Association of glycemic variability with left ventricular diastolic function in type 2 diabetes mellitus

The clinical importance of measuring glycaemic variability: Utilising new metrics to optimise glycaemic control

With the widespread use of continuous glucose monitoring (CGM), glycaemic variability (GV) is a glucose metric that has been gaining increasing attention. However, unlike other glucose metrics that are easily defined and have clear targets, GV has a large number of different measures given the complexity involved in assessment. While variabilities in HbA1c, fasting and postprandial glucose have been incorporated under the GV banner, short-term variability in glucose, within day and between days, is more in keeping with the correct definition of GV. This review is focused on short-term GV, as assessed by CGM data, although studies calculating GV from capillary glucose testing are also mentioned as appropriate. The different measures of GV are addressed, and their potential role in microvascular and macrovascular complications, as well as patient-related outcomes, discussed. It should be noted that the independent role of GV in vascular pathology is not always clear, given the inconsistent findings in different populations and the close association between GV and hypoglycaemia, itself an established risk factor for adverse outcomes. Therefore, this review attempts, where possible, to disentangle the contribution of GV to diabetes complications from other glycaemic parameters, particularly hypoglycaemia. Evidence to date strongly suggests an independent role for GV in vascular pathology but future large-scale outcome studies are required to fully understand the exact contribution of this metric to vascular complications. This can be followed by setting appropriate GV measures and targets in different diabetes subgroups, in order to optimise glycaemic management and limit the risk of complications.

Relationship between hemoglobin glycation index and risk of hypoglycemia in type 2 diabetes with time-in-range in target

BACKGROUND

In patients with type 2 diabetes mellitus (T2DM), the risk of hypoglycemia also occurs in at a time-in-range (TIR) of > 70%. The hemoglobin glycation index (HGI) is considered the best single factor for predicting hypoglycemia, and offers new perspectives for the individualized treatment of patients with well-controlled blood glucose levels that are easily ignored in clinical settings.

AIM

To investigate the relationship between HGI and hypoglycemia and the implications of HGI on hypoglycemia in T2DM with TIR > 70%.

METHODS

All participants underwent a 7-days continuous glucose monitoring (CGM) using a retrospective CGM system. We obtained glycemic variability indices using the CGM system. We defined HGI as laboratory hemoglobin A1c minus the glucose management indicator. Patients were categorized into low HGI (HGI < 0.5) and high HGI groups (HGI ≥ 0.5) according to HGI median (0.5). Logistic regression and receiver operating characteristic curve analyses were used to determine the risk factors for hypoglycemia.

RESULTS

We included 129 subjects with T2DM (54.84 ± 12.56 years, 46% male) in the study. Median TIR score was 90%. The high HGI group exhibited lower TIR and greater time below range with higher hemoglobin A1c than the low HGI group; this suggests more glycemic excursions and an increased incidence of hypoglycemia in the high HGI group. Multivariate analyses revealed that mean blood glucose, standard deviation of blood glucose and HGI were independent risk factors for hypoglycemia. Receiver operating characteristic curve analysis indicated that the HGI was the best predictor of hypoglycemia. In addition, the optimal cut-off points for HGI, mean blood glucose, and standard deviation of blood glucose in predicting hypoglycemia were 0.5%, 7.2 mmol/L and 1.4 mmol/L respectively.

CONCLUSION

High HGI was significantly associated with greater glycemic excursions and increased hypoglycemia in patients with TIR > 70%. Our findings indicate that HGI is a reliable predictor of hypoglycemia in this population.

Research progress on the association between glycemic variability index derived from CGM and cardiovascular disease complications

Currently, glycated hemoglobin A1c (HbA1c) has been widely used to assess the glycemic control of patients with diabetes. However, HbA1c has certain limitations in describing both short-term and long-term glycemic control. To more accurately evaluate the glycemic control of diabetes patients, the continuous glucose monitoring (CGM) technology has emerged. CGM technology can provide robust data on short-term glycemic control and introduce new monitoring parameters such as time in range, time above range, and time below range as indicators of glycemic fluctuation. These indicators are used to describe the changes in glycemic control after interventions in clinical research or treatment modifications in diabetes patient care. Recent studies both domestically and internationally have shown that these indicators are not only associated with microvascular complications of diabetes mellitus but also closely related to cardiovascular disease complications and prognosis. Therefore, this article aims to comprehensively review the association between CGM-based glycemic parameters and cardiovascular disease complications by analyzing a large number of domestic and international literature. The purpose is to provide scientific evidence and guidance for the standardized application of these indicators in clinical practice, in order to better evaluate the glycemic control of diabetes patients and prevent the occurrence of cardiovascular disease complications. This research will contribute to improving the quality of life for diabetes patients and provide important references for clinical decision-making.

