A novel scoring system based on sIL-2R for predicting IVIG resistance in Chinese children with KD

• Main Authors: Yuan-Yuan Zeng (Author), Su-Yue Zhu (Author), Kang-Kang Xu (Author), Lian-Fu Ji (Author), Yu-Qi Wang (Author), Yi Chen (Author), Feng Chen (Author), Shi-Wei Yang (Author)
• Format: Book
• Published: BMC, 2024-08-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 10.1186/s12969-024-01015-w; 1546-0096
• Keywords: Kawasaki disease; Intravenous immunoglobulin resistance; Risk scoring systems; Soluble interleukin-2 receptor; Pediatrics; RJ1-570; Diseases of the musculoskeletal system; RC925-935
• Source: Pediatric Rheumatology Online Journal, Vol 22, Iss 1, Pp 1-9 (2024)

Abstract Objective This study aimed to develop a novel scoring system utilizing circulating interleukin (IL) levels to predict resistance to intravenous immunoglobulin (IVIG) in Chinese patients with Kawasaki disease (KD). We further compared this scoring system against six previously established scoring methods to evaluate its predictive performance. Methods A retrospective analysis was conducted on KD patients who were treated at the cardiovascular medical ward of our institution from January 2020 to December 2022. Six scoring systems (Egami, Formosa, Harada, Kobayashi, Lan and Yang) were analyzed, and a new scoring system was developed based on our data. Results In our study, 521 KD patients were recruited, 42 of whom (8.06%) were identified as resistant to IVIG. Our study indicated that IVIG-resistant KD patients were at an increased risk for the development of coronary arterial lesions (CALs) (P = 0.001). The evaluation of IVIG resistance using various scoring systems revealed differing levels of sensitivity and specificity, as follows: Egami (38.10% and 88.52%), Formosa (95.24% and 41.13%), Harada (78.57% and 43.22%), Kobayashi (66.67% and 74.95%), Lan (66.67% and 73.49%), and Yang (69.05% and 77.24%). Our novel scoring system utilizing sIL-2R demonstrated the highest sensitivity and specificity of 69.29% and 83.91%, respectively, and calibration curves indicated a favorable predictive accuracy of the model. Conclusion Our newly developed scoring system utilizing sIL-2R demonstrated superior predictive performance in identifying IVIG resistance among Chinese patients with KD.