在不完全的川崎病中开发和验证冠状动脉病变的早期预测模型
Yongmao Xu1, Shuhui Wang2, Chi Zhang1
1Department of Cardiology, The Affiliated Xuzhou Children's Hospital of Xuzhou Medical University, Xuzhou, China.
Translational pediatrics
|December 10, 2025
概括
这项研究确定了患有不完全川崎病 (IKD) 的儿童冠状动脉病变 (CALs) 的关键风险因素. 使用这些因素的预测模型可以帮助早期识别高风险患者.
科学领域:
- 儿童心脏病学 儿童心脏病学
- 类风湿病学 类风湿病学
- 流行病学 流行病学
背景情况:
- 不完整的川崎病 (IKD) 发病率正在上升.
- IKD与冠状动脉病变 (CALs) 的风险增加有关.
- 在IKD中CAL的预测因素仍然不清楚.
研究的目的:
- 确定儿科IKD中CAL的危险因素.
- 在IKD患者中开发CAL发生的预测模型.
主要方法:
- 对IKD患者数据的回顾性分析 (2021-2023年).
- 最小绝对收缩和选择运算符 (LASSO) -逻辑回归以确定预测因素.
- 用于预测模型和外部验证的nomogram构建.
主要成果:
- 八个变量被确定为预测因素:性别,发烧持续时间,结膜注射,宫淋巴腺病,ESR,Neu%,ALT和AST.
- 诺莫格拉姆模型显示出良好的预测准确性 (训练中的AUC为0.817,测试中的AUC为0.888).
- 该模型在两个队列中都显示出高灵敏度和特异性.
结论:
- 综合临床和实验室变量的预测模型可以可靠地评估儿科IKD中CAL风险.
- 该模型有助于早期识别患有CAL风险的IKD患者.
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