摘要
目的探讨慢性阻塞性肺疾病急性加重期(acute exacerbation of chronic obstructive pulmonary disease,AECOPD)患者发生再入院的危险因素并构建疾病风险预测模型,旨在为早期识别并筛选AECOPD再次入院的高风险患者提供评估工具。方法选取云南省某三甲医院2016年1月1日至2021年1月1日诊断为AECOPD且符合纳入、排除标准的414例患者为研究对象。将其中70%(307例)的患者作为建模组,剩余30%(107例)患者作为验证组。根据患者是否发生再入院作为结局指标,分析AECOPD患者发生再入院的危险因素并构建疾病风险预测模型。结果最终纳入年龄(OR=0.958)、雾化吸入激素种类(OR=1.893)、FEF_(75)预计值(OR=0.583)、FEV_(1)实际值(OR=1.947)、合并呼吸衰竭(OR=0.501)5个预测因子。预测模型公式:P=1/{1+exp[−(3.361+(−0.043)×年龄+0.638×吸入雾化激素种类+(−0.539)×FEF_(75)预计值+0.666×FEV_(1)实际值+(−0.691)×合并呼吸衰竭)]},建模组受试者特征工作曲线下面积(AUC)为0.777,其灵敏度和特异度分别为0.898和0.549。验证组受试者特征工作曲线下面积(AUC)为0.821,灵敏度和特异度分别为0.857和0.7。结论研究所构建的AECOPD患者再入院风险预测模型具有良好的预测效能,为早期识别并筛选AECOPD再次入院的高风险患者提供了评估工具,为医护人员调整高风险患者的治疗和护理提供参考依据,为减轻患者痛苦,减少家庭及社会负担,提高护理服务质量提供科学依据。
Objective To explore the risk factors of readmission in patients with AECOPD and develop a disease risk prediction model,aiming to provide an evaluation tool for early identification and screening of patients at high risk of readmission with AECOPD.Methods A total of 414 patients diagnosed with AECOPD in a tertiary hospital in Yunnan Province from January 1,2016 to January 1,2021 and met the criteria for inclusion and exclusion were selected as the study subjects.70%(307)of these patients were included as the modeling group and the remaining 30%(107)patients were included as the validation group.According to whether patients have readmission as an outcome indicator,the risk factors for readmission of patients with AECOPD are analyzed and a disease risk prediction model is constructed.Results Age(OR=0.958),nebulized inhaled hormone(OR=1.893),predicted value of FEF_(75)(OR=0.583),actual value of FEV_(1)(OR=1.947)and combined respiratory failure(OR=0.501)were included.Prediction model formula:P=1/{1+exp[−(3.361+(−0.043)×age+0.638×type of inhaled nebulized hormone+(−0.539)×predicted value of FEF_(75)+0.666×actual value of FEV_(1)+(−0.691)×respiratory failure)]}.The area under ROC curve(AUC)of the modeling group was 0.777,and the sensitivity and specificity were 0.898 and 0.549,respectively.The area under ROC curve(AUC)of the verification group was 0.821,and the sensitivity and specificity were 0.857 and 0.7,respectively.Conclusion The risk prediction model for readmission of AECOPD patients established in this study has good predictive efficacy,providing an evaluation tool for early identification and screening of high-risk patients with AECOPD readmission,and provides a reference for medical staff to adjust the treatment and care of high-risk patients.
作者
张桂梅
陈蜀
宋云华
吴阳
周虹媛
ZHANG Guimei;CHEN Shu;SONG Yunhua;WU Yang;ZHOU Hongyuan(School of Nursing,Kunming Medical University,Kunming Yunnan 650500;Dept.of Respiratory and Critical Care Medicine,The 1st Affiliated Hospital of Kunming Medical University,Kunming Yunnan 650500,China)
出处
《昆明医科大学学报》
CAS
2022年第8期184-190,共7页
Journal of Kunming Medical University
基金
云南省教育厅科学研究基金资助项目(2021Y330)。
关键词
AECOPD
再入院
危险因素
预测模型
护理
AECOPD
Readmission
Influencing factors
Prediction model
Nursing care
