Correlation And Risk Prediction Model Of Cerebral Microhemorrhage With Plasma Homocysteine And Hba1c Levels

ObjectiveTo study the correlation between plasma Homocysteine(Hcy)and Glycosylated hemoglobin(GHb)levels and cerebral microbleeds(CMBs),and to develop a risk prediction model for CMBs.MethodsInto between January 2018 and June 2019,jinzhou medical university first affiliated hospital of neurology clinic and hospital small brain vascular disease(cerebral small vessel diseases,CSVD)patients,119 cases(45-80 years),according to the imaging the existence of CMBs divided into CMBs group and the control group,the main risk factors of patients with screening CMBs Logistic regression analysis for single factor and multiple factors,has the advantage of a statistically significant indicators than calculated value assignment,develop risk prediction model of CMBs,Furthermore,the continuity index with statistical significance was included into the ROC operating curve to predict the diagnostic performance of CMBs.Results1.Hcy(R=0.308,P=0.001),GHb(R=0.297,P=0.001),history of cerebral hemorrhage(R=0.274,P=0.003),and MTHFR genotype(R=0.199,P=0.031)were risk factors for CMBs.2.Hcy(OR = 1.038,P = 0.037)and available(OR = 1.451,P = 0.045)level for CMBs is specific and sensitive diagnostic value,when more than 12.25 u mol/l Hcy,into the CMBs high-risk area,every increase 1 unit,get 1.038 times increased risk of CMBs(sensitivity was 62.34%,71.43%),when available more than 5.7 tendency for l,into the CMBs high-risk area,every increase 1 unit,The risk of CMBs increased by 1.451 times(sensitivity was 62.34%,specificity was 69.05%),and the diagnostic value of Hcy(area under ROC curve =0.690) was comparable to that of GHb(area under ROC curve =0.657).The risk of CMBs in patients with cerebral hemorrhage history(OR=9.587,P=0.042)was 9.587 times that of patients without cerebral hemorrhage history.Patients with MTHFR TT genotype (OR=5.765,P=0.002) had a 5.765 times higher risk of developing CMBs than patients with CC genotype.3.Model fitting effect judgment,the accuracy of model prediction is 73.10%;4.According to the OR value and the risk prediction model of CMBs(full score: 17),the area under the ROC curve(AUC)was 0.783±0.0457(P<0.001).The optimal pointcut value of 9 points was used as the boundary value of high and low risk.≥9 points was used as the high-risk population of CMBs.The sensitivity was 83.12%,the specificity was 64.29%,and the youdon index was 47.41%.5.In the CMBs group,there was a negative correlation between Hcy and GHb(r=-0.288,P=0.011).With other factors unchanged,Hcy decreased by 2.921(B=-2.921,t=-1.751,P=0.044)for every unit of GHb increased.ConclusionHcy,GHb,cerebral hemorrhage history and MTHFR TT genotype are the main risk factors for CMBs in CSVD patients.The developed CMBs risk prediction model USES 9 points as the threshold value to classify high and low risks,which has high sensitivity and specificity,and can predict the risk of CMBs in CSVD patients,providing a basis for early intervention.