher (~5%) for cardiac surgery and carotid
 endarterectomy patients, with a stroke associated mortality of up to 60%. These patients
 could be immediately treated if their condition was detected on time. Currently, there is no
 standard brain monitoring procedure for anaesthetised patients. The purpose of the proposed
 study is to optimize and validate an online monitor for neurological deterioration under
 anaesthesia based on an easily operatable EEG system comprised of 4 electrodes, a reference
 electrode and a newely developed algorithm for analyzing the EEG signal. The monitor aims at
 generating an immediate warning at the onset of neurological deterioration. For the purpose
 of technology development with a minimal sample size, it is necessary to select a patient
 population that demonstrates significant neurological dynamics under anaesthesia. We will
 therefore focus on anesthesized patients undergoing neurovascular thrombectomy after CVA.
The research aim is to validate a novel ground-breaking and easy-to-use EEG-based algorithm
 for sensing cerebrovascular accident (CVA) events under anaesthesia. Today there is no
 standard tool for CVA detection in anaesthetized patients. Thus the possibility of waking up
 from anaesthesia with severe brain damage is devastating. Patients undergoing cardiac surgery
 (such as valve replacement, CABG, thoracic aorta replacement, PTCA, TAVI (trans-aortic valve
 implantation)), carotid endarterectomy and surgery in sitting position, are at exceptionally
 high risk. We have developed a unique algorithm for detecting brain ischemia in anaesthetized
 patients, based on data acquired from 4 EEG electrodes. Our final goal is to develop a system
 that triggers an alarm when an ischemia occurs in an anaesthetized patient and during the
 peri-operative period.

 In order to validate and optimize our system, we require a small sample size to test and
 validate the technology. The population for this study includes patients with acute CVA who
 undergo mechanical thrombectomy under anaesthesia. Although these patients already have CVA,
 clinical dynamics is high in this population, and will enable a demonstration of our ability
 to recognize immediate changes in neurological status (improvement or deterioration).

 We believe this innovative EEG based system could be of major significance to millions of
 patients annually.
Inclusion Criteria:

 -  Informed consent (by individual or guardian)

 -  Undergoing thrombectomy procedure under anaesthesia for acute CVA

 -  for control:

 -  Healthy individual, with no neurological disease undergoing sedation for procedure

 Exclusion Criteria:

 -  Age < 18 years

 -  no informed consent