Association of variability in hemoglobin A1c with cardiovascular diseases and mortality in Chinese patients with type 2 diabetes mellitus - A retrospective population-based cohort study

Trajectory of haemoglobin A1c and incidence of cardiovascular disease in patients with type 2 diabetes mellitus

AIM

To evaluate the association between changes in haemoglobin A1c (HbA1c) and the concurrent incidence of cardiovascular disease (CVD) in type 2 diabetes mellitus (T2DM) patients.

METHOD

We conducted a retrospective cohort study among T2DM patients with HbA1c measurement after T2DM diagnosis between August 2009 and September 2010. The patients were classified into six subgroups based on baseline HbA1c (<7%; 7%-7.9%; ≥8%) and age (<65; ≥65 years), and then clustered into classes by HbA1c trajectory and CVD incidence over the 12-year follow-up period using joint latent class mixture models. We explored the HbA1c trajectories and CVD incidences in each latent class. Multinomial logistic regression was used to compare the baseline characteristics among different latent classes.

RESULTS

A total of 128 843 T2DM patients were included with a median follow-up period of 11.7 years. Ten latent classes were identified in patients with baseline HbA1c ≥ 8% and age <65 years, while seven classes were identified in the other five groups. Among all the identified latent classes, patients with fluctuating HbA1c trajectories, characterized by alternating periods of increase and decrease, had higher CVD incidences. Male patients, and patients with higher baseline HbA1c and use of antidiabetic drugs were more likely to have a fluctuating HbA1c trajectory. More specifically, patients aged < 65 years with younger age or a smoking habit, and patients aged ≥ 65 years with a longer duration of T2DM were more likely to have a fluctuating HbA1c trajectory.

CONCLUSION

We found that T2DM patients with fluctuating HbA1c trajectories could have a higher CVD risk. Different trajectory-associated characteristics in age subgroups highlight the need for individualized management of T2DM patients.

Within-subject variation of HbA1c: A systematic review and meta-analysis

BACKGROUND

Glycosylated haemoglobin (HbA1c) measurement is used to diagnose and to guide treatment of diabetes mellitus. Within-subject variability in measured HbA1c affects its clinical utility and interpretation, but no comprehensive systematic review has described within-subject variability.

METHODS

A systematic review and meta-analysis was performed of within-subject variability of HbA1c. Multiple databases were searched from inception to November 2022 for follow-up studies of any design in adults or children, with repeated measures of HbA1c or glycosylated haemoglobin. Title and abstract screening was performed in duplicate, full text screening and data extraction by one reviewer and verified by a second. Risk of bias of included papers was assessed using a modified consensus-based standards for the selection of health measurement Instruments (COSMIN) tool. Intraclass correlation coefficient (ICC) results were pooled with a meta-analysis and coefficient of variation (CV) results were described by median and range.

RESULTS

Of 2675 studies identified, 111 met the inclusion criteria. Twenty-five studies reported variability data in healthy patients, 19 in patients with type 1 diabetes and 59 in patients with type 2 diabetes. Median within-subject coefficient of variation (CV) was 0.070 (IQR 0.034 to .09). For healthy subjects the median CV for HbA1c % was 0.017 (IQR 0.013 to 0.022), for patients with type 1 diabetes 0.084 (IQR 0.067 to 0.89) and for type 2 diabetes 0.083 (IQR 0.06 to 0.10). CV increased with mean population HbA1c.

LIMITATIONS

Assessment of variability was not the main aim of many of the included studies and some relevant papers may have been missed. Many included papers had few participants or few repeated measurements.

CONCLUSIONS

Within-subject variability of HbA1c is higher for patients with than without diabetes and increases with mean population HbA1c. This may confound observed relationships between HbA1c variability and health outcomes. Because of its importance in clinical decision-making there is a need for better estimates and understanding of factors associated with of HbA1c variability.

A study of factors influencing long-term glycemic variability in patients with type 2 diabetes: a structural equation modeling approach

Aim

The present study aims to utilize structural equation modeling (SEM) to investigate the factors impacting long-term glycemic variability among patients afflicted with type 2 diabetes.

Method

The present investigation is a retrospective cohort study that involved the collection of data on patients with type 2 diabetes mellitus who received care at a hospital located in Chengdu, Sichuan Province, over a period spanning from January 1, 2013, to October 30, 2022. Inclusion criteria required patients to have had at least three laboratory test results available. Pertinent patient-related information encompassing general demographic characteristics and biochemical indicators was gathered. Variability in the dataset was defined by standard deviation (SD) and coefficient of variation (CV), with glycosylated hemoglobin variation also considering variability score (HVS). Linear regression analysis was employed to establish the structural equation models for statistically significant influences on long-term glycemic variability. Structural equation modeling was employed to analyze effects and pathways.

Results

Diabetes outpatient special disease management, uric acid variability, mean triglyceride levels, mean total cholesterol levels, total cholesterol variability, LDL variability, baseline glycated hemoglobin, and recent glycated hemoglobin were identified as significant factors influencing long-term glycemic variability. The overall fit of the structural equation model was found to be satisfactory and it was able to capture the relationship between outpatient special disease management, biochemical indicators, and glycated hemoglobin variability. According to the total effect statistics, baseline glycated hemoglobin and total cholesterol levels exhibited the strongest impact on glycated hemoglobin variability.

Conclusion

The factors that have a significant impact on the variation of glycosylated hemoglobin include glycosylated hemoglobin itself, lipids, uric acid, and outpatient special disease management for diabetes. The identification and management of these associated factors can potentially mitigate long-term glycemic variability, thereby delaying the onset of complications and enhancing patients' quality of life.

Hemoglobin A1c Variability Metrics Predict Coronary Artery Calcium and Cardiovascular Events in Type 1 Diabetes: The CACTI Study

CONTEXT

Interventions that decrease mean glucose have reduced rates of micro- and macrovascular complications in type 1 diabetes (T1D). However, the difference in cardiovascular risk between people with T1D and the general population endures, suggesting that factors beyond hemoglobin A1C (HbA1c) normalization drive cardiovascular outcomes.

OBJECTIVE

To determine whether various HbA1c metrics predict anatomic cardiovascular disease (CVD) risk factors and/or CVD events in people with T1D.

METHODS

We used linear regression to analyze the relationship of several HbA1c metrics to anatomic CVD risk factors and then used Cox regression to model their relationship to incident CVD events in the CACTI Study (ClinicalTrials.gov Identifier: NCT00005754).

RESULTS

In linear regression models adjusted for age, sex, and T1D duration, baseline Hba1c (b = 0.3998, P = 0.0236), mean HbA1c (b = 0.5385, P = 0.0109), and HbA1c SD (b = 1.1521, P = 0.0068) were each positively associated with square root transformed coronary artery calcium volume. Conversely, only mean HbA1c (b = 1.659, P = 0.0048) positively associated with pericardial adipose tissue volume. In survival models adjusted for age, sex, and T1D duration, baseline HbA1c [hazard ratio (HR): 1.471, 95% CI: 1.257-1.721], mean HbA1c (HR: 1.850, 95% CI: 1.511-2.264), time-varying HbA1c (HR: 1.500, 95% CI: 1.236-1.821), and HbA1c SD (HR: 1.665, 95% CI: 1.022-2.711) each independently predicted CVD events over 14.3 ± 5.2 person-years of follow-up.

CONCLUSIONS/INTERPRETATION

We found that various HbA1c metrics positively correlated with CAC volume and independently predicted incident CVD events in the CACTI T1D cohort. These associations with CVD events persisted for baseline HbA1c, mean HbA1c, and time-varying HbA1c even after adjustment for numerous CVD risk factors.

Association between hemoglobin glycation index and diabetic kidney disease in type 2 diabetes mellitus in China: A cross- sectional inpatient study

Objective

To investigate the association between Hemoglobin Glycation Index (HGI) and Diabetic Kidney Disease (DKD) in Chinese type 2 diabetic individuals and to construct a risk score based on HGI to predict a person's risk of DKD.

Methods

We retrospectively analyzed 1622 patients with type 2 diabetes mellitus (T2DM). HGI was obtained by calculating the fasting plasma glucose (FPG) level into the formula, and they were grouped into low HGI group (L-HGI), medium HGI group (H-HGI) and high HGI group (H-HGI) according to tri-sectional quantile of HGI. The occurrence of DKD was analyzed in patients with different levels of HGI. Multivariate logistics regression analysis was used to analyze the risk factors of DKD in patients with T2DM.

