实用老年医学

实用老年医学 ›› 2024, Vol. 38 ›› Issue (6): 592-597.doi: 10.3969/j.issn.1003-9198.2024.06.012

• 临床研究 • 上一篇    下一篇

老年2型糖尿病病人6个月内低血糖风险预测模型的构建:一项纵向研究

郭淳, 易梦廷, 宗前兴, 周怡, 巫海娣, 莫永珍   

  1. 211166 江苏省南京市,南京医科大学护理学院(郭淳,宗前兴);
    215006 江苏省苏州市,苏州大学医学部护理学院(易梦廷,周怡);
    210024 江苏省南京市,南京医科大学附属老年医院糖尿病中心(巫海娣);老年综合评估研究室(莫永珍)
  • 收稿日期:2023-11-06 出版日期:2024-06-20 发布日期:2024-06-19
  • 通讯作者: 莫永珍,Email:yongzhenmo@vip.sina.com
  • 基金资助:
    江苏省干部保健科研项目(BJ21027);南京医科大学智慧康善产业学院项目(2023-95)

Development of a 6-month risk prediction model for hypoglycemia in elderly patients with type 2 diabetes mellitus: a longitudinal study

GUO Chun, YI Mengting, ZONG Qianxing, ZHOU Yi, WU Haidi, MO Yongzhen   

  1. School of Nursing, Nanjing Medical University, Nanjing 211166, China (GUO Chun, ZONG Qianxing);
    School of Nursing, Medical College of Soochow University, Suzhou 215006, China (YI Mengting, ZHOU Yi);
    Diabetes Center (WU Haidi); Department of Comprehensive Geriatric Assessment (MO Yongzhen), Affiliated Geriatric Hospital of Nanjing Medical University, Nanjing 210024, China
  • Received:2023-11-06 Online:2024-06-20 Published:2024-06-19
  • Contact: MO Yongzhen, Email: yongzhenmo@vip.sina.com

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摘要： 目的 构建老年2型糖尿病病人6个月内发生低血糖的风险预测模型。方法 便利抽样选取2022年2—8月于南京医科大学附属老年医院门诊及住院的老年2型糖尿病病人277例,根据随访6个月内是否出现低血糖分为低血糖组(69例) 和非低血糖组(208例)。 采用LASSO回归和多因素 Logistic 回归分析确定影响因素,构建列线图预测模型并对模型进行评价。结果 24.91%(69/277)的病人在6个月内发生低血糖。低血糖病史(OR=6.989,95%CI:3.671～13.844,P<0.001)是老年2型糖尿病病人6个月内发生低血糖的危险因素,而高MMSE得分(OR=0.890,95%CI:0.820～0.959,P=0.003)、TG≥1.7 mmol/L(OR=0.268,95%CI:0.083～0.708,P=0.014)是保护因素。构建的风险预测模型AUC为 0.801(95%CI:0.742～0.860),灵敏度为0.841,特异度为0.673,准确度为71.48%。在内部验证中矫正后的AUC为0.783;Hosmer-Lemeshow 拟合优度检验显示该模型具有良好的校准度(χ2=10.81,P=0.212);临床决策曲线分析(DCA) 结果显示,模型的预测阈值为0.02～0.69时,病人的临床净收益水平最高。结论 构建的低血糖风险预测模型具有较好的区分度、校准度和临床适用性,可为医护人员识别高风险人群并采取预防性干预提供依据。

关键词: 老年人, 2型糖尿病, 低血糖, 认知功能评定, 预测模型

Abstract: Objective To construct a risk prediction model for hypoglycemia within 6 months in the elderly patients with type 2 diabetes mellitus (T2DM). Methods Convenience sampling was used to select 277 elderly patients with T2DM in Affiliated Geriatric Hospital of Nanjing Medical University from February to August 2022. According to whether hypoglycemia occurred within 6 months of follow-up, the patients were divided into hypoglycemia group (69 cases) and non-hypoglycemia group (208 cases). LASSO regression and multivariate Logistic regression analysis were used to determine the influencing factors, and a nomogram prediction model was constructed and evaluated. Results 24.91% (69/277) of the patients presented with hypoglycemia within 6 months. History of hypoglycemia (OR=6.989, 95%CI: 3.671-13.844, P<0.001) was the risk factor, while high MMSE score (OR=0.890, 95%CI: 0.820-0.959, P=0.003) and triglyceride ≥1.7 mmol/L (OR=0.268, 95%CI: 0.083-0.708, P=0.014) were the protective factors for hypoglycemia in the elderly patients with T2DM within 6 months. The area under the receiver operating characteristic curve (AUC) of the model was 0.801 (95%CI: 0.742-0.860), with a sensitivity of 0.841, a specificity of 0.673, and an accuracy of 71.48%. In the internal validation, the corrected AUC was 0.783, indicating that the model had good discrimination. The Hosmer-Lemeshow goodness of fit test showed that the model had a good calibration (χ2=10.81,P=0.212). The results of clinical decision curve analysis showed that when the prediction threshold of the model was between 0.02 and 0.69, the net clinical benefit level of the patients was the highest. Conclusions The constructed model has good discrimination, calibration and clinical applicability, which can provide a basis for medical staff to identify high-risk group of hypoglycemia and take preventive intervention.

Key words: aged, type 2 diabetes mellitus, hypoglycemia, assessment of cognitive function, prediction model

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