Studys On Predictive Value Of Amplitude-integrated Electroencephalography On Severity And Prognosis In Comatose Patients

ObjectiveTo observe the changes of,to evaluate the accuracy,feasibility,and impact of amplitude-integrated electroencephalogram(aEEG) monitoring in acute comatose patiens with supratentorial lesion and to explore the predictive value of aEEG on severity and prognosis of comatose patients in order to seeking a new approach to evaluate the cerebral function(CF) of comatose patients at bedside.To provide objective evidence for medical decision making by judging patient's condition and predicting their outcome accurately.Methods217 patients with different disease and different level of consciousness were admitted in neurological intensive care unit(NICU) in Nan Fang Hospital from December 2007 to January 2009.We monitor all the patients' CF ambulatory including neurological examination and aEEG.The monitoring frequency of each patien varied from twice to 26 times.Nicolet one Monitor was used to record aEEG signle.The EEG signal for the single channel aEEG is usually recorded from one pair of parietally placed electrodes(corresponding to P₃ and P₄ according to the international EEG 10-20 classification,ground F_z).The signal is amplified and passed through an asymmetrical band-pass filter that strongly prefers higher frequencies over lower ones and suppresses activity below 2 Hz and above 15 Hz in order to minimise artefacts from such sources as sweating,movement,muscle activity and electrical interference.Additional processing includes semilogarithmic amplitude presentation,rectification,smoothing and considerable time compression.The signal is displayed on a semilogarithmic scale at slow speed(6 cm/h) at the cot side.A second tracing continuously displays the original EEG from either one or two channels.The electrode impedance is continuously recorded but not necessarily displayed,but there will be an alarm when there is high impedance,often due to a loose electrode.The band width in the output reflects variations in minimum and maximum EEG amplitude,both of which depend on the maturity and severity of illness of the newborn infant.Due to the semilogarithmic scale used to plot the output, changes in background activity of very low amplitude(＜5μV) are enhanced.The information in the aEEG trace can be enhanced by modifying the grey scale so that a particular spot is determined by the length of time spent at that spot.This feature is useful when defining the lower border of the trace and analysing changes caused by ictal periods and The duration of each aEEG monitoring was not less than 30 minutes.We used the software of NicoletOne monitor to transform raw electroencephalography(EEG) into aEEG.Cases admitted criteria:â‘ First evaluation performed in 3 days after onset.â‘¡Glasgow-Pittsberg coma scale(GPCS) score≤27.â‘¢Supratentorial lesion.Cases excluded criteria:â‘ Other diseases or factors such as metabolism and endocrine secretion diseases,shock,hypothermy,ect that affecting CF existed.â‘¡To be used with antiepileptic drugs(AEDs) or sedatives.â‘¢Obvious interfering artifact.â‘£Patient died of none central nervous system causes.63 cases(41 male,22 female,aged 15-87,average 54.8±20.0) met the criteria were brought into statistical analysis.Of all,cerebral infarction 26 cases,cerebral hemorrhage 11 cases, viral encephalitis 12cases,anoxic ischemic encephalopathy(HIE) 11 cases,multiple sclerosis 1 cases,suppurative encephalitis 1 cases,tuberculous encephalitisl case. NicoletOne monitor is one of the most advanced continuous EEG monitor at present. Raw EEG can be turned into some kinds of trends to reflect cerebral function changes directly by mathematical transformation.We used NicoletOne monitor to record aEEG.GPCS scores were counted at the same time.The results of aEEG were categorized into 3 grades(normal,mildly abnormal,severely abnormal aEEG).The judgement terminal time of prognosis was 3 monthes after onset or patien died in any time during the first 3 monthes.The prognosis results were categorized into 5 grades such as Gradeâ… :Good cerebral performance:conscious,alert,able to work, Gradeâ…¡:Moderate cerebral disability:conscious,can carry out independent activities, Gradeâ…¢:Severe neurological disability:conscious,dependent on others for daily support,Gradeâ…£:Coma or vegetative state,Gradeâ…¤:Dead.We regarded Gradeâ… and Gradeâ…¡as good outcome while