Comparative predictive ability of visit-to-visit HbA1c variability measures for microvascular disease risk in type 2 diabetes

Chen, Yang; Su, Pei Fang; Hung, Jo Ying; Ou, Horng Yih; Kuo, Shihchen

doi:10.1186/s12933-020-01082-9

Cited by 39 publications

(45 citation statements)

References 42 publications

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“…There are several ways to evaluate the HbA1c variability. One study showed that among the HbA1c variability parameters including mean of HbA1c, yearly mean HbA1c, HbA1c-SD, HbA1c-CV and HVS, HVS performed the best in predicting microvascular events [ 33 ]. One reason is that many of the HbA1c variability parameters are affected by the mean HbA1c value.…”

Section: Discussionmentioning

confidence: 99%

Higher long-term visit-to-visit glycemic variability predicts new-onset atrial fibrillation in patients with diabetes mellitus

Hsu

Yang

Chuang

et al. 2021

Cardiovasc Diabetol

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Background Atrial fibrillation (AF) is prevalent in patients with type 2 diabetes mellitus (T2DM). Glycemic variability (GV) is associated with risk of micro- and macrovascular diseases. However, whether the GV can increase the risk of AF remains unknown. Methods The cohort study used a database from National Taiwan University Hospital, a tertiary medical center in Taiwan. Between 2014 and 2019, a total of 27,246 adult patients with T2DM were enrolled for analysis. Each individual was assessed to determine the coefficients of variability of fasting glucose (FGCV) and HbA1c variability score (HVS). The GV parameters were categorized into quartiles. Multivariate Cox regression models were employed to estimate the relationship between the GV parameters and the risk of AF, transient ischemic accident (TIA)/ischemic stroke and mortality in patients with T2DM. Results The incidence rates of AF and TIA/ischemic stroke were 21.31 and 13.71 per 1000 person-year respectively. The medium follow-up period was 70.7 months. In Cox regression model with full adjustment, the highest quartile of FGCV was not associated with increased risk of AF [Hazard ratio (HR): 1.12, 95% confidence interval (CI) 0.96–1.29, p = 0.148] or TIA/ischemic stroke (HR: 1.04, 95% CI 0.83–1.31, p = 0.736), but was associated with increased risk of total mortality (HR: 1.33, 95% CI 1.12–1.58, p < 0.001) and non-cardiac mortality (HR: 1.41, 95% CI 1.15–1.71, p < 0.001). The highest HVS was significantly associated with increased risk of AF (HR: 1.29, 95% CI 1.12–1.50, p < 0.001), total mortality (HR: 2.43, 95% CI 2.03–2.90, p < 0.001), cardiac mortality (HR: 1.50, 95% CI 1.06–2.14, p = 0.024) and non-cardiac mortality (HR: 2.80, 95% CI 2.28–3.44, p < 0.001) but was not associated with TIA/ischemic stroke (HR: 0.98, 95% CI 0.78–1.23, p = 0.846). The Kaplan–Meier analysis showed significantly higher risk of AF, cardiac and non-cardiac mortality according to the magnitude of GV (log-rank test, p < 0.001). Conclusions Our data demonstrate that high GV is independently associated with the development of new-onset AF in patients with T2DM. The benefit of maintaining stable glycemic levels to improve clinical outcomes warrants further studies.

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Section: Discussionmentioning

confidence: 99%

Higher long-term visit-to-visit glycemic variability predicts new-onset atrial fibrillation in patients with diabetes mellitus

Hsu

Yang

Chuang

et al. 2021

Cardiovasc Diabetol

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“…Studies have provided evidence that long-term HbA1c variability predicted the risk of microvascular disease and DR in patients with type 2 DM [ 23 , 24 , 25 ]. In addition, the HbA1c variability was associated with macrovascular but not with microvascular diseases in type 2 DM patients, whereas short-term GV was associated with both macrovascular and microvascular events in the ADVANCE trial [ 26 ].…”

Section: Discussionmentioning

confidence: 99%

Glycemic Gap as a Useful Surrogate Marker for Glucose Variability and Progression of Diabetic Retinopathy

