Dataset Information

Glycemic variability assessed by continuous glucose monitoring and the risk of diabetic retinopathy in latent autoimmune diabetes of the adult and type 2 diabetes.

ABSTRACT:

Aims/introduction

The relationship between glycemic variability (GV) and diabetic complications has gained much interest and remains under debate. Furthermore, the association of GV with diabetic complications has not been examined in latent autoimmune diabetes of the adult (LADA). Therefore, we evaluated the relationships among several metrics of GV with diabetic retinopathy (DR) in patients with LADA and type 2 diabetes mellitus.

Materials and methods

A total of 192 patients with LADA and 2,927 patients with type 2 diabetes mellitus were enrolled. After continuous glucose monitoring for 72 h, three metrics of GV including standard deviation, coefficient of variation and mean amplitude of glycemic excursions were calculated. DR was assessed by fundus photography performed with a digital non-mydriatic camera.

Results

The prevalence of DR was 20.3 and 26.4% in LADA and type 2 diabetes mellitus patients (P < 0.001), respectively. Generally, LADA patients had fewer cardiometabolic risk factors than type 2 diabetes mellitus patients, and all GV metrics were significantly higher in LADA than in type 2 diabetes mellitus. In the multivariate logistic regression analysis, no metrics for GV were identified as independent risk factors of DR (standard deviation: P = 0.175; coefficient of variation: P = 0.769; mean amplitude of glycemic excursions: P = 0.388) in LADA. However, the standard deviation was significantly associated with DR (OR 1.15, P = 0.017) in patients with type 2 diabetes mellitus after adjusting for confounders. The independent relationships of coefficient of variation and mean amplitude of glycemic excursions with DR (P = 0.194 and P = 0.251, respectively) did not reach statistical significance in type 2 diabetes mellitus.

Conclusions

GV is more strongly associated with DR in type 2 diabetes than in LADA, suggesting that different glucose-lowering strategies should be used for these two types of diabetes.

SUBMITTER: Lu J

PROVIDER: S-EPMC6497773 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Publications

Glycemic variability assessed by continuous glucose monitoring and the risk of diabetic retinopathy in latent autoimmune diabetes of the adult and type 2 diabetes.

Lu Jingyi J Ma Xiaojing X Zhang Lei L Mo Yifei Y Ying Lingwen L Lu Wei W Zhu Wei W Bao Yuqian Y Zhou Jian J

Journal of diabetes investigation 20181107 3

<h4>Aims/introduction</h4>The relationship between glycemic variability (GV) and diabetic complications has gained much interest and remains under debate. Furthermore, the association of GV with diabetic complications has not been examined in latent autoimmune diabetes of the adult (LADA). Therefore, we evaluated the relationships among several metrics of GV with diabetic retinopathy (DR) in patients with LADA and type 2 diabetes mellitus.<h4>Materials and methods</h4>A total of 192 patients wit ...[more]

PMID: 30306722

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Project description:Aim: Patients with Type 2 Diabetes Mellitus (T2DM) have increased risk of developing vascular complications due to chronic hyperglycemia. Glycemic variability (GV) has been suggested to play an even more important role in the risk of developing diabetic complications than sustained hyperglycemia. Physical activity (PA) has shown reducing effects on mean plasma glucose; however, the effect on GV in T2DM needs further description. The objective of this review is to evaluate the effect of PA on GV, assessed by continuous glucose monitoring (CGM) in people with T2DM. Methods: A systematic literature search was conducted on MEDLINE and Embase to find randomized controlled trials (RCTs) covering the aspects T2DM, PA, and CGM. Following eligibility screening, variables of population characteristics, PA interventions, and GV outcomes were extracted and processed through qualitative synthesis. Risk of bias (ROB) was assessed using Cochrane ROB tool v2.0. Results: Of 1,825 identified articles, 40 full texts were screened. In the ten included RCTs matching the eligibility criteria, sample sizes ranged from nine to 63, mean age from 51 (SD 11) to 65 (SD 2) years and mean T2DM duration from four (SD 3) to ten (SD 6) years. Eight RCTs examined GV following single bouts of exercise, while two RCTs examined GV following training interventions. One RCT applied parallel group design, while nine RCTs applied crossover design. Numeric reductions in GV following acute exercise were seen, with four RCTs reaching statistical significance. Numeric reductions in GV were seen following training interventions, with one RCT reaching statistical significance. Numeric reductions of GV after PA appeared independently of intensity and T2DM progression but higher in participants with high baseline HbA1c and GV than with low. 80% of the trials were evaluated as uncertain/high ROB. Conclusion: The systematic literature search revealed limited and biased evidence showing that acute PA numerically reduced GV in patients with T2DM. PA reduced GV independently of PA intensity and T2DM progression. Prolonged RCTs with low ROB are needed to confirm reducing effects of PA on GV and to assess the influence of patient- and intervention characteristics on the effect of PA on GV.