Nocturnal Hypertension and Left Ventricular Diastolic Dysfunction in Patients With Diabetes With the Absence of Heart Failure: Prospective Cohort HSCAA Study

BACKGROUND

Diabetes is an important risk factor for heart failure (HF) and is associated with left ventricular (LV) diastolic dysfunction. However, diabetic comorbid conditions, such as nocturnal hypertension, as predictors of diastolic dysfunction are not known in the absence of an HF period. The present study was conducted as the longitudinal examination of the predictive value of nocturnal hypertension profiles on the progression of LV diastolic dysfunction in patients with and without diabetes without HF.

METHODS

The subjects (154 diabetes and 268 nondiabetes) in the absence of HF were followed for 36.8±18.2 months. The relationships among the patterns of nocturnal hypertension and the outcome of LV diastolic dysfunction, defined as an increase in E/e'>14, were investigated in the patients with and without diabetes.

RESULTS

The interaction effect of the diabetes status and the patterns of nocturnal hypertension on the hazard rate of the occurrence of E/e'>14 was statistically significant (P=0.017). Kaplan-Meier analysis results revealed that patients with diabetes with nondipper (P=0.021 versus dipper) and riser (P=0.006 versus dipper) had a greater risk for a diastolic dysfunction event. Furthermore, multivariable Cox proportional hazards analysis revealed that nondipper (hazard ratio, 4.56 [95% CI, 1.49-13.96]; P=0.007) and riser (hazard ratio, 3.89 [95% CI, 1.31-11.57]; P=0.014) patterns were associated with elevated risk of the outcome of LV diastolic dysfunction. In contrast, no similar significant associations were found in patients without diabetes.

CONCLUSIONS

During the absence of HF periods, nocturnal hypertension is an important predictor for the progression of LV diastolic dysfunction in patients with diabetes.

Glycemic variability: Measurement, target, impact on complications of diabetes and does it really matter?

Over the past two decades, there has been continuous advancement in the accuracy and complexity of continuous glucose monitoring devices. Continuous glucose monitoring provides valuable insights into blood glucose dynamics, and can record glucose fluctuations accurately and completely. Glycemic variability (GV) is a straightforward measure of the extent to which a patient's blood glucose levels fluctuate between high peaks and low nadirs. Many studies have investigated the relationship between GV and complications, primarily in the context of type 2 diabetes. Nevertheless, the exact contribution of GV to the development of diabetes complications remains unclear. In this literature review, we aimed to summarize the existing evidence regarding the measurement, target level, pathophysiological mechanisms relating GV and tissue damage, and population-based studies of GV and diabetes complications. Additionally, we introduce novel methods for measuring GV, and discuss several unresolved issues of GV. In the future, more longitudinal studies and trials are required to confirm the exact role of GV in the development of diabetes complications.

Association between glycosylated hemoglobin levels, diabetes duration, and left ventricular diastolic dysfunction in patients with type 2 diabetes and preserved ejection fraction: a cross-sectional study

Background

We aimed to explore the intricate interplay between glycated hemoglobin (HbA1C) levels, disease duration, and left ventricular diastolic dysfunction in patients with type 2 diabetes mellitus (T2DM) characterized by preserved ejection fraction.

Methods

A cross-sectional study was conducted at the Second Affiliated Hospital of Hebei Medical University from January 2022 to December 2022. A total of 114 inpatients from the Department of Endocrinology were randomly selected based on the inclusion and exclusion criteria. Patients with T2DM were stratified into three subgroups, each comprising 38 patients, based on disease duration and HbA1C levels. A sub-analysis was conducted to explore variations among these three distinct groups. A control group comprised 38 age, gender, body mass index (BMI), and smoking habit-matched healthy volunteers form the Physical Examination Center of the same hospital. General demographic information, biochemical results, and echocardiographic data were collected, and correlation and linear regression analyses were performed.

