中国卒中杂志 ›› 2020, Vol. 15 ›› Issue (01): 33-39.DOI: 10.3969/j.issn.1673-5765.2020.01.005

• 论著 • 上一篇    下一篇

西安地区卒中患者1年卒中复发预测模型的构建

蔺雪梅,王芳,王静,曹欢,逯青丽,刘仲仲,段康丽,吴松笛   

  1. 710002 西安市第一医院神经内科
  • 收稿日期:2019-02-09 出版日期:2020-01-20 发布日期:2020-01-20
  • 通讯作者: 吴松笛 wusongdi@gmail.com
  • 基金资助:

    陕西省科技计划项目(2017SF163)
    西安市科技计划重大项目[201805104YX12SF38(2)]
    西安市卫生健康委员会科技项目(J201703049)

Construction of Predictive Model of 1-year Stroke Recurrence for Stroke Patients in Xi'an

  • Received:2019-02-09 Online:2020-01-20 Published:2020-01-20

摘要:

目的 构建西安地区卒中患者1年卒中复发的预测模型。 方法 以西安市卒中数据库2016年1月1日-12月31日的急性卒中患者作为研究对象,收集患者的临床 资料,并在出院后1年时进行随访。应用Cox比例风险回归模型对影响患者卒中复发的危险因素进行单 因素和多因素分析,并应用逐步回归前进法构建卒中1年复发的预测模型。 结果 研究共纳入2775例急性卒中患者,一年随访结束时,累计复发144例,累计复发率为5.34%。 对与卒中复发有关的变量进行分析后,建立卒中1年复发的预测模型:h(t)=h0 exp(0.02900×年龄 +0.83649×既往卒中+0.26683×周围血管病+0.12887×入院NIHSS评分)。模型ROC曲线下的面积为 0.82,最佳截断值为0.197,敏感度及特异度分别为0.69和0.78,总的准确度为83%。 结论 本研究构建的西安地区卒中患者1年复发预测模型针对性强,简单实用,易于操作。通过预 测模型可以早期识别西安地区卒中高危患者并进行个体化治疗,从而降低本地区卒中复发率,改善 患者预后。

文章导读: 本研究基于西安卒中数据库,构建西安地区卒中患者1年卒中复发的预测模型,以期早期识别卒中复发的高危人群,为区域性卒中防控提供依据。

关键词: 卒中; 复发; 预测; 模型

Abstract:

Objective To construct a predictive model of 1-year stroke recurrence for stroke patients in Xi'an. Methods Data of acute stroke patients from Xi'an Stroke Database from January 1 to December 31, 2016 were collected. Clinical data included in-hospital data and the follow-up results at 1 year after discharge. After analyzing the risk factors affecting recurrent stroke, a predictive model of 1-year stroke recurrence was constructed using the Cox proportional hazard regression model. Results A total of 2775 patients with acute stroke were enrolled in this study. Recurrent stroke ocurred in 144 patients (accumulated risk 5.34%) within 1 year. A predictive model for the 1-year stroke recurrence as follows: h (t ) = h0 exp (0.02900×age + 0.83649×prior stroke + 0.26683×peripheral vascular disease history + 0.12887×NIHSS score at admission). The area under the ROC curve was 0.82, the best cut-off point was 0.197, the sensitivity and specificity were 0.69 and 0.78, respectively. The total accuracy of the predictive model is 83%. Conclusions The 1-year stroke recurrence predictive model for stroke patients in Xi'an is targeted, simple, practical and easy to operate. The high-risk stroke patients in Xi'an can be identified by the predictive model and are given individualized treatment timely, which will reduce the recurrence rate of stroke and improve the prognosis of stroke patients.

Key words: Stroke; Recurrence; Prediction; Model