BMC infectious diseases · 2026
Early risk stratification for ICU admission in hospitalized children with pertussis: development and internal validation of an admission-time prediction model.
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Xia Zhi, Chen Ming, Bao Liang, Shu Xiaolan, Zhang Xu, Luo Yifan, Hu Qin, Yang Wenqiang, Xu Manman, Shi Buyun
Аннотация
BACKGROUND: Severe pertussis in children can deteriorate rapidly, and early identification of patients likely to require intensive care remains challenging. We aimed to develop and internally validate an admission-time prediction model for ICU admission among hospitalized children with PCR-confirmed pertussis.
METHODS: We conducted a single-center retrospective prediction-model study based on a hospitalized cohort at a provincial pediatric infectious disease center. Consecutive hospitalized children with PCR-confirmed pertussis between 6 June 2020 and 24 June 2025 were screened. Two children were excluded because admission white blood cell count (WBC), a prespecified core predictor, was unavailable in the retrievable admission-time record, leaving 662 children aged 24 days to 14 years for analysis. The primary outcome was ICU admission, defined a priori as ICU length of stay > 0 days. We prespecified a multivariable logistic regression model using seven admission-time predictors: age (months), sex, symptom duration before admission (days), paroxysmal cyanosis documented at presentation, imaging consolidation/atelectasis, admission WBC scaled per 5 × 109 /L, and any recorded pertussis-containing vaccine dose. Internal validation used 5-fold cross-validation with out-of-fold predictions; model performance was assessed by discrimination (AUC), overall prediction error (Brier score), calibration, and decision curve analysis.
RESULTS: ICU admission occurred in 61/662 (9.2%) children. Compared with non-ICU patients, ICU-admitted children were younger (median 2.0 vs 60.0 months) and had higher admission WBC (median 18.7 vs 10.0 × 109 /L). Paroxysmal cyanosis (49.2% vs 6.0%) and imaging consolidation/atelectasis (23.0% vs 10.5%) were more frequent, whereas recorded vaccination was less common (23.0% vs 87.9%). On internal validation, the model showed excellent discrimination (AUC 0.953; 95% CI 0.933-0.972) with low overall prediction error (Brier score 0.045). Calibration was good (intercept -0.017; slope 0.992), and decision curve analysis suggested positive net benefit over clinically relevant threshold probabilities.
CONCLUSIONS: An admission-time multivariable model showed good internal performance for predicting ICU admission in pediatric pertussis and may support early risk stratification. External validation is required before routine implementation.
METHODS: We conducted a single-center retrospective prediction-model study based on a hospitalized cohort at a provincial pediatric infectious disease center. Consecutive hospitalized children with PCR-confirmed pertussis between 6 June 2020 and 24 June 2025 were screened. Two children were excluded because admission white blood cell count (WBC), a prespecified core predictor, was unavailable in the retrievable admission-time record, leaving 662 children aged 24 days to 14 years for analysis. The primary outcome was ICU admission, defined a priori as ICU length of stay > 0 days. We prespecified a multivariable logistic regression model using seven admission-time predictors: age (months), sex, symptom duration before admission (days), paroxysmal cyanosis documented at presentation, imaging consolidation/atelectasis, admission WBC scaled per 5 × 109 /L, and any recorded pertussis-containing vaccine dose. Internal validation used 5-fold cross-validation with out-of-fold predictions; model performance was assessed by discrimination (AUC), overall prediction error (Brier score), calibration, and decision curve analysis.
RESULTS: ICU admission occurred in 61/662 (9.2%) children. Compared with non-ICU patients, ICU-admitted children were younger (median 2.0 vs 60.0 months) and had higher admission WBC (median 18.7 vs 10.0 × 109 /L). Paroxysmal cyanosis (49.2% vs 6.0%) and imaging consolidation/atelectasis (23.0% vs 10.5%) were more frequent, whereas recorded vaccination was less common (23.0% vs 87.9%). On internal validation, the model showed excellent discrimination (AUC 0.953; 95% CI 0.933-0.972) with low overall prediction error (Brier score 0.045). Calibration was good (intercept -0.017; slope 0.992), and decision curve analysis suggested positive net benefit over clinically relevant threshold probabilities.
CONCLUSIONS: An admission-time multivariable model showed good internal performance for predicting ICU admission in pediatric pertussis and may support early risk stratification. External validation is required before routine implementation.