OBJECTIVES: The objective of this study was to find the predictors and generate a prediction score of resistance to intravenous immunoglobulin (IVIG) in patients with Kawasaki disease (KD). STUDY DESIGN: Patients diagnosed as having KD were sampled when they received initial high-dose IVIG treatment (2 g/kg dose) within 9 days of illness (n = 320). These patients were divided into 2 groups: the resistance (n = 41) and the responder (n = 279). The following data were obtained and compared between resistance and responder: age, sex, illness days at initial treatment, and laboratory data. RESULTS: Multivariate logistic regression analysis identified age, illness days, platelet count, alanine aminotransferase (ALT), and C-reactive protein (CRP) as significant predictors for resistance to IVIG. We generated prediction score assigning 1 point for (1) infants less than 6 months old, (2) before 4 days of illness, (3) platelet count <or= 30 x 10(10)/L, (4) CRP >or= 8 mg/dL, as well as 2 points for (5) ALT >or= 80 IU/L. Using a cut-off point of 3 and more with this prediction score, we could identify the IVIG-resistant group with 78% sensitivity and 76% specificity. CONCLUSIONS: Resistance to IVIG treatment can be predicted using age, illness days, platelet count, ALT, and CRP. Randomized, multicenter clinical trials are necessary to create a new strategy to treat these high-risk patients.
OBJECTIVES: The objective of this study was to find the predictors and generate a prediction score of resistance to intravenous immunoglobulin (IVIG) in patients with Kawasaki disease (KD). STUDY DESIGN:Patients diagnosed as having KD were sampled when they received initial high-dose IVIG treatment (2 g/kg dose) within 9 days of illness (n = 320). These patients were divided into 2 groups: the resistance (n = 41) and the responder (n = 279). The following data were obtained and compared between resistance and responder: age, sex, illness days at initial treatment, and laboratory data. RESULTS: Multivariate logistic regression analysis identified age, illness days, platelet count, alanine aminotransferase (ALT), and C-reactive protein (CRP) as significant predictors for resistance to IVIG. We generated prediction score assigning 1 point for (1) infants less than 6 months old, (2) before 4 days of illness, (3) platelet count <or= 30 x 10(10)/L, (4) CRP >or= 8 mg/dL, as well as 2 points for (5) ALT >or= 80 IU/L. Using a cut-off point of 3 and more with this prediction score, we could identify the IVIG-resistant group with 78% sensitivity and 76% specificity. CONCLUSIONS: Resistance to IVIG treatment can be predicted using age, illness days, platelet count, ALT, and CRP. Randomized, multicenter clinical trials are necessary to create a new strategy to treat these high-risk patients.
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: Paul Monagle; Anthony K C Chan; Neil A Goldenberg; Rebecca N Ichord; Janna M Journeycake; Ulrike Nowak-Göttl; Sara K Vesely Journal: Chest Date: 2012-02 Impact factor: 9.410
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