Results

Diabetic patients exhibited lower E/A values (0.85 (0.72, 1.17) vs. 1.20 (0.97, 1.30)) and elevated E/e' values (9.50 (8.75, 11.00) vs. 9.00 (7.67, 9.85)) compared to their normal controls. In the subgroup analysis, patients with a disease duration exceeding 2 years displayed reduced E/A values (0.85 (0.75, 1.10) vs. 1.10 (0.80, 1.30)) and elevated E/e' values (9.80 (9.20, 10.80) vs. 8.95 (7.77, 9.50)) in comparison to those with a disease duration of ≤2 years, p<0.05. Among patients with a disease duration surpassing 2 years, those with higher HbA1C levels exhibited lower E/A values (0.80 (0.70, 0.90) vs. (0.85 (0.75, 1.10)) and higher E/e' values (11.00 (9.87, 12.15) vs. 9.80 (9.20, 10.80)) in contrast to patients with low HbA1C levels, p<0.05. Multiple linear regression analysis identified HbA1C (β=0.294, p<0.001) and disease duration (β=0.319, p<0.001) as independent risk factors for the E/A value in diabetes patients. Furthermore, HbA1C (β=0.178, p=0.015) and disease duration (β=0.529, p<0.001) emerged as independent risk factors for the E/e' value in diabetic patients.

Conclusions

In individuals with T2DM exhibiting preserved ejection fraction, the presence of left ventricular diastolic dysfunction is significantly associated with HbA1C levels and the duration of diabetes.

Glycemic variability is associated with diastolic dysfunction in patients with type 2 diabetes

AIM

To investigate the relationship between glycemic variability (GV) and diastolic dysfunction in patients with type 2 diabetes mellitus (DM) without coronary artery disease.

METHODS

Seventy-eight patients with type 2 DM without coronary artery disease were enrolled into the study. Diastolic function was assessed by echocardiography (Philips IE33); GV was evaluated by continuous monitoring of glucose (CGM, Guardian™ Connect System, Medtronic). According to the GV all studied patients were divided into two groups: group I - standard deviation (SD) > 2 (high GV), n = 40; group II - SD ≤ 1.9 (normal GV), n = 38.

RESULTS

Group I were older (49±9 vs 46±5; p<0.05), with a longer duration of DM (10±9.5 vs 6±5.5; p<0.01). Patients in group I had more severe diastolic dysfunction which was characterized by an increased values of myocardial stiffness index (E/e' ratio), speed of early transmitral flow (E, sm/sec) and peak rate of tricuspid regurgitation (V max TR, m/sec). Multivariate regression analysis revealed that high GV and older age of patients were the only significant independent predictors for diastolic dysfunction.

CONCLUSIONS

Increased GV is associated with diastolic dysfunction and could predispose to development and progression of heart failure in patients with type 2 DM without coronary arteries disease.

Associations of advanced liver fibrosis with heart failure with preserved ejection fraction in type 2 diabetic patients according to obesity and metabolic goal achievement status

Background

Heart failure with preserved ejection fraction (HFpEF), a major cause of morbidity and mortality in patients with type 2 diabetes mellitus (T2DM), is frequently coexisted with obesity, poor glycemic, blood pressure (BP), and/or lipid control. We aimed to investigate the associations of nonalcoholic fatty liver disease (NAFLD) and its advanced fibrosis with HFpEF according to obesity, glycated hemoglobin A1c (HbA1c), BP, and low-density lipoprotein cholesterol (LDL-C) goal achievement status in T2DM patients.

Methods

A total of 2,418 T2DM patients who were hospitalized were cross-sectionally assessed. Liver fibrosis was evaluated by non-invasive biomarkers. Logistic regression analysis was used to evaluate the independent and combined associations of fibrosis status and diabetic care goal attainments with HFpEF risk.

Results

Simple steatosis was not associated with HFpEF risk compared with patients without steatosis, while advanced liver fibrosis was found to have significantly higher odds for HFpEF risk (odds ratio,1.59; 95% confidence interval, 1.22-2.08). Advanced fibrosis in NAFLD was significantly associated with an increased risk of HFpEF, regardless of obesity status, HbA1c, BP, and LDL-C goal achievement status. P values for the interactions between fibrosis status and HbA1c control status, fibrosis status and BP control status, fibrosis status and LDL-C control status, and fibrosis status and body mass index (BMI) status on HFpEF risk were 0.021, 0.13, 0.001, and 0.23, respectively.

Conclusion

In patients with T2DM, advanced hepatic fibrosis was significantly associated with HFpEF risk, irrespective of obesity status, HbA1c, BP, and LDL-C goal attainment status. Further, HbA1c and LDL-C goal attainment status modified this association.

