Effect of glycemic variability on short term prognosis in acute myocardial infarction subjects undergoing primary percutaneous coronary interventions

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.

Impact of acute glycemic variability on short-term outcomes in patients with ST-segment elevation myocardial infarction: a multicenter population-based study

BACKGROUND

Given the increasing attention to glycemic variability (GV) and its potential implications for cardiovascular outcomes. This study aimed to explore the impact of acute GV on short-term outcomes in Chinese patients with ST-segment elevation myocardial infarction (STEMI).

METHODS

This study enrolled 7510 consecutive patients diagnosed with acute STEMI from 274 centers in China. GV was assessed using the coefficient of variation of blood glucose levels. Patients were categorized into three groups according to GV tertiles (GV1, GV2, and GV3). The primary outcome was 30-day all-cause death, and the secondary outcome was major adverse cardiovascular events (MACEs). Cox regression analyses were conducted to determine the independent correlation between GV and the outcomes.

RESULTS

A total of 7136 patients with STEMI were included. During 30-days follow-up, there was a significant increase in the incidence of all-cause death and MACEs with higher GV tertiles. The 30-days mortality rates were 7.4% for GV1, 8.7% for GV2 and 9.4% for GV3 (p = 0.004), while the MACEs incidence rates was 11.3%, 13.8% and 15.8% for the GV1, GV2 and GV3 groups respectively (p < 0.001). High GV levels during hospitalization were significantly associated with an increased risk of 30-day all-cause mortality and MACEs. When analyzed as a continuous variable, GV was independently associated with a higher risk of all-cause mortality (hazard ratio [HR] 1.679, 95% confidence Interval [CI] 1.005-2.804) and MACEs (HR 2.064, 95% CI 1.386-3.074). Additionally, when analyzed as categorical variables, the GV3 group was found to predict an increased risk of MACEs, irrespective of the presence of diabetes mellitus (DM).

CONCLUSION

Our study findings indicate that a high GV during hospitalization was significantly associated with an increased risk of 30-day all-cause mortality and MACE in Chinese patients with STEMI. Moreover, acute GV emerged as an independent predictor of increased MACEs risk, regardless of DM status.

Prevalence and associated factors of mortality after percutaneous coronary intervention for adult patients with ST-elevation myocardial infarction: A systematic review and meta-analysis

Background

There is a paucity of systematic reviews on the associated factors of mortality among ST-elevation myocardial infarction (STEMI) patients after percutaneous coronary intervention (PCI). This meta-analysis was designed to synthesize available evidence on the prevalence and associated factors of mortality after PCI for adult patients with STEMI.

Materials and Methods

Databases including the Cochrane Library, PubMed, Web of Science, Embase, Ovid, Scopus, ProQuest, MEDLINE, and CINAHL Complete were searched systematically to identify relevant articles published from January 2008 to March 2020 on factors affecting mortality after PCI in STEMI patients. Meta-analysis was conducted using Stata 12.0 software package.

Results

Our search yielded 91 cohort studies involving a total of 199, 339 participants. The pooled mortality rate for STEMI patients after PCI was 10%. After controlling for grouping criteria or follow-up time, the following 17 risk factors were significantly associated with mortality for STEMI patients after PCI: advanced age (odds ratio [OR] = 3.89), female (OR = 2.01), out-of-hospital cardiac arrest (OR = 5.55), cardiogenic shock (OR = 4.83), renal dysfunction (OR = 3.50), admission anemia (OR = 3.28), hyperuricemia (OR = 2.71), elevated blood glucose level (OR = 2.00), diabetes mellitus (OR = 1.8), chronic total occlusion (OR = 2.56), Q wave (OR = 2.18), without prodromal angina (OR = 2.12), delay in door-to-balloon time (OR = 1.72), delay in symptom onset-to-balloon time (OR = 1.43), anterior infarction (OR = 1.66), ST-segment resolution (OR = 1.40), and delay in symptom onset-to-door time (OR = 1.29).

Conclusion

The pooled prevalence of mortality after PCI for STEMI patients was 10%, and 17 risk factors were significantly associated with mortality for STEMI patients after PCI.