Results

A total of 1622 patients with T2DM were enrolled in the study. Among them, 390 cases were DKD. The prevalence of DKD among the three groups was 16.6%, 24.2% and 31.3%. The difference was statistically significant (P = 0.000). There were significant differences in age (P=0.033), T2DM duration (P=0.005), systolic blood pressure (SBP) (P=0.003), glycosylated hemoglobin (HbA1c) (P=0.000), FPG (P=0.032), 2-hour postprandial plasma glucose (2h-PPG) (P=0.000), fasting C-peptide FCP (P=0.000), 2-hour postprandial C-peptide (2h-CP) (P=0.000), total cholesterol (TC) (P=0.003), low density lipoprotein cholesterol (LDL-C) (P=0.000), serum creatinine (sCr) (P=0.001), estimated glomerular filtration rate (eGFR) (P=0.000) among the three groups. Mantel-Haenszel chi-square test showed that there was a linear relationship between HGI and DKD (x2=177.469, p < 0.001). Pearson correlation analysis showed that with the increase of HGI level the prevalence of DKD was increasing (R= 0.445, P=0.000). It was indicated by univariate logistic regression analysis that individuals in H-HGI was more likely to develop DKD (OR: 2.283, 95% CI: 1.708~ 3.052) when compared with L-HGI. Adjusted to multiple factors, this trend still remained significant (OR: 2.660, 95% CI: 1.935~ 3.657). The combined DKD risk score based on HGI resulted in an area under the receiver operator characteristic curve (AUROC) of 0.702.

Conclusions

High HGI is associated with an increased risk of DKD. DKD risk score may be used as one of the risk predictors of DKD in type 2 diabetic population.

Long-term HbA1c variability and macro-/micro-vascular complications in type 2 diabetes mellitus: a meta-analysis update

AIMS

The aim of the present study was to evaluate, by means of a meta-analysis approach, whether new available data, appeared on qualified literature, can support the effectiveness of an association of HbA1c variability with the risk of macro- and/or micro-vascular complications in type 2 diabetes mellitus (T2DM).

METHODS

The meta-analysis was conducted according to PRISMA Statement guidelines and considered published studies on T2DM, presenting HbA1c variability as standard deviation (SD) or its derived coefficient of variation (CV). Literature search was performed on PubMed in the time range 2015-July 2022, with no restrictions of language.

RESULTS

Twenty-three selected studies fulfilled the aims of the present investigation. Overall, the analysis of the risk as hazard ratios (HR) indicated a significant association between the HbA1c variability, expressed either as SD or CV, and the complications, except for neuropathy. Macro-vascular complications were all significantly associated with HbA1c variability, with HR 1.40 (95%CI 1.31-1.50, p < 0.0001) for stroke, 1.30 (95%CI 1.25-1.36, p < 0.0001) for transient ischaemic attack/coronary heart disease/myocardial infarction, and 1.32 (95%CI 1.13-1.56, p = 0.0007) for peripheral arterial disease. Micro-vascular complications yielded HR 1.29 (95%CI 1.22-1.36, p < 0.0001) for nephropathy, 1.03 (95%CI 0.99-1.08, p = 0.14) for neuropathy, and 1.15 (95%CI 1.08-1.24, p < 0.0001) for retinopathy. For all-cause mortality, HR was 1.33 (95%CI 1.27-1.39, p < 0.0001), and for cardiovascular mortality 1.25 (95%CI 1.17-1.34, p < 0.0001).

CONCLUSIONS

Our meta-analysis on HbA1c variability performed on the most recent published data since 2015 indicates positive association between HbA1c variability and macro-/micro-vascular complications, as well as mortality events, in T2DM, suggesting that this long-term glycaemic parameter merits further attention as a predictive, independent risk factor for T2DM population.

Population-Based Clinical Studies Using Routinely Collected Data in Hong Kong, China: A Systematic Review of Trends and Established Local Practices

Background: Routinely collected health data are increasingly used in clinical research. No study has systematically reviewed the temporal trends in the number of publications and analyzed different aspects of local research practices and their variations in Hong Kong, China, with a specific focus on research ethics governance and approval.

Methods: PubMed was systematically searched from its inception to March 28, 2023, for studies using routinely collected healthcare data from Hong Kong.

Results: A total of 454 studies were included. Between 2000 and 2009, 32 studies were identified. The number of publications increased from 5 to 120 between 2010 and 2022. Of the investigator-led studies using the Hospital Authority (HA)’s cross-cluster data (n = 393), 327 (83.2%) reported receiving ethics approval from a single cluster/university-based REC, whereas 50 studies (12.7%) did not report approval from a REC. For use of the HA Data Collaboration Lab, approval by a single hospital-based or University-based REC is accepted. Repeated submission of identical ethics applications to different RECs is estimated to cost HK$4.2 million yearly.

Conclusions: Most studies reported gaining approval from a single cluster REC before retrieval of cross-cluster HA data. Substantial cost savings would result if repeated review of identical ethics applications were not required.

Joint effect of blood pressure and glycemic variation on the risk of cardiovascular morbidity and mortality in persons with type 2 diabetes

OBJECTIVE

Few studies have explored the association of visit-to-visit variation in blood pressure (BP) and glycemic factors with cardiovascular disease (CVD) morbidity and mortality. This study aimed to examine the independent and joint effect of visit-to-visit BP and glycemic variation on CVD morbidity and mortality in persons with T2DM.

METHODS

The present study consisted of two retrospective cohort studies. The Taiwan Diabetes Study was based on a database of the National Diabetes Care Management Program (DCMP) and linked with cardiovascular morbidity incidence. The Taichung Diabetes Study was based on the DCMP database of a medical center, which can be linked with the National Death Registry dataset. The outcomes were analyzed by using Cox's proportional hazard models.

RESULTS

A total of 13,280 and 10,894 persons with T2DM in Taiwan and Taichung Diabetes Study, respectively, were included. SBP-CV, FPG-CV, and HbA1c-CV were significant predictors of stroke, CVD event or death, all-cause mortality, and expanded CVD mortality, whereas DBP-CV was a significant predictor of all-cause mortality and expanded and non-expanded CVD mortality. The joint effect of SBP, FPG, and HbA1c predicted the incidence of stroke and CVD event or death with increased risks of 16 %-35 %. In addition, the joint effect of SBP, DBP, FPG, and HbA1c was associated with all-cause and expanded CVD mortality with increased risks of 29 %-81 %.

CONCLUSIONS

The joint effect of BP and glucose variation improved the prediction of cardiovascular morbidity and mortality. Moreover, simultaneous measurement of visit-to-visit BP and glycemic variation may stratify persons with cardiovascular risks and may be regarded as important therapeutic goals in the care of T2DM.

Visit-to-visit glycated hemoglobin A1c variability in adults with type 2 diabetes: a systematic review and meta-analysis

BACKGROUND

Current practice uses the latest measure of glycated hemoglobin (HbAlc) to facilitate clinical decision-making. Studies have demonstrated that HbAlc variability links the risk of death and complications of diabetes. However, the role of HbAlc variability is unclear in clinical practice. This systematic review summarized the evidence of visit-to-visit HbAlc variability regarding different metrics in micro- and macro-vascular complications and death in people with type 2 diabetes.

METHODS

We searched PubMed, EMBASE (via OVID), and Cochrane Central Register (CENTRAL, via OVID) for studies investigating the association between HbAlc variability and adverse outcomes in patients with type 2 diabetes and performed random-effects meta-analysis stratified by HbAlc variability metrics in terms of standard deviation (SD), coefficient of variation (CV), and HbAlc variability score (HVS).

RESULTS

In people with type 2 diabetes, the highest quantile of all three HbAlc variability metrics (HbAlc-standard deviation [HbAlc-SD], HbAlc-coefficient of variance [HbAlc-CV], and HVS) is associated with increased risks of all-cause mortality, cardiovascular events, progression to chronic kidney disease, amputation, and peripheral neuropathy. For example, the hazard ratio of HbAlc-SD on all-cause mortality was l.89 with 95% confidence interval (95% CI) l.46-2.45 (HbAlc-CV l.47, 95% CI l.26-l.72; HVS l.67, 95% CI l.34-2.09).

CONCLUSIONS

High HbAlc variability leads to micro- and macro-vascular complications of type 2 diabetes and related death. People with type 2 diabetes and high HbAlc variability need additional attention and care for the potential adverse outcomes.

Age and sex-specific associations of visit-to-visit variability of glycated hemoglobin A1c with all-cause mortality in patients with diabetes

BACKGROUND

Visit-to-visit variability (VVV) of glycated hemoglobin (HbA1c) levels have been found to be associated with prognosis of diabetes. However, little is known about whether or to what extent sex and age may modify the effects of VVV.

METHODS

To investigate age- and sex-specific rates of mortality from all causes and relative hazards of mortality in association with VVV of HbA1c levels, 47,145 patients with diabetes and prescription of any antidiabetic agents >6 months were identified from outpatient visits of a tertiary medical center in northern Taiwan during 2003-2018. VVV of HbA1c was measured by quartiles of standard deviation (SD), coefficient of variation (CV), and average real variability (ARV), respectively. The study subjects were linked to Taiwan's National Death Registry to identify all-cause mortality. The person-year approach with the Poisson assumption was used to assess the all-cause mortality rates, and Cox proportional hazard regression model was used to evaluate the relative hazards of all-cause mortality concerning various levels of VVV of HbA1c.