Visit-to-Visit Variability in Fasting Blood Glucose Predicts the New-Onset Heart Failure: Results From Two Large Chinese Cohorts

Previous studies have hypothesized an association between higher fasting blood glucose (FBG) and heart failure (HF). However, FBG values fluctuate continuously over time, the association between FBG variability and the risk of HF is uncertain. We investigated the relationship between visit-to-visit variability in FBG and the risk of new-onset HF. This cohort study used data from a prospective Kailuan cohort (recruited during 2006-2007) and a retrospective cohort of family medicine patients from Hong Kong (recruited during 2000-2003) were followed up until December 31st, 2016, and December 31st, 2019, respectively, for the outcome of incident HF. Four indexes of variability were used, including standard deviation (SD), coefficient of variation (CV), variability independent of the mean (VIM), and average real variability (ARV). Cox regression was used to identify HF. In total, 98,554 and 22,217 subjects without preexisting HF from the Kailuan and Hong Kong cohorts were analyzed, respectively, with 1218 cases of incident HF in the former and 4,041 in the latter. Subjects in the highest quartile of FBG-CV had the highest risk of incident HF in both cohorts (Kailuan: HR 1.245, 95% CI 1.055-1.470); Hong Kong: HR 1.362, 95%CI 1.145-1.620; compared with the lowest quartile). Similar results were observed when using FBG-ARV, FBG-VIM, and FBG-SD. Meta-analysis showed similar results (highest versus lowest quartile: HR 1.30, 95%CI 1.15-1.47, P < 0.0001). As observed from 2 large, geographically distinct Chinese cohorts, a higher FBG variability was independently associated with higher risk of incident HF.

Complications of Diabetes and Metrics of Glycemic Management Derived From Continuous Glucose Monitoring

CONTEXT

Although glycated hemoglobin A1c is currently the best parameter used clinically to assess risk for the development of diabetes complications, it does not provide insight into short-term fluctuations in glucose levels. This review summarizes the relationship between continuous glucose monitoring (CGM)-derived metrics of glycemic variability and diabetes-related complications.

EVIDENCE ACQUISITION

PubMed and Embase databases were searched from January 1, 2010 to August 22, 2020, using the terms type 1 diabetes, type 2 diabetes, diabetes-related microvascular and macrovascular complications, and measures of glycaemic variability. Exclusion criteria were studies that did not use CGM and studies involving participants who were not diabetic, acutely unwell (post stroke, post surgery), pregnant, or using insulin pumps.

EVIDENCE SYNTHESIS

A total of 1636 records were identified, and 1602 were excluded, leaving 34 publications in the final review. Of the 20 852 total participants, 663 had type 1 diabetes (T1D) and 19 909 had type 2 diabetes (T2D). Glycemic variability and low time in range (TIR) showed associations with all studied microvascular and macrovascular complications of diabetes. Notably, higher TIR was associated with reduced risk of albuminuria, retinopathy, cardiovascular disease mortality, all-cause mortality, and abnormal carotid intima-media thickness. Peripheral neuropathy was predominantly associated with standard deviation of blood glucose levels (SD) and mean amplitude of glycemic excursions (MAGE).

CONCLUSION

The evidence supports the association between diabetes complications and CGM-derived measures of intraday glycemic variability. TIR emerged as the most consistent measure, supporting its emerging role in clinical practice. More longitudinal studies and trials are required to confirm these associations, particularly for T1D, for which there are limited data.

Inhibition of SGLT1 Alleviates the Glycemic Variability-Induced Cardiac Fibrosis via Inhibition of Activation of Macrophage and Cardiac Fibroblasts

Glycemic variability has been considered one of the predictors of diabetes complications in patients with diabetes mellitus (DM). In this work, we evaluated whether glycemic variability induces cardiac fibrosis through regulating cardiac fibroblast activation and macrophage polarization. Moreover, we determined whether glucose transporter sodium-glucose cotransporter 1 (SGLT1) plays an important role in this process. Glycemic variability-induced mice were established using DM mice (GVDM mice), and intermittent high-glucose (IHG) treatment was used to simulate glycemic variability in RAW264.7 macrophages and cardiac fibroblasts. The short hairpin RNA for SGLT1 was used to knock down SGLT1. The results showed that glycemic variability aggravated the cardiac fibrosis in GVDM mice. Additionally, glycemic variability promoted the expression of fibrogenic cytokine and the extracellular matrix proteins in left ventricular tissues and cardiac fibroblasts. GVDM mice showed a higher incidence of macrophage infiltration and M1 polarization in left ventricular tissues. Moreover, IHG-promoted RAW264.7 macrophages tended to differentiate to M1 phenotype. SGLT1 knockdown alleviated cardiac fibrosis in GVDM mice and inhibited activations of cardiac fibroblast and macrophage M1 polarization. Our results indicated that glycemic variability aggravates cardiac fibrosis through activating cardiac fibroblast and macrophage M1 polarization, which could be partially inhibited by SGLT1 knockdown.

