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Review
. 2017 Nov 14:16:45.
doi: 10.1186/s40200-017-0323-5. eCollection 2017.

Glucose variability for cardiovascular risk factors in type 2 diabetes: a meta-analysis

Shuang Liang  1 , Hang Yin  1 , Chunxiang Wei  1 , Linjun Xie  1 , Hua He  1 , Xiaoquan Liu  1
Affiliations
Review

Glucose variability for cardiovascular risk factors in type 2 diabetes: a meta-analysis

Shuang Liang et al. J Diabetes Metab Disord. .

Abstract

Aims: It is consensus that glucose variability (GV) plays an important role in maccomplications of type 2 diabetes, but whether GV has a causal role is not yet clear for cardiovascular disease (CVD). This study sought to explore the effect on GV for CVD risk factors with type 2 diabetes.

Methods: The systematic literature search was performed to identify all GV and CVD risk factors, including total cholesterol (TC), LDL cholesterol (LDL-C), triglyceride (TG), HDL cholesterol (HDL-C), Body Mass Index (BMI), waist circumference (WC), High-Sensitivity C-reactive protein (Hs-CRP), Homeostasis model assessment (HOMA) and carotid intima-media thickness (IMT). Preferred Reporting Items was synthesized for Systematic reviews and Meta Analyses guideline. And the pooled analyses were undertaken using Review Manager 5.3.

Results: Twenty two studies were included with a total of 1143 patients in high glucose variability group (HGVG) and 1275 patients low glucose variability group (LGVG). Among these selected CVD risk factors, HOMA-IR and reduced IMT were affected by GV. HOMA-IR level was significantly lower in LGVG than in HGVG (MD = 0.58, 95% CI: 0.26 to 0.91, P = 0.0004), with evidence of heterogeneity between studies (I2 = 0%; P = 0.47).Reduced IMT level was significantly lower in LGVG than in HGVG (SMD = 0.28, 95% CI: 0.09 to 0.47, P = 0.003), with evidence of heterogeneity between studies (I2 = 0%; P = 0.48). However, the others were no significant statistical difference.

Conclusions: Among these selected CVD risk factors in type 2 diabetes, minimizing GV could improve insulin resistance and reduced IMT, consistent with a lowering in risk of CVD.

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Figures

Fig. 1
Fig. 1
Flow diagram for identifying eligible studies
Fig. 2
Fig. 2
Forest plots of the effect of glucose variability for CVD risk factors in type 2 diabetes patients, showing differences in outcomes of trials with LGVG and HGVG. (i) Effect of GV on HOMA-IR. (ii) Effect of GV on IMT. (iii) Effect of GV on TG. (CL: confidence interval. LGVG: low glucose variability group. HGVG: high glucose variability group. IMT: carotid intima-media thickness TG: triglyceride
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