RESULTS

The lowest all-cause mortality rate was found in either the first or second quartile of various measures for VVV of HbA1c, but the highest mortality rate was consistently observed in the fourth quartile of VVV, regardless of SD, CV, or ARV across ages and sexes. Increased hazards of overall all-cause mortality were noticed from the second to fourth quartile of VVV of HbA1c. In detailed age- and sex-stratified analyses, elevated risk of mortality was seen in the fourth quartile of those aged <50 years while in those aged >69 years, increased risk of mortality was noticed in the third and fourth quartiles of any VVV of HbA1c irrespective of sex. In those aged 50-69 years, incremental increased hazards of mortality were consistently observed in the second to fourth quartiles of VVV of HbA1c.

CONCLUSION

HbA1c variability whether it was SD, CV, or ARV could strongly predict the risks of all-cause mortality. The extent of the relationship between VVV of HbA1c and all-cause mortality in different age groups was comparable between both sexes. Given the importance of long-term glucose fluctuation, the inclusion of HbA1c variability calculated from the standardized method should be considered by clinical guideline policymakers as part of the biochemical panel in daily diabetes management.

Enterocyte HKDC1 Modulates Intestinal Glucose Absorption in Male Mice Fed a High-fat Diet

Hexokinase domain containing protein-1, or HKDC1, is a widely expressed hexokinase that is genetically associated with elevated 2-hour gestational blood glucose levels during an oral glucose tolerance test, suggesting a role for HKDC1 in postprandial glucose regulation during pregnancy. Our earlier studies utilizing mice containing global HKDC1 knockdown, as well as hepatic HKDC1 overexpression and knockout, indicated that HKDC1 is important for whole-body glucose homeostasis in aging and pregnancy, through modulation of glucose tolerance, peripheral tissue glucose utilization, and hepatic energy storage. However, our knowledge of the precise role(s) of HKDC1 in regulating postprandial glucose homeostasis under normal and diabetic conditions is lacking. Since the intestine is the main entry portal for dietary glucose, here we have developed an intestine-specific HKDC1 knockout mouse model, HKDC1Int-/-, to determine the in vivo role of intestinal HKDC1 in regulating glucose homeostasis. While no overt glycemic phenotype was observed, aged HKDC1Int-/- mice fed a high-fat diet exhibited an increased glucose excursion following an oral glucose load compared with mice expressing intestinal HKDC1. This finding resulted from glucose entry via the intestinal epithelium and is not due to differences in insulin levels, enterocyte glucose utilization, or reduction in peripheral skeletal muscle glucose uptake. Assessment of intestinal glucose transporters in high-fat diet-fed HKDC1Int-/- mice suggested increased apical GLUT2 expression in the fasting state. Taken together, our results indicate that intestinal HKDC1 contributes to the modulation of postprandial dietary glucose transport across the intestinal epithelium under conditions of enhanced metabolic stress, such as high-fat diet.

A guide for the use of LibreView digital diabetes platform in clinical practice: Expert paper of the Italian Working Group on Diabetes and Technology

Wider access to continuous glucose monitoring systems, including flash glucose monitoring, has enabled people with diabetes to achieve lower HbA1c levels and reduce the amount of time they spend in hypoglycaemia or hyperglycaemia, and has improved their quality of life. An International Consensus Panel proposed different target glucose ranges and recommendations according to different ages and situations (adults, young people and children with type 1 or type 2 diabetes, as well as elderly people who are at higher risk of hypoglycaemia, and women with diabetes during pregnancy). In this expert opinion, we interpret the international recommendations in the context of established clinical practice for diabetes care, and propose three different step-by-step algorithms to help the healthcare professionals use the most innovative glucose metrics, including time in glucose ranges, glucose management indicator, coefficient of variation, and ambulatory glucose profile. In detail, we focus on glucose metrics as measured by the FreeStyle Libre system and as visualized on the LibreView digital diabetes platform to support appropriate interpretation of flash glucose monitoring data. This is specifically structured for healthcare professionals and general practitioners who may have a low level of confidence with diabetes technology, with the aim of optimizing diabetes management, ensuring effective use of healthcare resources and to maximise outcomes for people with diabetes.

The Scope of HbA1c Variability and Risk of Vascular Complications Among Patients with Type 2 Diabetes: A Systematic Review and Meta-Analysis of Prospective Studies

Glycated hemoglobin (HbA1c) variability is emerging as an indicator of long-term glycemic control, which may play a significant role during vascular complications. We conducted a systematic review and meta-analysis to assess the association between the scope of HbA1c variability and vascular complications in patients with type 2 diabetes mellitus. PubMed and Embase were searched for studies that evaluated the association of HbA1c variability with vascular complications in patients with type 2 diabetes. Two reviewers independently completed data extraction. Random-effects meta-analysis was conducted with stratification according to the type of vascular complications. Nine studies were eligible for inclusion in our systematic review and meta-analysis. Six studies evaluated the impact of the standard deviation of HbA1c (HbA1c-SD) on cardiovascular events and showed an association of HbA1c-SD with cardiovascular events (HR: 1.25, 95% CI 1.18-1.32, 5 studies). Six studies evaluated renal disease associated with HbA1c-SD and showed that HbA1c-SD was correlated with an increased risk of renal disease (HR: 1.19, 95% CI 1.13-1.24). Two studies evaluated HbA1c-SD and the risk of retinopathy and showed that no significant association was found between retinopathy and HbA1c-SD (HR 1.08, 95% CI 0.92-125). For HbA1c-SD ranging from 0.6 to 0.8%, HbA1c-SD was associated with an increased risk of cardiovascular events (HR: 1.25, 95% CI 1.15-1.35) and renal disease (HR: 1.16, 95% CI 1.11-1.22). For individuals with index HbA1c variability greater than or equal to 0.6%, HbA1c variability was significantly associated with vascular complications in patients with type 2 diabetes mellitus.

Utilizing the New Glucometrics: A Practical Guide to Ambulatory Glucose Profile Interpretation

Traditional continuous glucose monitoring and flash glucose monitoring systems are proven to lower glycated haemoglobin levels, decrease the time and impact of hypoglycaemia or hyperglycaemia and, consequently, improve the quality of life for children and adults with type 1 diabetes mellitus (T1DM) and adults with type 2 diabetes mellitus (T2DM). These glucose-sensing devices can generate large amounts of glucose data that can be used to define a detailed glycaemic profile for each user, which can be compared with targets for glucose control set by an International Consensus Panel of diabetes experts. Targets have been agreed upon for adults, children and adolescents with T1DM and adults with T2DM; separate targets have been agreed upon for older adults with diabetes, who are at higher risk of hypoglycaemia, and women with pregestational T1DM during pregnancy. Along with the objective measures and targets identified by the International Consensus Panel, the dense glucose data delivered by traditional continuous glucose monitoring and flash glucose monitoring systems is used to generate an ambulatory glucose profile, which summarizes the data in a visually impactful format that can be used to identify patterns and trends in daily glucose control, including those that raise clinical concerns. In this article, we provide a practical guide on how to interpret these new glucometrics using a straightforward algorithm, and clear visual examples that demystify the process of reviewing the glycaemic health of people with T1DM or T2DM such that forward-looking goals for diabetes management can be agreed.

Association Between Long-Term Visit-to-Visit Hemoglobin A1c and Cardiovascular Risk in Type 2 Diabetes: The ACCORD Trial

Background: To explore the association between visit-to-visit variability of glycated hemoglobin (HbA1c) and cardiovascular outcomes in the patients with type 2 diabetes mellitus (T2DM) of the Action to Control Cardiovascular Risk in Diabetes (ACCORD) study.

Methods: We conducted a post-hoc analysis on the ACCORD population including 9,544 participants with T2DM. Visit-to-visit variability of HbA1c was defined as the individual SD, coefficient of variation (CV), and variability independent of the mean (VIM) across HbA1c measurements. The clinical measurements included primary outcome [the first occurrence of non-fatal myocardial infarction (MI), non-fatal stroke or cardiovascular death], total mortality, cardiovascular death, non-fatal MI event, non-fatal stroke, total stroke, heart failure, macrovascular events, and major coronary events (CHD).

Results: Over a median follow-up of 4.85 years, 594 and 268 participants experienced all-cause mortality and cardiovascular mortality, respectively. After adjusting for baseline HbA1c levels and confounding factors, the adjusted hazard ratio (HR) comparing patients in the highest vs. the lowest quartile CV of HbA1c variability was 1.61 (95% CI 1.29–2.00) for the primary outcome. Similar trends for secondary outcome were also observed. There was no association between HbA1c fluctuation and non-fatal stroke. Noticeably, there was 66% greater risk for the all-cause mortality among patients in the highest vs. the lowest quartile (HR 1.66, 95% CI 1.27–2.17).

Conclusions: Greater variability of HbA1c is associated with higher risk for cardiovascular complications and all-cause death in T2DM. Our study stresses the significance of well-controlled glycemic levels for improving cardiovascular outcomes. Further randomized clinical trials are required to confirm these findings.

