基于深度学习的横截面研究,以探索甘油三/葡萄糖指数对牙周炎的影响:基于大型NHANES数据库的分析
Oral health & preventive dentistry
|February 10, 2026
概括
甘油三糖 (TyG) 指数是胰岛素抵抗的标志物,与牙周炎风险有关. 一个深度学习模型显示,TyG指数有效预测牙周炎,有助于早期检测和管理.
科学领域:
- 口腔健康 口腔健康
- 代谢综合征是代谢综合征的一种.
- 生物标志物发现发现
背景情况:
- 牙周炎是一种常见的慢性炎症性疾病,与代谢综合征有关.
- 甘油三糖指数 (TyG) 是一种已知的胰岛素耐药性的标志物.
- 在TyG指数和牙周炎之间的关系还不清楚.
研究的目的:
- 使用深度学习模型探索TyG指数对牙周炎的预测价值.
- 调查TyG指数与牙周炎风险之间的相关性.
- 为此分析利用国家健康和营养检查调查 (NHANES) 数据库.
主要方法:
- 使用了NHANES数据,包括人口统计,实验室和口腔健康信息.
- 开发和训练了一个深度学习神经网络模型来预测牙周炎.
- 采用后勤回归和夏普利添加式前计划 (SHAP) 进行验证和解释.
主要成果:
- 深度学习模型在预测牙周炎时实现了0.7482的AUC-ROC和87.13%的准确性.
- 在模型中,TyG指数被确定为最有影响力的预测因素.
- 在TyG指数和牙周炎风险之间观察到显著的剂量反应关系.
结论:
- 根据剂量,TyG指数与牙周炎风险相关.
- 深度学习模型显示了牙周炎的强大预测性能.
- 泰格指数显示,作为一种简单,低成本的牙周炎风险分层和早期识别生物标志物的潜力.
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