关键词: 大环内酯类耐药, 重症肺炎支原体肺炎, 预测模型, 列线图, 儿童

Abstract: Objective To explore the risk factors and to construct a nomogram prediction model for severe macrolide-resistant Mycoplasma pneumoniae pneumonia（MPP）in children．Methods The clinical data during the initial admission period of 1 121 children with macrolide-resistant MPP who were hospitalized in the Department of Pediatrics of the Affiliated Panyu Central Hospital of Guangzhou Medical University from January 2023 to September 2024 were retrospectively collected．The children data were randomly divided into a training set（n=784）and a validation set（n=337）at a ratio of 7∶3．With R language software（version 4.4.1）,least absolute shrinkage and selection operator（LASSO）regression analysis with tenfold cross-validation was used to screen risk factors,Logistics regression analysis was used to establish prediction model,and a visualization of the risk variables was created using a nomogram．The receiver operating characteristic（ROC）curves,calibration curves,Hosmer-Lemeshow（HL）test and clinical decision curve analysis（DCA）were used to evaluate the discrimination,calibration and clinical application value of the model．Results In the training set,LASSO regression analysis combined with Logistics regression analysis showed that prehospital fever duration > 5.5 days,alanine aminotransferase level> 14.5 U/L,lactate dehydrogenase level> 287.5 U/L,C-reactive protein > 18.65 mg/L,lung consolidation,and co-infection with virus were risk factors for severe macrolide-resistant MPP（P<0.05）．A nomogram prediction model was constructed based on the above risk factors．The area under the ROC curves of the training set and the validation set were 0.847 and 0.822,respectively．The calibration curves and HL test showed that the model had good calibration． The DCA curves showed that the prediction model had the best prediction performance when the risk threshold was between 0.05-0.95．Conclusions Prehospital fever duration,alanine aminotransferase level,lactate dehydrogenase level,C-reactive protein level,lung consolidation and co-infection with virus were risk factors for prediction of severe macrolide-resistant MPP．The nomogram model based on the above factors had a good prediction efficiency,which was conducive to early identification of severe cases with macrolide-resistant,and taking early effective interventions to improve the prognosis．

Key words: macrolide-resistant, severe Mycoplasma pneumoniae pneumonia, prediction model, nomogram, children