HbA1C variability among type 2 diabetic patients: a retrospective cohort study

BACKGROUND

Studies have found that HbA1C variability is an independent risk factor for diabetic complications in type 2 diabetic patients. This study aims to find factors contributing to higher HbA1C variability in the community.

METHODS

The study was conducted in the southern district of Israel, in Clalit Health Services (CHS). The study population was type 2 diabetic individuals aged 40-70 years in 2005, with a follow-up period of 11 years, until 2015. The definition of HbA1C variability was done by the standard deviation from the average HbA1C value of the entire study period, which was calculated for each participant. The study population was divided into two groups, "variability group" with HbA1C SD > 1.2, and "comparison group" of participants with HbA1C SD ≤ 1.2. In the univariate analysis we used X² or Fisher test for categorical variables and independent t-test for numeric continuous variables. In the multivariate analysis we used logistic regression as well as assessing for possible interactions. Statistical analysis was ascribed for p < 0.05. All the data was drawn from the computerized medical system used by all primary care physicians and nurses in CHS working in the community.

RESULTS

The study population included 2866 participants, the average age was 58.6 years, 43.3% men and 56.7% women. Each participant had an average of 20.9 HbA1C measures in their computerized medical record during the 11 years of follow up. The mean HbA1C value was 7.8%. We found 632 patients (22%) with a high variability, whereas 2234 (78%) had a low variability of HbA1C. In the "variability group" there was a higher percentage of smokers, BMI ≥ 30 and a higher rate of visits to diabetic clinics compared to the "no variability" group. In the "variability group" we found a much higher use of insulin and ACE inhibitors. The highest frequency of variability was between HbA1c values of 8.1-8.5. The multivariate analysis showed that HbA1C variability was associated with insulin use (OR = 4.1, p < 0.001), with age (OR = 0.939, p < 0.001), and Ischemic heart disease (OR = 1.258, p = 0.03). BMI ≥ 30 was almost statistically significant (OR = 1.206, p = 0.063). Gender was statistically insignificant.

CONCLUSIONS

In conclusion, HbA1C variability might be used as an additional marker in Diabetes Mellitus type 2, reflecting the disease complexity characteristics and the patient's lifestyle profile.

Habitual Miso (Fermented Soybean Paste) Consumption Is Associated with Glycemic Variability in Patients with Type 2 Diabetes: A Cross-Sectional Study

Glycemic control, including glycemic variability, is important for the prevention of diabetic vascular complications in patients with type 2 diabetes mellitus (T2DM). There was an association between miso soup intake and insulin resistance. However, the relationship between habitual miso consumption and glycemic control, including glycemic variability, in patients with T2DM remains unknown. We defined people without habitual miso consumption if they did not consume miso soup at all in a day. The average, standard deviation (SD), and coefficient of variation (CV), calculated as CV = (SD/average HbA1c) × 100 (%), of hemoglobin (Hb) A1c levels were evaluated. The proportions of habitual miso consumption of male and female were 88.1% and 82.3%, respectively. The average (7.0 [6.4-7.5] vs. 7.3 [6.8-8.4] %, p = 0.009), SD (0.21 [0.12-0.32] vs. 0.37 [0.20-0.72], p = 0.004), and CV (0.03 [0.02-0.04] vs. 0.05 [0.03-0.09], p = 0.005) of HbA1c levels in female with habitual miso consumption were lower than those of female without. Moreover, habitual miso consumption correlated with average (β = -0.251, p = 0.009), SD (β = -0.175, p = 0.016), and CV (β = -0.185, p = 0.022) of HbA1c levels after adjusting for covariates. However, no association between habitual miso consumption and any glycemic parameters was shown among male. This study clarified the association between habitual miso consumption and good glycemic control, including glycemic variability, in female, but not in male.

The Frequency and Determinants of HbA1c Variability in Type 2 Diabetic Patients

Aim: Glycated hemoglobin (HbA1c) is an efficient and easy test to evaluate glycemic control of patients with type 2 diabetes (T2DM). This study aims to evaluate HbA1c variability and associated factors in patients with T2DM. Methods: Four hundred four consecutive patients with T2DM who gave consent to participate and who were eligible were included. The inclusion criterion was presence of three or more HbA1c levels in 1 year. A change ≥0.5% in HbA1c was identified as a significant variability in HbA1c in 1 year. Primary endpoint of the study was to identify the factors associated with HbA1c variability. Patients were grouped as (1) without variability, (2) one variability, and (3) more than one variability. Variability frequency and associated factors such as body mass index, smoking, and c-peptide value were assessed. Results: There were 404 patients (45.3% male) with mean age 58.91 ± 10.8 years. Thirty-four patients (8.4%) had no variability, 19 patients (4.7%) had one variability, and 351 patients (86.9%) had more than one variability. Patients only on insulin treatment and patients on both oral antidiabetic agents (OAD) and insulin had higher variability than patients only on OAD (P = 0.002; P < 0.01). Patients with variability had higher HbA1c levels than patients without variability (P < 0.01). A 1% increase in HbA1c had a 4.864-fold (95% confidence interval: 2.360-10.023) increased variability risk. Conclusions: HbA1c variability is seen in 9 of 10 patients with T2DM and higher HbA1c values and poor glycemic control are associated with a higher risk of HbA1c variability.

The Effect of Physical Activity on Glycemic Variability in Patients With Diabetes: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

PURPOSE

The effect of physical activity on glycemic variability remains controversial. This meta-analysis aimed to assess the overall effect of physical activity treatment on glycemic variability in patients with diabetes.

METHODS

PubMed/MEDLINE, Embase, and Cochrane databases were searched for clinical trials that conducted in patients with type 1 diabetes mellitus and type 2 diabetes mellitus with reports of the mean amplitude of glycemic excursion (MAGE), time in range (TIR), time above range (TAR), or time below range (TBR). Eligible trials were analyzed by fixed-effect model, random effect model, and meta-regression analysis accordingly.

RESULTS

In total, thirteen trials were included. Compared with the control group, physical activity intervention was significantly associated with increased TIR (WMDs, 4.17%; 95% CI, 1.11 to 7.23%, P<0.01), decreased MAGE (WMDs, -0.68 mmol/L; 95% CI, -1.01 to -0.36 mmol/L, P<0.01) and decreased TAR (WMDs, -3.54%; 95% CI, -5.21 to -1.88%, P<0.01) in patients with diabetes, but showed insignificant effects on TBR. Patients with higher baseline BMI levels was associated with a greater decrease in MAGE (β=-0.392, 95% CI: -0.710, -0.074), and patients with lower baseline HbA1c levels was associated with a greater increase in TBR during physical activities (β=-0.903, 95% CI: -1.550, -0.255).

CONCLUSION

Physical activity was associated with significantly decreased glycemic variability in patients with diabetes. Patients with higher BMI might benefit more from physical activity therapy in terms of a lower MAGE. Hypoglycemia associated with physical activity treatment still warranted caution, especially in patients with intensive glycemic control.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO [CRD42021259807].

Long-Term Glycemic Variability and Vascular Complications in Type 2 Diabetes: Post Hoc Analysis of the FIELD Study

AIMS

To investigate whether long-term glycemic variability (GV) is associated with vascular complication development in type 2 diabetes.

METHODS

In a post hoc FIELD trial analysis, GV was calculated as the standard deviation and coefficient of variation (CV) of glycated hemoglobin A1c (HbA1c) and fasting plasma glucose. Baseline variables were compared across quartiles of on-study variability by chi square and ANOVA. Prospective associations between baseline to 2-year GV and subsequent vascular and mortality outcomes were analyzed using landmark logistic and Cox proportional hazards regression.

RESULTS

Baseline factors associated with higher on-study GV included younger age, male gender, longer diabetes duration, and higher pharmacological therapies usage. Both HbA1c and fasting glucose CV were associated with increased risk of microvascular complications (HR 1.02 [95% CI, 1.01-1.03] P < 0.01; and HR 1.01 [95% CI, 1.00-1.01] P < 0.001, respectively). HbA1c and fasting glucose CV were associated with increased cardiovascular disease (HR 1.02 [95% CI, 1.00-1.04]; and HR 1.01 [95% CI, 1.00-1.02], both P < 0.05). HbA1c CV associated with increased stroke (HR 1.03 [95% CI, 1.01-1.06) P < 0.01). Glucose CV associated with increased coronary events (HR 1.01 [95% CI, 1.00-1.02] P < 0.05). Both HbA1c and glucose CV associated with increased total mortality (HR 1.04 [95% CI, 1.02-1.06]; and HR 1.01 [95% CI, 1.01-1.02], both P < 0.001) and noncardiovascular mortality (HR 1.05 [95% CI, (1.03-1.07]; and HR 1.02 [95% CI, 1.01-1.03], both P < 0.001). HbA1c CV associated with coronary mortality (HR 1.04 [95% CI, 1.01-1.07] P < 0.05).