Fasting Glucose Variability as a Risk Indicator for End-Stage Kidney Disease in Patients with Diabetes: A Nationwide Population-Based Study

Given the fact that diabetes remains a leading cause of end-stage kidney disease (ESKD), multi-aspect approaches anticipating the risk for ESKD and timely correction are crucial. We investigated whether fasting glucose variability (FGV) could anticipate the development of ESKD and identify the population prone to the harmful effects of GV. We included 777,192 Koreans with diabetes who had undergone health examinations more than three times in 2005-2010. We evaluated the risk of the first diagnosis of ESKD until 2017, according to the quartile of variability independent of the mean (VIM) of FG using multivariate-adjusted Cox proportional hazards analyses. During the 8-year follow-up, a total of 7290 incidents of ESKD were found. Subjects in the FG VIM quartile 4 had a 27% higher risk for ESKD compared to quartile 1, with adjustment for cardiovascular risk factors and the characteristics of diabetes. This effect was more distinct in patients aged < 65 years; those with a long duration of diabetes; the presence of hypertension or dyslipidemia; and prescribed angiotensin-converting enzyme inhibitors, metformin, sulfonylurea, α-glucosidase inhibitors, and insulin. In contrast, the relationship between baseline FG status and ESKD risk showed a U-shaped association. FGV is an independent risk factor for kidney failure regardless of FG.

Differences in outcomes of hospitalizations for heart failure after SGLT2 inhibitor treatment: effect modification by atherosclerotic cardiovascular disease

Background

The treatment effects on hospitalization for heart failure (hHF) from sodium-glucose cotransporter 2 (SGLT2) inhibitors may vary among type 2 diabetes (T2D) patients depending on whether or not they have established atherosclerotic cardiovascular diseases (ASCVD). We aimed to examine differences in hHF outcomes after dapagliflozin or empagliflozin use between T2D patients with and without a history of established ASCVD.

Methods

We conducted a retrospective multi-institutional cohort study in Taiwan. We included T2D patients newly receiving dapagliflozin or empagliflozin during 2016–2019, and followed them up until December 31, 2020. We implemented 1:1 propensity score matching to create homogenous groups for comparisons. We generated Cox proportional hazard models to compare the risk of hHF between dapagliflozin and empagliflozin (reference group). We included interaction terms of SGLT2 inhibitor and ASCVD history in the regression models to examine effect modification by ASCVD.

Results

We included a total cohort of 9,586 dapagliflozin new users and 9,586 matched empagliflozin new users. The overall hHF risks were similar for dapagliflozin and empagliflozin (HR: 0.90, 95% CI 0.74–1.09). However, differential hHF risks between dapagliflozin and empagliflozin were observed only in the subgroup without ASCVD (HR: 0.67, 95% CI 0.49–0.90), while not in the subgroup with ASCVD (HR: 1.12, 95% 0.87–1.45), and the p-value for examining interaction was 0.0097.

Conclusion

In this study, history of established ASCVD was associated with different hHF risks among SGLT2 inhibitors. For T2D patients without ASCVD, dapagliflozin may offer a more favorable hHF reduction effect, compared to empagliflozin, in clinical practice. Future prospective studies should be conducted to validate our findings.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12933-021-01406-3.

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

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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12933-021-01341-3.

Impact of type 2 diabetes mellitus on left ventricular diastolic function in patients with essential hypertension: evaluation by volume-time curve of cardiac magnetic resonance

Background

Essential hypertension and type 2 diabetes mellitus (T2DM) are two common chronic diseases that often coexist, and both of these diseases can cause heart damage. However, the additive effects of essential hypertension complicated with T2DM on left ventricle (LV) diastolic function have not been fully illustrated. This study aims to investigate whether T2DM affects the diastolic function of the LV in patients with essential hypertension using the volume-time curve from cardiac magnetic resonance (CMR).

Methods

A total of 124 essential hypertension patients, including 48 with T2DM [HTN(T2DM +) group] and 76 without T2DM [HTN(T2DM-) group], and 52 normal controls who underwent CMR scans were included in this study. LV volume-time curve parameters, including the peak ejection rate (PER), time to peak ejection rate (PET), peak filling rate (PFR), time to peak filling rate from end-systole (PFT), PER normalized to end-diastolic volume (PER/EDV), and PFR normalized to EDV (PFR/EDV), were measured and compared among the three groups. Multivariate linear regression analyses were performed to determine the effects of T2DM on LV diastolic dysfunction in patients with hypertension. Pearson correlation was used to analyse the correlation between the volume-time curve and myocardial strain parameters.

