列线图模型在肺炎支原体感染患儿中塑型性支气管炎发生的预测价值

目的：探究列线图模型在肺炎支原体肺炎（MPP）患儿中塑型性支气管炎（PB）发生的预测价值。方法：以2018年6月至2022年6月兰州市西固区人民医院儿科收治的MPP患儿246例为研究对象进行回顾性分析，根据患儿是否发生PB分为PB组（n=66）和非PB组（n=180）。通过单因素分析及多因素Logistic回归分析筛选变量，构建MPP患儿PB发生的列线图预测模型，再分别通过校准曲线评估预测模型的一致性，受试者工作特征（ROC）曲线评估预测模型的准确性，决策曲线分析（DCA）评估预测模型的临床价值。结果：与非PB组比较，PB组患儿热程、体温热峰、中性粒细胞百分比、白细胞介素-6、乳酸脱氢酶、D-二聚体、C-反应蛋白、低氧血症比例、应用糖皮质激素比例、肺不张比例、胸腔积液比例显著升高（P<0.05），血小板显著降低（P<0.05）。多因素Logistic回归结果示，热程、体温热峰、肺不张、胸腔积液、中性粒细胞百分比、血小板、白细胞介素-6、乳酸脱氢酶是MPP患儿PB发生的影响因素。校准曲线结果示，列线图模型预测PB的发生概率与实际发生率的一致性较好。ROC曲线结果示，列线图模型...

The predictive value of nomogram model in the occurrence of plastic bronchitis in patients with Mycoplasma pneumoniae infection

Objective: To explore the predictive value of nomogram model in the occurrence of plastic bronchitis (PB) in children with Mycoplasma pneumoniae pneumonia (MPP). Methods: A retrospective analysis was performed on 246 children with MPP who were admitted to the pediatrics department of Lanzhou Xigu District People’s Hospital from June 2018 to June 2022. Children were divided into PB group (n=66) and non-PB group (n=180) according to whether PB occurred or not. The variables were screened by univariate analysis and multivariate logistic regression analysis, and a nomogram prediction model for the occurrence of PB in children with MPP was constructed. Then, the consistency of the prediction model by calibration curve, the accuracy of the prediction model by receiver operating characteristic (ROC) curve, and the clinical value of the prediction model was evaluated by decision curve analysis (DCA). Results: The values of fever duration, peak body temperature, neutrophil percentage, interleukin-6, lactate dehydrogenase, D-dimer, C-reactive protein and the proportions of children with hypoxemia, glucocorticoids, atelectasis and pleural effusion were significantly higher than those in the non-PB group (P<0.05), while the platelet count was significantly lower than that in the non-PB group (P<0.05). Multivariate logistic regression results showed that fever duration, peak body temperature, atelectasis, pleural effusion, neutrophil percentage, platelet count, interleukin-6 and lactate dehydrogenase were the influencing factors of PB in children with MPP. The calibration curve results showed that the incidence of PB predicted by the nomogram model had a good agreement with the actual incidence. The ROC curve resultsshowed that the AUC of the nomogram model was 0.925 (95%CI=0.886 -0.965, P<0.05). The DCA curve results showed that the nomogram model had a higher rate of clinical net benefit. Conclusion: In this study, a nomogram prediction model for the occurrence of PB in children with MPP was constructed by using fever duration, peak body temperature, atelectasis, pleural effusion, neutrophil percentage, platelet count, interleukin-6 and lactate dehydrogenase, which has good consistency and accuracy, clinical application value.