摘要
目的探究重症肺炎合并脓毒症患者预后影响因素并构建预测模型。方法回顾性纳入南京医科大学附属泰州人民医院2019年3月至2022年3月重症肺炎合并脓毒症318例患者作为研究对象,按大约3∶1比例,用R软件随机分为建模集(n=233)和验证集(n=85)。建模集患者根据入院30 d结局分为生存组(n=180)和死亡组(n=53)。采用多因素Cox回归分析评估建模集患者入院30 d预后的影响因素,使用R软件构建列线图预测模型,并通过受试者工作特征曲线(ROC)、决策曲线分析(DCA)和calibrate校准曲线用验证集数据对构建的模型进行验证。结果多因素Cox回归分析提示,脓毒性休克(HR=2.32,95%CI 1.37~3.89,P=0.013)、中性粒细胞/淋巴细胞比值(NLR)(HR=2.52,95%CI 1.23~5.61,P=0.017)是重症肺炎合并脓毒症患者入院30 d死亡的独立危险因素,而白蛋白/纤维蛋白原比值(AFR)(HR=0.64,95%CI 0.41~0.83,P=0.011)和预后营养指数(PNI)(HR=0.68,95%CI 0.57~0.83,P=0.009)是重症肺炎合并脓毒症患者入院30 d死亡的独立保护因素。ROC曲线分析提示,列线图模型AUC在建模集和验证集中分别为0.875和0.880。DCA曲线结果提示,该模型在建模集和验证集中的临床效益均优于"所有"或"无"曲线;calibrate曲线结果提示该模型的实际、矫正曲线拟合好,且接近于理想曲线。结论基于脓毒性休克、AFR、NLR和PNI构建的预测模型对于重症肺炎合并脓毒症患者预后具有较好的预测价值。
Objective To construct a prediction model for prognosis of severe pneumonia patients combined with sepsis.Methods Clinical data of 318 severe pneumonia patients combined with sepsis admitted at Taizhou People’s Hospital affiliated to Nanjing Medical University from March 2019 to March 2022 were retrospectively analyzed.Patients were randomized into a modeling set(n=233)and a validation set(n=85)with a 3∶1 ratio.In the modeling set there were 180 survival cases and 53 fatal cases according to the clinical outcomes within 30 days of admission.Multivariate Cox regression analysis was used to evaluate the independent prognostic factors for patients in the modeling set.A nomogram prediction model was constructed by R based on these prognostic factors and further verified using the data of the validation set with receiver operating curve(ROC),decision curve analysis(DCA),and calibrated with calibration curve analyses.Results Multivariate Cox regression analysis suggested that septic shock(HR=2.32,95%CI 1.37-3.89,P=0.013)and neutrophil/lymphocyte ratio(NLR)(HR=2.52,95%CI 1.23-5.61,P=0.017)were independent risk factors for mortality in severe pneumonia patients combined with sepsis within 30 days of admission,while albumin/fibrinogen ratio(AFR)(HR=0.64,95%CI 0.41-0.83,P=0.011)and prognostic nutritional index(PNI)(HR=0.68,95%CI 0.57-0.83,P=0.009)were independent protective factors.The area under ROC curve(AUC)of the nomogram model based on these four indicators in the modeling and validation sets were 0.875 and 0.880,respectively.The DCA curve analysis indicated that the clinical benefit of this model was better than"All"or"None"curves in both the modeling and verification sets.The calibrate curve analysis indicated that the actual and corrected curves fitted well and were close to the ideal curve.Conclusion The constructed nomogram model based on septic shock,AFR,NLR and PNI has a well prognostic value in severe pneumonia patients combined with sepsis.
作者
张玮
华璐
邰慧宇
周大明
Zhang Wei;Hua Lu;Tai Huiyu;Zhou Daming(Department of Infectious Diseases,Taizhou People’s Hospital Affiliated to Nanjing Medical University,Taizhou 225300,Jiangsu Province,China;Department of Oncology,Taizhou People’s Hospital Affiliated to Nanjing Medical University,Taizhou 225300,Jiangsu Province,China;Intensive Care Unit,Taizhou People’s Hospital Affiliated to Nanjing Medical University,Taizhou 225300,Jiangsu Province,China)
出处
《中华临床感染病杂志》
CAS
CSCD
2022年第5期352-359,共8页
Chinese Journal of Clinical Infectious Diseases
基金
南京医科大学附属泰州人民医院科研基金项目(ZL202230)。
关键词
重症肺炎
脓毒症
预后
列线图模型
Severe pneumonia
Sepsis
Prognosis
Nomogram model