Perioperative blood glucose variability and autonomic nervous system activity in on-pump cardiac surgery patients: Study protocol of a single-center observational study

INTRODUCTION

On-pump coronary artery bypass graft (CABG) and surgical valve replacement (SVR) are high-risk procedures. Several studies reported that perioperative blood glucose (BG) variability was independently associated with impaired postoperative outcome. However, the underlying mechanisms contributing to increased perioperative BG variability and to its deleterious impact remain unknown. The hypothesis of the study is that perioperative BG variability could be related to perioperative alteration of the autonomic nervous system (ANS) activity and to preoperative BG variability.

METHODS AND ANALYSIS

We designed a prospective observational single-center study. Four groups of 30 patients will be studied: group 1, including insulin-requiring type 2 diabetic patients undergoing on-pump CABG; group 2, including non-insulin-requiring type 2 diabetic patients undergoing on-pump CABG; group 3, including non-diabetic patients undergoing aortic SVR; and group 4, including non-diabetic patient undergoing on-pump CABG. Preoperative (baseline) and postoperative BG variability will be quantified using the Abbott's Freestyle Libre Pro sensor allowing for continuous subcutaneous BG monitoring. Preoperative (baseline) and postoperative ANS activity will be measured using noninvasive continuous heart rate monitoring (Mooky HR memory®). Blood level and urinary concentration of inflammatory and endothelial dysfunction biomarkers will be measured from blood and urinary samples at the end of the surgery and on postoperative day 1 and 2. The primary objective is to describe the relationship between baseline BG variability and postoperative BG variability. The secondary objectives are to describe the relationship: between baseline and postoperative BG variability according to the diabetes phenotype and to the type of surgery; between the ANS activity and the BG variability; and between postoperative BG variability and, urinary and blood biomarkers.

Glycaemic variability and risk of adverse cardiovascular events in acute coronary syndrome

OBJECTIVE

The relationship between different glycaemic variability (GV) indexes and adverse cardiovascular outcomes is not well understood. This study aims to determine whether GV is related to the occurrence of adverse cardiovascular events in patients with acute coronary syndrome (ACS).

METHODS

PubMed, EMBASE, and Web of Science were comprehensively searched from the establishment of databases to 29 June 2022. The relationship between two important GV indexes, including the mean amplitude of glycemic excursion (MAGE) and standard deviation (SD), and the adverse cardiovascular events in ACS patients were evaluated, respectively.

RESULTS

A total of 11 studies with 3709 ACS patients were included. Pooled results showed that patients with higher GV had significantly increased risk of adverse cardiovascular events, including MAGE (relative risk [RR] = 1.76, 95% CI: 1.40 to 2.22, p < 0.001, I² = 25%) and SD (RR = 2.14, 95% CI: 1.73 to 2.66, p < 0.001, I² = 0%).

CONCLUSIONS

Increased GV is related to the poor prognosis in patients with ACS. Additionally, more well-designed studies comparing different indicators of GV with adverse cardiovascular events in ACS patients are still warranted.

Glycemic Variability Assessment with a 14-Day Continuous Glucose Monitoring System: When and How Long to Measure MAGE (Mean Amplitude of Glucose Excursion) for Optimal Reliability?

Mean amplitude of glucose excursion (MAGE) is considered as the "gold standard" for assessing the short-term within-day glycemic variability (GV), which is an important component of overall glycemic control. A 14-day continuous glucose monitoring system is now widely used and allows easier assessment of GV. However, it is still unknown whether MAGE, usually calculated on a 48-hour period is identical whatever the time during the 14-day lifespan of the sensor and whether a longer time period might give additional information. We evaluated in 68 patients with type 1 diabetes, MAGE during three 2-day periods (day1-day3; day6-day8; day11-day13) and during periods of 3 days and 4 days. MAGE calculated at the three 2-day periods were identical and not different from MAGE of the 3-day or 4-day periods.

Elevated Glycated Albumin in Serum Is Associated with Adverse Cardiac Outcomes in Patients with Acute Coronary Syndrome Who Underwent Revascularization Therapy

AIMS

The associations between increased glycated albumin (GA) in the serum and diabetic complications and mortality have been revealed in the general population. However, less is known regarding the prognostic value of GA in patients diagnosed with acute coronary syndrome (ACS).

METHODS

In this study, all patients admitted for ACS who underwent a successful percutaneous coronary intervention (PCI) at our center from January 2018 to February 2019 were retrospectively examined. Clinical characteristics, laboratory results (e.g., serum GA levels), and procedural details were collected. The primary outcome included a composite of major adverse cardio-cerebral events (MACCE), such as death, myocardial infarction, stroke, and unplanned revascularization. The association between serum GA levels and clinical outcomes was tested in three multivariable models using Cox proportional hazard analysis. Subgroup analysis was performed in patients who were diagnosed with diabetes versus patients without diabetes.

