ISSN 2097-6046（网络）
ISSN 2096-7446（印刷）
CN 10-1655/R
主管：中国科学技术协会
主办：中华护理学会
中华急危重症护理杂志

中华急危重症护理杂志 ›› 2024, Vol. 5 ›› Issue (10): 869-875.doi: 10.3761/j.issn.2096-7446.2024.10.001

• 论著 •    下一篇

慢加急性肝衰竭患者肺部感染风险评分工具的构建及应用研究

王李晶子, 李沛, 张岚, 吴沙沙, 杜虹, 党肖   

  1. 710038 西安市 空军军医大学第二附属医院传染科
  • 收稿日期:2023-11-13 发布日期:2024-10-21
  • 通讯作者: 党肖,E-mail：513307098@qq.com
  • 作者简介:王李晶子：女,硕士,护师,护士,E-mail：wanglijingzhi16@163.com
  • 基金资助:
    空军军医大学第二附属医院社会人才项目（2021SHRC057）

Development and application of a risk scoring tool for pulmonary infection in patients with acute-on-chronic liver failure

WANG Lijingzi, LI Pei, ZHANG Lan, WU Shasha, DU Hong, DANG Xiao   

  1. Department of Infectious Diseases,The Second Affiliated Hospital of Air Force Military Medical University,Xi‘an, 710038,China
  • Received:2023-11-13 Published:2024-10-21

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摘要： 目的 构建及验证慢加急性肝衰竭（acute-on-chronic liver failure,ACLF）患者发生肺部感染风险评分工具。方法 便利选取2009年1月—2022年9月西安市某三级甲等医院收治的585例ACLF患者,按7 ∶ 3比例分配入建模组（411例）和验证组（174例）。采用单因素和多因素Logistic回归分析ACLF患者发生肺部感染的危险因素,使用建模组数据构建ACLF患者肺部感染风险预测模型,使用验证组数据对模型进行验证。采用受试者工作特征曲线和H-L检验对构建的模型进行区分度和校准度评价。在风险预测模型的基础上构建风险评分工具,并进行临床验证。结果 纳入ACLF患者585例,肺部感染总发生率为36.41%。建模组和验证组肺部感染发生率分别为37.71%和33.33%。多因素Logistic回归结果显示,发热、咳嗽、合并其他感染、联合使用抗生素≥2种、股静脉置管治疗及Child-Pugh分级是ACLF患者发生肺部感染的危险因素（P<0.05）。预测模型受试者操作特征曲线下面积为0.949（0.928~0.970）,灵敏度为96.1%,特异度为80.5%,H-L检验χ2=9.850,P=0.276。模型预测、校准度较好。开发的评分工具约登指数最大值为0.766,临界值为16分。结合ACLF患者发生肺部感染评分-概率对照图将患者分为低、中、中高及高风险4个等级。对应的灵敏度为96.1%,特异度为80.5%,H-L检验χ2=6.005,P=0.650。将风险评分工具初步应用到临床中,显示模型的准确率为86.8%。结论 风险评分工具有较高的区分度和校准度,可帮助医护人员临床快速、便捷、早期识别ACLF患者发生肺部感染的风险。

关键词: 慢加急性肝衰竭, 肺部感染, 评分工具, 护理

Abstract: Objective To develop and validate a risk scoring tool for pulmonary infection in patients with acute-on-chronic liver failure（ACLF）. Methods 585 patients with ACLF in a tertiary Class A hospital from January 2009 to September 2022 were selected and assigned to the modeling group（411 cases） and the validation group（174 cases） in a 7 ∶ 3 ratio. We used univariate and multivariate logistic regression to analyze the risk factors for pulmonary infection in ACLF patients. We constructed a predictive model for pulmonary infection risk in ACLF patients using modeling group data,and validated the model using validation group data. The discriminability and calibration of the constructed model were evaluated using receiver operating characteristic curves and H-L test. Then we developed a risk scoring tool based on a risk prediction model and applied it in clinical practice. Results 585 patients with ACLF were included,and a total incidence of pulmonary infection was 36.41%. The incidence rates of pulmonary infection in modeling group and validation group were 37.71% and 33.33%,respectively. The results of multivariate logistic regression showed that fever,cough,concomitant infections,combined use of antibiotics≥2,femoral vein catheterization treatment,and Child-Pugh grading were risk factors for pulmonary infection in ACLF patients（P<0.05）. The area under the ROC curve of the prediction model is 0.949（0.928~0.970）,with a sensitivity of 96.1% and a specificity of 80.5%. The H-L test result was（χ2=9.850,P=0.276）. The results showed that the model has good prediction and calibration. The maximum value of the developed scoring tool‘s Youden index wss 0.766,with a critical score of 16. Based on the probability comparison chart of ACLF patients with pulmonary infection,the patients were divided into four levels：low,medium,medium high,and high risk. The corresponding sensitivity was 96.1%,the specificity was 80.5%,and the H-L test result was（χ2=6.005,P=0.650）. And the risk scoring tool was initially applied to clinical practice,with an accuracy of 86.8%. Conclusion The risk scoring tool for pulmonary infection has a high degree of discrimination and calibration,which can help medical staff quickly,conveniently,and early identify the risk of pulmonary infection in ACLF patients.

Key words: Acute-on-Chronic Liver Failure, Pulmonary Infection, Scoring Tool, Nursing Care