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估计生活中必不可少的8分,不包括单个指标的不完整数据
Yi Zheng1, Tianyi Huang1,2, Marta Guasch-Ferre3,4,5
1Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States.
Frontiers in cardiovascular medicine
|August 11, 2023
概括
使用美国心脏协会的生命必需8 (LE8) 来估计心血管健康 (CVH) 是一个挑战. 常规收集的健康因素可以准确地预测LE8得分,当所有指标都不可用时.
科学领域:
- 心血管健康 心血管健康
- 健康指标评估 评估健康指标
- 预测建模预测建模
背景情况:
- 美国心脏协会的生命必不可少的8 (LE8) 是一个全面的心血管健康 (CVH) 评估.
- 在研究和临床环境中,同时测量所有八个LE8指标往往是不切实际的.
- 这种限制阻碍了对长期CVH轨迹的评估.
研究的目的:
- 开发和验证一个预测模型来估计基于LE8的CVH分数.
- 为了确定是否常规收集的健康因素可以准确地近似完整的LE8测量.
- 为了方便对CVH的评估随着时间的推移,即使有不完整的数据.
主要方法:
- 利用来自护士健康研究 (NHS,NHSII),卫生专业人员随访研究 (HPFS) 和国家健康和营养检查调查 (NHANES) 的数据.
- 训练有素的梯度增强决策树模型使用例行收集的因素 (人口统计,BMI,吸烟,高血压,高胆固醇,糖尿病) 和较少的因素 (体力活动,饮食,血压,睡眠健康).
- 在内部和外部数据集中使用根平均平方误差 (RMSE) 验证模型性能.
主要成果:
- 在NHS,NHSII和HPFS上训练的基准模型显示了8.06 (内部) 和16.72 (外部) 的验证RMSE.
- 包括额外的预测因素改善了模型性能.
- 在使用NHANES数据训练的模型中观察到一致的结果,表明可靠的CVH得分预测.
结论:
- 当LE8指标不完整时,常规测量CVH相关因素可以有效估计整体CVH.
- 这种方法提高了在不同环境中评估CVH轨迹的可行性.
- 预测模型为跟踪心血管健康提供了一个实用的解决方案.
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