RESULTS

A total of 1,806 ACS patients (mean age of 59.4 years; 77.8% were men; 44.9% were diagnosed with diabetes) were enrolled in this study, where the majority exhibited unstable angina (81.6%) and showed preserved left ventricular systolic function. Patients in the high GA level group were commonly female and were more likely to have metabolic disorders and to exhibit severe CAD (all p＜0.05). MACCE occurred in 126 patients (7.0%) during a mean follow-up time of 17.2 months. The cumulative risk of MACCE at the 18-month follow-up visit significantly increased in a stepwise fashion along with increased GA levels (log-rank p=0.018) in the serum. The association between serum GA levels and MACCE was further determined after adjusting traditional risk factors and hemoglobin A1c (HbA1c) (GA, per 1% increase: hazard ratio [HR] 1.09, 95% confidence interval [CI] 1.06-1.13; GA, higher vs. lower tertial: HR 1.92, 95% CI 1.01-3.67). In a subgroup analysis, the prognostic role of serum GA only existed in diabetic patients, even when adjusting for traditional risk factors and HbA1c levels.

CONCLUSIONS

Elevated GA levels in the serum were associated with poor intermediate-term outcomes in low-risk ACS patients who underwent PCI, especially in patients with preexisting diabetes.

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.

Associations of hypoglycemia, glycemic variability and risk of cardiac arrhythmias in insulin-treated patients with type 2 diabetes: a prospective, observational study

Background

Insulin-treated patients with type 2 diabetes (T2D) are at risk of hypoglycemia, which is associated with an increased risk of cardiovascular disease and mortality. Using a long-term monitoring approach, we investigated the association between episodes of hypoglycemia, glycemic variability and cardiac arrhythmias in a real-life setting.

Methods

Insulin-treated patients with T2D (N = 21, [mean ± SD] age 66.8 ± 9.6 years, BMI 30.1 ± 4.5 kg/m², HbA1c 6.8 ± 0.4% [51.0 ± 4.8 mmol/mol]) were included for a one-year observational study. Patients were monitored with continuous glucose monitoring ([mean ± SD] 118 ± 6 days) and an implantable cardiac monitor (ICM) during the study period.

Results

Time spend in hypoglycemia was higher during nighttime than during daytime ([median and interquartile range] 0.7% [0.7–2.7] vs. 0.4% [0.2–0.8]). The ICMs detected 724 episodes of potentially clinically significant arrhythmias in 12 (57%) participants, with atrial fibrillation and pauses accounting for 99% of the episodes. No association between hypoglycemia and cardiac arrhythmia was found during daytime. During nighttime, subject-specific hourly incidence of cardiac arrhythmias tended to increase with the occurrence of hypoglycemia (incident rate ratio [IRR] 1.70 [95% CI 0.36–8.01]) but only slightly with increasing time in hypoglycemia (IRR 1.04 [95% CI 0.89–1.22] per 5 min). Subject-specific incidence of cardiac arrhythmias during nighttime increased with increasing glycemic variability as estimated by coefficient of variation whereas it decreased during daytime (IRR 1.33 [95% CI 1.05–1.67] and IRR 0.77 [95% CI 0.59–0.99] per 5% absolute increase, respectively).

Conclusions

Cardiac arrhythmias were common in insulin-treated patients with T2D and were associated with glycemic variability, whereas arrhythmias were not strongly associated with hypoglycemia.

Trial registration: NCT03150030, ClinicalTrials.gov, registered May 11, 2017. https://clinicaltrials.gov/ct2/show/NCT03150030

Supplementary Information

The online version contains supplementary material available at 10.1186/s12933-021-01425-0.

