Development of a Nomogram for Predicting Refractory Mycoplasma pneumoniae Pneumonia in Children

Abstract

BackgroundIn children, refractory Mycoplasma pneumoniae pneumonia (RMPP) may result in severe complications and high medical costs. There is research on a simple and easy-to-use nomogram for early prediction and timely treatment of RMPP.MethodsFrom December 2018 to June 2021, we retrospectively reviewed medical records of 299 children with Mycoplasma pneumoniae pneumonia (MPP) hospitalized in Tianjin Children's Hospital. According to their clinical manifestations, patients were divided into the RMPP group and the general Mycoplasma pneumoniae pneumonia (GMPP) group. The clinical manifestations, laboratory indicators, and radiological data of the two groups were obtained. Stepwise regression was employed for variable selection of RMPP. The predictive factors selected were used to construct a prediction model which presented with a nomogram. The performance of the prediction model was evaluated by C statistics, calibration curve, and receiver operating characteristic (ROC) curve.ResultsThe RMPP group significantly showed a higher proportion of females, longer fever duration, and longer hospital stay than the GMPP group (P < 0.05). Additionally, the RMPP group revealed severe clinical characteristics, including higher incidences of extrapulmonary complications, decreased breath sounds, unilateral pulmonary consolidation >2/3, and plastic bronchitis than the GMPP group (P < 0.05). The RMPP group had higher neutrophil ratio (N%), C-reactive protein (CRP), interleukin-6 (IL-6), lactic dehydrogenase (LDH), and D-dimer than the GMPP group (P < 0.05). Stepwise regression demonstrated that CRP [OR = 1.075 (95% CI: 1.020–1.133), P < 0.001], LDH [OR = 1.015 (95% CI: 1.010–1.020), P < 0.001], and D-dimer [OR = 70.94 (95% CI: 23.861–210.904), P < 0.001] were predictive factors for RMPP, and developed a prediction model of RMPP, which can be visualized and accurately quantified using a nomogram. The nomogram showed good discrimination and calibration. The area under the ROC curve of the nomogram was 0.881, 95% CI (0.843, 0.918) in training cohorts and 0.777, 95% CI (0.661, 0.893) in validation cohorts, respectively.ConclusionC-reactive protein, LDH, and D-dimer were predictive factors for RMPP. The simple and easy-to-use nomogram assisted us in quantifying the risk for predicting RMPP, and more accurately and conveniently guiding clinicians to recognize RMPP, and contribute to a rational therapeutic choice.

Development and validation of a nomogram for predicting Mycoplasma pneumoniae pneumonia in adults

“…Dynamic monitoring of CRP levels can be used to assess the prognosis of hospitalized CAP patients 31 . In a prior investigation, CRP was found to be an independent predictor of refractory mycoplasma pneumonia in children 32 . We found that CRP was a predictor of MPP in adults and was mildly elevated in MPP adult patients, which suggested a mild inflammatory response in patients.…”

“…Nomograms, which are intuitive and visualized risk prediction models, have been widely used in recent years to predict cancer and surgical prognosis 12 – 14 , can rapidly and accurately identify high-risk groups and can improve the diagnostic efficacy. In the latest research, a nomogram was used to predict the occurrence of refractory Mycoplasma pneumoniae pneumonia (RMPP) in children and bronchial mucus plugs in children with MPP, and both showed good predictive performance 15 , 16 . However, few predictive models have been reported for MPP in adults.…”

Construction of a Nomogram for Identifying Refractory Mycoplasma pneumoniae Pneumonia Among Macrolide-Unresponsive Mycoplasma pneumoniae Pneumonia in Children

“…Compared with other published papers, [40][41][42] the enrolled patients in our study differed in two points: 1) patients were confirmed as macrolide-unresponsive MPP (MUMPP); 2) patients continued to be treated with macrolide (azithromycin) after the confirmation of MUMPP without antibiotic changes. In addition, the purpose of this study is different from other studies.…”

Research status and challenges of Mycoplasma pneumoniae pneumonia in children: A bibliometric and visualization analysis from 2011 to 2023

“…In the recent 2 years, as a new type of predictive model with easy clinical application, strong discriminatory ability and high accuracy, the nomogram model has been confirmed in several retrospective studies for its validity as an early identification of RMPP. [19][20][21][22][23] However, the variability of the indicators included in different studies has led to a lack of consistency in the nomogram model, and external validation by prospective multicenter studies is needed for its clinical application.…”