Differentiate Clinical Characteristics Between Viral Pneumonia and Mycoplasma pneumoniae and Nomograms for Predicting Mycoplasma pneumoniae : A Retrospective Study in Primary Hospitals

Navigating the outbreak: a comprehensive analysis of pediatric Mycoplasma pneumoniae pneumonia via targeted next-generation sequencing in Wuhan, 2022-2023

This study aims to delineate the epidemiological characteristics and impacts of the Mycoplasma pneumoniae (MP) outbreak, utilizing targeted next-generation sequencing (tNGS) to assess pathogen prevalence and co-infections in pediatric pneumonia cases. Pediatric patients admitted to Wuhan Children's Hospital with pneumonia from 1 October 2022 to 31 October 2023 were included. tNGS was used for comprehensive pathogen detection, including MP and other respiratory pathogens, with additional sequencing of the 23S rRNA gene V region to identify macrolide resistance mutations. This study enrolled 10,223 patients with pneumonia with a positivity rate of 98.4% by targeted next-generation sequencing. Fever (86.4%) and cough (79.3%) were the most common symptoms of Mycoplasma pneumoniae pneumonia (MPP). Lung consolidation (25.8%) was a common imaging feature, and corticosteroid use was noted in 22.5% of MPP patients. MP proved to be the primary pathogen, particularly evident during the MP pandemic, which began in March 2023 and peaked in October with a detection rate of 63.2%. Of the 4,397 MPP cases, 34.5% were sole infections, while 65.6% were co-infections, mostly with viruses. The main causative agents of co-infections were Haemophilus influenzae and Rhinovirus. The macrolide resistance rate was 79.03%. The A2063G mutation in the 23S rRNA V region is the dominant mutation. High-sensitivity C-reactive protein and serum amyloid A were significantly elevated in MPP, while the absolute counts of CD3+T, CD4+T, CD8+T, CD19+B, and NK cells were significantly reduced. This study demonstrates the utility of tNGS in identifying MP co-infections and macrolide resistance and highlights the role of inflammatory markers and lymphocyte subpopulations in differentiating MPP from non-Mycoplasma pneumoniae pneumonia for clinical management.IMPORTANCEOur study is of great scientific value as it provides practical solutions to clinical challenges and supports both clinical decision-making and public health policy. First, it presents new and important insights into the application of targeted next-generation sequencing (tNGS) technology, which enables rapid and accurate pathogen detection and overcomes the limitations of conventional diagnostic methods. Second, the large sample size, focusing specifically on children during a Mycoplasma pneumoniae epidemic, provides valuable epidemiologic data specifically for the Wuhan region. Finally, by integrating rapid tNGS detection with inflammatory markers and lymphocyte subsets, our study demonstrates direct clinical applications that have the potential to improve patient outcomes. This approach highlights the practical utility of our research in enhancing clinical decision-making and contributes important knowledge to the field.

Biomarkers associated with the diagnosis and prognosis of Mycoplasma pneumoniae pneumonia in children: a review

Community-acquired pneumonia (CAP) is a major cause of death in children, and Mycoplasma pneumoniae (MP) is the main pathogen of CAP in children in China. Although Mycoplasma pneumoniae pneumonia (MPP) is usually a self-limiting disease, many children develop multiple complications due to drug resistance or untimely diagnosis and treatment, and may even progress to severe MPP or refractory MPP with a poor prognosis. It is important to explore the value of biomarkers that can be used in clinical practice to assess the severity of pneumonia and assist in clinical decision making. In this article, we searched the literature in the last four years to review the roles of various types of biomarkers in MPP and the associated clinical predictive models, with the aim of helping pediatricians to understand the evaluation indexes related to MPP in children other than microbiology.

The value of common blood parameters for the differential diagnosis of respiratory tract infections in children