Association between visit-to-visit variability of glycemic indices and lipid profile and the incidence of coronary heart disease in adults with type 2 diabetes

Coronary heart disease (CHD) is one of the major causes of mortality and morbidity in patients with type 2 diabetes mellitus. In this study, we aimed to assess the association between visit-to-visit variability of fasting blood sugar (FBS), HbA1c, blood sugar 2 h post-prandial (BS2hpp), lipid indices, creatinine, systolic and diastolic blood pressure (SBP, DBP) and incident CHD in patients with type 2 diabetes during a median follow-up of ten years. The current case-cohort study consisted of 1500 individuals with type 2 diabetes, followed up for the occurrence of CHD from 2002 to 2019. The patients had at least four annual follow-ups during which glycemic and lipid profile were measured. Co-efficient of variance (CV) for each parameter was calculated by 10-21 measurements. Cox regression analysis was performed to assess the association between CV of glycemic indices, lipid profile, blood pressure, creatinine, weight and incident CHD during the follow-up period. Hazard ratios (HR) were adjusted for the confounding variables. Glycemic indices variability (i.e., CV-HbA1c, CV-FBS, and CV-BS2hpp), were significantly higher in the group with incident CHD (P=0.034, P=0.042, and P=0.044, respectively). Hazard ratios were 1.42 (95 % CI=1.13-2.09) for CV-HbA1c, 1.37 (95 % CI=1.02-2.10) for CV-FBS, and 1.16 (95 % CI=1.01-1.63) for CV-BS2hpp (P=0.012, P=0.046, P=0.038, respectively). Creatinine was significantly higher in the group with incident CHD (P=0.036) and it was significantly associated with higher incidence of CHD (HR=1.14, 95 % CI=1.02-2.17, P=0.048). Visit to visit variability of glycemic indices of the patients with type 2 diabetes is associated with incident CHD independent of their baseline and mean values.

Association between Changes in the Systolic Blood Pressure from Evening to the Next Morning and Night Glucose Variability in Heart Disease Patients

Objectve To assess the impact of glycemic variability on blood pressure in hospitalized patients with cardiac disease. Methods In 40 patients with cardiovascular disease, the glucose levels were monitored by flash continuous glucose monitoring (FGM; Free-Style Libre™ or Free-Style Libre Pro; Abbott, Witney, UK) and self-monitoring blood glucose (SMBG) for 14 days. Blood pressure measurements were performed twice daily (morning and evening) at the same time as the glucose level measurement using SMBG. Results The detection rate of hypoglycemia using the FGM method was significantly higher than that with the 5-point SMBG method (77.5% vs. 5.0%, p<0.001). Changes in the systolic blood pressure from evening to the next morning [morning - evening (ME) difference] were significantly correlated with night glucose variability (r=0.63, P<0.001). A multiple regression analysis showed that night glucose variability using FGM was more closely correlated with the ME difference [r=0.62 (95% confidence interval, 0.019-0.051); p<0.001] than with the age, body mass index, or smoking history. Night glucose variability was also more closely associated with the ME difference in patients with unstable angina pectoris (UAP) than in those with acute myocardial infarction (AMI) or heart failure (HF) (r=0.83, p=0.058). Conclusion Night glucose variability is associated with the ME blood pressure difference, and FGM is more accurate than the 5-point SMBG approach for detecting such variability.

The Role of Glycemic Variability in Cardiovascular Disorders

Diabetes mellitus (DM) is one of the most common and costly disorders that affect humans around the world. Recently, clinicians and scientists have focused their studies on the effects of glycemic variability (GV), which is especially associated with cardiovascular diseases. In healthy subjects, glycemia is a very stable parameter, while in poorly controlled DM patients, it oscillates greatly throughout the day and between days. Clinically, GV could be measured by different parameters, but there are no guidelines on standardized assessment. Nonetheless, DM patients with high GV experience worse cardiovascular disease outcomes. In vitro and in vivo studies showed that high GV causes several detrimental effects, such as increased oxidative stress, inflammation, and apoptosis linked to endothelial dysfunction. However, the evidence that treating GV is beneficial is still scanty. Clinical trials aiming to improve the diagnostic and prognostic accuracy of GV measurements correlated with cardiovascular outcomes are needed. The present review aims to evaluate the clinical link between high GV and cardiovascular diseases, taking into account the underlined biological mechanisms. A clear view of this challenge may be useful to standardize the clinical evaluation and to better identify treatments and strategies to counteract this DM aspect.

