Early recovery of frontal EEG slow wave activity during propofol sedation predicts outcome after cardiac arrest

Abstract

Aim of the study: EEG slow wave activity (SWA) has shown prognostic potential in post-resuscitation care. In this prospective study, we investigated the accuracy of continuously measured early SWA for prediction of the outcome in comatose cardiac arrest (CA) survivors.Methods: We recorded EEG with a disposable self-adhesive frontal electrode and wireless device continuously starting from ICU admission until 48 h from return of spontaneous circulation (ROSC) in comatose CA survivors sedated with propofol. We determined SWA by offline calculation of C-Trend 1 Index describing SWA as a score ranging from 0 to 100. The functional outcome was defined based on Cerebral Performance Category (CPC) at 6 months after the CA to either good (CPC 1À2) or poor (CPC 3À5).Results: Outcome at six months was good in 67 of the 93 patients. During the first 12 h after ROSC, the median C-Trend Index value was 38.8 (interquartile range 28.0À56.1) in patients with good outcome and 6.49 (3.01À18.2) in those with poor outcome showing significant difference (p < 0.001) at every hour between the groups. The index values of the first 12 h predicted poor outcome with an area under curve of 0.86 (95% CI 0.61À0.99). With a cutoff value of 20, the sensitivity was 83.3% (69.6%À92.3%) and specificity 94.7% (83.4%À99.7%) for categorization of outcome. Conclusion:EEG SWA measured with C-Trend Index during propofol sedation offers a promising practical approach for early bedside evaluation of recovery of brain function and prediction of outcome after CA.

Monitoring of nighttime EEG slow‐wave activity during dexmedetomidine infusion in patients with hyperactive ICU delirium: An observational pilot study

“…C‐Trend is a CE marked medical device software that utilizes artificial intelligence in producing a parameter, C‐Trend Index, of the SWA in EEG. The parameter ranges from 0 to 100 in values, values above 80 referring to high normal SWA and values below 50 referring to abnormal or low SWA 17 . The software automatically rejects data sequences it considers to contain too much noise.…”

“…The parameter ranges from 0 to 100 in values, values above 80 referring to high normal SWA and values below 50 referring to abnormal or low SWA. 17 The software automatically rejects data sequences it considers to contain too much noise. The average index value calculated over the entire recording was used to indicate the average SWA.…”

“…In addition to the objective quantitative evaluation using EEG, the night shift nurse that spent the night bedside also clinically evaluated sleep at 6 a.m. using the Richards-Campbell Sleep Questionnaire (RCSQ). 18 For this analysis, the RCSQ parameters "sleep depth" and Sepsis, n (%) 5 (33) Total ICU length of stay, days 5.7 [4][5][6][7][8][9] Total hospital length of stay, days 15 [12][13][14][15][16][17][18][19][20][21][22][23][24][25][26] Good recovery at 3 months (cerebral performance category score <3) "sleep quality" were used, with a range from 0 to 100 for each parameter, with 100 corresponding to deep and good-quality sleep. Scores <70 were considered to indicate poor sleep quality and sleep depth.…”

Post–cardiac arrest Sedation Promotes Electroencephalographic Slow-wave Activity and Improves Survival in a Mouse Model of Cardiac Arrest

“…These results are in alignment with the recent clinical observation that early recovery of EEG slow-wave activity during propofol sedation is associated with favorable outcomes in comatose cardiac arrest survivors. 20 Slow oscillations have been considered as a shared EEG feature of general anesthesia and sleep in healthy brains. 14,21 Sedative-hypnotic agents cause neocortical neurons to oscillate at approximately 1 Hz between a depolarizing state of intense firing and a hyperpolarizing state of silence.…”

Long-Term Polygraphic Monitoring through MEMS and Charge Transfer for Low-Power Wearable Applications

“…Moreover, by providing real-time, long-term, and free-living dynamic information, new, noninvasive wearable solutions for EEG monitoring would support the differential diagnosis of pathological conditions characterized by transitory changes in focal brain activity, including epileptic and non-epileptic disorders, such as the loss of consciousness (i.e., cardiovascular syncope) and parasomnias (i.e., REM behavior disorder (RBD)) [ 6 , 7 ]. Lastly, a similar device would represent a feasible and practical tool also in hospital settings to continuously assess patients at the bedside, especially those suffering from specific pathological conditions, such as comatose survivors to cardiac arrest [ 8 ]. To testify the importance of portability, in the last few years, several wearable EEG devices have finally been introduced on the market.…”