Results

PFR and PFR/EDV decreased from the control group, through HTN(T2DM −), to HTN(T2DM +) group. PFT in the HTN(T2DM-) group and HTN(T2DM +) group was significantly longer than that in the control group. The LV remodelling index in the HTN(T2DM −) and HTN(T2DM +) groups was higher than that in the normal control group, but there was no significant difference between the HTN(T2DM −) and HTN(T2DM +) groups. Multiple regression analyses controlling for covariates of systolic blood pressure, age, sex, and heart rate demonstrated that T2DM was independently associated with PFR/EDV (β = 0.252, p < 0.05). The volume-time curve method has good repeatability, and there is a significant correlation between volume-time curve parameters (PER/EDV and PFR/EDV) and myocardial peak strain rate, especially circumferential peak strain rate, which exhibited the highest correlation (r = − 0.756 ~ 0.795).

Conclusions

T2DM exacerbates LV diastolic dysfunction in patients with essential hypertension. The LV filling model changes reflected by the CMR volume-time curve could provide more information for early clinical intervention.

Diabetic phenotype and prognosis of patients with heart failure and preserved ejection fraction in a real life cohort

Background

Heart failure with preserved ejection fraction (HFpEF) is a heterogeneous syndrome, with several underlying etiologic and pathophysiologic factors. The presence of diabetes might identify an important phenotype, with implications for therapeutic strategies. While diabetes is associated with worse prognosis in HFpEF, the prognostic impact of glycemic control is yet unknown. Hence, we investigated phenotypic differences between diabetic and non-diabetic HFpEF patients (pts), and the prognostic impact of glycated hemoglobin (HbA1C).

Methods

We prospectively enrolled 183 pts with HFpEF (78 ± 9 years, 38% men), including 70 (38%) diabetics (type 2 diabetes only). They underwent 2D echocardiography (n = 183), cardiac magnetic resonance (CMR) (n = 150), and were followed for a combined outcome of all-cause mortality and first HF hospitalization. The prognostic impact of diabetes and glycemic control were determined with Cox proportional hazard models, and illustrated by adjusted Kaplan Meier curves.

Results

Diabetic HFpEF pts were younger (76 ± 9 vs 80 ± 8 years, p = 0.002), more obese (BMI 31 ± 6 vs 27 ± 6 kg/m², p = 0.001) and suffered more frequently from sleep apnea (18% vs 7%, p = 0.032). Atrial fibrillation, however, was more frequent in non-diabetic pts (69% vs 53%, p = 0.028). Although no echocardiographic difference could be detected, CMR analysis revealed a trend towards higher LV mass (66 ± 18 vs 71 ± 14 g/m², p = 0.07) and higher levels of fibrosis (53% vs 36% of patients had ECV by T1 mapping > 33%, p = 0.05) in diabetic patients.

Over 25 ± 12 months, 111 HFpEF pts (63%) reached the combined outcome (24 deaths and 87 HF hospitalizations). Diabetes was a significant predictor of mortality and hospitalization for heart failure (HR: 1.72 [1.1–2.6], p = 0.011, adjusted for age, BMI, NYHA class and renal function). In diabetic patients, lower levels of glycated hemoglobin (HbA1C < 7%) were associated with worse prognosis (HR: 2.07 [1.1–4.0], p = 0.028 adjusted for age, BMI, hemoglobin and NT-proBNP levels).

Conclusion

Our study highlights phenotypic features characterizing diabetic patients with HFpEF. Notably, they are younger and more obese than their non-diabetic counterpart, but suffer less from atrial fibrillation. Although diabetes is a predictor of poor outcome in HFpEF, intensive glycemic control (HbA1C < 7%) in diabetic patients is associated with worse prognosis.

Comprehensive elaboration of glycemic variability in diabetic macrovascular and microvascular complications

Diabetes mellitus is the major risk factor for the development of macrovascular and microvascular complications. It is increasingly recognized that glycemic variability (GV), referring to oscillations in blood glucose levels and representing either short-term or long-term GV, is involved in the pathogenesis of diabetic complications and has emerged as a possible independent risk factor for them. In this review, we summarize the metrics and measurement of GV in clinical practice, as well as comprehensively elaborate the role and related mechanisms of GV in diabetic macrovascular and microvascular complications, aiming to provide the mechanism-based therapeutic strategies for clinicians to manage diabetes mellitus.

A Coloured Pen Needle Education System Improves Insulin Site Rotation Habits: Results of a Randomized Study

INTRODUCTION

Needle reuse and repeated injection of insulin into the same site encourage lipohypertrophy. We explored the potential of coupling a novel pen needle strategy with community pharmacists to improve injection site rotation.

