Effect of Dapagliflozin on Glycemic Variability in Patients with Type 2 Diabetes under Insulin Glargine Combined with Other Oral Hypoglycemic Drugs

Short-term Glycemic Variability and Its Association With Macrovascular and Microvascular Complications in Patients With Diabetes

The introduction of continuous glucose monitoring inaugurated a new era in clinical practice by shifting the characterization of glycemic control from HbA1c to novel metrics. The one that gained widespread attention over the past decades was glycemic variability (GV), which typically refers to peaks and nadirs of blood glucose measured over a given time interval. GV can be dichotomized into two main categories: short-term and long-term. Short-term GV reflects within-day and between-day glycemic oscillations, and its contribution to diabetic complications remains an enigma. In this review, we summarize the available data about short-term GV and its possible association with both microvascular and macrovascular complications, evaluating different pathogenic mechanisms and demonstrating nonpharmaceutical, as well as pharmaceutical, therapeutic interventions.

Gut Microbiota-Tryptophan Metabolism-GLP-1 Axis Participates in β-Cell Regeneration Induced by Dapagliflozin

Sodium-glucose cotransporter 2 inhibitors, efficacious antidiabetic agents that have cardiovascular and renal benefits, can promote pancreatic β-cell regeneration in type 2 diabetic mice. However, the underlying mechanism remains unclear. In this study, we aimed to use multiomics to identify the mediators involved in β-cell regeneration induced by dapagliflozin. We showed that dapagliflozin lowered blood glucose level, upregulated plasma insulin level, and increased islet area in db/db mice. Dapagliflozin reshaped gut microbiota and modulated microbiotic and plasmatic metabolites related to tryptophan metabolism, especially l-tryptophan, in the diabetic mice. Notably, l-tryptophan upregulated the mRNA level of glucagon-like peptide 1 (GLP-1) production-related gene (Gcg and Pcsk1) expression and promoted GLP-1 secretion in cultured mouse intestinal L cells, and it increased the supernatant insulin level in primary human islets, which was eliminated by GPR142 antagonist. Transplant of fecal microbiota from dapagliflozin-treated mice, supplementation of l-tryptophan, or treatment with dapagliflozin upregulated l-tryptophan, GLP-1, and insulin or C-peptide levels and promoted β-cell regeneration in db/db mice. Addition of exendin 9-39, a GLP-1 receptor (GLP-1R) antagonist, or pancreatic Glp1r knockout diminished these beneficial effects. In summary, treatment with dapagliflozin in type 2 diabetic mice promotes β-cell regeneration by upregulating GLP-1 production, which is mediated via gut microbiota and tryptophan metabolism.

ARTICLE HIGHLIGHTS

Simultaneous assessment of stress hyperglycemia ratio and glycemic variability to predict mortality in patients with coronary artery disease: a retrospective cohort study from the MIMIC-IV database

BACKGROUND

Stress hyperglycemia and glycemic variability (GV) can reflect dramatic increases and acute fluctuations in blood glucose, which are associated with adverse cardiovascular events. This study aimed to explore whether the combined assessment of the stress hyperglycemia ratio (SHR) and GV provides additional information for prognostic prediction in patients with coronary artery disease (CAD) hospitalized in the intensive care unit (ICU).

METHODS

Patients diagnosed with CAD from the Medical Information Mart for Intensive Care-IV database (version 2.2) between 2008 and 2019 were retrospectively included in the analysis. The primary endpoint was 1-year mortality, and the secondary endpoint was in-hospital mortality. Levels of SHR and GV were stratified into tertiles, with the highest tertile classified as high and the lower two tertiles classified as low. The associations of SHR, GV, and their combination with mortality were determined by logistic and Cox regression analyses.

