使用Kokuho数据库对糖尿病并发症的预测模型,并将其应用于日本公共卫生服务
Shumpei Chiba1, Takaaki Itoga1, Kazuo Asada1
1EY Strategy and Consulting Co., Ltd., Tokyo, Japan.
Journal of diabetes investigation
|April 2, 2025
概括
一个新的模型预测了日本3年糖尿病并发症风险.
科学领域:
- 医疗信息学 医疗信息学
- 公共卫生 公共卫生
- 预测分析是一种预测分析.
背景情况:
- 日本的具体健康指导 (SHG) 计划旨在预防糖尿病并发症.
- 有效的参与者选择对于计划的有效性至关重要.
- 预测大血管,小血管疾病和CKD风险是公共卫生的优先事项.
研究的目的:
- 为3年糖尿病并发症风险开发一个预测模型.
- 改进日本SHG计划的参与者选择.
- 为了识别高风险的个人对宏观血管疾病,微血管疾病,和CKD.
主要方法:
- 利用Kokuho数据库 (2016-2019) 对没有基线糖尿病并发症的个人.
- 使用后勤回归与健康检查数据,问卷,诊断和处方.
- 通过五倍交叉验证使用曲线下的面积 (AUC) 评估模型性能.
主要成果:
- 优化的模型实现了所有并发症的AUC> 0.7.
- 微血管并发症和CKD的AUC超过0.8,表明高精度.
- 模型在符合SHG标准的个人中发现了更高的风险.
结论:
- 预测模型可以增强SHG针对性,以便及时干预.
- 实施可能会显著减少严重的糖尿病并发症.
- 早期检测和治疗是模型所促进的.
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