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Antigen-Capture Enzyme-Linked Immunosorbent Assay for Specific Detection of Mycoplasma pneumoniae
Published on: February 24, 2023
Early identification of severe Mycoplasma pneumoniae pneumonia in children: A retrospective model development study
Zijuan Dong1, Xiaojuan Zhang1, Lina Gu1
1Department of Infectious Disease, Affiliated Children's Hospital of Jiangnan University, Wuxi Children's Hospital, 299-1 Qingyang Road, Wuxi, 214023, China.
Background:
A nationwide resurgence of pediatric Mycoplasma pneumoniae pneumonia (MPP) has been observed in China since mid-2023, yet contemporary tools for early recognition of severe MPP (SMPP) are lacking.
Methods:
In this retrospective study we analyzed 908 children (≤14 years) hospitalized with MPP at Wuxi Children's Hospital between August 2023 and August 2024. Demographic, clinical, laboratory and medication features were compared between SMPP (n = 277) and non-SMPP (n = 631) groups. Independent predictors were identified by stepwise logistic regression and incorporated into a five-parameter nomogram. Internal validity was assessed with 1000-bootstrap resampling.
Results:
SMPP accounted for 30.5 % of all admissions. Multivariable analysis showed that higher neutrophil percentage (OR = 1.02 per %, 95% CI 1.01-1.03), older age (OR = 1.21 per year, 95% CI 1.12-1.28), longer pre-admission azithromycin exposure (OR = 1.34 per day, 95% CI 1.11-1.37), higher peak temperature (OR = 1.37 per °C, 95% CI 1.07-1.75) and elevated lactate dehydrogenase (LDH) (OR = 1.24 per 100 U/L, 95 % CI 1.04-1.47) independently predicted SMPP (all P < 0.05). The optimism-corrected area under the ROC curve (AUC) was 0.75 (95% CI 0.72-0.78); the calibration slope was 0.96, intercept 0.02, and Brier score 0.04.
Conclusions:
Almost one-third of children admitted with MPP during the 2023-2024 outbreak developed severe disease. A five-parameter nomogram based on routinely available admission data provides accurate, internally validated risk estimation and may facilitate timely escalation of care. External validation and prospective evaluation of macrolide resistance are required before large-scale implementation.
Insights
A recent outbreak saw nearly one-third of pediatric Mycoplasma pneumoniae pneumonia (MPP) cases become severe. A new nomogram using admission data helps predict severe MPP (SMPP) in children, aiding early treatment.
Area of Science:
- Pediatric Infectious Diseases
- Respiratory Medicine
- Clinical Epidemiology
Background:
- A significant increase in pediatric Mycoplasma pneumoniae pneumonia (MPP) cases has been noted in China since mid-2023.
- There is a current lack of effective tools for the early identification of severe pediatric MPP (SMPP).
Purpose of the Study:
- To identify independent predictors of severe pediatric MPP (SMPP).
- To develop and validate a predictive nomogram for SMPP risk in hospitalized children.
Main Methods:
- Retrospective analysis of 908 children (≤ 14 years) hospitalized with MPP.
- Comparison of demographic, clinical, laboratory, and medication data between severe MPP (SMPP) and non-SMPP groups.
- Development of a five-parameter nomogram using logistic regression and internal validation via bootstrap resampling.
Main Results:
- Severe pediatric MPP (SMPP) constituted 30.5% of all admissions.
- Independent predictors for SMPP included higher neutrophil percentage, older age, prolonged pre-admission azithromycin exposure, higher peak temperature, and elevated lactate dehydrogenase (LDH).
- The developed nomogram demonstrated good predictive accuracy with an AUC of 0.75.
Conclusions:
- Nearly one-third of pediatric MPP admissions during the 2023-2024 outbreak progressed to severe disease.
- A five-parameter nomogram utilizing routine admission data offers reliable risk stratification for SMPP.
- The nomogram may support timely clinical decision-making, though external validation and macrolide resistance assessment are needed.
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