Mycoplasma pneumoniae and influenza A virus are common pathogens that cause respiratory tract infection in children. Both pathogens present with similar clinical symptoms, and their epidemic periods often overlap. Consequently, it is challenging for clinicians to make a rapid preliminary diagnosis. However, common blood tests is simple and efficient, Therefore, the purpose of this study is to preliminarily distinguish Mycoplasma pneumoniae and influenza A virus infection in children by analyzing the results of common blood tests, thereby guiding clinical diagnosis and treatment.The results showed that, compared with children in the influenza A virus-positive group, children in the Mycoplasma pneumoniae-positive group had higher white blood cell (WBC), red blood cell (RBC), haemoglobin (HGB), platelet (PLT) counts, lymphocyte (LYM) and eosinophil (EOS) counts and ratios, as well as higher concentrations of C-reactive protein (CRP) and serum amyloid A (SAA), while neutrophil (NEU) and monocyte (MONO) counts and ratios, Neutrophil to Lymphocyte ratio( NLR) were lower, in addition, LYM, EOS counts and ratios, and NLR were all more effective in differentiating between the two pathogen infections, A combined analysis of these indicators further improved the differentiation efficacy. Therefore, LYM and EOS counts and ratios, along with NLR, can serve as effective blood parameters for differentiating Mycoplasma pneumoniae infections from influenza A virus infections in children.

Cytokine-based nomogram for discriminating viral pneumonia from Mycoplasma pneumoniae pneumonia in children

For children with pneumonia, differential diagnosis between viral infection and Mycoplasma pneumoniae (MP) infection is difficult. We retrospectively enrolled 336 hospitalized children who were diagnosed with community-acquired pneumonia and whose infection was exclusively viral or MP. We analyzed hematological indicators, biochemical markers, and cytokines. Least absolute shrinkage and selection operator (LASSO) regression analysis and logistic regression analysis were performed to identify and validate the factors that predicted the pathogenic diagnosis. The final predictive model incorporated four factors: tumor necrosis factor-α/interleukin (IL)-10, age, IL-8 and procalcitonin. This predictive model was visualized with a nomogram and had good performance. Using logistic regression analysis, the C-index of this predictive model was 0.878. Using receiver operating characteristic plot, the area under the curve was 0.8785. We established a model with a nomogram to discriminate viral infection from MP infection in hospitalized children with community-acquired pneumonia.

Reemergence of Mycoplasma pneumoniae disease: Pathogenesis and new approaches

The review discusses the recurrence of Mycoplasma pneumoniae (M. pneumoniae), a bacterium causing atypical pneumonia, primarily affecting Europe and Asia due to climate change, immunity decline, antibiotic resistance, and genetic heterogeneity. The COVID-19 pandemic initially reduced M. pneumoniae cases due to preventative measures, but its reemergence suggests different transmission dynamics and exacerbates clinical severity with co-infections with other viruses. The pathogenicity of M. pneumoniae is attributed to its intracellular changes, toxin release, and adhesion processes, which can result in a variety of symptoms and problems. Antibiotics and immunomodulators are used in treatment, and attempts are being made to create vaccines. Effective management of its reappearance necessitates surveillance and preventative measures, especially in the context of co-infections and potential outbreaks. M. pneumoniae's resurgence highlights its reliance on a polarized cytoskeletal architecture for host cell attachment and pathogenicity through cytoadherence and cytotoxic agent synthesis. M. pneumoniae has returned even though the COVID-19 pandemic originally reduced incidence; this might be because of things like declining immunity and particular pathogenic characteristics. Meteorological factors like temperature and humidity, along with air quality, including pollutants like PM2.5 and NO2, increase susceptibility to environmental hazards. During the pandemic, non-pharmaceutical measures decreased transmission but did not eradicate the infection. Epidemics typically occur three to five years apart, emphasizing the need for ongoing study and observation. Antimicrobial resistance is a serious issue, necessitating caution and alternative therapies, especially in macrolides. COVID-19 pandemic lessons, such as mask use and hand hygiene, may help limit M. pneumoniae transmission.

Prospective cohort study on the clinical significance of interferon-γ, D-dimer, LDH, and CRP tests in children with severe mycoplasma pneumonia

BACKGROUND

Mycoplasma pneumoniae is a significant cause of respiratory infections in children, often leading to severe pneumonia. This study aimed to assess the clinical relevance of interferon-gamma (interferon-γ), D-dimer, lactate dehydrogenase (LDH), and C-reactive protein (CRP) as biomarkers in the severity of mycoplasma pneumonia in pediatric patients.

METHODS

In this prospective study, 203 pediatric patients with mycoplasma pneumonia were classified into mild (123 patients) and severe (80 patients) groups. Biomarkers including interferon-γ, D-dimer, LDH, and CRP were measured and analyzed. Statistical methods employed included Pearson and Spearman correlation analyses, logistic regression, and receiver operating characteristic curve analysis.

