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Clinical Predictors of Wheezing Among Children Infected With Mycoplasma Pneumoniae
Kaimeng Kong1, Ying Ding1, Beirong Wu1
1Department of Respiratory Medicine, Shanghai Children's Hospital, Shanghai Jiao Tong University, Shanghai, China.
Abstract:
Background: Mycoplasma pneumoniae (MP) not only was a common pathogen of respiratory tract infections, but also could trigger the exacerbation of asthmatic symptoms in children with or without asthma. Objective: This study aimed to identify possible risk factors associated with wheezing among children diagnosed with MP infection. Methods: A retrospective analysis of medical records of children aged 28 days to 18 years old who visited the Shanghai Children's Hospital between January 2019 and January 2020 was carried out, and all children were then classified into three groups: two wheezing groups (with or without MP infection) and a non-wheezing group with MP infection. Information including patient's demographics, clinical features, laboratory data, and radiography findings was extracted from the electronic medical record system. Chest radiographs were reviewed independently by two board-certified, blinded pediatric radiologists. Results: A total of 1,512 patients were included in our study, and 21.9% of them belonged to the wheezing group without MP infection. Among 1,181 patients with MP infection, 295 people (25.0%) suffered from wheezing, and males accounted for 61%. Through the multivariable logistic regression analyses, we found that six variables were positively associated with wheezing attacks in children with MP infection: male gender (likelihood ratio [LR] = 2.124, 95% confidence interval [CI]: 1.478-3.053), history of allergy (LR= 3.301, 95% CI: 2.206-4.941), history of wheezing (LR = 7.808, 95% CI: 5.276-11.557), autumn in reference to summer (LR = 2.414, 95% CI: 1.500-3.885), non-end-point infiltration in reference to consolidation or pleural effusion (LR = 1.982, 95% CI: 1.348-2.914), and infiltration scope (LR = 1.773, 95% CI: 1.293-2.432). However, the model showed that the probability of wheezing after MP infection decreased as age increased (LR = 0.257, 95% CI: 0.196-0.337). Moreover, the area under the curve (AUC) of the regression model was as high as 0.901 (0.847-0.955). Conclusion: The model integrated with factors including gender, age, season, radiological patterns, infiltration scope, and history of allergy performed well in predicting wheezing attack after MP infection in children.
Insights
Mycoplasma pneumoniae (MP) infection can cause wheezing in children. Factors like male gender, allergy history, and season increase risk, while older age decreases it, according to a predictive model.
Area of Science:
- Pediatric Respiratory Medicine
- Infectious Diseases
- Clinical Pediatrics
Background:
- Mycoplasma pneumoniae (MP) is a common respiratory pathogen.
- MP infection can exacerbate asthma symptoms in children, with or without a prior asthma diagnosis.
Purpose of the Study:
- To identify risk factors for wheezing in children diagnosed with MP infection.
- To develop a predictive model for wheezing attacks following MP infection.
Main Methods:
- Retrospective analysis of 1,512 children (28 days to 18 years) at Shanghai Children's Hospital (Jan 2019-Jan 2020).
- Classification into three groups: wheezing with MP infection, wheezing without MP infection, and non-wheezing with MP infection.
- Multivariable logistic regression analysis of demographics, clinical features, lab data, and chest radiography findings.
Main Results:
- Among 1,181 children with MP infection, 25.0% experienced wheezing.
- Significant risk factors for wheezing included male gender, history of allergy, prior wheezing, autumn season, non-endpoint infiltration, and broader infiltration scope.
- Increased age was associated with a decreased probability of wheezing (LR = 0.257).
- The predictive model achieved a high Area Under the Curve (AUC) of 0.901.
Conclusions:
- A predictive model incorporating gender, age, season, radiological patterns, infiltration scope, and allergy history effectively identifies children at risk for wheezing post-MP infection.
- This model can aid in predicting and managing wheezing exacerbations in pediatric MP infections.
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