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Risk factors and an early predictive model for Kawasaki disease shock syndrome in Chinese children
Mingming Zhang1, Congying Wang1,2, Qirui Li3
1Department of Cardiology, Children's Hospital Capital Institute of Pediatrics, Beijing, 10020, China.
Insights
Early diagnosis of Kawasaki disease shock syndrome (KDSS) is vital for preventing cardiovascular issues. This study identified key risk factors and developed a predictive model to aid pediatricians in timely KDSS detection.
Area of Science:
- Pediatric Cardiology
- Infectious Diseases
- Clinical Research
Background:
- Kawasaki disease shock syndrome (KDSS) is a rare but serious condition with a high risk of cardiovascular complications.
- Early diagnosis of KDSS is critical for improving patient outcomes and preventing long-term sequelae.
- Identifying risk factors and developing predictive tools are essential for timely KDSS management.
Purpose of the Study:
- To identify independent risk factors associated with the development of KDSS.
- To construct and validate a predictive model for KDSS onset in children.
- To aid in the early diagnosis and management of KDSS.
Main Methods:
- A case-control study involving children diagnosed with KDSS and Kawasaki disease (KD) without shock.
- Propensity score matching was used to create comparable groups for analysis.
- Univariable and stepwise logistic regression analyses were employed to identify significant risk factors.
Main Results:
- Five independent risk factors for KDSS were identified: elevated Interleukin-10 (IL-10), low platelet count (PLT), elevated C-reactive protein (CRP), elevated procalcitonin (PCT), and low albumin (Alb).
- A nomogram model incorporating these factors demonstrated high predictive accuracy (AUCs of 0.91 and 0.90) in both development and validation datasets.
- The model exhibited good sensitivity and specificity, indicating its clinical utility for predicting KDSS.
Conclusions:
- Interleukin-10, platelet count, C-reactive protein, procalcitonin, and albumin are significant risk factors for KDSS.
- The developed nomogram model provides an effective tool for the early prediction of KDSS in Chinese children.
- This predictive model can assist pediatricians in making earlier diagnoses, thereby preventing cardiovascular complications associated with KDSS.
Background:
Kawasaki disease shock syndrome (KDSS), though rare, has increased risk for cardiovascular complications. Early diagnosis is crucial to improve the prognosis of KDSS patients. Our study aimed to identify risk factors and construct a predictive model for KDSS.
Methods:
This case-control study was conducted from June, 2015 to July, 2023 in two children's hospitals in China. Children initially diagnosed with KDSS and children with Kawasaki disease (KD) without shock were matched at a ratio of 1:4 by using the propensity score method. Laboratory results obtained prior to shock syndrome and treatment with intravenous immunoglobulin were recorded to predict the onset of KDSS. Univariable logistic regression and forward stepwise logistic regression were used to select significant and independent risk factors associated with KDSS.
Results:
After matching by age and gender, 73 KDSS and 292 KD patients without shock formed the development dataset; 40 KDSS and 160 KD patients without shock formed the validation dataset. Interleukin-10 (IL-10) > reference value, platelet counts (PLT) < 260 × 109/L, C-reactive protein (CRP) > 80 mg/ml, procalcitonin (PCT) > 1ng/ml, and albumin (Alb) < 35 g/L were independent risk factors for KDSS. The nomogram model including the above five indicators had area under the curves (AUCs) of 0.91(95% CI: 0.87-0.94) and 0.90 (95% CI: 0.71-0.86) in the development and validation datasets, with a specificity and sensitivity of 80% and 86%, 66% and 77%, respectively. Calibration curves showed good predictive accuracy of the nomogram. Decision curve analyses revealed the predictive model has application value.
Conclusions:
This study identified IL-10, PLT, CRP, PCT and Alb as risk factors for KDSS. The nomogram model can effectively predict the occurrence of KDSS in Chinese children. It will facilitate pediatricians in early diagnosis, which is essential to the prevention of cardiovascular complications.
