Automated external defibrillators (AEDs) have become the mainstay technology of resuscitation after cardiac arrest. It is well established that electrical stimulation can re-start the arrested myocardium and therapeutically modulate the heart beat rythm. Yet a similar resuscitation technology to facilitate the recovery of physiologically normal brain activity in the critical hours following cardiac resuscitation does not currently exist. After a cardiopulmonary arrest and return of spontaneous circulation, 80% of all patients reach the ICU in a comatose state and of these patients, only 20% will survive and regain consciousness. Moreover, as many as 45% of the pediatric patients will die within 1 week after cardiac resuscitation despite having recovered spontaneous circulation, of which 81% are pronounced dead or disconnected from life-support due to neurological damage. A key indicator of such damage is the insufficient recovery of normal EEG activity or the bilateral absence of N20 waves of short-latency somato sensory evoked potentials. While therapeutic hypothermia and fever avoidance provide some neuroprotection, new technologies are clearly needed to support the recovery of normal brain patterns after resuscitation and increase survival. Recently, one of the partners in the DeepSpark consortium discovered of hypoxia-resilient neurons in the cortex of primates up to 2 hours after total arrest of cardiac activity. We propose that closed-loop selective brain stimulation, time-locked to these neuronal pools, could serve as a trigger of EEG pattern normalization. Artificial Intelligence deep-learning will be used to set optimal stimulation parameters for vagus nerve and transcranial stimulation as a function of real-time EEG, transcranial infra-read oxygenation and metabolic data, and doppler ultra-sound blood flow information. The technology developed by the consortium could become a key tool against irreversible decay of brain activity after resuscitation.
Project leader: Enric Claverol
Institution: AFFERENT TECHNOLOGIES AS