CONCLUSIONS

Long-term GV was associated with increased risk of vascular outcomes in type 2 diabetes.

Impact of long-term glucose variability on coronary atherosclerosis progression in patients with type 2 diabetes: a 2.3 year follow-up study

Background

Glycemic variability (GV) confers a risk of cardiovascular events. In this study, we aimed to investigate whether long-term GV has an impact on coronary atherosclerosis progression in patients with type 2 diabetes mellitus (T2DM).

Methods

A total of 396 patients with T2DM who had coronary computed tomography angiography and laboratory data available at baseline and for follow-up evaluations [median 2.3 (1.8–3.1) years] were included. Fasting plasma glucose (FPG) was measured every 1–3 months, and HbA1c was measured quarterly. The coefficient of variation (CV) of HbA1c and FPG were calculated as measures of GV. Quantitative assessment of coronary plaques was performed by measuring the annual change and progression rate of total plaque volume (TPV). Significant progression was defined as annual TPV progression ≥ 15%. Multivariable regression analyses were used to assess the effects of GV on atherosclerosis progression.

Results

In the 396 patients, the annual change in TPV was 12.35 ± 14.23 mm³, and annual progression rate was 13.36 ± 12.69%. There were 143 (36.11%) patients with significant progression, and they had a significantly higher CV-HbA1c (P < 0.001) and CV-FPG (P < 0.001) than those without significant progression. In multivariable regression analyses, both CV-HbA1c and CV-FPG were independent predictors of annual change in TPV [CV-HbA1c: β = 0.241 (0.019–0.462), P = 0.034; CV-FPG_: β = 0.265 (0.060–0.465), P = 0.012], annual TPV progression [CV-HbA1c: β = 0.214 (0.023–0.405), P = 0.029; CV-FPG_: β = 0.218 (0.037–0.399), P = 0.019], and significant atherosclerosis progression [CV-HbA1c: odds ratio [OR] = 1.367 (1.149–1.650), P = 0.010; CV-FPG_: OR = 1.321 (1.127–1.634), P = 0.013].

Conclusions

Long-term GV is associated with accelerated progression of coronary atherosclerosis independent of conventional risk factors in patients with T2DM.

Trial registration ClinicalTrials.gov (NCT02587741), October 27, 2015; retrospectively registered

Prediction models for the risk of cardiovascular diseases in Chinese patients with type 2 diabetes mellitus: a systematic review

OBJECTIVES

Diabetes mellitus (DM) is a serious public health issue worldwide, and DM patients have higher risk of cardiovascular diseases (CVDs), which is the leading cause of DM-related deaths. China has the largest DM population, yet a robust model to predict CVDs in Chinese DM patients is still lacking. This systematic review is carried out to summarize existing models and identify potentially important predictors for CVDs in Chinese DM patients.

STUDY DESIGN

Systematic review.

METHODS

Medline and Embase were searched for data from April 1st, 2011 to May 31st, 2018. A study was eligible if it developed CVD (defined as total CVD or any major cardiovascular component) risk prediction models or explored potential predictors of CVD specifically for Chinese people with type 2 DM. Standardized forms were utilized to extract information, appraise applicability, risk of bias, and availabilities.

RESULTS

Five models and 29 studies focusing on potential predictors were identified. Models for a primary care setting, or to predict total CVD, are rare. A number of common predictors (e.g. age, sex, diabetes duration, smoking status, glycated hemoglobin (HbA1c), blood pressure, lipid profile, and treatment modalities) were observed in existing models, in which urine albumin:creatinine ratio (ACR) and estimated glomerular filtration rate (eGFR) are highly recommended for the Chinese population. Variability of blood pressure (BP) and HbA1c should be included in prediction model development as novel factors. Meanwhile, interactions between age, sex, and risk factors should also be considered.

CONCLUSIONS

A 10-year prediction model for CVD risk in Chinese type 2 DM patients is lacking and urgently needed. There is insufficient evidence to support the inclusion of other novel predictors in CVDs risk prediction functions for routine clinical use.

Age-specific associations of glycated haemoglobin variability with cardiovascular disease and mortality in patients with type 2 diabetes mellitus: A 10- year cohort study

AIMS

To investigate the associations of increased variability in glycated haemoglobin (HbA1c) with cardiovascular disease (CVD) and mortality risk in patients with diabetes.

MATERIALS AND METHODS

This prospective cohort study included 147 811 patients aged 45 to 84 years with type 2 diabetes mellitus, without CVD and with at least three HbA1c values recorded before baseline in the period 2008 to 2010. HbA1c variability was evaluated using a mixed effects model to reduce regression dilution bias. Age-specific associations (45- 54, 55- 64, 65- 74 and 75- 84 years) between HbA1c variability and risk of CVD and mortality were assessed by Cox regression, adjusted for patient characteristics and usual HbA1c.

RESULTS

After a median follow-up of 7.4 years(1.02 million person-years), an overall incidence of 40 785 events including CVD (incidence 27  793) and all-cause mortalities (incidence 23 175) were identified. Positive log-linear associations between HbA1c variability and CVD and mortality were identified in all age groups. The hazard ratios (HRs) for the composite of CVD and all-cause mortality showed that age was inversely associated with HbA1c variability, with a 28% higher risk per 1% increase in HbA1c variability in the age group 45 to 54 years (all composite outcomes: HR 1.28, 95% confidence interval [CI] 1.21, 1.35), whereas only a 14% higher risk in the 75- 84 age group (all composite outcomes: HR 1.14, 95% CI 1.11, 1.17). Subgroup analysis showed the risk in patients with usual HbA1c <53mmol/mol was about eight times higher than in those with usual HbA1c ≥64mmol/mol.

CONCLUSIONS

HbA1c variability was strongly related to CVD and mortality in patients with diabetes across all age groups. Whilst pursuing optimal HbA1c targets, attention should be given to patients with high HbA1c variability, especially younger patients with good HbA1c control.

Clinical Recommendations for the Use of the Ambulatory Glucose Profile in Diabetes Care

BACKGROUND

The ambulatory glucose profile (AGP) uses the wealth of data that are generated by continuous glucose monitoring, including flash glucose monitoring technologies, to provide a visual representation of glucose levels over a typical standard day of usually the most recent two weeks for a person with diabetes and helps to identify patterns and trends in glucose control. The AGP allows certain patterns of glucose levels to be identified and analyzed, such that treatment adjustments can be made, and new individual treatment goals can be defined. This helps to ensure increased treatment satisfaction and adherence, quality of life, and an improvement in metabolic management for people with diabetes.

OBJECTIVE

To date, a range of approaches exists for interpreting the information contained in an AGP, with different priorities given to identifying and targeting patterns of hypoglycemia and the degree of variability and stability underlying the glucose levels. The objective of the present recommendation is to describe the steps for assessing an AGP in detail and to illustrate these steps using visual examples.

CONCLUSION

This paper describes the consensus recommendations from a group of German expert diabetologists on the necessary steps for assessing an AGP in a structured and detailed way and to explain these steps using practical clinical examples.

Living alone is associated with visit-to-visit HbA1c variability in men but not in women in people with type 2 diabetes: KAMOGAWA-DM cohort study

The purpose of this study was to evaluate the association between living alone and glycemic parameters, especially glycemic variability, in men and women with type 2 diabetes. Lifestyle factors, including living alone, were assessed by a questionnaire in this cross-sectional study. Average, standard deviation (SD), and coefficient of variation (CV) of HbA1c were calculated using the values of HbA1c, which were extracted from the medical record for 1 year. Eighteen percent of men (35/198) and 17% of women (18/103) were living alone. In men, the average of HbA1c (59.9 mmol/mol [11.0] vs. 55.7 mmol/mol [9.1], 7.6% [1.0] vs. 7.2% [0.8], p = 0.018), and CV of HbA1c (0.06 [0.03-0.08] vs. 0.03 [0.02-0.05], p < 0.001) were all significantly higher in men who were living alone than in men who weren't. However, there were no differences in the average (53.2 mmol/mol [11.4] vs. 56.0 mmol/mol [8.8], 7.0% [1.0] vs. 7.3% [0.8], p = 0.252) or CV (0.03 [0.02-0.05] vs. 0.03 [0.02-0.04], p = 0.845) between women who were living alone and women who weren't. Multiple regression analyses revealed that living alone was associated with CV of HbA1c after adjusting for covariates in men (β = 0.180, p = 0.005), but not in women (β = 0.085, p = 0.369). We showed that living alone is associated with visit-to-visit HbA1c variability in men, but not women, with type 2 diabetes. In clinical practice, it is necessary to pay attention to glycemic control in men who are living alone.

Effect of mean HbA1c on the association of HbA1c variability and all-cause mortality in patients with type 2 diabetes

AIM

To evaluate the effect of mean HbA1c on the correlation between HbA1c variability and all-cause mortality, and the risks associated with different levels of HbA1c and glycaemic control status in patients with type 2 diabetes.