Coronary Flow Reserve and Glycemic Variability in Patients with Coronary Artery Disease

Objective Glycemic variability is being increasingly recognized as an early indicator of glucose metabolic disorder and may contribute to the development of diabetic vascular complications, such as coronary microvascular dysfunction. The present study sought to investigate the relationship between coronary microvascular function assessed by intracoronary thermodilution method and glycemic variability on a continuous glucose monitoring system (CGMS). Methods We prospectively enrolled 40 patients with or without known diabetes mellitus who had epicardial coronary artery disease referred for coronary angiography and were not treated with diabetic medications. Of these, two had a significant stenosis in the left main coronary artery and were therefore excluded from the analyses. In the end, 38 patients were equipped with a CGMS and underwent intracoronary physiological assessments in the unobstructed left anterior descending artery. The mean amplitude of glycemic excursion (MAGE) and standard deviation were calculated from the obtained CGMS data as indicators of glucose variability. Results Coronary flow reserve (CFR) was negatively correlated with MAGE (r=-0.328, p=0.044) and standard deviation (r=-0.339, p=0.037) on CGMS, while the index of microcirculatory resistance showed no such correlation. Multivariable linear regression analyses showed that MAGE on CGMS was significantly associated with CFR after adjusting for age, sex, fractional flow reserve and hemoglobin A1c. Conclusion Higher MAGE on CGMS was associated with reduced CFR in stable patients with coronary artery disease, suggesting a potential effect of glycemic variability on coronary microvascular flow regulation. A further study with a larger sample size needs to be conducted to confirm our findings.

Inhibitory Effect of Sargassum fusiforme and Its Components on Replication of Respiratory Syncytial Virus In Vitro and In Vivo

Sargassum fusiforme, a plant used as a medicine and food, is regarded as a marine vegetable and health supplement to improve life expectancy. Here, we demonstrate that S. fusiforme extract (SFE) has antiviral effects against respiratory syncytial virus (RSV) in vitro and in vivo mouse model. Treatment of HEp2 cells with a non-cytotoxic concentration of SFE significantly reduced RSV replication, RSV-induced cell death, RSV gene transcription, RSV protein synthesis, and syncytium formation. Moreover, oral inoculation of SFE significantly improved RSV clearance from the lungs of BALB/c mice. Interestingly, the phenolic compounds eicosane, docosane, and tetracosane were identified as active components of SFE. Treatment with a non-cytotoxic concentration of these three components elicited similar antiviral effects against RSV infection as SFE in vitro. Together, these results suggest that SFE and its potential components are a promising natural antiviral agent candidate against RSV infection.

Glucose Variability is Independently Correlated with Serum Level of Pigment Epithelium-Derived Factor in Type 2 Diabetes

INTRODUCTION

Pigment epithelium-derived factor (PEDF) may play a role in cardiometabolic disorders. The aim of this study was to investigate which biochemical and clinical parameters are independently associated with serum PEDF levels in patients with type 2 diabetes mellitus (T2DM).

METHODS

We performed a cross-sectional analysis of 124 patients with T2DM who underwent continuous glucose monitoring (CGM) and blood chemistry analysis, including the diacron-reactive oxygen metabolites (d-ROMs) test and serum PEDF measurement (study 1). Then we investigated whether the changes in the studied biochemical and clinical parameters after 24 weeks of treatment (Δparameters) with anti-hyperglycemic agents, including sodium-glucose cotransporter 2 inhibitors, glucagon-like peptide 1 receptor agonists, and/or insulin and anti-hypertensive drugs and statins, were independently correlated with change in PEDF (ΔPEDF) in 52 of the patients with T2DM for whom there was sufficient serum samples to perform the post-treatment analysis (study 2). Serum levels of PEDF were measured with an enzyme-linked immunosorbent assay. CGM metrics were calculated on days 2 and 3. Oxidative stress was evaluated using the d-ROMs test.

RESULTS

Body mass index (BMI), triglycerides, fasting C-peptide, mean amplitude of glycemic excursions (MAGE), urinary albumin-to-creatinine ratio (UACR), and d-ROMs were positively associated with serum PEDF level, and high-density lipoprotein cholesterol (HDL-C) and estimated glomerular filtration rate (eGFR) were inversely associated with serum PEDF level. Because these parameters were correlated with each other, multivariate stepwise analysis was performed: eGFR, HDL-C, BMI, MAGE, and UACR remained significant (R² = 0.452). Furthermore, ΔMAGE and Δd-ROMs were positively correlated with ΔPEDF in study 2.

CONCLUSIONS

The results of this study suggest that MAGE may be independently correlated with elevations in serum PEDF level in patients with T2DM.

