Predictive value of magnetic resonance diffusion weighted imaging combined with miR-21-5p for poor prognosis of patients with acute brainstem infarction
Objective To analyze the predictive value of magnetic resonance diffusion weighted imaging(DWI)parameters combined with microRNA-21-5p(miR-21-5p)for poor prognosis in patients with acute brain stem infarction.Methods A total of 88 patients with acute brainstem infarction admitted to Lishui Central Hospital from June 2021 to June 2023 were retrospectively selected.The patients received routine symptomatic treatment and DWI examination while admission.They were followed up for 3 months after treatment,and their prognosis was evaluated according to the modified Rankin Scale(mRS).The parameters of DWI in infarction area[apparent diffusion coefficient(ADC),square measure of DWI(SDWI)]and serum miR-21-5p expression of patients with different prognosis were compared.Multivariate logistic regression was used to analyze the independent risk factors for poor prognosis of patients with acute brainstem infarction.ROC curve was drawn to analyze the predictive value of ADC,SDWI and miR-21-5p for poor prognosis of patients with acute brainstem infarction.Results The ADC of the poor prognosis group was lower than that of the good prognosis group,and the expressions of SDWI and miR-21-5p were higher than those of the good prognosis group(all P＜0.05).Multivariate logistic regression analysis showed that high blood pressure(OR=2.081),decreased ADC(OR=1.948),increased SDWI(OR=1.960)and increased miR-21-5p(OR=2.136)were independent risk factors for poor prognosis of patients with acute brain stem infarction(all P＜0.05).ROC curve analysis showed that the area under the curve(AUC)of ADC,SDWI,miR-21-5p and combined detection were 0.807,0.817,0.815 and 0.930,respectively,and the AUC of combined detection was superior to that of any single detection.Conclusion DWI parameters combined with miR-21-5p have a certain value in predicting the prognosis of patients with acute brain stem infarction.
国家科技期刊平台
NSTL
万方数据