MATERIALS AND METHODS

Patients with type 2 diabetes and at least three HbA1c measurements within 12-24 months were included. HbA1c variability score, coefficient of variation (CV) and standard deviation (SD) were used to evaluate variability. A variability score of 50 was set as a cutoff to define low and high variability.

RESULTS

A total of 4216 patients were included, of whom 1196 died during the observation period (11.1 ± 3.2 years). All-cause mortality increased with HbA1c variability score and the quartiles of HbA1c CV and SD. The strength of this association was attenuated after adjustment for mean HbA1c, and the risks associated with HbA1c variability and glycaemic control status were similar. The highest associated risk was observed with an HbA1c variability score of >50 and mean HbA1c of ≥7.5%. Mortality risk was significantly higher with a mean HbA1c of ≤6.0% and >8.5% and of ≤6.0% and >8.0% for low and high HbA1c variability, respectively.

CONCLUSIONS

Mean HbA1c contributed to the correlation between HbA1c variability and all-cause mortality. The risks associated with HbA1c variability and glycaemic control status were similar. The relationship between mean HbA1c and mortality presented a J-shaped distribution for both low and high HbA1c variability.

Association between visit-to-visit variability of HbA1c and cognitive decline: a pooled analysis of two prospective population-based cohorts

AIMS/HYPOTHESIS

The aim of this study was to investigate the association between visit-to-visit variability in HbA1c and cognitive function decline in the elderly population.

METHODS

We performed a pooled analysis of two prospective population-based cohorts (the Health Retirement Study [HRS] and the English Longitudinal Study of Ageing [ELSA]). Cognitive function, including memory and executive function, were assessed at baseline and every 2 years, while HbA1c levels were assessed at baseline and every 4 years. Visit-to-visit variability (VVV) in HbA1c was calculated using the CV, SD and variation independent of the mean (VIM) during the follow-up period. Linear mixed models were used to evaluate the association between HbA1c variability and cognitive function decline with adjustment for demographics, mean HbA1c, education, smoking, alcohol consumption, BMI, baseline hypertension, baseline diabetes status and HDL-cholesterol.

RESULTS

The study enrolled 6237 participants (58.23% women, mean age 63.38 ± 8.62 years) with at least three measurements of HbA1c. The median follow-up duration was 10.56 ± 1.86 years. In the overall sample, compared with the lowest quartile of HbA1c variability, participants in the highest quartile of HbA1c variability had a significantly worse memory decline rate (-0.094 SD/year, 95% CI -0.185, -0.003) and executive function decline rate (-0.083 SD/year, 95% CI -0.125, -0.041), irrespective of mean HbA1c values over time. Among individuals without diabetes, each 1-SD increment in HbA1c CV was associated with a significantly higher rate of memory z score decline (-0.029, 95% CI -0.052, -0.005) and executive function z score decline (-0.049, 95% CI -0.079, -0.018) in the fully adjusted model.

CONCLUSIONS/INTERPRETATION

We observed a significant association between long-term HbA1c variability and cognitive decline among the non-diabetic population in this study. The effect of maintaining steady glucose control on the rate of cognitive decline merits further investigation.

Impact of HbA1c variability on subclinical left ventricular remodeling and dysfunction in patients with type 2 diabetes mellitus

BACKGROUND

Glycemic instability confers a risk of poor prognosis in patients with type 2 diabetes mellitus (T2DM). This study aimed to investigate whether HbA1c variability provided additional value over mean HbA1c for predicting subclinical left ventricular remodeling and dysfunction in T2DM patients.

METHODS

A total of 466 T2DM patients with normal cardiac structure and function were recruited and prospectively followed up for a median of 4.7 y. HbA1c was measured quarterly. The intrapersonal mean and standard deviation (SD) of HbA1c measurements were calculated, and SD-HbA1c was considered as a measure of HbA1c variability. All participants underwent transthoracic echocardiography at baseline and after follow-up.

RESULTS

In multivariable regression analyses, SD-HbA1c was independently associated with annualized changes in left ventricular end diastolic diameter, interventricular septum, left ventricular posterior wall, left ventricular mass index, left ventricular ejection fraction, E/e' ratio, and E/A ratio (P < 0.001). Subgroup analysis based on mean HbA1c levels (<7.0%, 7.0-7.5%, and ≥7.5%) further confirmed that SD-HbA1c was associated with most of the above parameters regardless of mean HbA1c levels.

CONCLUSION

This study indicates that HbA1c variability adds to the mean value in predicting subclinical left ventricular remodeling and dysfunction in T2DM patients.

Variability in Glycated Hemoglobin and Risk of Poor Outcomes Among People With Type 2 Diabetes in a Large Primary Care Cohort Study

OBJECTIVE

Diabetes guidelines focus on target glycated hemoglobin (HbA_1c) levels. Long-term variability in HbA_1c may be predictive of hospitalization or mortality, but its importance at different average levels or trajectories is unclear.

RESEARCH DESIGN AND METHODS

Using English primary care data, 58,832 patients with type 2 diabetes had HbA_1c average (mean of annual means), variability (coefficient of variation), and trajectory (annual regression slope) estimated during 2006-2009. Hazard ratios (HRs) for mortality and emergency hospitalization during 2010-2015, with adjustment for age, sex, smoking, BMI, duration of diabetes, and deprivation, were estimated using Cox regression. The simultaneous impact of HbA_1c average, variability, and trajectory was estimated using percentiles.

RESULTS

In mutually adjusted models, HbA_1c variability showed a consistent dose-response relationship with all-cause mortality, while average level was only important among individuals in the highest or lowest 10% of the distribution, and trajectory had no independent effect. Individuals with the most unstable HbA_1c (top 10%) were almost twice as likely to die (HR 1.93 [95% CI 1.72-2.16]) than were those with the most stable (bottom 10%)-an association attenuated but not explained by hypoglycemia. For emergency hospitalizations, similar trends were seen except for coronary artery disease (CAD) and ischemic stroke (IS), where increasing average rather than variability was predictive.

CONCLUSIONS

HbA_1c variability was strongly associated with overall mortality and emergency hospitalization and not explained by average HbA_1c or hypoglycemic episodes. Only for CAD and IS hospitalizations was no association found, with average HbA_1c strongly predictive. Targets should focus on both stability and absolute level of HbA_1c.

Diabetes Mellitus and Cause-Specific Mortality: A Population-Based Study

BACKGROUND

To investigate whether diabetes contributes to mortality for major types of diseases.

METHODS

Six National Health and Nutrition Examination Survey data cycles (1999 to 2000, 2001 to 2002, 2003 to 2004, 2005 to 2006, 2007 to 2008, and 2009 to 2010) and their linked mortality files were used. A population of 15,513 participants was included according to the availability of diabetes and mortality status.

RESULTS

Participants with diabetes tended to have higher all-cause mortality and mortality due to cardiovascular disease, cancer, chronic lower respiratory diseases, cerebrovascular disease, influenza and pneumonia, and kidney disease. Confounder-adjusted Cox proportional hazard models showed that both diagnosed diabetes category (yes or no) and diabetes status (diabetes, prediabetes, or no diabetes) were associated with all-cause mortality and with mortality due to cardiovascular disease, chronic lower respiratory diseases, influenza and pneumonia, and kidney disease. No associations were found for cancer-, accidents-, or Alzheimer's disease-related mortality.

CONCLUSION

The current study's findings provide epidemiological evidence that diagnosed diabetes at the baseline is associated with increased mortality risk due to cardiovascular disease, chronic lower respiratory diseases, influenza and pneumonia, and kidney disease, but not with cancer or Alzheimer's disease.

Impact of long-term glycemic variability on development of atrial fibrillation in type 2 diabetic patients

OBJECTIVE

It is well known that patients with type 2 diabetes mellitus (T2DM) have a high risk of atrial fibrillation (AF). The current study was designed to determine the relationship between long-term glycemic variability and incidence of new-onset AF in T2DM patients.

METHODS

Between January 2008 and December 2009, we conducted a retrospective cohort study in patients with T2DM referred to our hospital. In 505 consecutive patients without any medical history of AF at baseline, the relationship between hemoglobin A1c (HbA1c) variability and future AF incidence was evaluated, with adjustments for other possible confounding factors. HbA1c variability was determined by standard deviation (SD) and coefficient of variation (CV).

RESULTS

Over a median of 6.9-year follow-up period, 48 patients (9.5%) developed incident AF. Multiple cox regression revealed that higher HbA1c-SD (HR: 1.726, 95% CI: 1.104-1.830, p=0.001) or HbA1c-CV (HR: 1.241, 95% CI: 1.029-1.497, p=0.024) remained the remarkable predictor of new-onset AF after adjusting for age, body mass index, left ventricular mass index, and left atrium diameter. Receiver operating curve analysis identified thresholds for HbA1c-SD (0.665%, sensitivity 71.4%, specificity 54.9%) and HbA1c-CV (8.970%, sensitivity 73.8%, specificity 47.1%) to detect new-onset AF development.