Type 2 Diabetes and the Use of Real-Time Continuous Glucose Monitoring

The role of continuous glucose monitoring (CGM) in type 1 diabetes (T1D) is well established in improving glycemic control and reducing hypoglycemia. Type 2 diabetes (T2D) is more prevalent than T1D and management of T2D is more heterogeneous, requiring treatment ranging from lifestyle modification to oral medications to intensive insulin therapy. Recent randomized controlled trials in intensively insulin-treated T2D demonstrated the efficacy and safety of real-time CGM (rtCGM) in reducing glycated hemoglobin without increasing hypoglycemia. Although evidence is limited, early studies have indicated a role for rtCGM in selected patients with non-insulin requiring T2D to improve glycemic control and/or reduce hypoglycemia. Based on literature review, we summarized current data on the use of rtCGM in T2D management and provided future research direction to generate more evidence on the utility of CGM in this population.

Postload glucose spike but not fasting glucose determines prognosis after myocardial infarction in patients without known or newly diagnosed diabetes

BACKGROUND

The effect of postload glucose spikes (PGS), the difference between 2 hour post-load plasma glucose (2hPLPG) and fasting plasma glucose (FPG), on post-myocardial infarction (post-MI) prognosis in nondiabetic patients is unexplored.

METHODS

This is a retrospective cohort analysis of 847 nondiabetic post-MI survivors who underwent a predischarge oral glucose tolerance test (median PGS: 2.4 mmol/L). Patients were divided into the unmatched groups 1 and 2 (PGS ≤ and > 2.4 mmol/L) and the propensity score-matched groups 1M and 2M (355 pairs assembled from the overall cohort), and these groups were compared. Major adverse cardiac events (MACE: death and nonfatal reinfarction) were recorded during follow-up (median: 3.4 years). Event-free survival was compared by the Kaplan-Meier method. Multivariate Cox proportional hazards regression determined the predictors of MACE. C-statistics (change in area under the curve, δAUC), continuous net reclassification improvement (NRI^>0 ), and integrated discrimination improvement (IDI) were used to compare models.

RESULTS

The number of MACE was higher in groups 2 (27.3% vs 14.2%, P < .001) and 2M (24.5% vs 15.5%, P < .001). Event-free survival was worse in groups 2 (hazard ratio [HR] 2.01; 95% CI, 1.49-2.71; P < .001) and 2M (HR 1.63; 95% CI, 1.17-2.27; P = .004). PGS independently predicted MACE-free survival in the whole (HR 1.16; 95% CI, 1.06-1.26; P = .002) and matched cohort (HR 1.12; 95% CI, 1.02-1.24; P = .021). PGS, but not FPG or 2hPPG, improved the predictive performance of the base model (δAUC 0.013, P = .046), with greater improvement seen when PGS was added and compared to 2hPPG (δAUC 0.005, P = .034; NRI^>0 0.2107, P = .013; IDI 0.0042, P = .046).

CONCLUSION

PGS is a better predictor of post-MI prognosis than 2hPPG in nondiabetic patients.

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.

Acute glycemic variability on admission predicts the prognosis in hospitalized patients with coronary artery disease: a meta-analysis

PURPOSE

Increased glycemic variability has been related with poor prognosis in patients with coronary artery disease (CAD). However, whether diabetic status or subtype of CAD could affect the association remains unknown. We performed a meta-analysis to systematically evaluate the association between the mean amplitude of glycemic excursions (MAGE) on continuous glucose monitoring and the incidence of major adverse cardiovascular events (MACEs) in CAD patients.

METHODS

Relevant prospective cohort studies were identified through search of PubMed, Embase, WanFang, and CNKI databases. A random-effect model was used to pool the results. Subgroup analyses were performed to evaluate the influences of the predefined study characteristics on the outcome.

RESULTS

Eleven cohort studies with 2666 hospitalized patients with acute coronary syndrome (ACS) or stable CAD for percutaneous coronary intervention were included. Pooled results showed that higher MAGE at admission was associated with higher incidence of MACEs during follow-up (adjusted relative risk [RR]: 1.84, p < 0.001; I² = 12%). Stratified analyses showed that the association between higher MAGE and higher risk of MACEs in CAD patients were consistent in patients with or without diabetes, and in those with ACS or stable CAD (p for subgroup difference both >0.05). Significant publication bias was detected (p = 0.041). Trim-and-fill analysis retrieved three studies to generate symmetrical funnel plots. Meta-analysis that incorporated these studies showed similar results (RR: 1.80, p < 0.001).

CONCLUSIONS

Increased glycemic variability may be associated with poor prognosis in CAD patients regardless of the diabetic status and the subtype of CAD.