RESULTS

A total of 2789 patients were included, with a mean age of 69.6 years, and 30.1% were female. Overall, 138 (4.9%) patients died in the hospital, and 404 (14.5%) patients died at 1 year. The combination of SHR and GV was superior to SHR (in-hospital mortality: 0.710 vs. 0.689, p = 0.012; 1-year mortality: 0.644 vs. 0.615, p = 0.007) and GV (in-hospital mortality: 0.710 vs. 0.632, p = 0.004; 1-year mortality: 0.644 vs. 0.603, p < 0.001) alone for predicting mortality in the receiver operating characteristic analysis. In addition, nondiabetic patients with high SHR levels and high GV were associated with the greatest risk of both in-hospital mortality (odds ratio [OR] = 10.831, 95% confidence interval [CI] 4.494-26.105) and 1-year mortality (hazard ratio [HR] = 5.830, 95% CI 3.175-10.702). However, in the diabetic population, the highest risk of in-hospital mortality (OR = 4.221, 95% CI 1.542-11.558) and 1-year mortality (HR = 2.013, 95% CI 1.224-3.311) was observed in patients with high SHR levels but low GV.

CONCLUSIONS

The simultaneous evaluation of SHR and GV provides more information for risk stratification and prognostic prediction than SHR and GV alone, contributing to developing individualized strategies for glucose management in patients with CAD admitted to the ICU.

Impact of SGLT2 Inhibitors on Corneal Nerve Morphology and Dendritic Cell Density in Type 2 Diabetes

PURPOSE

This study aims to determine the effects of SGLT2 inhibitors on corneal dendritic cell density and corneal nerve measures in type 2 diabetes.

METHODS

Corneal dendritic cell densities and nerve parameters were measured in people with type 2 diabetes treated with SGLT2 inhibitors (T2DM-SGLT2i) [n = 23] and those not treated with SGLT2 inhibitors (T2DM-no SGLT2i) [n = 23], along with 24 age and sex-matched healthy controls.

RESULTS

There was a reduction in all corneal nerve parameters in type 2 diabetes groups compared to healthy controls (All parameters: p < 0.05). No significant differences in corneal nerve parameters were observed between T2DM-SGLT2i and T2DM-no SGLT2i groups (All parameters: p > 0.05). Central corneal dendritic cells were significantly reduced [mature (p = 0.03), immature (p = 0.06) and total (p = 0.002)] in the T2DM-SGLT2i group compared to the T2DM-no SGLT2i group. Significantly, higher mature (p = 0.04), immature (p = 0.004), total (p = 0.002) dendritic cell densities in the T2DM-no SGLT2i group were observed compared to the healthy controls. In the inferior whorl, no significant difference in immature (p = 0.27) and total dendritic cell densities (p = 0.16) between T2DM-SGLT2i and T2DM-no SGLT2i were observed except mature dendritic cell density (p = 0.018). No differences in total dendritic cell density were observed in the central (p > 0.09) and inferior whorl (p = 0.88) between T2DM-SGLT2i and healthy controls.

CONCLUSION

The present study showed a reduced dendritic cell density in people with type 2 diabetes taking SGLT2 inhibitors compared to those not taking these medications.

Glycemic variability correlates with medial temporal lobe atrophy and decreased cognitive performance in patients with memory deficits

Background

In the past, researchers have observed a significant link between glycemia and dementia. Medial temporal atrophy (MTA) is regarded as a common marker of dementia. The correlation between glycemic variability and MTA is unclear, and it has not been determined whether glycemic variability can be utilized as a biomarker of MTA and cognitive performance.

Methods

The patients in a memory clinic who underwent brain MRI scans and cognitive assessments within the first week of their hospital visit, were enrolled. All participants underwent three fasting blood glucose and one HBA1c assessments on three self-selected days within 1 week of their first visit. The variability independent of the mean (VIM) was employed. Validated visual scales were used to rate the MTA results. The mini-mental state examination (MMSE) and Montreal Cognitive Assessment (MoCA) scales were employed to assess the cognitive functions of the participants. Spearman's correlation and regression models were used to examine the relationship between the MMSE and MoCA scales, and also determine the link between the MRI characteristics and cognitive status, where vascular risk factors, educational status, age, gender, and mean glucose parameters served as covariates.