CONCLUSION

In patients with T2DM, higher HbA1c variability is significantly associated with future AF development.

What to do with diabetes therapies when HbA1c lowering is inadequate: add, switch, or continue? A MASTERMIND study

BACKGROUND

It is unclear what to do when people with type 2 diabetes have had no or a limited glycemic response to a recently introduced medication. Intra-individual HbA1c variability can obscure true response. Some guidelines suggest stopping apparently ineffective therapy, but no studies have addressed this issue.

METHODS

In a retrospective cohort analysis using the UK Clinical Practice Research Datalink (CPRD), we assessed the outcome of 55,530 patients with type 2 diabetes starting their second or third non-insulin glucose-lowering medication, with a baseline HbA1c > 58 mmol/mol (7.5%). For those with no HbA1c improvement or a limited response at 6 months (HbA1c fall < 5.5 mmol/mol [0.5%]), we compared HbA1c 12 months later in those who continued their treatment unchanged, switched to new treatment, or added new treatment.

RESULTS

An increase or a limited reduction in HbA1c was common, occurring in 21.9% (12,168/55,230), who had a mean HbA1c increase of 2.5 mmol/mol (0.2%). After this limited response, continuing therapy was more frequent (n = 9308; 74%) than switching (n = 1177; 9%) or adding (n = 2163; 17%). Twelve months later, in those who switched medication, HbA1c fell (- 6.8 mmol/mol [- 0.6%], 95%CI - 7.7, - 6.0) only slightly more than those who continued unchanged (- 5.1 mmol/mol [- 0.5%], 95%CI - 5.5, - 4.8). Adding another new therapy was associated with a substantially better reduction (- 12.4 mmol/mol [- 1.1%], 95%CI - 13.1, - 11.7). Propensity score-matched subgroups demonstrated similar results.

CONCLUSIONS

Where glucose-lowering therapy does not appear effective on initial HbA1c testing, changing agents does not improve glycemic control. The initial agent should be continued with another therapy added.

Glycaemic variability in diabetes: clinical and therapeutic implications

Glycaemic variability is an integral component of glucose homoeostasis. Although it has not yet been definitively confirmed as an independent risk factor for diabetes complications, glycaemic variability can represent the presence of excess glycaemic excursions and, consequently, the risk of hyperglycaemia or hypoglycaemia. Glycaemic variability is currently defined by a large and increasing number of metrics, representing either short-term (within-day and between-day variability) or long-term glycaemic variability, which is usually based on serial measurements of HbA_1c or other measures of glycaemia over a longer period of time. In this Review, we discuss recent evidence examining the association between glycaemic variability and diabetes-related complications, as well as non-pharmacological and pharmacological strategies currently available to address this challenging aspect of diabetes management.

Ten-year risk prediction models of complications and mortality of Chinese patients with diabetes mellitus in primary care in Hong Kong: a study protocol

INTRODUCTION

Diabetes mellitus (DM) is a major disease burden worldwide because it is associated with disabling and lethal complications. DM complication risk assessment and stratification is key to cost-effective management and tertiary prevention for patients with diabetes in primary care. Existing risk prediction functions were found to be inaccurate in Chinese patients with diabetes in primary care. This study aims to develop 10-year risk prediction models for total cardiovascular diseases (CVD) and all-cause mortality among Chinese patients with DM in primary care.

METHODS AND ANALYSIS

A 10-year cohort study on a population-based primary care cohort of Chinese patients with diabetes, who were receiving care in the Hospital Authority General Outpatient Clinic on or before 1 January 2008, were identified from the clinical management system database of the Hospital Authority. All patients with complete baseline risk factors will be included and followed from 1 January 2008 to 31 December 2017 for the development and validation of prediction models. The analyses will be carried out separately for men and women. Two-thirds of subjects will be randomly selected as the training sample for model development. Cox regressions will be used to develop 10-year risk prediction models of total CVD and all-cause mortality. The validity of models will be tested on the remaining one-third of subjects by Harrell's C-statistics and calibration plot. Risk prediction models for diabetic complications specific to Chinese patients in primary care will enable accurate risk stratification, prioritisation of resources and more cost-effective interventions for patients with DM in primary care.

ETHICS AND DISSEMINATION

The study was approved by the Institutional Review Board of the University of Hong Kong-the Hospital Authority Hong Kong West Cluster (reference number: UW 15-258).

TRIAL REGISTRATION NUMBER

NCT03299010; Pre-results.

Type 2 Diabetes and Glycemic Variability: Various Parameters in Clinical Practice

It has become possible to measure blood glucose levels continuously from 24 h to approximately 2 weeks due to the recent development of relevant devices such as continuous glucose monitoring and flash glucose monitoring systems. This has enabled not only medical professionals but also patients to monitor details of glycemic variability (GV) which was not possible in the past. Details of GV for both short and intermediate periods can now be obtained, and it is important in patient care to appropriately evaluate the data obtained. Types of GV in terms of time frame vary from short-term to long-term. Several studies reported that long-term GV was related to micro- and macro-angiopathies in patients with type 2 diabetes mellitus (T2DM). However, there are still unknown aspects regarding the relationships of various durations of GV with prognosis. Further clinical trials are required to examine the mechanism of GV and to evaluate whether GV can be a valuable therapeutic target in treatment of patients with T2DM.

Prognostic impact of HbA1c variability on long-term outcomes in patients with heart failure and type 2 diabetes mellitus

Background

The prognostic impact of long-term glycemic variability on clinical outcomes in patients with heart failure (HF) and type 2 diabetes mellitus (T2DM) remains unclear. We determined and compared hemoglobin A1c (HbA1c) variability and clinical outcomes for patients with HF with preserved ejection fraction (HFpEF), HF with mid-range ejection fraction (HFmrEF) and HF with reduced ejection fraction (HFrEF) in a prospective longitudinal study.

Methods

Patients with HF and T2DM, undergone 3 or more HbA1c determinations during the first 18 months, were then followed for 42 months. The primary outcome was death from any cause. Secondary outcome was composite endpoints with death and HF hospitalization. Cox proportional hazards models were used to compare outcomes for patients with HFpEF, HFmrEF and HFrEF.

Results

Of 902 patients enrolled, 32.2% had HFpEF, 14.5% HFmrEF, and 53.3% HFrEF. During 42 months of follow-up, 270 (29.9%) patients died and 545 (60.4%) patients experienced composite endpoints of death and HF readmission. The risk of all-cause death or composite endpoints was lower for HFpEF than HFrEF. Moreover, higher HbA1c variability was associated with higher all-cause mortality or composite endpoints and HbA1c variability was an independent predictor of all-cause mortality or composite endpoints, regardless of EF.

Conclusions

This prospective longitudinal study showed that the all-cause death and composite events was lower for HFpEF than HFrEF. HbA1c variability was independently and similarly predictive of death or combined endpoints in the three HF phenotypes.

Electronic supplementary material

The online version of this article (10.1186/s12933-018-0739-3) contains supplementary material, which is available to authorized users.

Time Trend, Age and Sex Distribution of Deceased from Diabetes Mellitus at the Regional Level in the Slovak Republic

AIM

To describe the time trends, age and sex distribution of death from diabetes mellitus (E10-E14) as a significant part of endocrine, nutritional and metabolic diseases (E00-E90), during 1996-2014 in the Slovak regions, and to estimate the influence of social characteristics on mortality.

METHODS

Secondary data on deaths during 1996-2014 were gathered from the National Health Information Center in the Slovak Republic. The total crude death rate per 100,000 of the standard Slovak population and age-standardized death rate per 100,000 of the standard European population were calculated by direct standardization. Multilevel logistic regression analysis was performed.

RESULTS

Deaths from diabetes mellitus account for 91.6% of deaths registered in the endocrine, nutritional and metabolic diseases Chapter. The age-standardized death rate per 100,000 of inhabitants decreased from 19.2 in 1996 to 15.3 in 2014 in the Slovak Republic, although a massive increase of up to 32.5 was reported in 1999. The highest age-standardized death rates per 100,000 inhabitants were typical for the Košice, Nitra and Trenčín regions. On the other hand, the lowest counts were recorded in the Bratislava region. Mortality from diabetes mellitus starts to be evident in the 45-49 year age-group in both sexes. The median age of death for women is lower in the 75-79 year age-group in comparison to men although the total crude death rate for men in lower age groups is higher. After age 80 the situation is reversed. The odds of dying due to endocrine, nutritional and metabolic diseases decreases by 0.4% each year. The odds of dying are lower by 17% and 12.3%, respectively, in the Žilina and Prešov regions compared to Bratislava region. Women have a higher probability of dying by 38% in contrast to men, and married couples by 16.7% than singles. Age is proved to be an insignificant factor.

CONCLUSIONS

In spite of the declining trend of mortality from diabetes mellitus, it is necessary to reduce the risk of its incidence by healthier food consumption and physical activity.