Increased Glucose Variability Is Associated With Major Adverse Events After Coronary Artery Bypass

BACKGROUND

Elevated preoperative hemoglobin A_1c (HbA_1c) is a predictor of poor outcomes after coronary artery bypass grafting (CABG), but the role of postoperative glucose variability (GV) is unknown. We hypothesized that short-term postoperative GV is associated with major adverse events (MAEs) after isolated CABG.

METHODS

This retrospective study evaluated 2215 patients who underwent isolated CABG from January 2012 to March 2018 at 2 medical centers. Postoperative GV in the first 12 hours and 24 hours was measured by the SD, coefficient of variation, and mean amplitude of glycemic excursions. The primary outcome (MAEs) was the composite of postoperative cardiac arrest, pneumonia, renal failure, stroke, sepsis, reoperation, and 30-day mortality. Multivariate logistic regression assessed the independent association of GV with MAE.

RESULTS

A total of 2215 patients met the study criteria, and an MAE developed in 260 patients (11.7%). High 12-hour and 24-hour postoperative GV were associated with elevated HbA_1c, insulin-dependent diabetes, renal failure, and nonelective operation. Multivariate logistic regression analysis showed MAEs were associated with increased mean postoperative glucose in the first 12 hours (odds ratio [OR], 1.013; 95% confidence interval [CI], 1.008-1.018; P < .001), the first 24 hours (OR, 1.017; 95% CI, 1.010-1.024; P < .001), and 24-hour postoperative GV (OR, 1.22; 95% CI, 1.09-1.37; P < .001). MAEs were not associated with preoperative HbA_1c or 12-hour postoperative GV.

CONCLUSIONS

Increased 24-hour but not 12-hour postoperative GV after CABG is a predictor of poor outcomes. Preoperative HbA_1c is not associated with MAEs after adjusting for postoperative mean glucose and GV.

Glycaemic variability is associated with severity of coronary artery disease in patients with poorly controlled type 2 diabetes and acute myocardial infarction

BACKGROUND

In patients with type 2 diabetes (T2D), glycaemic variability (GV), another component of glycaemic abnormalities, is a novel potentially aggravating factor for coronary artery disease (CAD).

OBJECTIVES

The aim of our study was to identify interactions between GV and severity of CAD in diabetes patients admitted for acute myocardial infarction (AMI).

METHODS

All patients with T2D admitted to our university hospital for AMI from March 2015 to February 2017 who received intravenous (IV) insulin therapy and underwent coronary angiography were included. GV was assessed by mean amplitude of blood glucose excursion (MAGE) values taken within 2 days of admission. Patients with higher GV (highest MAGE tertile) were compared with those with lower GV (first and second MAGE tertiles).

RESULTS

A total of 204 patients were included: median age was 72 (61-81) years; 32% were female; HbA_1c was 7.3% (6.4-8.2%); diabetes duration was 10 (2-17.5) years; and MAGE value was 0.65 (0.43-0.92) g/L. Compared with those with lower GV, patients with the highest GV were more often women, treated with previous insulin, and had higher blood glucose and HbA_1c levels. In addition, patients with elevated GV had significantly higher SYNTAX scores: 17 (10-28) vs. 12 (6-22) (P = 0.009). Indeed, SYNTAX scores (OR: 1.05, 95% CI: 1.02-1.08; P = 0.001) remained independently associated with high GV beyond HbA_1c levels (OR: 1.51, 95% CI: 1.2-1.89; P <  0.001).

CONCLUSION

In AMI patients with poorly controlled diabetes, GV is associated with CAD severity beyond chronic hyperglycaemia. Although no causality can be determined from our observational study, the results suggest that, in AMI, early evaluation of GV might contribute to the identification of those diabetes patients at high risk, and serve as a therapeutic target for both primary and secondary prevention.

Glycemic variability in the development of cardiovascular complications in diabetes

Diabetes mellitus represents a major risk factor for the development of coronary artery disease and other vascular complications. Glycated haemoglobin, fructosamine, and fasting blood glucose levels are partial parameters to exhaustively describe patient dysglycemic status. Thus, recently the new concept of glycemic variability has emerged, including information about two major aspects: the magnitude of blood glucose excursions (from nadir to peak, thus lower and higher spikes) and the time intervals in which these fluctuations occur. Despite the lack of consensus regarding the most appropriate definition and tools for its assessment, glycemic variability seems to have more deleterious effects than sustained hyperglycemia in the pathogenesis of diabetic cardiovascular complications. This manuscript aimed to review the most recent evidence on glycemic variability and its potential use in everyday clinical practice to identify diabetic patients at higher risk of cardiovascular complications and thus needing stricter monitoring and treatment.