Results

Four hundred sixty-one subjects completed the MMSE scale, while 447 participants completed the MoCA scale. Data analysis revealed that 47.72% of the participants were men (220/461), and the median age of the patients was 69.87 ± 5.37 years. The findings of Spearman's correlation analysis exhibited a strong negative relationship between the VIM and MMSE score (r = -0.729, P < 0.01), and the MoCA score (r = -0.710, P < 0.01). The VIM was regarded as an independent risk factor for determining cognitive impairment in both the MMSE and MoCA assessments. The results were unaffected by sensitivity analysis. In addition, a non-linear relationship was observed between the VIM and MTA scores.

Conclusion

The variability in the blood glucose levels, which was presented as VIM, was related to the reduced cognitive function, which was reflected by MMSE and MoCA scales. The relationship between the VIM and the MTA score was non-linear. The VIM was positively related to the MTA score when the VIM was less than 2.42.

What is Glycaemic Variability and which Pharmacological Treatment Options are Effective? A Narrative Review

Glycated haemoglobin is currently used for diagnosis and follow-up of diabetes mellitus. However, it has important limitations; as it only reflects the average glycaemia over the last 3 months, it does not allow the identification of crucial events, such as episodes of hypoglycaemia and hyperglycaemia. Strict control of hyperglycaemia can result in severe hypoglycaemia that can be life threatening and can have important sequelae. Recently, the concept of glycaemic variability has been developed to provide information about the magnitude of glycaemic excursions and the duration of these fluctuations. This new approach has the potential to improve outcomes, decrease the risk of hypoglycaemia, and decrease cardiovascular risk. This review describes the most commonly prescribed non-insulin anti-diabetic drugs for diabetes management, their mechanism of action, and the existing evidence about their effectiveness in improving glycaemic variability and diabetes control.

Divergent effect of blood glucose dysregulation on long-term clinical outcome in acute decompensated heart failure: A reappraisal in contemporary practice

BACKGROUND

The prognostic implication of elevated or decreased blood glucose (BG) level in acute decompensated heart failure (ADHF) has been still controversial. Indices of stress hyperglycemia, expressed by the ratio of BG and chronic BG control, has been reported to be associated with poor outcome in different disease population. We sought to assess BG at admission and %ΔBG, an index of BG deviation from estimated average BG calculated from glycated hemoglobin (HbA1c), on the long-term outcome in ADHF patients.

METHODS AND RESULTS

The West Tokyo Heart Failure (WET-HF) Registry is a prospective multicenter registry enrolling consecutive hospitalized ADHF patients. Among the patients (N = 3078, 77 [67-84] years, male 59%), BG at admission discriminated the long-term (1000 days) incidence of ADHF rehospitalization, but not cardiac death. BG at admission showed a U-shape relationship with the long-term incidence of ADHF rehospitalization after adjustment for covariates. Especially, in patients with HbA1c ≥ 6.5%, the lowest quartile showed the highest risk of ADHF rehospitalization. On the contrary, %ΔBG showed U-shape relationship with the long-term incidence of cardiac death after discharge, rather than ADHF rehospitalization after adjustment for covariates. In addition, elevated %ΔBG was associated with the long-term risk of sudden cardiac death (SCD) even after adjustment for covariates.

CONCLUSIONS

For ADHF patients, BG at admission and %ΔBG might be a simple, useful tool for predicting and stratifying long-term risk of cardiac events. Especially, elevated %ΔBG might be an important in predicting hard events such as cardiac death or SCD.