Hsing

Lin

Chen

et al. 2021

JPM

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(1) Background: Recent studies have reported that the glucose variability (GV), irrespective of glycosylated hemoglobin (HbA1c), could be an additional risk factor for the development of diabetic retinopathy (DR). However, measurements for GV, such as continuous glucose monitoring (CGM) and fasting plasma glucose (FPG) variability, are expensive and time consuming. (2) Methods: This present study aims to explore the correlation between the glycemic gap as a measurement of GV, and DR. In total, 2565 patients were included in this study. We evaluated the effect of the different types of glycemic gaps on DR progression. (3) Results: We found that the area under the curve (AUC) values of both the glycemic gap and negative glycemic gap showed an association with DR progression. (4) Conclusions: On eliminating the possible influences of chronic blood glucose controls, the results show that GV has deleterious effects that are associated with the progression of DR. The glycemic gap is a simple measurement of GV, and the predictive value of the negative glycemic gap in DR progression shows that GV and treatment-related hypoglycemia may cause the development of DR. Individual treatment goals with a reasonable HbA1c and minimal glucose fluctuations may help in preventing DR.

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“…One study showed that among the HbA1c variability parameters including mean of HbA1c, yearly mean HbA1c, HbA1c-SD, HbA1c-CV and HVS, HVS performed the best in predicting microvascular events. [29]. One reason is that many of the HbA1c variability parameters are affected by the mean HbA1c value.…”

Section: Discussionmentioning

confidence: 99%

Higher Long-term Visit-to-Visit Glycemic Variability Predicts New-Onset Atrial Fibrillation in Patients with Diabetes Mellitus

Hsu

Yang

Chuang

et al. 2021

Preprint

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BackgroundAtrial fibrillation (AF) is prevalent in patients with type 2 diabetes mellitus (T2DM). Glycemic variability (GV) is associated with risk of micro- and macrovascular diseases. However, whether the GV can increase the risk of AF remains unknown.MethodsThe cohort study used a database from National Taiwan University Hospital, a tertiary medical center in Taiwan. Between 2014 and 2019, a total of 27246 adult patients with T2DM were enrolled for analysis. Each individual was assessed to determine the coefficients of variability of fasting glucose (FGCV) and HbA1c variability score (HVS). The GV parameters were categorized into quartiles. Multivariate Cox regression models were employed to estimate the relationship between the GV parameters and the risk of AF, transient ischemic accident (TIA)/ischemic stroke and mortality in patients with T2DM.ResultsThe incidence rates of AF and TIA/ischemic stroke were 21.31 and 13.71 per 1000 person-year respectively. The medium follow-up period was 70.7 months. In Cox regression model with full adjustment, the highest quartiles of FGCV was not associated with increased risk of AF (Hazard ratio (HR): 1.11, 95% confidence interval (CI): 0.96-1.29, p=0.165) or TIA/ischemic stroke (HR: 1.03, 95% CI: 0.82-1.29, p=0.821), but was associated with increased risk of total mortality (HR: 1.34, 95% CI: 1.13-1.60, p<0.001) and non-cardiac mortality (HR: 1.42, 95% CI: 1.17-1.72, p<0.001). The highest HVS was significantly associated with increased risk of AF (HR: 1.29, 95% CI: 1.12-1.48, p<0.001), total mortality (HR: 2.44, 95% CI: 2.04-2.91, p<0.001), cardiac mortality (HR: 1.48, 95% CI: 1.04-2.10, p=0.028) and non-cardiac mortality (HR: 2.83, 95% CI: 2.31-3.14, p<0.001) but was not associated with TIA/ischemic stroke (HR: 1.00, 95% CI: 0.79-1.26, p=0.989). The Kaplan-Meier analysis showed significantly higher risk of AF, cardiac and non-cardiac mortality according to the magnitude of GV(log-rank<0.001). ConclusionsHigher GV is independently associated with the development of new-onset AF in patients with T2DM. Reducing GV may be a potential new therapeutic target to prevent AF.

show abstract

Comparative predictive ability of visit-to-visit HbA1c variability measures for microvascular disease risk in type 2 diabetes

Cited by 39 publications

References 42 publications

Higher long-term visit-to-visit glycemic variability predicts new-onset atrial fibrillation in patients with diabetes mellitus

Higher long-term visit-to-visit glycemic variability predicts new-onset atrial fibrillation in patients with diabetes mellitus

Glycemic Gap as a Useful Surrogate Marker for Glucose Variability and Progression of Diabetic Retinopathy

Higher Long-term Visit-to-Visit Glycemic Variability Predicts New-Onset Atrial Fibrillation in Patients with Diabetes Mellitus

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