BACKGROUND: In the present study, we developed models to predict unresponsiveness to intravenous immunoglobulin (IVIG) in Kawasaki disease (KD). METHODS AND RESULTS: We reviewed clinical records of 546 consecutive KD patients (development dataset) and 204 subsequent KD patients (validation dataset). All received IVIG for treatment of KD. IVIG nonresponders were defined by fever persisting beyond 24 hours or recrudescent fever associated with KD symptoms after an afebrile period. A 7-variable logistic model was constructed, including day of illness at initial treatment, age in months, percentage of white blood cells representing neutrophils, platelet count, and serum aspartate aminotransferase, sodium, and C-reactive protein, which generated an area under the receiver-operating-characteristics curve of 0.84 and 0.90 for the development and validation datasets, respectively. Using both datasets, the 7 variables were used to generate a simple scoring model that gave an area under the receiver-operating-characteristics curve of 0.85. For a cutoff of 0.15 or more in the logistic regression model and 4 points or more in the simple scoring model, sensitivity and specificity were 86% and 67% in the logistic model and 86% and 68% in the simple scoring model. The kappa statistic is 0.67, indicating good agreement between the logistic and simple scoring models. CONCLUSIONS: Our predictive models showed high sensitivity and specificity in identifying IVIG nonresponders among KD patients.
BACKGROUND: In the present study, we developed models to predict unresponsiveness to intravenous immunoglobulin (IVIG) in Kawasaki disease (KD). METHODS AND RESULTS: We reviewed clinical records of 546 consecutive KDpatients (development dataset) and 204 subsequent KDpatients (validation dataset). All received IVIG for treatment of KD. IVIG nonresponders were defined by fever persisting beyond 24 hours or recrudescent fever associated with KD symptoms after an afebrile period. A 7-variable logistic model was constructed, including day of illness at initial treatment, age in months, percentage of white blood cells representing neutrophils, platelet count, and serum aspartate aminotransferase, sodium, and C-reactive protein, which generated an area under the receiver-operating-characteristics curve of 0.84 and 0.90 for the development and validation datasets, respectively. Using both datasets, the 7 variables were used to generate a simple scoring model that gave an area under the receiver-operating-characteristics curve of 0.85. For a cutoff of 0.15 or more in the logistic regression model and 4 points or more in the simple scoring model, sensitivity and specificity were 86% and 67% in the logistic model and 86% and 68% in the simple scoring model. The kappa statistic is 0.67, indicating good agreement between the logistic and simple scoring models. CONCLUSIONS: Our predictive models showed high sensitivity and specificity in identifying IVIG nonresponders among KDpatients.
Authors: Andrea P Salgado; Negar Ashouri; Erika K Berry; Xiaoying Sun; Sonia Jain; Jane C Burns; Adriana H Tremoulet Journal: J Pediatr Date: 2017-04-10 Impact factor: 4.406
Authors: Sang Hun Lee; Kyung Ok Ko; Jae Woo Lim; Jung Min Yoon; Young Hwa Song; Jong Wook Lee; Eun Jung Cheon Journal: Rheumatol Int Date: 2019-09-23 Impact factor: 2.631