Association between Variability of Metabolic Risk Factors and Cardiometabolic Outcomes

Despite strenuous efforts to reduce cardiovascular disease (CVD) risk by improving cardiometabolic risk factors, such as glucose and cholesterol levels, and blood pressure, there is still residual risk even in patients reaching treatment targets. Recently, researchers have begun to focus on the variability of metabolic variables to remove residual risks. Several clinical trials and cohort studies have reported a relationship between the variability of metabolic parameters and CVDs. Herein, we review the literature regarding the effect of metabolic factor variability and CVD risk, and describe possible mechanisms and potential treatment perspectives for reducing cardiometabolic risk factor variability.

Glycaemic variabilities: Key questions in pursuit of clarity

After years of intensive investigation, the definition of glycaemic variability remains unclear and the term variability in glucose homoeostasis might be more appropriate covering both short and long-term glycaemic variability. For the latter, we remain in the search of an accurate definition and related targets. Recent work leads us to consider that the within-subject variability of HbA1c calculated from consecutive determinations of HbA1c at regular time-intervals could be the most relevant index for assessing the long-term variability with a threshold value of 5% (%CV = SD of HbA1c/mean HbA1c) to separate stability from lability of HbA1c. Presently, no one can deny that short- and long-term glucose variability should be maintained within their lower ranges to limit the incidence of hypoglycaemia. Usually, therapeutic strategies aimed at reducing post-meal glucose excursions, i.e. the major contributor to daily glucose fluctuations, exert a beneficial effect on the short-term glucose variability. This explains the effectiveness of adjunct therapies with either GLP- receptor agonists or SGLT inhibitors in type 2 diabetes. In type 1 diabetes, the application of a CGM device alone reduces the short-term glycaemic variability. In contrast, sophisticated insulin delivery does not necessarily lead to such reductions despite marked downward shifts of 24-hour glycaemic profiles. Such contrasting observations raise the question as to whether the prolonged wear of CGM devices is or not the major causative factor for improvement in glucose variability among intensively insulin-treated persons with type 1 diabetes.

Effect of Add-On Therapy of Sodium-Glucose Cotransporter 2 Inhibitors and Dipeptidyl Peptidase 4 Inhibitors on Adipokines in Type 2 Diabetes Mellitus

Background

Excess adiposity is associated with an increased risk of cardiovascular disease due to metabolic changes in the body. Visceral obesity increases the risk of diabetes mellitus through adipocytokines and hence the effective targeting therapies are essential to control obesity in high-risk individuals. The study's main objective was to evaluate the effect of add-on therapy of sodium-glucose cotransporter 2 (SGLT2) inhibitors and dipeptidyl peptidase 4 (DPP4) inhibitors on visceral fat-associated serum adipokines.

Methods

The study included 90 subjects diagnosed with type 2 diabetes mellitus. The blood samples were taken before starting first-line therapy with metformin, 12 weeks after starting metformin therapy and 12 weeks after starting add-on therapy. Serum adipokines were analyzed with enzyme-linked immunosorbent assay (ELISA). Hemoglobin A1c (HbA1c) level was estimated with high-performance liquid chromatography (HPLC). The biochemical variables were measured using Cobas^® 6000 analyzer.

Results

The mean adiponectin level was significantly elevated with add-on therapy using SGLT2 inhibitors and DPP4 inhibitors (P < 0.001). The mean retinol binding protein 4 (RBP4), fatty acid binding protein 4 (FABP4) and visfatin levels were reduced considerably (P < 0.001). The SGLT2 inhibitors are more effective on serum FABP4 in patients with type 2 diabetes (P = 0.038). The mean fasting plasma glucose (FPG), postprandial blood glucose (PPBG) and HbA1c levels were reduced significantly with add-on therapy (P < 0.001). Lipid profile was also altered significantly with this add-on therapy (P < 0.001).

Conclusions

The results indicate that add-on therapy exerts a beneficial effect in type 2 diabetic patients insufficiently controlled with metformin only by altering the visceral fat-associated adipokine levels and controlling the metabolic activities.