Predictive value of quantitative electroencephalogram in the poor outcome of children with non-traumatic disturbance of consciousness in pediatric intensive care unit
10.3760/cma.j.cn112140-20201126-01058
- VernacularTitle:量化脑电图对儿童重症监护病房非创伤性意识障碍患儿不良结局的预测价值
- Author:
Wu ZHAO
1
;
Yi LIU
;
Huiru PAN
;
Ke GAO
;
Hang HANG
Author Information
1. 蚌埠医学院第一附属医院儿科233004
- Keywords:
Electroencephalography;
Consciousness disorders;
Prognosis;
Child
- From:
Chinese Journal of Pediatrics
2021;59(5):374-379
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore the predictive value of quantitative electroencephalogram (qEEG) in the poor outcome of children with non-traumatic disturbance of consciousness (DoC) in the pediatric intensive care unit (PICU).Methods:A prospective study was conducted. From January 2019 to May 2019, a total of 62 patients aged from 1 month to 11 years with non-traumatic DoC in the PICU of the First Affiliated Hospital of Bengbu Medical College were enrolled. Bedside monitoring with NicoletOne monitor was performed within 24 hours after admission, and qEEG parameters, including amplitude-integrated electroencephalogram (aEEG), relative alpha variability (RAV), relative band power (RBP), and spectral entropy (SE) were recorded. The state of consciousness was assessed with modified pediatric Glasgow coma scale (MPGCS) before monitoring. According to the pediatric cerebral performance category score at 1 year after discharge, the enrolled subjects were divided into good and poor outcome groups. The association between these variables and the poor outcome was analyzed by univariate and multivariate logistic regression analysis, and the predictive performance was analyzed by receiver operator characteristic (ROC) curve.Results:There were 39 males and 23 females, with the age of 12.0 (5.8, 24.0) months. Fifty patients (81%) were in the good outcome group and 12 patients (19%) in the poor outcome group. The univariate Logistic regression analysis showed that age ( OR=1.037, 95% CI 1.001-1.074, P=0.041), severe abnormal aEEG ( OR=128.000, 95% CI 10.274-1 594.656, P<0.01), RAV ( OR=0.877, 95% CI 0.810-0.949, P=0.001), SE ( OR=0.892, 95% CI 0.814-0.978, P=0.015), and MPGCS score ( OR=0.511, 95% CI 0.349-0.747, P=0.001) were significantly associated with the poor outcome. However, the multivariate Logistic regression analysis showed that only severe abnormal aEEG ( OR=315.692, 95% CI 6.091-16 362.298, P=0.004) and RAV ( OR=0.808, 95% CI 0.664-0.983, P=0.033) were significantly associated with the poor outcome. The area under the curve (AUC) of the aEEG and RAV in predicting the poor outcome were 0.848 (95% CI 0.735-0.927, P<0.01) and 0.847 (95% CI 0.733-0.926, P<0.01), respectively. The optimal cut-off value was severe abnormal for the aEEG and 38% for the RAV, with sensitivity of 67% and 83%, specificity of 98% and 84%, positive predictive value of 89% and 55%, negative predictive value of 92% and 95%, and Youden index of 0.647 and 0.673, respectively. The AUC of the novel combined index of aEEG and RAV for predicting the poor outcome was 0.974 (95% CI 0.898-0.998, P<0.01). Conclusions:The aEEG and RAV are reliable predictors for the poor outcome of children with non-traumatic DoC, and the novel combined index of aEEG and RAV can improve the predictive performance. The qEEG can be used as a routine method for outcome assessment due to its good objectivity.