Project description:BackgroundDeterioration of sleep quality has been reported to contribute to the incidence of diabetes and may be responsible for glycemic status in diabetes. The present study explored the relationship between sleep quality and glycemic variability in patients with type 2 diabetes (T2D).MethodsWe recruited 111 patients with T2D for this cross-sectional study. Each patient underwent flash glucose monitoring for 14 days to obtain glycemic variability parameters, such as standard deviation of glucose (SD), coefficient of variation of glucose (CV), mean amplitude of glycemic excursions (MAGE), mean of daily differences (MODD), and time in glucose range of 3.9-10 mmol/L (TIR3.9-10). After 14 days of flash glucose monitoring, each patient received a questionnaire on the Pittsburgh Sleep Quality Index (PSQI) to evaluate subjective sleep quality. HbA1c was also collected to assess average glucose.ResultsHbA1c was comparable among the subgroups of PSQI score tertiles. Across ascending tertiles of PSQI scores, SD, CV and MAGE were increased, while TIR3.9-10 was decreased (p for trend < 0.05), but not MODD (p for trend = 0.090). Moreover, PSQI scores were positively correlated with SD, CV, MODD and MAGE (r = 0.322, 0.361, 0.308 and 0.354, respectively, p < 0.001) and were inversely correlated with TIR3.9-10 (r = - 0.386, p < 0.001). After adjusting for other relevant data by multivariate linear regression analyses, PSQI scores were independently responsible for SD (β = 0.251, t = 2.112, p = 0.041), CV (β = 0.286, t = 2.207, p = 0.033), MAGE (β = 0.323, t = 2.489, p = 0.018), and TIR3.9-10 (β = - 0.401, t = - 3.930, p < 0.001) but not for MODD (β = 0.188, t = 1.374, p = 0.177).ConclusionsIncreased glycemic variability assessed by flash glucose monitoring was closely associated with poor subjective sleep quality evaluated by the PSQI in patients with T2D.

Project description:BackgroundIt is presently unclear whether glycemic variability (GV) is associated with baroreflex sensitivity (BRS), which is an early indicator of cardiovascular autonomic neuropathy. The present study is the first to examine the relationships between BRS and GV measured using continuous glucose monitoring (CGM).MethodsThis was a multicenter, prospective, open-label clinical trial. A total of 102 patients with type 2 diabetes were consecutively recruited for this study. GV was assessed by measuring the standard deviation (SD), glucose coefficient of variation (CV), and the mean amplitude of glycemic excursions (MAGE) during CGM. The BRS was analyzed from electrocardiogram and blood pressure recordings using the sequence method on the first day of hospitalization.ResultsA total of 94 patients (mean diabetes duration 9.7?±?9.6 years, mean HbA1c 61.0?±?16.8 mmol/mol [7.7?±?1.5%]) were analyzed. In the univariate analysis, CGM-SD (r?=?-?0.375, p?=?0.000), CGM-CV (r?=?-?0.386, p?=?0.000), and MAGE (r?=?-?0.395, p?=?0.000) were inversely related to BRS. In addition to GV, the level of BRS correlated with the coefficient of variation in the R-R intervals (CVR-R) (r?=?0.520, p?=?0.000), heart rate (HR) (r?=?-?0.310, p?=?0.002), cardio-ankle vascular index (CAVI) (r?=?-?0.326, p?=?0.001), age (r?=?-?0.519, p?=?0.000), and estimated glomerular filtration rate (eGFR) (r?=?0.276, p?=?0.007). Multiple regression analysis showed that CGM-CV and MAGE were significantly related to a decrease in BRS. These findings remained after adjusting the BRS for age, sex, hypertension, dyslipidemia, HR, eGFR, CAVI, and CGM-mean glucose. Additionally, BRS was divided according to quartiles of the duration of diabetes (Q1-4). BRS decreased after a 2-year duration of diabetes independently of age and sex.ConclusionsGV was inversely related to BRS independently of blood glucose levels in type 2 diabetic patients. Measurement of BRS may have the potential to predict CV events in consideration of GV. Trial registration UMIN Clinical Trials Registry UMIN000025964, 28/02/2017.

Project description:BackgroundHbA1c variability is independent of mean HbA1c, and associated with mortality due to vascular complications. However, the significance of HbA1c variability is unknown at present. In this study, we used flash glucose monitoring (FGM) and evaluated glycemic intraday variations, and then examined the association with HbA1c variability.MethodsWe conducted a retrospective pilot study of 26 patients treated at the Outpatient department for type 2 diabetes mellitus (T2DM), and evaluated the following items associated with blood glucose levels and their changes/variations using FGM. The primary endpoint was factor(s) associated with standard deviation (SD) HbA1c over a 6-month period. To adjust for the effect of varying numbers of HbA1c measurements, we used the adjusted SD of HbA1c.ResultsThere were significant correlations between mean HbA1c and each of glucose management indicator, maximum, percent time at glucose > 180 mg/day, mean of daily difference of blood glucose, and high blood glucose index. Adjusted SD HbA1c correlated significantly with percent time at glucose < 70 mg/dL and low blood glucose index. We estimated the regression coefficient of adjusted SD HbA1c using multivariate linear regression analysis, and noted that the presence of hypoglycemia affected Adjusted SD HbA1c (β = 0.130, SE = 0.044, P = 0.008). Hypoglycemia was noted in 17 patients, and adjusted SD HbA1c was significantly higher (p = 0.001) in the hypoglycemic group (0.22 ± 0.12%), compared with the non-hypoglycemic group (0.08 ± 0.05%). The cut-off value of adjusted SD HbA1c was 0.109% in the hypoglycemic group.ConclusionsThe results showed that HbA1c variability is associated with hypoglycemia. For patients with high HbA1c variability, we recommend evaluation for the presence of hypoglycemia and reconsideration of their treatment regimen including their glucose-lowering medications. Trial registration The study protocol and opt-out method of informed consent were approved by the ethics committees of the University of Occupational and Environmental Health (Trial registration: H27-186, Registered 25 Dec 2015).

Dataset Information

Glycemic variability assessed by continuous glucose monitoring and the risk of diabetic retinopathy in latent autoimmune diabetes of the adult and type 2 diabetes.

Aims/introduction

Materials and methods

Results

Conclusions

Publications

Glycemic variability assessed by continuous glucose monitoring and the risk of diabetic retinopathy in latent autoimmune diabetes of the adult and type 2 diabetes.

Similar Datasets

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