Purpose: Early diagnosis of refractory Mycoplasma pneumoniae pneumonia (RMPP) is challenging because of the lack of practical diagnostic imaging tools. Lung ultrasound (LUS) is an emerging tool for diagnosing childhood pneumonia. Hence, we evaluated the role of a nomogram combining LUS findings, clinical features, and laboratory indices in the early prediction of RMPP in children.
Patients and Methods: We retrospectively analyzed 225 children with Mycoplasma pneumoniae pneumonia (MPP) admitted to our hospital between Dec 2018 and Aug 2021. Logistic regression analysis incorporated LUS findings and clinical predictors into the nomogram. Ninety patients hospitalized from Sep 2021 to Dec 2021 were used for external validation of the prediction model. Receiver operating characteristics (ROC) and calibration curves were used to evaluate the performance of the nomogram in the early diagnosis of RMPP.
Results: Ultimately, Consolidation size /BSA (odds ratio (OR) 1.015, 95% confidence interval (CI) 1.536– 2.446), Pleural Effusion (OR 3.551, 95% CI 1.921– 15.600), LDH (OR 1.044, 95% CI 1.006– 1. 021) and CRP (OR 3.293, 95% CI 1.019– 1.098) were independent risk factors for the development of RMPP. The prediction model was represented visually as a nomogram. The area under the ROC curve for the predictive nomogram was 0.955 (95% CI 0.919– 0.978) in the training cohort and 0.916 (95% CI 0.838– 0.964) in the validation cohort. The calibration curve is close to the diagonal.
Conclusion: This is the first-time lung ultrasound was added to the predicted nomogram, which can more comprehensively assess the condition and more accurately predict the occurrence of RMPP early. Therefore, this nomogram can be widely used in the early diagnosis of RMPP, especially in primary care hospitals.
Keywords: predictive model, risk factors, diagnosis, Mycoplasma pneumoniae pneumonia