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Development of a Nomogram for Predicting Refractory Mycoplasma pneumoniae Pneumonia in Children
Fangfang Shen1, Chunjuan Dong1, Tongqiang Zhang1
1Department of Pediatric Respiratory Medicine, Tianjin Children's Hospital, Tianjin University Children's Hospital, Tianjin, China.
Insights
A new nomogram can predict refractory Mycoplasma pneumoniae pneumonia (RMPP) in children using C-reactive protein, LDH, and D-dimer levels. This tool aids early RMPP detection and guides treatment choices.
Area of Science:
- Pediatric Infectious Diseases
- Respiratory Medicine
- Biostatistics
Background:
- Refractory Mycoplasma pneumoniae pneumonia (RMPP) in children leads to severe complications and high healthcare costs.
- Early prediction and timely intervention are crucial for managing RMPP.
- A simple nomogram can aid in the early identification and treatment of RMPP.
Purpose of the Study:
- To develop and validate a predictive model for RMPP in children.
- To identify key clinical and laboratory indicators for RMPP prediction.
- To create a user-friendly nomogram for risk quantification and clinical decision support.
Main Methods:
- Retrospective review of 299 children with Mycoplasma pneumoniae pneumonia (MPP).
- Division of patients into RMPP and general MPP (GMPP) groups based on clinical manifestations.
- Stepwise regression analysis to identify predictive factors for RMPP, followed by nomogram construction and validation.
Main Results:
- RMPP group showed higher rates of female patients, prolonged fever, and longer hospital stays.
- RMPP was associated with more severe clinical features, including extrapulmonary complications and unilateral pulmonary consolidation.
- C-reactive protein (CRP), lactate dehydrogenase (LDH), and D-dimer were identified as significant predictors of RMPP.
Conclusions:
- CRP, LDH, and D-dimer are key predictive factors for RMPP in children.
- The developed nomogram effectively quantifies RMPP risk, aiding clinicians in early recognition and treatment.
- The nomogram provides a convenient tool for guiding rational therapeutic choices in RMPP management.
Background:
In 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.
Methods:
From 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.
Results:
The 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.
Conclusion:
C-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.
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