使用随机森林算法深入探索和精确识别糖尿病外围神经病变的关键风险因素
Yongnan Li1, Yongsheng Li2, Gan Sen3,4
1Department of Nursing, Suzhou BenQ Medical Center, Suzhou, China.
Frontiers in endocrinology
|January 23, 2026
概括
糖尿病外围神经病变 (DPN) 的风险是由年龄,糖尿病持续时间,HbA1c和GSP水平预测的. 维生素D水平具有保护作用,有助于糖尿病患者的DPN预防策略.
科学领域:
- 内分泌学和新陈代谢学
- 神经学 神经学
- 生物统计学 生物统计学
背景情况:
- 糖尿病外围神经病变 (DPN) 是糖尿病的常见和衰弱的并发症,增加了残疾和死亡率.
- 早期干预和有效的管理对于降低DPN的风险和进展至关重要.
研究的目的:
- 开发和验证2型糖尿病 (T2DM) 的住院患者中DPN的风险预测模型.
- 确定与DPN相关的关键风险因素,以改善临床风险评估和个性化管理策略.
主要方法:
- 对1004名住院的T2DM患者进行了回顾性队列研究.
- 使用随机森林 (RF) 算法开发DPN风险预测模型.
- 后勤回归分析以确定DPN的重大风险因素.
主要成果:
- 确定了五个重要的DPN风险因素:年龄增长,糖尿病持续时间长,HbA1c升高和更高的GSP水平.
- 较低的血清25(OH) D3水平被发现对DPN有保护作用.
- 基于射频的DPN风险预测模型表现出优异的歧视性性能,AUC为0.829.
结论:
- 开发的随机森林模型通过结合关键的临床和生物化学因素,有效预测DPN风险.
- 该模型为T2DM患者个性化DPN预防和管理策略提供了有价值的工具.
- 这些发现支持将这种风险评估工具整合到临床实践中,以提供积极的糖尿病护理.
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