Study On The Correlations Among Deficiency-excess Syndrome, Eeg Features And Prognosis Of Stroke Patients

Objective:Explore the correlations among stroke syndrome, electroencephalogram (EEG) and prognosis of stroke patients, and study on the effect of syndrome and EEG on stroke patients'prognosis. Enhance the cognition of stroke syndrome and improve the accuracy of therapy due to syndrome differentiation.Method:The research was divided into two parts, the first part is about the correlation between deficiency-excess syndrome evolution and prognosis in stroke patients, selecting the qi deficiency syndrome (QDS) and phlegm-heat syndrome as representation. The second part is about the effect of EEG on stroke prognosis, selecting the (Revised Brain Symmetry Index, r-BSI) as representation, and preliminarily exploring the correlation between deficiency-excess syndrome and r-BSI.Part1:Study on the correlation between deficiency-excess syndrome evolution and prognosis of stroke.Chapter1:Recruited were706stroke patients with complete clinical information including diagnostic scale scoring of elements such as wind, fire, phlegm, blood stasis, qi deficiency, and yin deficiency, scoring of The National Institutes of Health Stroke Scale (NIHSS) within72h from attack, on the7th,14th,28th, and90th day after attack, and Barthel index (BI) scoring on the90th day. They were assigned to the qi deficiency syndrome (QDS) group (330cases) and the non-QDS group (376cases). The NIHSS scores at different time points were compared between the two groups using analysis of variance of repeated measure data. Then294phlegm-heat syndrome were extracted from data base, Then the effect of phlegm-heat syndrome on neurological deficit degree of stroke were explored with application of Repeated Measures analysis of variance. On the90th day of attack,427patients with BI≥95(accounting for60%) had favorable prognosis, while279with BI＜95(accounting for40%) had unfavorable prognosis. The correlation between each syndrome element and the long-term prognosis of stroke patients was studied by using Logistic regression analysis.Chapter2:234ischemic stroke patients were extracted from database, each syndrome element, NIHSS at admission, medical history, age and gender as the dependent variable, and BI as the independent variable, effect of deficiency-excess syndrome on short-term prognosis were also explored.Part2:Study on the correlation between EEG feature-r-BSI and prognosis of stroke patients.Twenty-nine patients presenting with acute ischemic stroke (AIS) and persistent neurological deficits at EEG recording were incrementally included. Two a posteriori groups were arbitrarily created based on patient outcomes and evaluated with the modified Rankin Scale (mRS) and BI on21or90days (BI>60or BI≤60and mRS<3or mRS≥3). Student's T-tests were used to compare the differences of the r-BSI between normal subjects and stroke patients, differences between patients with different EEG scale and patients with different outcomes. In addition, we explored the correlation of EEG and prognosis of stoke patients with application of liner regression and Decision Tree. Based on the above research, we further explored the correlation between syndrome and EEG.Results:Part1:Chapter1:The results of Repeated measures analysis of variance showed that, Higher NIHSS score was found in patients of QDS than those of non-QDS at each time point (P<0.01). Statistical difference existed in NIHSS score between the two groups at each time point (P<0.01, P<0.05). Stroke patients with phlegm-heat syndrome have higher NIHSS score than patients without the syndrome (P=0.000<0.01), and there appears a decreased NIHSS score with time points delay(P=0.000<0.01). QDS on the7th and14th day were independed risk factor of90th-day BI, and were negatively correlated with the B value being-0.524and-0.493respectively, QDS in acute ischemic stroke means a lower90th-day BI, and an unfavorable prognosis.Chapter2:The results of Logistic regression showed that, the wind on the7th day, the wind and QDS on the10th day were independed risk factor of21th-day BI, and were negatively correlated with the B value being-0.905,-1.425and-0.895respectively, The wind and QDS in acute ischemic stroke means an unfavorable prognosis.Part2:Compared with healthy controls(0.060), the r-BSI of stroke patients is0.0107, there is a significant statistical difference(P=0.000<0.01).The size of r-BSI is consistent with EEG classification, higher EEG classification with higher r-BSI. Student's T-tests and liner regression implied that r-BSI at admission was correlated with mRS and BI at both21d and90d. There is also difference in r-BSI between patients with QDS and patients with non-QDS (P=0.04).Conclusion:1. Accurately grasping the characteristics of symptoms dynamic time and space is benifit to study the change, transformation and outcome of disease. There should be constant dynamic consept should be established in diagnosis and treatment of disease.2. There are close relationship between syndrome change and prognosis. Stroke patients of QDS had more severe neurological impairment degree than those of non-QDS, QDS of acute-stage was closely correlated with unfavorable prognosis, early actively invigorating healthy qi is essesial in acute-stage. Phlegm-heat syndrome in patients who have suffered stroke has an effect on the degree of neurological deficiency, disappearance of phlegm-heat syndrome may improve the degree of neurological deficit observed in stroke patients. Early invigorating healthy qi and removing the phlegm-heat, and correctly handling the correlation between deficiency-excess, to ajust the body into a normal state.3. It is significant of EEG feature for predicting the prognosis of stroke patients. A higher r-BSI predicts a poorer short-term prognosis for stroke patients. Acute EEG monitoring may be of prognostic value for patients'outcomes. 4. There are some correlation between syndrome and EEG. There is also difference in r-BSI between patients with QDS and patients with non-QDS (P=0.04).The research provided some data support for the importance of QDS in prognosis predicting of stroke patients.Highlight of innovation:1. This study brought new ideas for the use of repeated measures analysis of variance,. It is the repeated measurements at different points of a measure of the same object. There is self-correlation between the point data. We applied the method in syndrome study of stroke patients.2. According to the characteristics of Stroke Symptom, we explored the correlation of syndrome and prognosis. Higher NIHSS score was found in patients of QDS than those of non-QDS at each time point. Stroke patients with phlegm-heat syndrome have higher NIHSS score than patients without the syndrome.3. We used the EEG feature to predict the prognosis of stroke patients and explored the correlation between syndrome and EEG.