Development and validation of a simple‐to‐use nomogram for predicting refractory Mycoplasma pneumoniae pneumonia in children

Abstract Objective This study aimed to develop and validate a simple‐to‐use nomogram for predicting refractory Mycoplasma pneumoniae pneumonia (RMPP) in children. Methods A total of 73 children with RMPP and 146 children with general Mycoplasma pneumoniae pneumonia were included. Clinical, laboratory, and radiological data were obtained. A least absolute shrinkage and selection operator (LASSO) regression model was used to determine optimal predictors. The nomogram was plotted by multivariable logistic regression. The performance of the nomogram was assessed by calibration, discrimination, and clinical utility. Results The LASSO regression analysis identified lactate dehydrogenase, albumin, neutrophil ratio, and high fever as significant predictors of RMPP. This nomogram‐illustrated model showed good discrimination, calibration, and clinical value. The area under the receiver operating characteristic curve of the nomogram was 0.884 (95% CI, 0.823‐0.945) in the training set and 0.881 (95% CI, 0.807‐0.955) in the validating set. Calibration curve and Hosmer‐Lemeshow test showed good consistency between the predictions of the nomogram and the actual observations, and decision curve analysis showed that the nomogram was clinically useful. Conclusion A simple‐to‐use nomogram for predicting RMPP in early stage was developed and validated. This may help physicians recognize RMPP earlier.