Relationship between hemoglobin glycation index and risk of hypoglycemia in type 2 diabetes with time-in-range in target.

IF 4.2 3区 医学 Q1 ENDOCRINOLOGY & METABOLISM World Journal of Diabetes Pub Date : 2024-10-15 DOI:10.4239/wjd.v15.i10.2058
Bei-Si Lin, Zhi-Gu Liu, Dan-Rui Chen, Yan-Ling Yang, Dai-Zhi Yang, Jin-Hua Yan, Long-Yi Zeng, Xu-Bin Yang, Wen Xu
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Abstract

Background: In patients with type 2 diabetes mellitus (T2DM), the risk of hypoglycemia also occurs in at a time-in-range (TIR) of > 70%. The hemoglobin glycation index (HGI) is considered the best single factor for predicting hypoglycemia, and offers new perspectives for the individualized treatment of patients with well-controlled blood glucose levels that are easily ignored in clinical settings.

Aim: To investigate the relationship between HGI and hypoglycemia and the implications of HGI on hypoglycemia in T2DM with TIR > 70%.

Methods: All participants underwent a 7-days continuous glucose monitoring (CGM) using a retrospective CGM system. We obtained glycemic variability indices using the CGM system. We defined HGI as laboratory hemoglobin A1c minus the glucose management indicator. Patients were categorized into low HGI (HGI < 0.5) and high HGI groups (HGI ≥ 0.5) according to HGI median (0.5). Logistic regression and receiver operating characteristic curve analyses were used to determine the risk factors for hypoglycemia.

Results: We included 129 subjects with T2DM (54.84 ± 12.56 years, 46% male) in the study. Median TIR score was 90%. The high HGI group exhibited lower TIR and greater time below range with higher hemoglobin A1c than the low HGI group; this suggests more glycemic excursions and an increased incidence of hypoglycemia in the high HGI group. Multivariate analyses revealed that mean blood glucose, standard deviation of blood glucose and HGI were independent risk factors for hypoglycemia. Receiver operating characteristic curve analysis indicated that the HGI was the best predictor of hypoglycemia. In addition, the optimal cut-off points for HGI, mean blood glucose, and standard deviation of blood glucose in predicting hypoglycemia were 0.5%, 7.2 mmol/L and 1.4 mmol/L respectively.

Conclusion: High HGI was significantly associated with greater glycemic excursions and increased hypoglycemia in patients with TIR > 70%. Our findings indicate that HGI is a reliable predictor of hypoglycemia in this population.

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血红蛋白糖化指数与 2 型糖尿病低血糖风险之间的关系,以及目标时间范围。
背景:在 2 型糖尿病(T2DM)患者中,低血糖风险的时间范围(TIR)也大于 70%。血红蛋白糖化指数(HGI)被认为是预测低血糖的最佳单一因素,并为临床上容易被忽视的血糖控制良好的患者的个体化治疗提供了新的视角。目的:研究 HGI 与低血糖之间的关系,以及 HGI 对 TIR > 70% 的 T2DM 低血糖的影响:所有参与者均使用回顾性 CGM 系统接受了 7 天连续血糖监测 (CGM)。我们利用 CGM 系统获得了血糖变异性指数。我们将 HGI 定义为实验室血红蛋白 A1c 减去血糖管理指标。根据 HGI 中位数(0.5)将患者分为低 HGI 组(HGI < 0.5)和高 HGI 组(HGI ≥ 0.5)。采用逻辑回归和接收器操作特征曲线分析确定低血糖的风险因素:研究共纳入 129 名 T2DM 患者(54.84 ± 12.56 岁,46% 为男性)。TIR 评分中位数为 90%。与低 HGI 组相比,高 HGI 组的 TIR 值更低,低于范围的时间更长,血红蛋白 A1c 更高;这表明高 HGI 组的血糖偏离更多,低血糖发生率更高。多变量分析显示,平均血糖、血糖标准差和 HGI 是低血糖的独立风险因素。接收者操作特征曲线分析表明,HGI 是预测低血糖的最佳指标。此外,HGI、平均血糖和血糖标准差预测低血糖的最佳临界点分别为 0.5%、7.2 mmol/L 和 1.4 mmol/L:在 TIR > 70% 的患者中,高 HGI 与更大的血糖偏离和更多的低血糖显著相关。我们的研究结果表明,HGI 是该人群发生低血糖的可靠预测指标。
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来源期刊
World Journal of Diabetes
World Journal of Diabetes ENDOCRINOLOGY & METABOLISM-
自引率
2.40%
发文量
909
期刊介绍: The WJD is a high-quality, peer reviewed, open-access journal. The primary task of WJD is to rapidly publish high-quality original articles, reviews, editorials, and case reports in the field of diabetes. In order to promote productive academic communication, the peer review process for the WJD is transparent; to this end, all published manuscripts are accompanied by the anonymized reviewers’ comments as well as the authors’ responses. The primary aims of the WJD are to improve diagnostic, therapeutic and preventive modalities and the skills of clinicians and to guide clinical practice in diabetes. Scope: Diabetes Complications, Experimental Diabetes Mellitus, Type 1 Diabetes Mellitus, Type 2 Diabetes Mellitus, Diabetes, Gestational, Diabetic Angiopathies, Diabetic Cardiomyopathies, Diabetic Coma, Diabetic Ketoacidosis, Diabetic Nephropathies, Diabetic Neuropathies, Donohue Syndrome, Fetal Macrosomia, and Prediabetic State.
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