| BackgroundCerebral infarction is a process of ischemia,hypoxia and necrosis caused by insufficient cerebrovascular blood supply and local cerebral perfusion disturbance caused by various reasons,and its mechanism involves inflammatory reaction,oxidative stress,vascular endothelial cell injury and thrombosis.It is one of the most important causes of disability or death of patients.Atherosclerotic cerebral infarction is the most common and the most harmful to the human body.Timely diagnosis and prevention of cerebral infarction is very important.At present,imaging methods such as head and neck CT+CTA and MRI+MRA are commonly used to diagnose and distinguish the type of infarction,but there are no specific biomarkers to provide help,Its brings a lot of inconvenience for clinical treatment.ObjectiveThis study intends to start from the most commonly used biomarkers in clinic retrospective analysis of cystatin-C,D-dimer,homocysteine,C-reactive protein,hypersensitive C-reactive protein.In order to analyse the predictive value of cystatin-C and other biomarkers in the prediction of atherosclerotic cerebral infarction,complement serology and imaging,to provide help for clinical diagnosis.MethodsIn this paper,we collected the data of patients with cerebral infarction admitted from the emergency department in Nanfang Hospital of Southern Medical University from January 2017 to January 2018.Then we selected patients with symptoms within one week of admission.The patients were confirmed the focus of intracranial infarction by CT or MRI and were diagnosed acute cerebral infarction by neurologists based on these files.These patients were included in the retrospective analysis.The laboratory department of our hospital completed the analysis and report on plasma D-dimer,cystatin-C,homocysteine,C-reactive protein,hypersensitive C-reactive protein,high density lipoprotein,low density lipoprotein,triglyceride,total cholesterol and very low density lipoprotein.All statistical analyses were performed with SPSS24.0 version,and the statistical significance was set as P<0.05.Kmurs test was used to evaluate the normality of continuous variables.The continuous variables of normal distribution were represented by mean±standard deviation(SD)and analyzed by two independent sample t-test.The non-normal distribution variable is expressed as the median with quartile range(IQR)and analyzed by Mann-Whitney U test.Meanwhile,chi-square test was used to compare the frequency and percentage of classified variables.The influencing factors of atherosclerotic cerebral infarction were analyzed by Logistic regression equation.ResultsThe results showed that the level of cystatin-C in the atherosclerosis group(n=106,1.161±0.23)was higher than that in the non-atherosclerosis group(n=56,0.93±0.27),P<0.001,and the difference was statistically significant.In binary Logistic regression,the regression coefficient of gender was 1.665,P=0.007 and OR=5.288,95%CI(1.588,17.613),indicating that gender had a statistically significant effect on atherosclerotic cerebral infarction.The regression coefficient of cystatin-C was 1.046,P<0.001,OR=2.845,95%(1.588,5.096),indicating that cystatin-C had a statistically significant effect on atherosclerotic cerebral infarction and was a risk factor for atherosclerotic cerebral infarction.With a prediction probability of 0.5,the sensitivity of this Logistic regression model to distinguish atherosclerotic cerebral infarction was 76.8%,the specificity was 66.7%,and the total correct rate was 72.8%.AUC=0.772.ConclusionIt was found in this study that the level of cystatin-C in patients with atherosclerotic cerebral infarction is significantly higher than that in patients with non-atherosclerotic cerebral infarction.It was found that cystatin-C can be used as a risk factor for atherosclerotic cerebral infarction to predict the occurrence of atherosclerotic cerebral infarction after adjusting for confounding factors. |
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