Principal Investigator: Safdar  Ansari
Keywords: Wireless EEG , Coma Department: Neurology
IRB Number: 00059288
Specialty: Neurology
Sub Specialties: EEG
Recruitment Status: Not yet recruiting

Contact Information

Julie  Martinez

Brief Summary

Despite its clinical significance, the pathophysiology of coma is still under investigation and the physiology of emergence from coma remains a mystery. Furthermore, predictors of emergence from coma, despite their obvious clinical value, remain un-established. Because of its low arousal state and hypothesized parallel neurophysiological mechanisms, sleep has been studied as both an animal and human model of coma, and awakening from sleep has likewise been studied as a surrogate of coma emergence. In this study, we will determine whether certain electrographic patterns, known as spectral shifts, which have correlates in normal sleep, are predictive of eventual awakening from coma and the time course of this emergence. To detect spectral shifts in comatose patients, EEG monitoring must be performed for several days. Quick, simple, and reliable EEG recording in the ICU will be enhanced by a small device that can be easily and properly positioned on the head by hospital personnel and which lacks cumbersome cables or receivers. Traditional EEG monitoring requires placement of up to 25 wires, which can impede efficient intensive patient care. Our hypothesis is that we can detect a difference in spectral shifts in comatose patients who will eventually emerge from coma as compared to comatose patients who do not wake up and that a wireless EEG patch-type device can effectively make this distinction.

Inclusion Criteria

All patients with brain injuries admitted to the NCCU will be screened for enrollment. The estimated enrollment will be for 100 patients. 90 patients will be comatose with GCS < 9. The other 10 patients will be control, non-comatose patients for quality control of the device. Consent for inclusion will be obtained from the patient or next of kin for all enrolled patients.

Exclusion Criteria