RESULTS

The severe group exhibited significantly higher median and interquartile ranges for interferon-γ, D-dimer, LDH, and CRP compared to the mild group. Logistic regression identified IL-10, IL-6, interferon-γ, tumor necrosis factor-alpha, D-dimer, and LDH as independent predictors of severity, with the model achieving 92% accuracy. Receiver operating characteristic curve analysis showed optimal diagnostic efficacy for interferon-γ, D-dimer, and LDH, with the best threshold values being 8.11, 0.64, and 379, respectively. A significant positive correlation was observed between IL-6 and LDH, as well as between interferon-γ and D-dimer.

CONCLUSION

This study showed that interferon-γ >8.11, D-dimer >0.64, and LDH >379 have an important role in the assessment of severe mycoplasma pneumonia.

Routine blood parameters as auxiliary diagnostic tools for Mycoplasma pneumoniae infection in children

Introduction. Recently, the incidence of Mycoplasma pneumoniae (M. pneumoniae) infection in children has been increasing annually. Early differential diagnosis of M. pneumoniae infection can not only avoid the abuse of antibiotics, but also is essential for early treatment and reduction of transmission.Gap statement. The change of routine blood parameters may have important clinical significance for the diagnosis of M. pneumoniae infection, but it has not been reported so far.Aim. This study aims to establish a predictive model for M. pneumoniae infection and explore the changes and clinical value of routine blood parameters in children with M. pneumoniae infection, serving as auxiliary indicators for the diagnosis and differentiation of clinical M. pneumoniae infection.Methodology. A total of 770 paediatric patients with respiratory tract infections were enrolled in this study, including 360 in the M. pneumoniae group, 40 in the SARS-CoV-2 group, 200 in the influenza A virus group, and 170 in the control group. The differences of routine blood parameters among all groups were compared, and risk factors were analysed using multivariate logistics analysis, and the diagnostic efficacy of differential indicators using ROC curves.Results. This study revealed that Mono% (OR: 3.411; 95% CI: 1.638-7.102; P=0.001) was independent risk factor associated with M. pneumoniae infection, and Mono% (AUC=0.786, the optimal cutoff at 7.8%) had a good discriminative ability between patients with M. pneumoniae infection and healthy individuals. Additionally, Mono% (OR: 0.424; 95% CI: 0.231-0.781; P=0.006) and Lymp% (OR: 0.430; 95% CI: 0.246-0.753; P=0.003) were independent risk factors for distinguishing M. pneumoniae infection from influenza A virus infection, and the Lymp% (AUC=0.786, the optimal cutoff at 22.1%) and Net% (AUC=0.761, the optimal cutoff at 65.2%) had good discriminative abilities between M. pneumoniae infection and influenza A infection. Furthermore, platelet distribution width (OR: 0.680; 95% CI: 0.538-0.858; P=0.001) was independent risk factor for distinguishing M. pneumoniae infection from SARS-CoV-2 infection. Meanwhile, the ROC curve demonstrated that PDW (AUC=0.786, the optimal cutoff at 15%) has a good ability to differentiate between M. pneumoniae infection and SARS-CoV-2 infection.Conclusion. This study demonstrates that routine blood parameters can be used as auxiliary diagnostic indicators for M. pneumoniae infection and provide reference for the diagnosis and differentiation of clinical M. pneumoniae infection.

Epidemiological characteristics and early predict model of children Mycoplasma Pneumoniae Pneumonia outbreaks after the COVID-19 in Shandong

Since October 2023, a significant outbreak of Mycoplasma Pneumoniae Pneumonia (MPP) has been observed in children in northern China. Chinese health authorities have attributed this epidemiological to immune debt resulting from the relaxation of coronavirus disease 2019 (COVID-19) control measures. This study described the epidemiological features of Mycoplasma pneumoniae (MP) prevalence in children and developed a straightforward prediction model to differentiate between MPP and viral pneumonia in children. The infection rate of MP in children notably increased from 8.12 in 2022 to 14.94% in 2023, peaking between October and November, especially among school-age children. Logistic regression screening identified four key indicators: Age, D-Dimer levels, erythrocyte sedimentation rate, and gender. The developed nomogram exhibited a receiver operator characteristic curve-area under the curve (ROC-AUC) of 0.858, with external validation confirming an ROC-AUC of 0.794. This study examined the epidemiological characteristics of MPP prevalence in children in Shandong Province during and after the COVID-19 pandemic. An early predict model was developed and validated to differentiate between Mycoplasma Pneumoniae and viral infections.