基于25(OH)D₃、CAR、TRAF1及临床资料构建新生儿肺炎链球菌肺炎病情转归的列线图预测模型

Nomogram prediction model for prognosis of neonatal streptococcus pneumoniae pneumonia based on 25(OH)D ₃,CAR,TRAF1 and clinical data

摘要

目的 探讨新生儿肺炎链球菌肺炎病情转归的影响因素,并构建预测模型。方法 选取2021年1月至2025年5月自贡市第四人民医院300例肺炎链球菌肺炎新生儿,按照7∶3比例分为训练集(210例)与验证集(90例),并根据病情转归分为不良组与良好组。比较两组临床资料及血清指标。采用Lasso与Logistic回归分析筛选独立预测因子,R软件构建预测模型,并对模型预测效能予以验证。结果 训练集与验证集中新生儿肺炎链球菌肺炎病情转归不良率分别为23.81%(50/210)、23.33%(21/90);病情重、降钙素原(PCT)、C反应蛋白/白蛋白比值(CAR)、肿瘤坏死因子受体相关因子1(TRAF1)均为新生儿肺炎链球菌肺炎病情不良转归的危险因素(OR介于1.535到2.495之间),25-羟基维生素D₃[25(OH)D₃]是新生儿肺炎链球菌肺炎病情不良转归的保护因素(OR=0.813,P<0.05);在训练集与验证集中,受试者工作特征(ROC)曲线分析显示,该预测模型的曲线下面积(AUC)分别为0.922(95%CI:0.882~0.963)、0.873(95%CI:0.796~0.951);校准曲线、Hosmer-Lemeshow拟合优度检验(P均>0.05)及决策曲线(DCA)显示,该模型拟合良好,预测精度可靠,且具有良好的临床实用性。结论 病情严重程度、PCT、CAR、TRAF1、25(OH)D₃均为新生儿肺炎链球菌肺炎病情转归的影响因素,据此构建的列线图预测模型综合预测性能及临床实用性良好。

Abstract

Objective To explore the influencing factors of the prognosis of neonatal streptococcus pneumoniae pneumonia and to construct a predictive model. Methods A total of 300 neonates with streptococcus pneumoniae pneumonia in Zigong Fourth People's hospital from January 2021 to May 2025 were selected.They were divided into a training set (210 cases) and a validation set (90 cases) at a ratio of 7:3,and were classified into the poor group and the good group based on the prognosis.The clinical data and serum indicators of the two groups were compared.Lasso and Logistic regression analysis were used to screen independent predictive factors.The prediction model was constructed using R software,and the predictive efficacy of the model was verified. Results The rates of poor prognosis of neonatal streptococcus pneumoniae pneumonia in the training set and the validation set were 23.81% (50/210) and 23.33% (21/90),respectively.Severe condition,procalcitonin (PCT),C-reactive protein to albumin ratio (CAR),and tumor necrosis factor receptor-associated factor 1 (TRAF1) were all risk factors for poor prognosis of neonatal streptococcus pneumoniae pneumonia (OR ranged from 1.535 to 2.495),and 25-hydroxyvitamin D₃ [25(OH)D₃]was a protective factor for poor prognosis of neonatal streptococcus pneumoniae pneumonia (OR =0.813,P <0.05).The receiver operating characteristic (ROC) curve analysis in the training set and the validation set showed that the area under the curve (AUC) of the prediction model was 0.922 (95%CI:0.882-0.963) and 0.873 (95%CI:0.796-0.951),respectively.The calibration curve,Hosmer-Lemeshow goodness-of-fit test (P>0.05),and decision curve analysis (DCA) showed that the model fit well,had reliable prediction accuracy,and had good clinical practicability. Conclusion The severity of the condition,PCT,CAR,TRAF1,and 25(OH)D₃ are all influencing factors of the prognosis of neonatal streptococcus pneumoniae pneumonia.The constructed nomogram prediction model has good comprehensive predictive performance and clinical practicability.

关键词

新生儿肺炎 / 肺炎链球菌 / 预后 / 列线图 / 预测模型

Key words

neonatal pneumonia / streptococcus pneumoniae / prognosis / nomogram / prediction model

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基金资助

四川省卫生健康委员会2023年四川省卫生健康科研课题(23PJ306)