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首发脑卒中患者5年生存率及死亡影响因素分析 被引量:4

Five-year survival rate and influencing factors of mortality among patients with initial cerebral stroke
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摘要 目的探讨首发脑卒中患者生存情况,分析其死亡的相关影响因素。方法收集2013年浙江省慢性病监测信息管理系统中脑卒中的新发病例,通过5年随访获得患者生存状况。应用Kaplan-Meier法进行生存率分析,采用Cox比例风险模型进行预后影响因素的分析。结果共收集2748例脑卒中患者,其中男性1415例,女性1333例,平均发病年龄(71.41±12.06)岁;脑卒中患者的1年生存率为84.01%,3年生存率为75.52%,5年生存率为66.42%;Cox比例风险分析显示影响患者死亡的主要因素有发病年龄(RR=1.082,P<0.05),文化程度(RR=0.669,P<0.05),脑卒中亚型(RR=1.767,P<0.05),高血压(RR=1.860,P<0.05)。结论萧山区首发脑卒中患者的生存率处于较高水平,有效进行脑卒中危险因素的干预,积极进行二级预防可显著减少脑卒中的死亡。 Objective To describe the survival status and to analyze the influencing factors of mortality on patients with initial cerebral stroke.Methods The patients with initial cerebral stroke registered in 2013 were collected from chronic disease surveillance information management system in Zhejiang province.The survival status were collected through 5 years’follow-up.Kaplan-Meier methods were used for survival analysis.Cox proportional hazard model was performed to analyze risk factors on mortality.Results 2748 patients with cerebral stroke weew selected,including 1415 males and 1333 females,mean age of onset was(71.41±12.06)years.The survival rate was 84.01%in one year,75.52%in three years and 66.42%in five years.The result of Cox proportional hazard analysis confirmed that age of onset(RR=1.082,P<0.05),educational level(RR=0.669,P<0.05),stroke subtype(RR=1.767,P<0.05),and past history of hypertension(RR=1.860,P<0.05)were the independent risk factors of the survival rate of patients with stroke.Conclusion The survival rate of patients with initial cerebral stroke in Xiaoshan District is at a high level.Effective intervention of risk factors of stroke and active secondary prevention can significantly reduce the death of stroke.
作者 王春丽 林君英 王冬飞 蒋园园 Wang Chunli;Lin Junying;Wang Dongfei;Jiang Yuanyuan(Center for Disease Control and Prevention of Xiaoshan District,Hangzhou 311200,China)
出处 《心脑血管病防治》 2020年第3期242-244,共3页 CARDIO-CEREBROVASCULAR DISEASE PREVENTION AND TREATMENT
关键词 脑卒中 生存分析 影响因素 Stroke Survival analysis Influencing factor
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