首都医科大学学报 ›› 2026, Vol. 47 ›› Issue (2): 353-359.doi: 10.3969/j.issn.1006-7795.2026.02.017

• 临床研究 • 上一篇    下一篇

列线图预测老年人空腹血糖受损的发病风险

李晓静1,申义1,杜扬帆1,姚明言2,杨卫3,董松1,柳洪宙1,4*   

  1. 1.航天中心医院内分泌科,北京  100049;  2.保定市第一中心医院内分泌科,河北保定  071000;  3.保定市第二医院呼吸内科,河北保定;  071051  4.邯郸市第一医院内分泌科,河北邯郸 056002
  • 收稿日期:2026-01-04 修回日期:2026-03-03 出版日期:2026-04-21 发布日期:2026-04-21
  • 通讯作者: 柳洪宙 E-mail:liuhongzhou@301hospital.com.cn
  • 基金资助:
    河北省医学科学研究课题计划资助项目(20241470,20231924)。

Nomogram for predicting the risk of impaired fasting glucose in older adults

Li Xiaojing1, Shen Yi1, Du Yangfan1, Yao Mingyan2, Yang Wei3, Dong Song1, Liu Hongzhou1,4*   

  1. 1.Department of Endocrinology, Aerospace Center Hospital, Beijing 100049, China; 2.Department of Endocrinology, Baoding No.1 Central Hospital, Baoding 071000, Hebei Province, China; 3.Department of respiratory medicine, the No. 2 Hospital of Baoding, 071051; 4.Department of Endocrinology, First Hospital of Handan City, Handan 056002, Hebei Province, China
  • Received:2026-01-04 Revised:2026-03-03 Online:2026-04-21 Published:2026-04-21
  • Supported by:
    This study was supported by Medical Science Research Project of Hebei(20241470,20231924)。

摘要: 目的  基于体检随访队列构建并验证预测血糖正常老年人在3年与5年内发生空腹血糖受损(impaired fasting glucose,IFG)风险的列线图模型。方法  采用回顾性队列研究设计,数据来源于瑞慈医疗集团健康体检数据库(2010—2016年)。纳入基线空腹血糖正常且资料完整的≥60岁老年人,按7∶3随机分为训练集与验证集。以Cox比例风险模型进行单因素筛选与多因素建模,确定IFG独立预测因子并建立列线图;通过C指数、受试者工作特征曲线及校准曲线评估模型区分度与校准度。结果  共纳入21 914名受试者,训练集15 340例、验证集6 574例;随访期间训练集新发IFG 1 411例、验证集新发602例。多因素分析提示年龄、体质量指数、基线空腹血糖、三酰甘油及丙氨酸氨基转移酶与IFG发生风险独立相关,并据此构建列线图。模型在训练集与验证集中均显示良好区分度(C指数分别为0.767与0.763),且校准曲线提示预测概率与实际发生率一致性较好。结论  基于常规体检指标构建的IFG风险列线图简便可行,具有较好的预测性能,可用于体检场景下的早期风险分层与筛查管理。

关键词: 列线图, 空腹血糖受损, 危险因素, C指数, 老年人, 预测模型

Abstract: Objective  To develop and validate a nomogram model based on a physical examination follow-up cohort to predict the risk of incident impaired fasting glucose (IFG) within 3 and 5 years among older adults with normal blood glucose at baseline. Methods  A retrospective cohort study was conducted using data from the health examination database of Ruici Medical Group (2010-2016). Older adults aged ≥60 years with normal baseline fasting plasma glucose (FPG) and complete data were included and randomly split into a training set and a validation set at a 7:3 ratio. Univariate screening and multivariable modeling were performed using the Cox proportional hazards model to identify independent predictors of IFG and construct a nomogram. Model discrimination and calibration were assessed using the concordance index (C-index), receiver operating characteristic (ROC) curves, and calibration plots. Results  A total of 21 914 participants were included (15 340 in the training set and 6 574 in the validation set). During follow-up, 1 411 incident IFG cases occurred in the training set and 602 in the validation set. Multivariable analysis showed that age, body mass index, baseline FPG, triglycerides, and alanine aminotransferase were independently associated with the risk of IFG, and a nomogram was developed accordingly. The model demonstrated good discrimination in both the training and validation sets (C-index: 0.767 and 0.763, respectively), and calibration plots indicated good agreement between predicted probabilities and observed incidence. Conclusion  The IFG risk nomogram constructed from routinely collected health examination indicators is simple and feasible, with good predictive performance, and can be used for early risk stratification and screening management in health check-up settings.

Key words: nomogram, impaired fasting glucose, risk factors, C-index, older adults, prediction model

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