Long-term visit-to-visit glycemic variability as predictor of micro- and macrovascular complications in patients with type 2 diabetes: The Rio de Janeiro Type 2 Diabetes Cohort Study

BACKGROUND

Long-term visit-to-visit glycemic variability is an additional measure of glycemic control. We aimed to evaluate the prognostic value of several measures of glycemic variability for the occurrence of micro- and macrovascular complications, and all-cause mortality in patients with type 2 diabetes.

METHODS

654 individuals were followed-up over a median of 9.3 years. Glycemic variability (SDs and coefficients of variation of HbA1c and fasting glycaemia) was measured during the first 12- and 24-months. Multivariate Cox analysis, adjusted for risk factors and mean HbA1c and fasting glycaemia levels, examined the associations between glycemic variability and the occurrence of microvascular (retinopathy, microalbuminuria, renal function deterioration, peripheral neuropathy) and macrovascular complications [total cardiovascular events (CVE), major adverse CVEs (MACE) and cardiovascular mortality], and of all-cause mortality.

RESULTS

During follow-up, 128 patients had a CVE (96 MACE), and 158 patients died (67 from cardiovascular diseases); 152 newly-developed or worsened diabetic retinopathy, 183 achieved the renal composite outcome (89 newly developed microalbuminuria and 91 deteriorated renal function), and 96 newly-developed or worsened peripheral neuropathy. Glycemic variability, particularly the 24-month parameters either estimated by HbA1c or by fasting glycemia, predicted all endpoints, except for retinopathy and peripheral neuropathy development/progression, and was a better predictor than mean HbA1c. Glycemic variability predicted retinopathy development/progression in patients with good glycemic control (HbA1c ≤ 7.5%, 58 mmol/mol) and predicted new-incident peripheral neuropathy.

CONCLUSIONS

Long-term visit-to-visit glycemic variability is an additional and frequently a better glycemic parameter than mean HbA1c levels for assessing the risk of future development of micro- and macrovascular complications in patients with type 2 diabetes.

Association of hemoglobin A1c variability and the incidence of heart failure with preserved ejection fraction in patients with type 2 diabetes mellitus and arterial hypertension

BACKGROUND

This study aimed to investigate the association between variability in hemoglobin A1c (HbA1c) and left ventricular (LV) diastolic function and incidence of symptomatic heart failure with preserved ejection fraction (HFpEF) in patients with type 2 diabetes mellitus (T2DM) and arterial hypertension.

METHODS

A retrospective cohort study was conducted on eligible patients with T2DM and hypertension and without clinical signs or symptoms of heart failure in our hospital medical record database. Variability in HbA1c was measured by standard deviation (SD) and coefficient of variation (CV). Risk of new onset of symptomatic HFpEF was evaluated by multivariable cox regression analysis.

RESULTS

A total of 201 subjects were categorized according to the median value of HbA1c variability indicators. Over a median follow-up of 7.3 years, the percentage of subjects who had new incidence of symptomatic HFpEF was higher in those with higher HbA1c-SD level (5/105 vs. 13/96, P=0.029) and higher HbA1c-CV level (5/101 vs. 13/100, P=0.046). Multivariable cox regression analysis also showed that higher HbA1c variability [HbA1c-SD (HR 1.754, 95% CI: 1.003-3.104, P=0.049) or HbA1c-CV (HR 1.604 95% CI: 1.064-2.419, P=0.024)] was associated with the presence of new-onset symptomatic HFpEF, independent of HbA1c-mean level, in T2DM and hypertensive patients. Moreover, lower HbA1c variability generated more prominent improvement in LV diastolic function (E/E') during the follow-up.

CONCLUSIONS

HbA1c variability may provide additional valuable information as a potential predictor of the progression of HFpEF in T2DM and hypertensive patients.

The relationship between fasting blood glucose variability and coronary artery collateral formation in type 2 diabetes patients with coronary artery disease

BACKGROUND

Coronary collaterals are an alternative source of blood supply to ischemic myocardium. Well-developed coronary collateral arteries in patients with coronary artery disease (CAD) limit the size of acute myocardial infarction and improves survival. The aim of this study was to investigate the relationship between glycemic variability and coronary collateral formation in patients with type 2 diabetes mellitus and CAD.

METHODS

Consecutive patients undergoing percutaneous coronary intervention or coronary artery bypass grafting procedures were studied. Multivariate logistic regression models were used to examine the association between coronary artery collateral formation graded by Rentrope classification and glycemic variability, measured by coefficient variation of fasting blood glucose.

RESULTS

In our study, we retrospectively enrolled 300 patients, of whom 239 were diabetic (age: 70.1±11.9, 56% men) and 61 were nondiabetic (age: 71.5±11.5, 72% men). Diabetic patients were further stratified as follows: those with poor coronary collateral artery development (n=171, age: 69.7±12.4, 55% men) and those with good coronary collateral artery development (n=68, age 71.1±10.8, 59% men) according to the Rentrope classification. Our findings did not show association between glycemic variability and coronary collateral vessels development after controlling for potential confounders (odds ratio: 2.51; 95% confidence interval: 0.57-11.03; P=0.22). The culprit lesion (≥75% stenosis) in the left anterior descending artery and the right coronary artery was more frequent in the good collateral group compared with the poor collateral group (66 vs. 50%, P=0.02; 63 vs. 45%, P=0.01 respectively).

CONCLUSION

Glycemic variability is not associated with coronary collateral artery formation in patients with type 2 diabetes mellitus and CAD.

Greater HbA1c variability is associated with increased cardiovascular events in type 2 diabetes patients with preserved renal function, but not in moderate to advanced chronic kidney disease

Emerging evidence suggests that glycemic variability may be a more reliable measure of glycemic control than mean HbA1c in type 2 diabetes mellitus. This study aimed to determine if HbA1c variability is associated with cardiovascular events in type 2 diabetic patients and if different renal functions affect such association. This longitudinal study enrolled 8259 diabetic patients from the Kaohsiung Medical University Research Database in 2009 and were followed-up until 2015. Intra-individual HbA1C variability was defined as the standard deviation (SD) of HbA1c and cardiovascular events were defined as hospitalization for coronary artery disease, unstable angina, myocardial infarction, stroke, peripheral artery disease, and cardiovascular death. The patients were grouped into two based on their estimated glomerular filtration rate (eGFR) ≥ 60 or < 60 min/ml/1.73m2. In a mean follow-up period of 6.3 years, cardiovascular events were recorded in 8.9% of the patients. In an adjusted Cox model, high HbA1c SD (hazard ratio, 1.290; 95% confidence interval, 1.008-1.650; p = 0.043), but not mean HbA1c, was associated with significantly increased risk of cardiovascular events in patients with eGFR ≥ 60 min/ml/1.73m2. This association was not seen in patients with eGFR < 60 min/ml/1.73m2. In this study, greater HbA1c variability is associated with increased risk of cardiovascular among patients with preserved renal function, but not in those with moderate to advanced chronic kidney disease.

Association of Visit-to-Visit Variability of Systolic Blood Pressure With Cardiovascular Disease and Mortality in Primary Care Chinese Patients With Type 2 Diabetes-A Retrospective Population-Based Cohort Study

OBJECTIVE

This study aimed to evaluate the impact of visit-to-visit variability (VVV) of systolic blood pressure (SBP) on cardiovascular disease (CVD) and mortality among primary care Chinese patients with type 2 diabetes mellitus (T2DM).

RESEARCH DESIGN AND METHODS

A retrospective cohort study was conducted in 124,105 Chinese adult primary care patients with T2DM and without prior diagnosed CVD from August 2008 to December 2009. The VVV of SBP was evaluated using SDs of SBP over 24 months. The risks of CVD and all-cause mortality associated with variability in SBP were evaluated using Cox proportional hazards regression. Subgroup analysis was conducted by the stratification of age, sex, duration of diabetes, the presence of chronic kidney disease, baseline SBP and trend, and the number and class of antihypertensive drugs.

RESULTS

A positive linear relationship between the VVV of SBP and the first incidence of CVD and all-cause mortality was identified over a median follow-up time of 39.5 months. Patients with a low SD of SBP of <5 mmHg had the lowest risks of CVD and all-cause mortality, and patients with an SD of SBP of ≥10 mmHg had significantly higher risks. For every 1 SD increase in the SD of SBP, the risks of CVD, all-cause mortality, and the composite of both events increased by 2.9% (95% CI 2.4-3.4%), 4.0% (95% CI 3.5-4.6%), and 3.4% (95% CI 3.0-3.8%), respectively. A direct linear relationship was also observed in all selected subgroups.

CONCLUSIONS

SBP variability, irrespective of the mean SBP level, is a potential predictor for the development of CVD and all-cause mortality in patients with diabetes. In addition to monitoring BP targets for their patients with diabetes, clinicians should also remain vigilant about the visit-to-visit fluctuation of BP.