METHODS

Between October 2018 and January 2019, adult insulin users with type 1 or 2 diabetes were enrolled by 16 community pharmacists across 7 Canadian provinces and randomized to their usual pen needles (control) or coloured pen needles packaged with education materials in boxes with reminder sound chips (intervention [mCPN]). A total of 203 individuals completed all requirements of the 30-day study. The primary outcome was a composite of the number of zones injected, the use of new injection zones if the number of zones equaled that at baseline, and the change in size of the injection area from baseline. The pharmacists completed two questionnaires, which provided insights into whether study participation elevated their comfort and confidence in providing injection site rotation counselling.

RESULTS

Compared to the control group, more participants in the mCPN arm improved their site rotation practices (54.1% vs. 33.7%; P = 0.005), 15 more increased the number of injection zones used (P = 0.03), and there was less needle reuse (25% vs. 12% reduction). The pharmacists reported improved knowledge of the consequences of lipohypertrophy and the proportion who were "very comfortable" with pen needle tip selection and use rose from 31.3% pre-study to 93.8% post-study.

CONCLUSION

The coloured pen needles with their education materials are a novel means of encouraging injection site rotation. Community pharmacists represent an untapped resource for improving injection self-care practices.

Single prognostic cut-off value for admission glycemia in acute myocardial infarction has been used although high-risk stems from hyperglycemia as well as from hypoglycemia (a narrative review)

All original articles and meta-analysis use the single cut-off value to distinguish high-risk hyperglycemic from other acute myocardial infarction (AMI) patients. The mortality rate is 3.9 times higher in non-diabetic AMI patients with admission glycemia ≥6.1mmol compared to normoglycemic non-diabetic AMI patients. On the other hand, admission hypoglycemia in AMI is an important predictor of mortality. Because both admission hypo- and hyperglycemia correspond to higher in-hospital mortality, this graph is recognized as "J or U shaped curve". The review suggests two cut-off values for admission glycemia for risk assessment in AMI instead of single one because hypoglycemia as well as hyperglycemia represents a high-risk factor.

Fibroblast growth factor-23 is associated with imaging markers of diabetic cardiomyopathy and anti-diabetic therapeutics

Background

The biomarker fibroblast growth factor-23 (FGF-23) has been associated with increased cardiovascular morbidity and mortality in both patients with and without type 2 diabetes. The aim of this study was to evaluate the relationship between FGF-23 and cardiac structure, function and perfusion in patients with type 2 diabetes and normal or mildly impaired kidney function. Furthermore, to investigate the association between FGF-23, anti-diabetes therapy and the classic complications and risk factors associated with type 2 diabetes.

Methods

In this cross-sectional study, 246 patients with type 2 diabetes underwent echocardiography and advanced cardiac magnetic resonance imaging to assess left ventricular (LV) structure and function. In addition, myocardial blood flow (MBF) during rest and pharmacological stress (adenosine 140 µg/kg/min) were evaluated in 183 of the patients. Patients with eGFR < 60 ml/min/1.73 m² were excluded.

Results

Median (Q1–Q3) FGF-23 was 74 (58–91) ng/L. Patients with FGF-23 above the median had lower MBF during stress (2.3 ± 0.9 vs. 2.7 ± 0.9 ml/min/g, P = 0.001) and lower overall myocardial perfusion reserve (MPR) (2.7 ± 0.8 vs. 3.3 ± 1.1, P < 0.001). LV mass (143 ± 40 vs. 138 ± 36 g, P = 0.04) and E/e* (8.5 ± 3.2 vs. 7.6 ± 2.7, P = 0.04) were higher in patients with FGF-23 above the median. In a linear model adjusted for age, sex, eGFR and hypertension, increasing FGF-23 was associated with decreased MPR (P < 0.01, R² = 0.11) and increased E/e* (P < 0.01, R² = 0.07). FGF-23 was lower in patients receiving glucagon like peptide-1 (GLP-1) analogues (71 (57–86) vs. 80 (60–98) ng/L, P = 0.01) than in those who did not receive GLP-1 analogues.

Conclusions

In patients with type 2 diabetes and normal or mildly impaired kidney function, increased levels of FGF-23 are associated with impaired cardiac diastolic function and decreased MPR, caused by a decrease in maximal MBF during stress. Use of GLP-1 analogues is associated with decreased levels of FGF-23.

