| Neurological complications are serious complications after cardiac surgery,which significantly increase the perioperative mortality and reduce the long-term quality of life.Neurological complications after cardiac surgery can be divided into typeⅠ and typeⅡ.typeⅠ is embolic stroke,cerebral hemorrhage,paralysis and coma;TypeⅡ is delirium and cognitive impairment.Incidence rate of typeⅠ is 2.2-14%in different series of cases,and the incidence rate of typeⅡ is 28-52%.Delirium,as the most important typeⅡ neurological complication after cardiac surgery,not only increases the perioperative adverse events of patients,but also related to long-term cognitive impairment.At present,the pathogenesis of delirium is not completely clear,although some studies have compared the risk factors of delirium after cardiac surgery and developed several prediction models.However,these prediction models are not ideal in further clinical verification;and still can not be widely used in clinic.In recent years,neurophysiological studies have shown that there is a strong correlation between EEG changes and delirium,such as burst suppression and the decrease of alpha power.Whether this specific EEG change can be used as a biomarker to predict delirium after cardiac surgery has not been studied.Therefore,this paper discusses the predictive value of EEG changes in different time periods and different brain lobes after cardiac surgery for delirium,and uses clinical data to verify the predictive value of the indicator.typeⅠ neurological complications,represented by stroke,are severe complications of aortic arch surgery and are significantly higher than those of valve replacement and coronary artery bypass grafting due to deep hypothermic circulatory arrest.Early literature reported a 30 day incidence of stroke up to 20%after aortic arch surgery.For patients with delayed awakening from aortic arch surgery,early diagnosis of neurological organic lesions has important value for clinical therapy.CT examination often cannot confirm the diagnosis at an early stage because of its low sensitivity within the " time window " of stroke.EEG monitoring has a good sensitivity and specificity for the decline in cerebral blood flow,relevant studies have shown that when the mean cerebral blood flow falls below 22ml/100g/min,EEG amplitude decreases and/or EEG frequency slows.Fast wave activity(αand β)decreased and subsequently appeared δ rhythm.EEG changes were detected 7 hours earlier than clinical diagnosis and 44 hours earlier than CT.In addition,nonconvulsive status epilepticus and periodic discharges are often important indicators suggesting a poor prognosis.In the study by Lara et al.,patients with non convulsive status epilepticus and periodic discharges on EEG had acute embolic stroke,and in one review it was found that patients with epilepsy lasting more than one hour had a 15 fold increase in mortality.Therefore in this part we investigate the role of EEG monitoring in the evaluation of neurological organic lesions in patients with delayed awakening after aortic arch surgery.Part I.Early alpha power in the frontal lobe area can predict delirium after cardiac surgeryObjective:Delirium is a common complication after cardiac surgery,leading to prolonged hospital stay and long-term cognitive decline.Relevant studies suggest that the EEG of patients with delirium may have characteristic changes,such as a decrease in alpaa-wave power.The goal of this study is to evaluate the value of alpha power at different time points and different brain parts in predicting postoperative delirium after cardiac surgeryMethods:The patients receiving routine cardiac surgery were prospectively enrolled in this study.These patients were given 12-hour ambulatory EEG monitoring immediately after returning to the ICU,and CAM-ICU standards were used to assess whether the patients were delirium on the first to five days after surgery.The value of alpha power was evaluated in the frontal,parietal,and occipital lobes of the brain immediately,in 6 hours,and 12 hours after surgery to predict postoperative delirium.New data was used to verify the predictive value of the indicator.Results:Of the 106 patients in the training sample,45 were diagnosed with delirium.The proportion of patients in the delirium group with a history of hypertension was higher,and the Extracorporeal circulation time and aortic clamping time during the operation were higher than those in the control group,alpha power of the frontal lobe area at TO after operation is the best predictor of postoperative delirium(area under the curve 0.91(CI 0.84-0.97).The area under the ROC curve of the verification model is 0.9188 in the 74 patients,(95%CI,0.87-0.99,P<0.001).Conclusions:alpha power in the frontal area can predict the incidence of delirium after cardiac surgery in the early phase.Part Ⅱ.The role of EEG monitoring in delayed awakening patients from aortic arch surgeryObjective:to study the significance of EEG monitoring in patients with delayed awakening after aortic arch surgery.Methods:Data of patients with delayed awakening after aortic arch surgery in XX Hospital from 2014 to 2019 were retrospectively analyzed.According to the prognosis,the patients were divided into two groups:the group without organic damage and the group with organic damage.The difference of EEG data between the two groups was compared.Results:Among the 49 patients,38 cases had no organic damage,11 cases had organic damage(7 cases of new cerebral infarction,1 case of extensive cortical hypoxia,1 case of air embolism,2 cases of epilepticus).The prognosis of organic damage group was worse than that of non organic damage group.In the organic damage group,slow wave was the main background wave,and the a variation rate was lower.The incidence of abnormal EEG(burst suppression and epileptic wave)in organic damage group was higher,with statistical difference.Young EEG classification in organic damage group was higher,with statistical difference.Conclusion:For patients with delayed awakening after arch surgery,EEG monitoring can help to make clinical judgment and prognosis analysis... |
PDF Full Text Request