关键词: Coronary artery lesions Kawasaki disease Risk factors The Systemic Immune-Inflammation Index (SII)

Mesh : Child Humans Mucocutaneous Lymph Node Syndrome / complications diagnosis Coronary Vessels Inflammation Risk Factors ROC Curve

来  源:   DOI:10.1007/s10238-023-01265-0   PDF(Pubmed)

Abstract:
Coronary artery lesions (CALs) are the most common complications of Kawasaki disease (KD) and play a crucial role in determining the prognosis of the disease. Consequently, the early identification of children with KD who are at risk of developing coronary artery damage is vitally important. We sought to investigate the relationship between the Systemic Immune-Inflammation Index (SII) and CALs in patients with KD and to assess its predictive value. We carried out a retrospective review and analysis of medical records for KD patients treated at the First Affiliated Hospital of Anhui Medical University between January 2017 and January 2023. We utilized single-variable tests, binary logistic regression analysis, ROC curve analysis, restricted cubic spline tests, and curve fitting to evaluate the association between SII and CALs. In our study, 364 patients were included, with 63 (17.3%) presenting with CALs at the time of admission. The binary logistic regression analysis indicated that SII was a significant risk factor for CALs at admission, evident in both unadjusted and models adjusted for confounders. The ROC curve analysis revealed an AUC (Area Under the Curve) value of 0.789 (95%CI 0.723-0.855, P < 0.001) for SII\'s predictive ability regarding CALs at admission. A consistent positive linear relationship between SII and the risk of CALs at admission was observed in both the raw and adjusted models. Our research findings suggest that SII serves as a risk factor for CALs and can be used as an auxiliary laboratory biomarker for predicting CALs.
摘要:
冠状动脉病变(CAL)是川崎病(KD)最常见的并发症,在决定疾病的预后中起着至关重要的作用。因此,早期发现有冠状动脉损伤风险的KD患儿至关重要.我们试图研究KD患者的全身免疫炎症指数(SII)与CAL之间的关系,并评估其预测价值。对2017年1月至2023年1月安徽医科大学第一附属医院KD患者的病历资料进行回顾性分析。我们利用单变量测试,二元逻辑回归分析,ROC曲线分析,受限三次样条测试,和曲线拟合来评估SII和CAL之间的关联。在我们的研究中,包括364名患者,63人(17.3%)在入院时出示CAL。二元logistic回归分析表明,SII是入院时CAL的重要危险因素,在未经调整的模型和针对混杂因素调整的模型中都很明显。ROC曲线分析显示,入院时SII对CAL的预测能力的AUC(曲线下面积)值为0.789(95CI0.723-0.855,P<0.001)。在原始模型和校正模型中均观察到SII与入院时CAL风险之间的一致正线性关系。我们的研究结果表明,SII是CAL的危险因素,可以用作预测CAL的辅助实验室生物标志物。
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