在慢性阻塞性肺病患者中构建和验证2型糖尿病发展的预测模型
Xi Kang1, Tianye Li2, Qinyang Chen1
1School of Public Health, Lan Zhou University, Lanzhou, China.
Frontiers in endocrinology
|September 2, 2025
概括
这项研究确定了慢性阻塞性肺病 (COPD) 患者2型糖尿病 (T2DM) 的关键因素,并开发了一个可视化的预测模型. 该模型有助于在COPD患者群体中早期识别T2DM风险.
科学领域:
- 肺部医学
- 内分泌学
- 生物统计学
背景情况:
- 2型糖尿病 (T2DM) 是慢性阻塞性肺病 (COPD) 患者经常出现的并发症.
- 这种并发症显著增加了COPD患者再入院和死亡的风险.
- 鉴定COPD的因素和预测T2DM对于患者的管理至关重要.
研究的目的:
- 在COPD患者中确定T2DM的影响因素.
- 构建COPD中T2DM的可视化预测模型.
- 帮助早期识别风险和针对性预防.
主要方法:
- 对1773名COPD患者的病历进行回顾性分析 (2020-2023年).
- 使用LASSO,皮尔森相关性和多线性诊断的变量选择.
- 通过向后阶段选择 (AIC) 和名图,通过ROC曲线,校准图,H-L测试,DCA和k折交叉验证进行验证.
主要成果:
- 在COPD患者中T2DM的患病率为27. 13%.
- 确定了七个独立的预测因素:PCO2,中性粒细胞计数,CRP,ESR,胆红素,甘油三和BMI.
- 可视化模型显示出良好的预测性能 (C指数=0. 78,AUC=0. 79- 0. 80) 和临床效用.
结论:
- 在COPD患者中开发了一种可视化T2DM风险预测模型,并进行了内部验证.
- 这种工具可以帮助提前识别高危人群.
- 建议进行外部验证以确认可通用性.
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