Clinical trial registrationhttps://www.clinicaltrials.gov. Unique identifier: NCT02684331. Date of registration: February 18, 2016

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

Glucose variability and the risks of stroke, myocardial infarction, and all-cause mortality in individuals with diabetes: retrospective cohort study

BACKGROUND

Previous research regarding long-term glucose variability over several years which is an emerging indicator of glycemic control in diabetes showed several limitations. We investigated whether variability in long-term fasting plasma glucose (FG) can predict the development of stroke, myocardial infarction (MI), and all-cause mortality in patients with diabetes.

METHODS

This is a retrospective cohort study using the data provided by the Korean National Health Insurance Corporation. A total of 624,237 Koreans ≥ 20 years old with diabetes who had undergone health examinations at least twice from 2005 to 2008 and simultaneously more than once from 2009 to 2010 (baseline) without previous histories of stroke or MI. As a parameter of variability of FG, variability independent of mean (VIM) was calculated using FG levels measured at least three times during the 5 years until the baseline. Study endpoints were incident stroke, MI, and all-cause mortality through December 31, 2017.

RESULTS

During follow-up, 25,038 cases of stroke, 15,832 cases of MI, and 44,716 deaths were identified. As the quartile of FG VIM increased, the risk of clinical outcomes serially increased after adjustment for confounding factors including duration and medications of diabetes and the mean FG. Adjusted hazard ratios (95% confidence intervals) of FG VIM quartile 4 compared with quartile 1 were 1.20 (1.16-1.24), 1.20 (1.15-1.25), and 1.32 (1.29-1.36) for stroke, MI and all-cause mortality, respectively. The impact of FG variability was higher in the elderly and those with a longer duration of diabetes and lower FG levels.

CONCLUSIONS

In diabetes, long-term glucose variability showed a dose-response relationship with the risk of stroke, MI, and all-cause mortality in this nationwide observational study.

Visit-to-visit fasting plasma glucose variability is associated with left ventricular adverse remodeling in diabetic patients with STEMI

Background

Patients with type 2 diabetes mellitus (T2DM) are predisposed to poor cardiovascular outcomes after ST-segment elevation myocardial infarction (STEMI). Left ventricular adverse remodeling (LVAR) triggered upon myocardial infarction is recognized as the predominant pathological process in the development of heart failure. In the present study, we sought to investigate whether visit-to-visit fasting plasma glucose (FPG) variability is a potential predictor of LVAR in T2DM patients after STEMI.

Methods

From January 2014 to December 2018 in Ruijin Hospital, T2DM patients with STEMI who underwent primary percutaneous coronary intervention were consecutively enrolled and followed up for ~ 12 months. The changes in left ventricular geometric and functional parameters between baseline and 12-month follow-up were assessed by echocardiography. The incidence of LVAR, defined as 20% increase in indexed left ventricular end-diastolic volume (LVEDV), and its relationship with visit-to-visit FPG variability were analyzed. Multivariate regression models were constructed to test the predictive value of FPG variability for post-infarction LVAR.

Results

A total of 437 patients with type 2 diabetes and STEMI were included in the final analysis. During a mean follow-up of 12.4 ± 1.1 months, the incidence of LVAR was 20.6% and mean enlargement of indexed LVEDV was 3.31 ± 14.4 mL/m², which was significantly increased in patients with higher coefficient variance (CV) of FPG (P = 0.002) irrespective of baseline glycemic levels. In multivariate analysis, FPG variability was independently associated with incidence of post-infarction LVAR after adjustment for traditional risk factors, baseline HbA1c as well as mean FPG during follow-up (OR: 3.021 [95% CI 1.081–8.764] for highest vs. lowest tertile of CV of FPG). Assessing FPG variability by other two measures, including standard deviation (SD) and variability independent of the mean (VIM), yielded similar findings.

Conclusions

This study suggests that visit-to-visit FPG variability is an independent predictor of incidence of LVAR in T2DM patients with STEMI.

Trial registration Trials number, NCT02089360; registered on March 17,2014.

Glycemic variability: adverse clinical outcomes and how to improve it?

Glycemic variability (GV), defined as an integral component of glucose homoeostasis, is emerging as an important metric to consider when assessing glycemic control in clinical practice. Although it remains yet no consensus, accumulating evidence has suggested that GV, representing either short-term (with-day and between-day variability) or long-term GV, was associated with an increased risk of diabetic macrovascular and microvascular complications, hypoglycemia, mortality rates and other adverse clinical outcomes. In this review, we summarize the adverse clinical outcomes of GV and discuss the beneficial measures, including continuous glucose monitoring, drugs, dietary interventions and exercise training, to improve it, aiming at better addressing the challenging aspect of blood glucose management.