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在川崎病的一个月冠状动脉动脉瘤的预测nomogram
Yunjia Tang1, Chuxin Ding1, Qiuqin Xu1
1Department of Cardiology, Children's Hospital of Soochow University, No 92, Zhongnan Street, Suzhou, People's Republic of China.
Italian journal of pediatrics
|November 7, 2023
概括
一个新的预测模型准确地识别了卡瓦萨基病 (KD) 的儿童冠状动脉动脉瘤 (CAA) 在发病一个月后. 这种使用年龄,性别和急性冠状动脉病变 (CALs) 的模型显示了早期干预的出色预测效用.
科学领域:
- 儿科 儿科 儿科
- 心脏病学 心脏病学
- 类风湿病学 类风湿病学
背景情况:
- 川崎病 (KD) 对冠状动脉动脉瘤 (CAA) 构成重大风险.
- 在KD患者中早期预测CAA对于及时干预和管理至关重要.
- 在KD发病后一个月评估冠状动脉状况对于长期结果至关重要.
研究的目的:
- 开发和验证一种预测模型,用于在患有川崎病后一个月的儿童中识别冠状动脉动脉瘤 (CAA).
- 评估与现有评分系统对比开发模型的预测性能.
主要方法:
- 使用KD患者的数据 (2017年5月至2018年12月) 开发了一个预测模型,并通过内部和外部验证 (2019年1月至2019年12月).
- 通过自适应最小绝对收缩和选择运营者 (LASSO) 回归,确定了关键预测因素:年龄,性别和急性冠状动脉病变 (CALs).
- 使用接收器操作特征 (ROC) 曲线,校准图表和决策曲线分析 (DCA) 评估模型性能.
主要成果:
- 拉索回归确定年龄,性别和CALs作为一个月后CAA的显著预测因素.
- 该模型实现了0.946的ROC曲线下的面积 (AUC),灵敏度为92.5%,特异性为90.5%.
- 内部和外部验证证实了该模型的可靠性,超过了Son得分 (AUC 0.941与0.860).
结论:
- 开发的预测模型证明了在KD患者中预测一个月后CAA的卓越实用性.
- 该模型为早期风险分层和对川崎病并发症的管理提供了可靠的工具.
- 这些发现支持在临床实践中使用该模型,以改善患者的治疗结果.
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