Clinical Study On Prognostic Factors Of Acute Cerebral Infarction In Anterior And Posterior Circulatory Systems And The Predictive Value Of THRIVE And Barthel Index

Stroke has become the world’s second largest cause of death,but also the population of China is one of the main causes of death.Acute ischemic stroke has a high disability and mortality.Therefore,it is particularly important for the prevention and treatment of acute cerebral infarction(ACI),and recognizing and controlling its controllable risk factors can improve prognosis and reduce mortality,reducing social burden.The use of scales provides an important reference for clinicians to accurately assess their prognosis.Posterior and anterior circulation strokes have many common clinical and pathophysiological features,but there are also distinct differences,mainly related to their respective cerebrovascular anatomy and brainstem function.Therefore,studying the adverse prognostic risk factors of the two can provide a valuable basis for better secondary prevention.Total Health Risk in Vascular Events(THRIVE)is an ACI prognostic assessment scale based on clinical variables that are commonly known to clinicians.The Barthel Index was published in 1965 to quantitatively assess a patient’s activities of daily living(ADL)ability.The lower the score,the more severe the disability and the greater the need for nursing assistance.These two scale evaluation methods are relatively simple,but they are very practical.Part one Adverse prognostic factors in acute cerebral infarction of the anterior and posterior circulatory systemsObjective: To assess the risk factors for 1-year adverse prognostic outcomes of ACI follow-up and the differences between risk factors for poor prognosis of ACI in different circulatory systems.Method: Continuous collection of 858 ACI patients hospitalized in the Department of Neurology,Peking University School of Aerospace Clinical Medicine from December 1,2012 to November 4,2015,including demographics,past history,pre-admission self-care ability,stroke severity,some biochemical indicators and imaging performance.At 1-year follow-up,death or moderate-to-severe dysfunction(modifed Rankin Scale,m RS≥3points)was regarded as the poor prognostic endpoint.The above data are analyzed by one factor and the stepwise regression analysis of multi-factor logistic to evaluate the risk factors of poor prognosis,and the predicted probability of the indicators obtained by Medcalc software is used to make receive operating characteristic(ROC)curve,and the area under the curve(AUC)prediction model is calculated.First,univariate analysis of anterior and posterior circulation ACI was carried out,and statistically significant indicators(P<0.1)were carried out,and then multivariate logistic stepwise regression analysis was performed according to the different circulatory systems of cerebral infarction to evaluate the risk factors.Results: A total of 858 patients met the inclusion criteria,21 patients(2.4%)were lost to follow-up,837 patients completed follow-up,630 patients(75.3%)had good prognosis,and 207 patients(24.7%)had poor prognosis.In univariate analysis,age,sex,smoking,drinking,diabetes,hypertension,previous cerebral infarction or cerebral hemorrhage or transient ischemic attack,chronic heart failure,coronary heart disease,atrial fibrillation,cancer and Barthel index on admission,admission National Institutes of Health Stroke Scale(NIHSS)score and m RS score,different circulatory systems,TOAST classification,hospitalization time,biochemical indicators(hemoglobin,triglyceride,cholesterol,low-density lipoprotein,blood sugar,Creatinine and blood urea nitrogen)were risk factors for poor prognosis(P<0.1).Multivariate Logistic stepwise regression analysis suggested that age,history of cerebral infarction and diabetes,Barthel index on admission,NIHSS and m RS on admission,different circulatory systems and length of stay were risk factors for poor prognosis(P<0.05).The multivariate model AUC=0.893,95%CI=0.870-0.913,indicating a good fit.Univariate analysis of anterior circulation ACI showed that the risk factors for poor prognosis were age,gender,previous diabetes,cerebral infarction,cerebral hemorrhage,atrial fibrillation,coronary heart disease,cancer,smoking,drinking,NIHSS score and m RS score on admission,Barthel index,hemoglobin,Triacylglycerol,blood glucose,blood urea nitrogen,length of hospital stay,TOAST classification(P<0.1).Univariate analysis of posterior circulation ACI showed that the risk factors for poor prognosis were age,previous diabetes,hypertension,cerebral infarction,blood glucose,creatinine,blood urea nitrogen,NIHSS score and m RS score at admission,Barthel index,length of stay,TOAST classification(P<0.1).The multivariate analysis of ACI in different circulatory systems showed that the risk factors for poor prognosis were different: ACI in the anterior circulation was age,history of cerebral infarction,NIHSS score on admission,length of stay,and Barthel index on admission(P<0.05);ACI in the posterior circulation was cerebral infarction Medical history,m RS score at admission,length of stay(P<0.05).Conclusion: Age,diabetes mellitus,and history of cerebral infarction were risk factors for poor prognosis of ACI;patients with higher NIHSS and m RS scores at admission and lower Barthel index at admission had poorer prognosis;longer hospitalization time,worse prognosis.There are differences in the prognosis of ACI in different circulation systems.The prognosis of patients with ACI in both anterior and posterior circulation is no different