[1]邹琦,段慧茹,万鑫柯,等.急性心肌梗死患者院前延迟风险预测模型的构建及评价[J].军事护理,2022,39(02):34-37.[doi:10.3969/j.issn.1008-9993.2022.02.009]
　ZOU Qi,DUAN Huiru,WAN Xinke,et al.Construction and Evaluation of Prehospital Delayed Risk Prediction Model in Patients with Acute Myocardial Infarction[J].Nursing Journal Of Chinese People's Laberation Army,2022,39(02):34-37.[doi:10.3969/j.issn.1008-9993.2022.02.009]
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急性心肌梗死患者院前延迟风险预测模型的构建及评价
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《军事护理》[ISSN:2097-1826/CN:31-3186/R]

卷:
39
期数:
2022年02期
页码:
34-37
栏目:
研究荟萃
出版日期:
2022-02-15

文章信息/Info

Title:
Construction and Evaluation of Prehospital Delayed Risk Prediction Model in Patients with Acute Myocardial Infarction
文章编号:
1008-9993(2022)02-0034-04
作者:
邹琦; 段慧茹; 万鑫柯; 臧舒婷
(河南省人民医院 急诊医学科,河南 郑州 450003)
Author(s):
ZOU Qi;  DUAN Huiru;  WAN Xinke;  ZANG Shuting
(Department of Emergency Medicine, Henan Provincial People's Hospital, Zhengzhou 450003, Henan Province, China)
关键词:
急性心肌梗死;  院前延迟;  预测模型;  列线图
Keywords:
acute myocardial infarction;  pre-hospital delay;  predictive model;  nomogram
分类号:
R473.54
DOI:
10.3969/j.issn.1008-9993.2022.02.009
文献标志码:
A
摘要:
目的 建立急性心肌梗死(acute myocardial infarction,AMI)患者院前延迟(pre-hospital delay time,PDT)风险预测模型,并评价模型的预测效能。方法 2019年1月至2020年12月,采用便利抽样法选取某院收治的AMI患者420例为研究对象,将其分为建模组(n=300)和验证组(n=120)。筛选影响建模组PDT的独立危险因素,建立AMI患者发生PDT的风险预测模型的列线图,并采用受试者工作曲线(receiver operating characteristic curve,ROC)验证模型的预测效果。结果 年龄(OR=1.327)、文化水平(OR=1.141)、独居(OR=2.167)、消化系统疾病史(OR=1.628)、Killip分级(OR=1.088)等是AMI患者出现PDT的独立风险因素。建模组Hosmer-Lemeshow检验显示,ROC曲线下的面积(area under curve,AUC)为0.933,灵敏度为84.29%,特异度为86.43%,约登指数为0.736。验证组Hosmer-Lemeshow检验显示,其AUC为0.902,灵敏度为82.97%,特异度为88.78%。结论 构建的列线图模型能有效预测AMI患者PDT发生风险,有利于AMI患者PDT的高效筛查和诊断。
Abstract:
Objective To establish a risk prediction model for pre-hospital delay time(PDT)in patients with acute myocardial infarction(AMI),and to evaluate the predictive efficacy.Methods From January 2019 to December 2020, 420 patients with AMI in a hospital were collected by convenience sampling method.They were divided into modeling group(n=300)and validation group(n=120).Single-factor and multi-factor logistic regression analysis were used to screen independent risk factors which affect PDT in the modeling group, and a risk prediction model and nomogram for PDT in AMI patients were established.The receiver operating curve(ROC)was used to verify the predictive effect of the model.Results Single factor and multivariate logistic regression analysis showed that age(OR=1.327), education level(OR=1.141), living alone(OR=2.167),history of digestive system disease(OR=1.628)and Killip classification(OR=1.088)were independent risk factors for PDT in AMI patients.The Hosmer-Lemeshow test results of the modeling group show that the area under curve(AUC)was 0.933, the sensitivity was 84.29%, the specificity was 86.43%, and the Youden index was 0.736.The validation group Hosmer-Lemeshow test results showed that the AUC was 0.902, the sensitivity was 82.97%, and the specificity was 88.78%.Conclusions The nomogram model constructed in this study can effectively predict the risk of PDT in AMI patients, and is beneficial to the efficient screening and diagnosis of PDT in AMI patients.

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备注/Memo

备注/Memo:
【 收稿日期 】 2021-06-21 【 修回日期 】 2021-12-24
【 基金项目 】 河南省2021年科技发展计划(212102310136)
【 作者简介 】 邹琦,本科,主管护师,从事急危重症的护理工作
【 通信作者 】 臧舒婷,电话:0371-65580120
更新日期/Last Update: 2022-02-15