Effect of Songling Xuemaikang Capsules Combined with Nimodipine on Patients with Hypertensive Cerebral Hemorrhage
Objective:To investigate the effect of Songling Xuemaikang Capsules combined with Nimodipine on patients with hypertensive cerebral hemorrhage(HICH).Method:A total of 78 patients with HICH who admitted to Fangxian People's Hospital from April 2020 to December 2022 were selected as the study objects,and they were divided into the study group and the control group by random number table method,39 cases in each group.The control group was treated with Nimodipine,and the study group was treated with Songling Xuemaikang Capsules combined with Nimodipine.The clinical efficacy,vascular endothelial function[endothelin-1(ET-1),nitric oxide(NO)],oxidative stress[serum reduced glutathione(GSH),malondialdehyde(MDA)],inflammatory factors[serum tumor necrosis factor-α(TNF-α),C-reactive protein(CRP),interleukin-6(IL-6)]and adverse reactions were compared between two groups.Result:The total clinical effective rate of the study group was higher than that of the control group,and the difference was statistically significant(P<0.05).After treatment,the levels of NO and GSH in two groups were higher than those before treatment,and those in the study group were higher than those in the control group,the levels of ET-1,MDA,TNF-α,CRP and IL-6 in two groups were lower than those before treatment,and those in the study group were lower than those in the control group,the differences were statistically significant(P<0.05).The incidence of adverse reactions in the study group was higher than that in the control group,but the difference was not statistically significant(P>0.05).Conclusion:Songling Xuemaikang Capsules combined with Nimodipine can reduce oxidative stress response and inflammatory factor levels in patients with HICH,improve vascular endothelial function,and improve the clinical efficacy,has high safety.
Songling Xuemaikang CapsulesNimodipineHypertensive cerebral hemorrhageOxidative stressVascular endothelial function
万方数据
维普