Gradeâ…¢- Gradeâ…¤as poor outcome. Follow-up menthod:8 patients saw dodtor at out-patient regularly,5 patients through telephone,2 patients still stayed,2 patients were lost.SPSS13.0 was used as statistic software.The correlation between aEEG grade and severity of coma was analyzed with Spearman Bivariate Correlations.x² test was used in group comparison.ORC Curve was used to get the optimum Cutoff point of aEEG grade and the one of GPCS score.Concordance of aEEG grade and GPCS score that predicting outcomes of comatose patiemts was explored withκcoefficient test.P＜0.05 was considered statistically significant.ResultsIn the initial aEEG parttern of all 63 cases,29 patients(46.0%) showed normal aEEG,13 patients(20.6%)showed mildly abnormal aEEG,21 patients (33.3%)showed severely abnormal aEEG.Semicoma in 29 patients(46.0%),moderate coma in 24 patients(38.1%)and deep coma in 10 patients(15.9%).13 patients got good outcome,48 patients suffered poor outcome and 2 patients were lost to follow-up.The results of aEEG classification were positively correlated with the severity of coma(r_s=0.523,P=0.000).We regarded poor outcome as state variable, aEEG grade and GPCS score as test variable respectively.With ORC Curve analysis,the optimum cutoff point of aEEG grade was normal aEEG.The optimum cutoff point of GPCS score was at the level of 21-27.Normal aEEG was regarded as favourable indicator for outcome and abnormal aEEG(including mildly abnormal aEEG and severely abnormal aEEG) was regarded as unfavourable indicator for outcome.Difference of outcome between the patients with abnormal aEEG and the patients with normal aEEG was statistically significant(x²=9.01,P=0.003).We regarded GPCS score 21～27 as favourable indicator for outcome,GPCS score 7～14 and GPCS score 15～20 as unfavourable indicator for outcome.Difference of outcome between these two groups was statistically significant(x²=6.85,P=0.009). Sensitivity,specificity,positive predict value,negative predict value of abnormal aEEG predicting poor outcome was 65.5%,84.6%,93.8%,57.9%respectively. Sensitivity,specificity,positive predict value,negative predict value of GPCS score 7～14 and GPCS score 15～20 predicting poor outcome was 56.3%,84.6%,93.1 %,34.8%respectively.Concordance of aEEG grade and GPCS score that predicting outcomes of comatose patiemts was good(κ=0.438,P=0.007).In initial CF evaluation 5 patients fit the cerebral death criteria,all of their EEG were flat,aEEGs were severely abnormal aEEG,waveform P40 of their somatosensory evoked potentials(SEPs) disappeared.Severely abnormal aEEG predicting cerebral death had Sensitivity of 100.0%,specificity of 72.4%,positive predict value of 23.8%, negative predict value of 100.0%.In 29 patients with initial normal aEEG,we recorded their aEEG 2-7 times ambulatory.11 patients who got good outcome kept normal aEEG all the while.8 of the 18 patients suffered poor outcome retained normal aEEG,but 10 of them changed to show mildly abnormal aEEG and severely abnormal aEEG.In 13 patients with initial mildly abnormal aEEG,we recorded their aEEG 3-5 times ambulatory.2 of the 13 patients changed to show normal aEEG and got good outcome.But 9 patients' aEEG parttern did not change,and their outcomes were poor.2 of them were lost to follow-up.In 21 patients with initial severely abnormal aEEG,we recorded their aEEG 3-5 times ambulatory.Their aEEG parttern last severely abnormal continuously.They all suffered poor outcome.Conclusions1.aEEG is feasible to monitor and evaluate adult comatose patients' CF in NICU.Result of aEEG can be categorized into 3 grades(normal,mildly abnormal, severely abnormal aEEG).The aEEG classification is positively correlated with the severity of coma.Abnormality of aEEG more serious,level of coma deeper.2.Sensitivity,specificity,positive predict value,negative-predict value of abnormal aEEG predicting poor outcome is 65.5%,84.6%,93.8%,57.9%respectively. It is significant to use aEEG as a prognosis tool to predict coma patient's outcome And aEEG has an equal accuracy when comparaed with clinical neurological examination.3.Ambulatory aEEG monitoring can reflect the Variation of pathogenetic condition and provide objective evidence for medical decision making.4.Severely abnormal aEEG predicting cerebral death has sensitivity of 100.0% and specificity of 72.4%.Sensitivity is high,but specificity not stronge.We can just apply aEEG as a screening instrument to judge cerebral death.