基于新型的人类指数,使用数据挖掘,预测10年发生的失脂症的发生率
Alireza Takhttavous1,2, Maryam Saberi-Karimian3,4, Somayeh Ghiasi Hafezi3
1Student Research Committee, Mashhad University of Medical Sciences, Mashhad, Iran.
Lipids in health and disease
|January 31, 2024
概括
这项研究开发了一种使用新型人类指数的10年失脂症发病率模型. 内脏肥胖指数 (VAI),体重指数 (BMI) 和脂质积累产物 (LAP) 是关键预测指标.
科学领域:
- 心血管疾病流行病学
- 代谢综合征研究 代谢综合征研究
- 生物识别分析 生物识别分析
背景情况:
- 脂质不良症对心血管和动脉样硬化疾病构成重大风险.
- 对于预防策略来说,精确的脂质障碍症发病率预测模型至关重要.
研究的目的:
- 建立一个10年模型来预测失脂症发病率.
- 调查新型人体指数对失脂症的预测能力.
主要方法:
- 数据挖掘技术应用于MASHAD研究的参与者 (n=1776).
- 后勤回归和决策树分析评估了血脂障碍和各种人类指数 (VAI,BMI,LAP等) 之间的关联. ) 的情况.
- 接收器运行特征 (ROC) 曲线分析评估了模型性能.
主要成果:
- 视觉肥胖指数 (VAI) 是失脂症的重要预测指标 (OR:2.81).
- 决策树分析发现VAI,BMI和LAP是预测失脂症发病率的最关键变量.
- 模型A证明了可接受的性能 (AUC=0.69) 对于10年的脂质失调症预测.
结论:
- 模型A显示了预测10年失脂症发病率的前景.
- 使用已确立的统计模型,VAI,BMI和LAP被确定为使用失脂症预测的主要人类学因素.
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