Meta-analysis of factors predicting resistance to intravenous immunoglobulin treatment in patients with Kawasaki disease.
PURPOSE
Studies have been conducted to identify predictive factors of resistance to intravenous immunoglobulin (IVIG) for Kawasaki disease (KD). However, the results are conflicting. This study aimed to identify laboratory factors predictive of resistance to high-dose IVIG for KD by performing meta-analysis of available studies using statistical techniques.


METHODS
All relevant scientific publications from 2006 to 2014 were identified through PubMed searches. For studies in English on KD and IVIG resistance, predictive factors were included. A meta-analysis was performed that calculated the effect size of various laboratory parameters as predictive factors for IVIG-resistant KD.


RESULTS
Twelve studies comprising 2,745 patients were included. Meta-analysis demonstrated significant effect sizes for several laboratory parameters: polymorphonuclear leukocytes (PMNs) 0.698 (95% confidence interval [CI], 0.469-0.926), C-reactive protein (CRP) 0.375 (95% CI, 0.086-0.663), pro-brain natriuretic peptide (pro-BNP) 0.561 (95% CI, 0.261-0.861), total bilirubin 0.859 (95% CI, 0.582-1.136), alanine aminotransferase (AST) 0.503 (95% CI, 0.313-0.693), aspartate aminotransferase (ALT) 0.436 (95% CI, 0.275-0.597), albumin 0.427 (95% CI, -0.657 to -0.198), and sodium 0.604 (95% CI, -0.839 to -0.370). Particularly, total bilirubin, PMN, sodium, pro-BNP, and AST, in descending numerical order, demonstrated more than a medium effect size.


CONCLUSION
Based on the results of this study, laboratory predictive factors for IVIG-resistant KD included higher total bilirubin, PMN, pro-BNP, AST, ALT, and CRP, and lower sodium and albumin. The presence of several of these predictive factors should alert clinicians to the increased likelihood that the patient may not respond adequately to initial IVIG therapy.
['Baek|Jin-Young|JY|', 'Song|Min Seob|MS|']
Meta-analysis Intravenous immunoglobulins Mucocutaneous lymph node syndrome Predictive value of tests