[Combining relative alpha variability and electroencephalogram reactivity to predict the prognosis of hypoxic-ischemic encephalopathy in adult patients].

Objective: To evaluate the role of combining relative alpha variability and electroencephalogram (EEG) reactivity to predict the prognosis of hypoxic-ischemic encephalopathy(HIE) in adult patients. Methods: A total of 28 adult patients with HIE admitted to general intensive care unit at Xiangya Hospital in Central South University were enrolled in this observational study from January2016 to April 2017. These patients with body temperature over 35℃ after 72-hour admission could be continuously monitored at least 12 hours byEEG.At the same time,each patient was assessed for EEG reactivity.Then we analyzed the correlation between EEG reactivity, relative alpha variability and clinical prognosis. Results: EEG reactivity was elicited in 15/28 patients, among whom 12 patients had a good outcome. While in the other 13 patients, EEG reactivity was not elicited, among whom only 3 patients had a good outcome. As to the results ofrelative alpha variability,11/13 patients with degree 3-4were of good prognosis; while only 3/15 patients with degree 1-2 were of good prognosis. Glasgow coma scale(GCS), EEG reactivity, and relative alpha variability were correlated with clinical outcome(χ(2)=5.073,9.073,-3.626, respectively,all P<0.05). The sensitivity of GCS, EEG reactivity, and relative alpha variability to predict the poor prognosis were 69.2%, 76.9%, 84.6%, respectively. The specificity were 73.3%, 80.0%, 73.3%, respectively. The consistency rates were 71.4%, 78.6%, 78.6%, respectively. The positive predictive values were 69.2%, 76.9%, 73.3%, respectively. The negative predictive values were 73.3%, 80.0%, 84.6%, respectively. More importantly, the accuracy of the relative alpha variability combined with EEG reactivity for the prediction of poor prognosis was much higher with the positive predictive value of 90.0%,the specificity of 93.3%, the sensitivity of 69.2%, the consistency rate of 82.1%,and the negative predictive values of 77.8%. Conclusions: The combination of relative alpha variability and EEG reactivityis reliable to predict clinical outcome of patients with HIE.

Combining relative alpha variability and electroencephalogram reactivity to predict the prognosis of hypoxic?ischemic encephalopathy in adult patients / 中华内科杂志

Objective To evaluate the role of combining relative alpha variability and electroencephalogram (EEG) reactivity to predict the prognosis of hypoxic?ischemic encephalopathy(HIE) in adult patients. Methods A total of 28 adult patients with HIE admitted to general intensive care unit at Xiangya Hospital in Central South University were enrolled in this observational study from January2016 to April 2017. These patients with body temperature over 35℃after 72?hour admission could be continuously monitored at least 12 hours byEEG.At the same time,each patient was assessed for EEG reactivity.Then we analyzed the correlation between EEG reactivity, relative alpha variability and clinical prognosis. Results EEG reactivity was elicited in 15/28 patients, among whom 12 patients had a good outcome. While in the other 13 patients, EEG reactivity was not elicited, among whom only 3 patients had a good outcome. As to the results ofrelative alpha variability,11/13 patients with degree 3?4were of good prognosis; while only 3/15 patients with degree 1?2 were of good prognosis. Glasgow coma scale(GCS), EEG reactivity, and relative alpha variability were correlated with clinical outcome(χ2=5.073,9.073,-3.626, respectively,all P<0.05). The sensitivity of GCS, EEG reactivity,and relative alpha variability to predict the poor prognosis were 69.2%, 76.9%, 84.6%, respectively. The specificity were 73.3%, 80.0%, 73.3%, respectively. The consistency rates were 71.4%, 78.6%, 78.6%, respectively. The positive predictive values were 69.2%, 76.9%, 73.3%, respectively. The negative predictive values were 73.3%, 80.0%, 84.6%, respectively. More importantly, the accuracy of the relative alpha variability combined with EEG reactivity for the prediction of poor prognosis was much higher with the positive predictive value of 90.0%,the specificity of 93.3%,the sensitivity of 69.2%, the consistency rate of 82.1%,and the negative predictive values of 77.8%. Conclusions The combination of relative alpha variability and EEG reactivityis reliable to predict clinical outcome of patients with HIE.

Predictive value of EEG-awakening for behavioral awakening from coma.

BACKGROUND: A reliable predictor for early recovery of consciousness in comatose patients is of great clinical significance. Here we aimed to investigate the potentially prognostic value of electroencephalogram-reactivity (EEG-R) in combination with sleep spindles, termed EEG-awakening, for behavioral awakening in etiologically diverse comatose patients. METHODS: We performed a prospectively observational study on a sample of patients, all of whom were in coma lasting longer than 3 days. Continuous EEG monitoring was performed for at least 24 h to detect the presence of EEG-R and sleep spindles. We then followed patients for 1 month to determine their subsequent level of consciousness, classifying them as either awakened or non-awakened. Finally, Univariate and multivariate analyses were employed to assess the association of predictors with consciousness recovery. RESULTS: One hundred and six patients with different etiologies leading to coma were included in the study. Of these, 48 patients (45.3 %) awoke and 58 patients (54.7 %) did not awake in the month after the onset of the study. Of note, 26 patients (24.5 %) had a good neurological outcome, and 31 patients (29.3 %) died. Univariate analysis revealed that the Glasgow Coma Scale (GCS) score, EEG-R, sleep spindles, and EEG-awakening were all associated with one-month awakening. Comparisons of the area under the receiving operator characteristic curve (AUC) showed that EEG-awakening (0.839; 0.757-0.921) was superior to all of the following: EEG-R (0.798; 0.710-0.886), sleep spindles (0.772; 0.680-0.864), and GCS scores (0.720; 0.623-0.818). However, age, gender, etiology, and pupillary light reflex did not correlate significantly with one-month awakening. Further logistic regression analysis showed that only EEG-awakening and GCS scores at study entry were significant independent predictors of awakening and that the prognostic model containing these two variables yielded an outstanding predictive performance with an AUC of 0.903. CONCLUSIONS: EEG-awakening incorporates both EEG-R and sleep spindles and is an excellent predictor for early behavioral awakening in comatose patients. The prognostic model combining EEG-awakening and GCS scores shows an outstanding discriminative power for awakening.