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Development and external validation of a simple nomogram for predicting apnea in children hospitalized with
Qiuyan Xu1, Linlin Li2, Li Shen3
1Department of Pediatrics, Suzhou Science / Technology Town Hospital, Suzhou, China.
Insights
A new nomogram can predict apnea risk in children hospitalized with bronchiolitis. This tool helps identify high-risk patients for early intervention and intensive monitoring, improving outcomes for pediatric respiratory illness.
Area of Science:
- Pediatrics
- Respiratory Medicine
- Clinical Prediction Models
Background:
- Apnea is a critical, life-threatening complication in pediatric bronchiolitis.
- Early identification of children at risk for apnea is crucial for timely intervention.
Purpose of the Study:
- To identify early predictors of apnea in hospitalized children with bronchiolitis.
- To develop a simple, visual nomogram for predicting individual apnea risk.
Main Methods:
- Retrospective observational study of 1,372 children hospitalized with bronchiolitis.
- Used LASSO regression and multivariable logistic regression to identify risk factors.
- Developed and validated a nomogram using a training and external validation cohort.
Main Results:
- 133 (9.69%) of 1,372 children experienced apnea.
- Independent risk factors identified: underlying diseases, feeding difficulties, tachypnea, retractions, pulmonary atelectasis.
- The nomogram demonstrated good discrimination (C-index: 0.883) and calibration.
Conclusions:
- A user-friendly nomogram was developed to predict apnea risk in pediatric bronchiolitis.
- This tool facilitates individualized risk assessment for early triage and intensive monitoring.
- The nomogram is clinically useful for managing children with bronchiolitis and associated apnea risk.
Background:
Apnea is one of the most life-threatening complications of bronchiolitis in children. This study aimed to determine early predictors of apnea in children hospitalized with bronchiolitis and develop a simple nomogram to identify patients at risk of apnea.
Methods:
This retrospective, observational study included children hospitalized with bronchiolitis in two hospitals in China. Demographic and clinical characteristics, laboratory results, pathogens, and pulmonary iconography results were recorded. A training cohort of 759 patients (one hospital) was used to identify early predictors of apnea during hospitalization. The least absolute shrinkage and selection operator (LASSO) regression analysis method was used to optimize variable selection. The nomogram was developed visually based on the variables selected by multivariable logistic regression analysis. Discrimination (concordance index, C-index), calibration, and decision curve analysis (DCA) were used to assess the model performance and clinical effectiveness.
Results:
A total of 1,372 children hospitalized with bronchiolitis were retrospectively evaluated, 133 (9.69%) of whom had apnea. Apnea was observed in 80 of the 759 patients with bronchiolitis in the training cohort and 53 of the 613 patients in the external validation cohort. Underlying diseases, feeding difficulties, tachypnea, retractions and pulmonary atelectasis in the training cohort were independent risk factors for apnea and were assembled into the nomogram. The nomogram exhibited good discrimination with a C-index of 0.883 (95% CI: 0.839-0.927) and good calibration. The DCA showed that the nomogram was clinically useful in estimating the net benefit to patients.
Conclusion:
We developed a nomogram that is convenient to use and able to identify the individualized prediction of apnea risk in patients with bronchiolitis. These patients might benefit from early triage and more intensive monitoring.
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