Impacts of glycemic variability on the relationship between glucose management indicator from iPro™2 and laboratory hemoglobin A1c in adult patients with type 1 diabetes mellitus

Hongxia Liu, Daizhi Yang, Hongrong Deng, Wen Xu, Jing Lv, Yongwen Zhou, Sihui Luo, Xueying Zheng, Hua Liang, Bin Yao, Liling Qiu, Funeng Wang, Fang Liu, Jinhua Yan, Jianping Weng, Hongxia Liu, Daizhi Yang, Hongrong Deng, Wen Xu, Jing Lv, Yongwen Zhou, Sihui Luo, Xueying Zheng, Hua Liang, Bin Yao, Liling Qiu, Funeng Wang, Fang Liu, Jinhua Yan, Jianping Weng

Abstract

Aims: Our aim was to investigate the impact of glycemic variability (GV) on the relationship between glucose management indicator (GMI) and laboratory glycated hemoglobin A1c (HbA1c).

Methods: Adult patients with type 1 diabetes mellitus (T1D) were enrolled from five hospitals in China. All subjects wore the iPro™2 system for 14 days before HbA1c was measured at baseline, 3 months and 6 months. Data derived from iPro™2 sensor was used to calculate GMI and GV parameters [standard deviation (SD), glucose coefficient of variation (CV), and mean amplitude of glycemic excursions (MAGE)]. Differences between GMI and laboratory HbA1c were assessed by the absolute value of the hemoglobin glycation index (HGI).

Results: A total of 91 sensor data and corresponding laboratory HbA1c, as well as demographic and clinical characteristics were analyzed. GMI and HbA1c were 7.20 ± 0.67% and 7.52 ± 0.73%, respectively. The percentage of subjects with absolute HGI 0 to lower than 0.1% was 21%. GMI was significantly associated with laboratory HbA1c after basic adjustment (standardized β = 0.83, p < 0.001). Further adjustment for SD or MAGE reduced the standardized β for laboratory HbA1c from 0.83 to 0.71 and 0.73, respectively (both p < 0.001). In contrast, the β remained relatively constant when further adjusting for CV. Spearman correlation analysis showed that GMI and laboratory HbA1c were correlated for each quartile of SD and MAGE (all p < 0.05), with the corresponding correlation coefficients decreased across ascending quartiles.

Conclusions: This study validated the GMI formula using the iPro™2 sensor in adult patients with T1D. GV influenced the relationship between GMI and laboratory HbA1c.

Keywords: diabetes mellitus; glucose management indicator; glycated hemoglobin A1c; glycemic variability; type 1.

Conflict of interest statement

Conflict of interest statement: The authors declare that there is no conflict of interest.

© The Author(s), 2020.

Figures

Figure 1.
Figure 1.
Disagreement between GMI and laboratory HbA1c. Mean glucose management indicator (GMI) and mean hemoglobin A1c (HbA1c) were compared in all data and separately by hemoglobin glycation index (HGI) group. Data are group means ± SD. GMI was similar to HbA1c in the low-HGI group, lower than HbA1c in the moderate-HGI and the high-HGI group. Dividing the data into HGI groups automatically produces subsets with similar GMI levels but different HbA1c levels (*Lowversus High, p = 0.001; #Moderate versus High,p = 0.001).
Figure 2.
Figure 2.
The relationship between GMI and laboratory HbA1c. GMI was measured by continuous glucose monitoring for 14 days before the HbA1c measurement. The solid line is the best fit. The SEM of the slope and the intercept are 0.06 and 0.44, respectively. GMI, glucose management indicator; HbA1c, hemoglobin A1c; SEM, standard error of the mean.

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