from that of anterior circulation ACI or posterior circulation ACI(P>0.05);the prognosis of anterior circulation ACI is worse than that of posterior circulation ACI(P<0.05).Different circulatory system ACIs have different risk factors for poor prognosis.Part two Evaluation of short and long-term poor outcomes of acute cerebral infarction in the anterior and posterior circulation by THRIVE and BIObjective: To assess the predictive effects of THRIVE and BI each for adverse outcome at 3 month and 1 year follow-up in anterior and posterior circulation ACI,and compare the differences in the predicted values of THRIVE and BI at the same time.Method: Data of 858 patients with ACI who were hospitalized in the Department of Neurology,Peking University Aerospace Clinic School of Medicine from December 1,2012 to November 4,2015 were prospectively and consecutively collected,including demographics,past history,preadmission self-care ability,and stroke.Severity,some biochemical indicators and imaging findings.At 3 months and 1 year of follow-up,death or moderate-to-severe disability(modified Rankin Scale,m RS≥3)was regarded as an adverse prognostic end point.Medcalc software was used to make the ROC curve of THRIVE and BI,and AUC was calculated to compare the predictive effects of THRIVE and BI in the anterior and posterior circulation of ACI,and the predictive value of THRIVE and BI for ACI at 3 months and 1year of follow-up.Results: 858 patients were enrolled,and 21(2.4%)were lost to follow-up.Completed follow-up of 837 cases,including 538 cases of anterior circulation ACI and 242 cases of posterior circulation ACI.At 3-month follow-up,the AUC of THRIVE for anterior circulation ACI was 0.685,95% CI(0.644-0.724),and posterior circulation ACI was 0.709,95% CI(0.647-0.765);the difference between the two areas was 0.0235,95% CI(-0.0728-0.120),P =0.6330(>0.05);the AUC of THRIVE for anterior circulation ACI at 1 year was 0.701,95% CI(0.660-0.740),posterior circulation ACI was 0.747,95%CI(0.687-0.800);the area difference between the two was 0.0458,95% CI(-0.0489-0.140),P = 0.3436(>0.05),and the above differences were not statistically significant.At 3-month follow-up,the AUC of BI for the anterior circulation ACI was 0.751,95% CI(0.712-0.787),and the posterior circulation ACI was 0.788,95% CI(0.731-0.837);the difference between the two areas was 0.0363,95% CI(-0.0553-0.128),P=0.4372(>0.05).The AUC of BI for the anterior circulation ACI at 1-year follow-up was 0.760,95% CI(0.721-0.795),and the posterior circulation ACI was 0.760,95% CI(0.701-0.812);the difference between the two area is 0.0000803,95%CI(-0.100-0.101),P=0.9988(>0.05);the above differences were not statistically significant.The area difference of AUC between THRIVE and BI with ACI at 3-month followup was 0.0760,95%CI(0.0303-0.122),Z=3.258,P=0.0011;the area difference of AUC between THRIVE and BI with ACI score at 1-year followup was 0.0574,95%CI(0.0106-0.104),Z=2.403,P=0.0163;the above differences were statistically significant(P<0.05).Conclusion: Both THRIVE and BI were each well predictive of short-and long-term adverse outcomes in anterior or posterior circulation ACI,and were equally predictive for both circulation ACI.BI predicted better than THRIVE.Part Three Study on the predictive value of Barthel,PLAN and NIHSS scores of death in the 5-year follow-up of acute cerebral infarctionObjective: This study aimed to investigate the value of Barthel,PLAN,and NIHSS scores in predicting mortality in patients with ACI during 5-year follow-up after hospital discharge,and to search for a simple and convenient predictive scale.Method: We collected data from 678 patients with ACI.After 5 years of follow-up,the patient’s death was considered a final event.When comparing baseline characteristics,the normal distribution test is firstly performed,which does not conform to the normal distribution,the continuous variables are represented by the median and interquartile range,and nonparametric double independent sample tests are performed respectively;categorical variables are used χ2 test,if necessary A Yates continuity correction or Fisher’s exact probability test was performed.Med Calc software was used to draw the ROC curve,calculate the AUC,and use the Delong et al method to compare the predictive power of the three scales in pairs.Statistical significance was established at P<0.05.Hosmer-Lemeshow test was used to evaluate the fit of each model,and Statistical significance was established at P>0.05.Predictors of death within 5 years were analyzed using logistic multivariate analysis.All tests were two-sided,and Statistical significance was established at P<0.05.Results: Multivariate analysis showed that BI score was an independent predictor of ACI death at 5-year follow-up.Barthel,PLAN,and NIHSS scale scores predicted 5-year mortality with ACI,AUC values of 0.687 [95%CI(0.649-0.722)],0.621 [95%CI(0.583-0.659)],0.637 [95%CI(0.599-0.674)],the H-L test showed that P>0.05,indicating that the three models had a good fit.In pairwise comparison,the AUC value of BI score was significantly higher than that of NIHSS score [AUC area difference=0.0495,95%CI(0.0140-0.0851),Pc=0.0189].The AUC values for BI and PLAN scores were compared,which were very close to statistically significant[AUC area difference=0.0652,95%CI(0.0116-0.119),Pc=0.0513].However,there was no significant difference between PLAN and NIHSS scores[AUC area difference = 0.0157,95% CI(-0.0404-0.0718),Pc=1.7493].Conclusion: Simple BI scores had a high predictive value for death within 5 years in ACI patients.