A predictive model for macrolide unresponsive Mycoplasma pneumoniae pneumonia in children
- Author:
RAO Rui
;
LI Zhixin
;
JIA Zhongli
;
LI Song
;
SONG Liyao
;
DONG Wenbin
- Publication Type:Journal Article
- Keywords:
application value of the predictive model. Conclusions Pleural effusion, highest body temperature before admission, neutrophil count, C-reactive protein, and procalcitonin are independent risk factors for MUMPP in children. The prediction model constructed based on the above variables has high predictive efficacy and clinical application value.
- From:
China Tropical Medicine
2024;24(7):783-
- CountryChina
- Language:Chinese
-
Abstract:
Abstract: Objective To explore the risk factors for macrolide unresponsive mycoplasma pneumoniae pneumonia (MUMPP) in children and to develop a model for predicting the risk of MUMPP. Methods Children with mycoplasma pneumoniae pneumonia admitted to the Pediatric Department of Leshan People's Hospital who met the inclusion criteria from March 1, 2023, to December 1, 2023, were retrospectively selected and divided into the responsive group and unresponsive group according to their reactions to macrolides. General patient data, laboratory tests, and imaging findings were collected and compared. Logistic regression analysis was used to analyze the risk factors of the Macrolide unresponsive mycoplasma pneumoniae pneumonia, and R language (R4.2.3) to establish the nomogram model. The goodness of fit, discriminative ability, calibration, and clinical utility of the model were assessed using the Hosmer-Lemeshow goodness of fit test, receiver operating characteristic (ROC) curve analysis, calibration curve analysis, and decision curve analysis, respectively. Results A total of 224 patients were included in the analysis of children. Among them, 156 (70%) were randomly selected as the training set, and the remaining 68 cases (30%) were used as the validation set. Logistic regression analysis revealed that pleural effusion (OR=6.986, 95%CI 1.362-35.847), highest temperature before admission (OR=3.095, 95%CI 1.487-6.439), neutrophil count (OR=1.294, 95%CI:1.103-1.519), C-reactive protein (OR=1.030, 95%CI 1.002-1.058), and procalcitonin (OR=2.899, 95%CI:1.353-6.214) were independent risk factors for MUMPP in children (all P<0.05). A nomogram was established using R software. The Hosmer-Lemeshow goodness of fit tests for the training set and the validation set were χ2=4.018 and χ2=4.657 (all P>0.05), indicating a good fit of the model. The AUC values for the training set and validation were 0.825 (95%CI: 0.755-0.894) and 0.828 (95%CI 0.729-0.928), respectively, suggesting good discriminative ability of the model. Calibration curve analysis suggested that the model had good predictive performance, while decision curve analysis indicated a high clinical application value of the predictive model. Conclusions Pleural effusion, highest body temperature before admission, neutrophil count, C-reactive protein, and procalcitonin are independent risk factors for MUMPP in children. The prediction model constructed based on the above variables has high predictive efficacy and clinical application value.
- Full text:2025062010473512695.A predictive model for macrolide unresponsive Mycoplasma pneumoniae pneumonia in children.pdf
