Model establishment and clinical value of Nomogram-based prediction of severe Mycoplasma pneumoniae pneumonia in children
Objective To develop a model for predicting severe Mycoplasma pneumoniae pneumonia(SMPP)in chil-dren based on Nomograms and to analyse the clinical value of the model.Methods Totally 350 children with Mycoplas-ma pneumoniae pneumonia(MPP)admitted to our hospital from June 2021 to June 2023 were collected as study sub-jects and divided into training set and validation set according to the random number table method in the ratio of 7∶3 ret-rospectively.After admission,the children were divided into mild and severe groups according to the progression of their disease.In the training set,the x2test was used for univariate analyses,and binary logistic regression analysis was used for multivariate analyses.Nomogram prediction model was established based on independent risk factors.Calibration and receiver operating characteristic(ROC)curves were used to assess the predictive accuracy of the model,and clinical decision curve analysis(DCA)was used to assess the clinical safety and utility of the model.Results Comparison of general clinical data between the training and validation sets showed no statistically significant differences(P＞0.05).Univariate analysis of the training set showed statistically significant differences(P＜0.05)when comparing age,tem-perature,fever duration,mycoplasma antibody titer,ESR and CRP between the mild and severe groups.The results of multivariate analysis showed that age＜7 years,temperature ≥39.0℃,fever duration ≥5d,mycoplasma antibody ti-ter＞1∶160,ESR＞20 mm/h and CRP＞10 mg/L were independent risk factors for the development of SMPP.The ar-ea under the curve(AUC)of the Nomogram prediction model based on the above risk factors was 0.905 in the training set and 0.873 in the validation set.The calibration curves showed high fit and consistency in both the training and vali-dation sets.The results of the DCA showed that the Nomogram model demonstrated a high degree of safety and utility in the prediction of SMPP.Conclusion The occurrence of SMPP in children is associated with age,temperature,duration of fever,mycoplasma antibody titer,ESR and CRP.The Nomogram prediction model constructed with the above factors is highly accurate and helps to identify the risk of SMPP in children at an early stage,so that effective preventive and therapeutic measures can be taken.
NomogramMycoplasma pneumoniae pneumoniaSevereChildrenPredictive model
NETL
NSTL
万方数据
