基于复合型免疫炎症指标的列线图模型对重症腺病毒肺炎患儿并发呼吸衰竭的预测价值  

Predictive value of a nomogram model based on complex immunoinflammatory indicators for respiratory failure in the children with severe adenovirus pneumonia

作　　者：高哲 李静 颜洋 毛淑炯[3] Gao Zhe;Li Jing;Yan Yang;Mao Shujiong(Department of Pediatrics,Graduate School,Zhejiang Chinese Medical University,Hangzhou 310053,China)

机构地区：[1]浙江中医药大学研究生院儿科,浙江杭州310053 [2]杭州市余杭区第三人民医院儿科,浙江杭州311115 [3]杭州市第一人民医院儿科,浙江杭州310006

出　　处：《中国急救医学》2025年第3期218-225,共8页Chinese Journal of Critical Care Medicine

摘　　要：目的探讨基于复合型免疫炎症指标的列线图模型对重症腺病毒肺炎患儿并发呼吸衰竭的预测价值。方法回顾性研究杭州市余杭区第三人民医院2021年1月至2024年10月的202例重症腺病毒肺炎患儿,记录患儿住院期间的各项临床指标,根据重症腺病毒肺炎后3 d内是否发生呼吸衰竭分为呼吸衰竭组(n=104)和非呼吸衰竭组(n=98),利用Logistic回归分析识别呼吸衰竭的关键风险因素并构建对应列线图预测模型。通过内部验证法(校准曲线和Bootstrap法)评估模型的准确性。进一步通过受试者工作特征(ROC)曲线分析模型的效能,最终以临床决策曲线分析(DCA)探讨模型的实际应用价值。结果本研究重症腺病毒肺炎患儿的呼吸衰竭发生率为51.5%,Logistic回归分析发现重症腺病毒肺炎患儿发生呼吸衰竭的独立危险因素包括合并低蛋白血症(OR=9.845,95%CI 1.904~50.903,P=0.006)、多器官功能障碍评分(MODS,OR=1.773,95%CI 1.113~2.825,P=0.016)、社区获得性肺炎评分(CURB-65,OR=1.884,95%CI 1.160~3.060,P=0.010)、急性生理与慢性健康状况评分Ⅱ(APACHEⅡ,OR=1.293,95%CI 1.118~1.496,P<0.001)、中性粒细胞/淋巴细胞比值(NLR,OR=1.868,95%CI 1.271~2.744,P=0.001)、系统免疫炎症指数(SII,OR=1.002,95%CI 1.001~1.003,P=0.001)。基于以上独立危险因素构建列线图预测模型,ROC曲线分析其预测呼吸衰竭发生的曲线下面积(AUC)为0.806,95%CI为0.745~0.874,提示该模型具有较好的预测效能。Hosmer-Lemeshow检验显示该模型具有较好的拟合度(P=0.089),DCA提示该模型具有较高的临床应用价值。结论呼吸衰竭在重症腺病毒肺炎患儿中的发生率较高,基于低蛋白血症、MODS评分、CURB-65评分、APACHEⅡ评分、NLR、SII构建的列线图模型在预测重症腺病毒肺炎患儿发生呼吸衰竭风险中具有一定临床应用价值,早期监测并对症干预上述因素可能有利于改善患儿预后。Objective To investigate the predictive value of a nomogram model based on complex immunoinflammatory indicators for respiratory failure in the children with severe adenovirus pneumonia.Methods A study was carried out retrospectively on 202 children diagnosed with severe adenovirus pneumonia in the Third People′s Hospital of Yuhang District,Hangzhou City from January 2021 to October 2024.The clinical parameters measured during their hospital stay were documented,and the children were categorized into two groups:respiratory failure group(n=104)and without respiratory failure group(n=98)based on whether respiratory failure occurred within 3 days after the onset of severe adenovirus pneumonia.Logistic regression analysis was employed to pinpoint the key risk factors associated with respiratory failure,and a nomogram prediction model was constructed accordingly.The model′s accuracy was assessed by internal validation techniques such as the calibration curve and the Bootstrap method.Furthermore,the model′s performance was evaluated by using the receiver operating characteristic(ROC)curve,while the clinical decision curve analysis(DCA)was utilized to investigate the practical utility of the model.Results In the children with severe adenovirus pneumonia,the frequency of respiratory failure was found to be 51.5%.Logistic regression analysis showed that several factors were independently associated with an increased risk of respiratory failure in these children,including hypoalbuminemia(OR=9.845,95%CI 1.904-50.903,P=0.006),multiple organ dysfunction score(MODS,OR=1.773,95%CI 1.113-2.825,P=0.016),confusion,uremia,respiratory rate,blood pressure,age over 65 years(CURB-65,OR=1.884,95%CI 1.160-3.060,P=0.010),acute physiology and chronic health years evaluationⅡ(APACHEⅡ,OR=1.293,95%CI 1.118-1.496,P<0.001),neutrophil/lymphocyte ratio(NLR,OR=1.868,95%CI 1.271-2.744,P=0.001),and systemic immunoinflammatory index(SII,OR=1.002,95%CI 1.001-1.003,P=0.001).To assist in predicting the likelihood of respiratory failure,a nomog

关 键 词：呼吸衰竭 重症腺病毒肺炎 免疫炎症指标 危险因素 预测模型 

分 类 号：R725.6[医药卫生—儿科]