中国中老年人群脑卒中发病的影响因素探索及列线图模型构建  

Exploring the influencing factors of stroke and constructing a nomogram prediction model in Chinese middle-aged and older population

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作  者:李瑾[1] 侯候[2] 王亚新 张新[1] 宋振强[1] 孙明艳[1] LI Jin;HOU Hou;WANG Yaxin;ZHANG Xin;SONG Zhenqiang;SUN Mingyan(Department of Neurology,Chu Hsien-I Memorial Hospital,Tianjin Medical University&Tianjin Institute of Endocrinology&NHC Key Laboratory of Hormones and Development&Tianjin Key Laboratory of Metabolic Diseases,2.Department of Rheumatology and Immunology,Tianjin Medical University General Hospital,Tianjin 300134,China)

机构地区:[1]天津医科大学朱宪彝纪念医院神经内科、天津市内分泌研究所,国家卫生健康委员会激素与发育重点实验室,天津市代谢性疾病重点实验室,天津市300134 [2]天津医科大学总医院风湿免疫科,天津市300134

出  处:《中国动脉硬化杂志》2024年第10期865-871,共7页Chinese Journal of Arteriosclerosis

基  金:天津市医学重点学科(专科)建设项目(TJYXZDXK-032A)。

摘  要:[目的]探讨中国中老年人群脑卒中发病的相关影响因素,并构建列线图预测模型,以期为脑卒中的防治提供更为个性化的参考依据。[方法]本研究共包括13 063名来源于中国健康与养老追踪调查项目的参与对象。该项目通过多阶段抽样,于2011年对全国28个省(自治区、直辖市)的150个县、450个社区(村)的45岁以上的中老年人进行横断面调查,并详细收集了参与者的社会人口学特征、体格测量资料、健康状况、医疗保健情况、家庭收入和消费状况。分别于2013年、2015年和2018年随访了研究对象脑卒中的发病情况。采用单因素和多因素Cox回归筛选与脑卒中发病有关的影响因素,并构建列线图预测模型。[结果]随访过程中,新发脑卒中774人。多因素Cox回归结果显示,高龄(HR=1.028,95%CI:1.019~1.038)、单身(HR=1.295,95%CI:1.031~1.626)、吸烟(HR=1.264,95%CI:1.074~1.489)、体质指数异常(HR=1.204,95%CI:1.020~1.420)、高血压(HR=2.200,95%CI:1.855~2.609)和糖尿病(HR=1.483,95%CI:1.117~1.970)是影响脑卒中发病的危险因素,高水平的家庭人均年支出(HR=0.783,95%CI:0.642~0.953)是脑卒中发病的拮抗因素。基于以上因素构建的列线图具有较好的预测性能,其曲线下面积(AUC)约为0.700。[结论]高龄、单身、吸烟、体质指数异常、高血压和糖尿病是脑卒中发病的独立危险因素,基于这些因素构建的列线图有助于预测脑卒中的发病率。Aim To explore the related influencing factors of stroke in middle-aged and elderly population in China,and to construct a nomogram prediction model to provide more personalized reference for the prevention and treatment of stroke.Methods This study included 13063 participants from the China Health and Retirement Tracking Survey project.This project conducted a cross-sectional survey in 2011 using a multi-stage sampling method,targeting individuals aged 45 and above from 150 counties and 450 communities(villages)in 28 provinces(autonomous regions and municipalities).Detailed data were collected on participants socio-demographic characteristics,physical measurements,health status,healthcare utilization,household income,and expenditure.The study participants were followed up to assess stroke in 2013,2015,and 2018.Univariate and multivariate Cox regression analyses were employed to identify the factors associated with stroke incidence and to construct a nomogram predictive model.Results During the follow-up,774 participants developed to stroke.Multivariate Cox regression results showed that older age(HR=1.028,95%CI:1.019~1.038),being single(HR=1.295,95%CI:1.031~1.626),smoking(HR=1.264,95%CI:1.074~1.489),abnormal body mass index(HR=1.204,95%CI:1.020~1.420),hypertension(HR=2.200,95%CI:1.855~2.609)and diabetes(HR=1.483,95%CI:1.117~1.970)were the risk factors affecting the incidence of stroke,high levels of annual per capita expenditure(HR=0.783,95%CI:0.642~0.953)are antagonistic factors in the incidence of stroke.The nomogram constructed based on the above factors had good predictive performance,and its area under the curve(AUC)was about 0.700.Conclusion Old age,being single,smoking,abnormal body mass index,history of hypertension and diabetes are independent risk factors for stroke,the nomogram constructed based on these factors can help predict the incidence rate of stroke.

关 键 词:脑卒中 中老年人群 列线图 影响因素 

分 类 号:R5[医药卫生—内科学] R743.3[医药卫生—临床医学]

 

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