开发和评估一种风险预测模型,用于患有视力威胁性糖尿病视网膜病变的2型糖尿病患者
Di Gong1,2, Lyujie Fang2, Yixian Cai2
1Shenzhen Eye Hospital, Jinan University, Shenzhen, Guangdong, China.
Frontiers in endocrinology
|September 11, 2023
概括
一种新的诺莫图谱使用临床数据预测2型糖尿病 (T2DM) 患者的视力威胁性糖尿病视网膜病变 (VTDR). 关键因素包括年龄,BMI,血压,糖尿病持续时间和HbA1C水平.
科学领域:
- 眼科医生 眼科 眼科
- 内分泌学 在内分泌学.
- 生物统计学 生物统计学
背景情况:
- 糖尿病视网膜病变 (DR) 是2型糖尿病 (T2DM) 患者视力丧失的主要原因.
- 对视力威胁性糖尿病视网膜病变 (VTDR) 的预测模型对于早期干预和管理至关重要.
- 非成像临床数据为风险分层提供了一个潜在的可访问方法.
研究的目的:
- 开发和验证使用非成像临床数据来预测T2DM患者的VTDR风险的诺姆图.
- 在这个人群中确定与VTDR相关的独立风险因素.
主要方法:
- 利用了来自广东沙冈糖尿病队列研究的数据 (n=2294名T2DM患者).
- 数据被分为训练 (n=1605) 和测试 (n=689) 集.
- 多变量逻辑回归确定了风险因素;使用ROC曲线,AUC和Hosmer-Lemeshow测试构建并验证了一个名图.
主要成果:
- 确定年龄,BMI,静脉血压 (SBP),糖尿病持续时间和糖化血红蛋白 (HbA1C) 作为VTDR的独立风险因素.
- 诺米图实现了0.7193 (训练) 和0.6897 (测试) 的AUC.
- 在预测和观察概率之间观察到很高的一致性 (Hosmer-Lemeshow测试P > 0.46对于两组).
结论:
- 开发的名图有效地对T2DM患者的VTDR风险进行了分层.
- 年龄,BMI,SBP,持续时间和HbA1C等临床变量是有价值的预测因素.
- 这种非成像方法为T2DM管理中的风险评估提供了一个实用的工具.
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