Objective
The purpose of this study was to develop a model for predicting severe mycoplasma pneumoniae pneumonia (SMMP) in pediatric patients with MMP on admission by laboratory indicators.
Methods
Pediatric patients with MPP from January 2019 to December 2020 in our hospital were enrolled in this study. SMMP was diagnosed according to guideline for diagnosis and treatment of community acquired pneumonia in children (2019 version). Prediction model was developed according to the admission laboratory indicators. ROC curve and Goodness of fit test were analyzed for the predictive value.
Results
A total of 233 MMP patients were included in the study, with 121 males and 112 females, aged 4.541 (1–14) years. Among them, 84 (36.1%, 95% CI 29.9%-42.6%) pediatric patients were diagnosed as SMPP. Some admission laboratory indicators (IgM, eosinophil proportion, eosinophil count, hemoglobin, ESR, total protein, albumin and prealbumin) were found statistically different (P < 0.05) between non-SMMP group and SMMP group. Logistic regress analysis showed IgM, eosinophil proportion, eosinophil count, ESR, and prealbumin were independent risk factors for SMMP. According to these five admission laboratory indicators, Nomograph prediction model was developed. The AUC of the Nomograph prediction model was 0.777, and the goodness of fit test showed that the predicted incidence of the model was consistent with the actual incidence (χ2 = 244.51, P = 0.203).
Conclusion
We developed a model for predicting SMMP in pediatric patients by admission laboratory indicators. This model has good discrimination and calibration, which provides a basis for the early identification SMMP on admission.