Epidemiological characteristics and early prediction model of Mycoplasma pneumoniae pneumonia outbreak in children after COVID-19 in Shandong


On November 13, the National Health Commission reported an increase in respiratory illnesses among children across the country, particularly in northern regions. Investigations showed that the increase was mainly due to the relaxation of COVID-19 control measures with the onset of cold weather11,12,13After the epidemic ended, many children who had not been exposed to these germs for a long time became susceptible to them.14,15. As previously common respiratory pathogens re-emerged, widespread non-seasonal outbreaks have begun. Recent reports of respiratory illnesses, particularly an increase in childhood pneumonia cases, have been attributed primarily to a combination of MP and viral infections.

The incidence rate of MP confirmed by direct detection in all age groups worldwide was 8.61% from 2017 to 2020. However, during the COVID-19 pandemic, this rate fell to 1.69% between 2020 and 2021, possibly due to non-pharmaceutical interventions12,16Our own research findings are in line with this trend, showing the detection rate of MP using the PCR NGS method to be 8.12% in 2022, increasing to 14.96% in 2023.

This study compared data from four MP detection methods, with the MP-IgM antibody detection method providing the highest detection rate at 21.16%. This high rate can be attributed to the inherent limitations of antibody detection. While antibodies typically appear 4–5 days after MP infection, their prolonged presence can lead to false positives. Interestingly, all three methods (PCR-NGS, RT-PCR, MP-IgM) showed a peak in detection between October and November in 2023, which aligns with the seasonal epidemic pattern observed in northern China. The introduction of the antigen detection method in September and its full implementation in October resulted in a detection rate that differed from the other methods, providing limited comparative value.

In terms of seasonal epidemics, MPP exhibited a significant epidemic peak during autumn and winter of 2023, a phenomenon not observed in the corresponding seasons of 2022. This increase is due to the “immunity debt” resulting from the easing of COVID-19 pandemic restrictions. Furthermore, MP outbreaks occurred in early 2022 (winter 2021), which is consistent with existing research findings17,18This pattern highlights the seasonal characteristics of the MP epidemic.

In terms of age distribution, all three methods except antigen testing indicated a higher incidence of MP infection in school-age children than in infants and preschoolers, which is consistent with previous research (P< 0.001)19,20,21,22Notably, antigen testing methods displayed higher incidence in preschoolers, which was likely due to the small sample size of antigen testing cases.

The symptoms of MPP were atypical and easily confused with viral pneumonia, especially during widespread outbreaks of MPP in children. To improve the early and accurate identification of MPP, facilitate early treatment, reduce children's discomfort, and prevent serious complications, this study developed a nomogram to assist clinical doctors to effectively distinguish between MPP and viral pneumonia.

Easily accessible clinical and laboratory data of pediatric patients were extracted and analyzed to compare differences in various indicators. Our findings showed that the MP group displayed higher values ​​for DD, FG, ESR, NEU count, NLR, and PLR, while presenting lower values ​​for PCT, LYM count, and LMR compared to the virus group, which aligns with the existing literature.23Subsequently, logistic regression identified age, DD, erythrocyte sedimentation rate, and gender as the four variables used to construct the nomogram.

In this study, we initially included C-reactive protein (CRP) and serum amyloid A (SAA) as indicators, as they were commonly used pediatric inflammatory markers in laboratory settings.24. However, the results proved unreliable due to the excessive number of out-of-range data points, such as values ​​below 0.5. After conducting in-depth statistical analysis, we finally decided not to use CRP and SAA as differentiating indicators. Although there was a statistically significant difference in oxygen breathing between the two groups, the primary purpose of our study was to differentiate MPP from viral pneumonia in the early stages. The indicators included in our analysis could be easily obtained when the children were hospitalized; therefore, it was not included in subsequent models.

MP was more common in children over 5 years of age, which was confirmed in a large number of literature; D-dimer is considered to be a specific decomposition product of fibrin, which can reflect the coagulation function and fiber activity of the body20However, current research has found that immune cells release a variety of inflammatory mediators following infection with MP, causing damage to endothelial cells and increased D-dimer levels.25,26As a marker of infection and inflammation, the ESR also increases during MP infection20,27,

We validated this nomogram not only in discrimination ability and calibration ability but also in diagnostic value. Compared with previous research results, the AUC value results of this prediction model were similar to the nomogram established by Huixian Guo, but their model had 6 parameters, which was more complicated than our model.23Considering the results of this curve and the ease of obtaining these variables at the time of admission, this model may help contribute to timely intervention and appropriate treatment for MP children.

Nevertheless, we identified several limitations in our research. First, this study was based on patient data from a single medical center. Although we performed external validation on data from the same medical center in different years, our findings and nomogram utility should be carefully validated in future multicenter studies. Secondly, the model diagram was based on retrospective research and individuals with incomplete data were excluded, which may lead to selection bias.

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