基于外周血炎症指标的重症成人社区获得性肺炎预测模型的构建与验证

Development and validation of a prediction model for severe community-acquired pneumonia in adults based on peripheral blood inflammatory indicators

目的探讨基于外周血炎症指标的重症成人社区获得性肺炎预测模型的构建与验证。方法收集2021年4月至2022年8月重庆地区7家医院收治的204例成人社区获得性肺炎患者静脉血标本,检测C反应蛋白(CRP)、外周血白细胞计数(WBC)、中性粒细胞与淋巴细胞比值(NLR)、细胞因子、淋巴细胞亚群和中性粒细胞CD64指数等指标。根据患者入院时间的先后顺序将患者分为训练集和验证集。采用单因素和多因素Logistic回归分析训练集数据,筛选出重症化特征性指标以构建列线图模型并用验证集数据验证模型。根据训练集和验证集的受试者工作特征(ROC)曲线、校准曲线和决策曲线分析(DCA)以评价模型对重症成人社区获得性肺炎的预测能力。结果Logistic回归分析显示,年龄、CRP、WBC、白细胞介素(IL)-4/干扰素γ比值、IL-6/IL-10比值是重症成人社区获得性肺炎的独立危险因素。列线图模型在训练集和验证集中ROC曲线的曲线下面积分别为0.893和0.880。校准曲线和DCA结果表明,该模型对重症成人社区获得性肺炎具有良好的预测效果。结论该模型纳入的炎症指标简单且临床上非常容易获得,区分度和准确度较好,可以作为预测重症成人社区获得性肺炎的实用工具,具有一定的临床应用价值。

Objective To explore the development and validation of a prediction model for severe community-acquired pneumonia in adults based on peripheral blood inflammatory indicators.Methods Venous blood samples of 204 community-acquired pneumonia in adults patients admitted to 7 hospitals in Chongqing area from April 2021 to August 2022 were collected to detect C-reactive protein(CRP),peripheral white blood cell count(WBC),neutrophil to lymphocyte ratio(NLR),cytokines,lymphocyte subgroups and neutrophil CD64 index.All of patients were divided into a training group and a validation group according to the time of admission.Univariate and multivariate Logistic regression were used to analyze the data of the training group,the characteristic factors of severe progression for pneumonia were selected to construct the nomogram model,and the data of the validation group was used to verify the model.The receiver operating characteristic(ROC)curve,calibration curve and decision curve analysis(DCA)were used to evaluate the prediction ability of the model for severe community-acquired pneumonia in adults.Results Logistic regression analysis showed that age,CRP,WBC,interleukin(IL)-4/interferon gamma ratio and IL-6/IL-10 ratio were independent risk factors for severe community-acquired pneumonia in adults.The area under the ROC curve of the nomogram model in the training group and the validation group was 0.893 and 0.880,respectively.The calibration curve and DCA results shown that the model had a good prediction effect for severe community-acquired pneumonia in adults.Conclusion The inflammatory indicators included in this model are simple and easy to obtain clinically.This model with good differentiation and accuracy,it can be used as a practical tool to predict severe community-acquired pneumonia in adults,and has certain clinical application value.