胰岛素抵抗的预测模型和青年MASLD的影响:一个新的标志物,儿科胰岛素抵抗评估得分
Kyungchul Song1, Eunju Lee2, Young Hoon Youn3
1Department of Pediatrics, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Korea.
Yonsei medical journal
|July 25, 2025
概括
一个新的评分系统,儿科胰岛素抵抗评分,有效地预测青少年的胰岛素抵抗 (IR) 和与代谢功能障碍相关的脂肪性肝病 (MASLD). 该工具有助于早期识别和管理这些疾病.
科学领域:
- 儿科内分泌学 儿科内分泌学
- 代谢健康 代谢健康
- 肝脏疾病研究 肝脏疾病研究
背景情况:
- 胰岛素抵抗 (IR) 与心血管风险和与代谢功能障碍相关的脂肪性肝病 (MASLD) 有关.
- MASLD是一种新出现的并发症,与儿童群体的IR相关.
- 开发青少年IR和MASLD的预测工具对于早期干预至关重要.
研究的目的:
- 开发和验证年轻人胰岛素抵抗 (IR) 的预测模型.
- 评估模型在预测代谢功能障碍相关的脂肪性肝病 (MASLD) 中的实用性.
- 为临床应用创建一个用户友好的诺莫格拉姆评分系统.
主要方法:
- 利用基于人口的数据进行培训 (1588名年轻人) 和现实世界的临床数据进行测试 (121名IR,50名MASLD).
- 采用了各种机器学习模型,包括后勤回归,随机森林,XGBoost,轻 GBM 和 DNN.
- 构建了一个基于多变量逻辑回归的nomogram评分系统,用于概率预测.
主要成果:
- 确定的主要预测因素包括年龄,BMI SDS,WC,静脉血压,HbA1c,HDL,甘油三和ALT.
- 命名图表显示了强大的预测性能,用于IR和MASLD.
- 随机森林在外部验证中实现了MASLD预测的最高AUC (0.95) 和IR预测的物流回归 (0.75).
结论:
- 儿科胰岛素抵抗评分是一个新且有效的工具.
- 这种评分系统有助于预测儿科患者的IR和MASLD.
- 该得分有助于早期识别和管理青年代谢并发症.
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