Parameters of glycemic variability in continuous glucose monitoring as predictors of diabetes: a prospective evaluation in a non-diabetic general population.

IF 1.1 Q4 MEDICAL LABORATORY TECHNOLOGY
Advances in laboratory medicine Pub Date : 2025-03-07 eCollection Date: 2025-03-01 DOI:10.1515/almed-2025-0011
Javier Rodríguez García, Felix Camiña Darriba, Juan B Ortolá Devesa, Santiago Rodríguez-Segade Villamarín, Andrea Valle Rodríguez
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Abstract

Objectives: To prospectively examine the ability of some glycemic variability metrics from continuous glucose monitoring (CGM) to predict the development of diabetes in a non-diabetic population.

Methods: A total of 497 non-diabetic patients from the AEGIS study were included. Participants used a CGM system (iPro2®) over a six-day period. The following parameters were analyzed: standard deviation (SD), coefficient of variation (CV) and mean amplitude of glucose excursion (MAGE). Six-years follow-up was performed. ROC curves were constructed to determine the predictive value of glycemic variability metrics. Sensitivity and specificity were calculated.

Results: Of the 497 participants, 16 women (4.9 %) and 9 men (5.2 %) developed diabetes. Initial HbA1c and fasting glucose levels were significantly higher in the participants who ultimately developed diabetes. Glycemic variability metrics were also significantly higher in these subjects (SD: 18 vs. 13 mg/dL; CV: 17 vs. 14 %; MAGE: 36 vs. 27 mg/dL; p<0.001 in all cases). SD showed the highest AUC (0.81), with a sensitivity of 80 % and a specificity of 72 % for a cut-off of 14.9 mg/dL. AUCs were higher in men for all metrics.

Conclusions: The metrics obtained by MCG, especially SD, are effective predictors of progression to type 2 diabetes in a non-diabetic population. These findings suggest that glycemic variability is useful for the early identification of subjects at a higher risk of developing diabetes.

Abstract Image

连续血糖监测中的血糖变异性参数作为糖尿病的预测指标:对非糖尿病人群的前瞻性评估。
目的:前瞻性地研究一些来自连续血糖监测(CGM)的血糖变异性指标在非糖尿病人群中预测糖尿病发展的能力。方法:纳入来自AEGIS研究的497例非糖尿病患者。参与者在六天的时间内使用CGM系统(iPro2®)。分析以下参数:标准差(SD)、变异系数(CV)和葡萄糖偏移平均幅度(MAGE)。随访6年。构建ROC曲线以确定血糖变异性指标的预测价值。计算敏感性和特异性。结果:在497名参与者中,16名女性(4.9 %)和9名男性(5.2 %)患糖尿病。在最终发展为糖尿病的参与者中,初始HbA1c和空腹血糖水平明显更高。这些受试者的血糖变异性指标也显著较高(SD: 18 vs. 13 mg/dL;CV: 17 vs. 14 %;MAGE: 36 vs. 27 mg/dL;结论:MCG获得的指标,尤其是SD,是非糖尿病人群进展为2型糖尿病的有效预测指标。这些发现表明,血糖变异性对早期识别患糖尿病风险较高的受试者是有用的。
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