使用机器学习解读重金属对心血管不良事件的影响
Guanmou Li1, Tong Zhang2, Kunyang He3
1State Key Laboratory of Traditional Chinese Medicine Syndrome,Department of Cardiovascular Surgery, Guangdong Provincial Hospital of Chinese Medicine, the Second Affiliated Hospital of Guangzhou University of Chinese Medicine, the Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong 510120, China; Zhu Jiang Hospital, Southern Medical University, Guangzhou 510260, China.
长期暴露于重金属,显著增加了主要不良心血管事件 (MACE) 的风险,包括心脏病发作和心力衰竭. 公共卫生工作的重点应该是减少环境中的暴露.
科学领域:
- 环境健康 环境健康
- 心血管疾病流行病学
- 毒理学 毒理学 毒理学
背景情况:
- 长期暴露于,和等重金属是越来越严重的公共卫生问题.
- 心血管疾病 (CVD) 仍然是全球主要的死亡原因.
- 了解CVD的特定环境决定因素对于有效的预防策略至关重要.
研究的目的:
- 调查慢性暴露于 (Pb), (As) 和 (Cd) 与主要心血管不良事件 (MACE) 之间的关联.
- 评估机器学习模型在评估重金属暴露对心血管结果风险方面的预测能力.
- 阐明通过哪些机制途径影响心血管健康.
主要方法:
- 利用了2003-2018年NHANES调查中的15342名参与者的数据.
- 采用了八种机器学习算法 (例如,逻辑回归,随机森林,XGBoost,LightGBM) 和夏普利添加式扩展 (SHAP) 分析.
- 在分析心痛,心肌梗塞 (MI) 和心力衰竭 (HF) 时,根据人口和社会经济因素进行调整.
主要成果:
- (Cd) 被确定为所有心血管结果的主要危险因素,超过了 (Pb) 和 (As).
- 机器学习模型显示了显著的关联:RandomForest用于胸痛,XGBoost用于心脏病,以及LightGBM用于高风险.
- 多类建模证实Cd暴露显著提高了MACE的整体风险,其特征的重要性高于Pb和As.
结论:
- 是心血管疾病发病的一个关键决定因素,显著增加MACE风险.
- 机械洞察力表明,Cd通过破坏信号传递,氧化应激,炎症和纤维化促进心血管病理.
- 针对环境暴露减轻的优先公共卫生干预措施对于减少心血管疾病负担至关重要.
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