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.

Investigation of glucose fluctuations by approaches of multi-scale analysis

Glucose variability provides detailed information on glucose control and fluctuation. The aim of this study is to investigate the glucose variability by multi-scale analysis approach on 72-h glucose series captured by continuous glucose monitoring system (CGMS), gaining insights into the variability and complexity of the glucose time series data. Ninety-eight type 2 DM patients participated in this study, and 72-h glucose series from each subject were recorded by CGMS. Subjects were divided into two subgroups according to the mean amplitude of glycemic excursions (MAGE) value threshold at 3.9 based on Chinese standard. In this study, we applied two types of multiple scales analysis methods on glucose time series: ensemble empirical mode decomposition (EEMD) and refined composite multi-scale entropy (RCMSE). With EEMD, glucose series was decomposed into several intrinsic mode function (IMF), and glucose variability was examined on multiple time scales with periods ranging from 0.5 to 12 h. With RCMSE, complexity of the structure of glucose series was quantified at each time scale ranging from 5 to 30 min. Subgroup with higher MAGE value (>3.9) presented higher glycemic baseline and variability. There were significant differences in glycemic variability on IMFs3-5 between subgroups with MAGE>3.9 and MAGE < = 3.9 (p<0.001), but no significant differences in variability on IMFs1-2. The complexity of glucose series quantified by RCMSE showed statistically difference on each time scale from 5 to 30 min between subgroups (p<0.05). Glucose series from subjects with higher MAGE value represented higher variability but lower complexity on multiple time scales. Compared with traditional matrices measuring the glucose variability, approaches of EEMD and RCMSE can quantify the dynamic glycemic fluctuation in multiple time scales and provide us more detailed information on glycemic variability and complexity.

Effects of the Mean Amplitude of Glycemic Excursions and Vascular Endothelial Dysfunction on Cardiovascular Events in Nondiabetic Patients With Coronary Artery Disease

Background

Mean amplitude of glycemic excursion (MAGE) is commonly used to gauge the degree of glucose level fluctuations. MAGE plays a significant role in vascular endothelial dysfunction and cardiovascular events in patients with diabetes mellitus (DM), but its significance is not clear in non‐DM patients. Thus, we examined the impact of MAGE and vascular endothelial dysfunction on clinical outcomes in non‐DM patients with coronary artery disease.

Methods and Results

We followed non‐DM patients (n=65) for 12 months who underwent percutaneous coronary intervention and assessed the relationship among MAGE, reactive hyperemia index (RHI) measured by reactive hyperemia peripheral arterial tonometry as endothelial function, and cardiovascular events. Cardiovascular events analyzed were cardiovascular death, myocardial infarction, unstable angina, and revascularizations. Compared with patients with MAGE <65 mg/dL (normal glycemic excursions), the group with MAGE ≥65 mg/dL (high glycemic excursions) had significantly higher high‐sensitivity C‐reactive protein (0.10±0.11 mg/dL versus 0.18±0.13 mg/dL, P=0.006) and lower RHI (0.64±0.21 versus 0.51±0.22, P=0.035). The multivariable analysis identified high MAGE and low RHI (≤0.56) as risk factors associated with cardiovascular events (hazard ratio, 5.6; 95% RI, 1.72–18.4 [P=0.004] versus hazard ratio, 4.5; 95% RI, 1.37–14.9 [P=0.013]). When the prognosis was classified by combination with MAGE and RHI, the incidence of cardiovascular events was 46.7% (high MAGE+low RHI), 26.7% (high MAGE+high RHI), 20.0% (low MAGE+low RHI), and 6.6% (low MAGE+high RHI) in descending order (P=0.014). Receiver operating characteristic curve analysis revealed that MAGE, RHI, and MAGE+RHI were each associated with cardiovascular events (area under the curve 0.780, 0.727, and 0.796, respectively).

Conclusions

MAGE was associated with cardiovascular events in non‐DM patients with coronary artery disease. Furthermore, the combination with MAGE and RHI was useful for further subdivision of the risk of cardiovascular events.

Poststroke glycemic variability increased recurrent cardiovascular events in diabetic patients

BACKGROUND AND PURPOSE

The association between blood glucose fluctuation and poststroke cardiovascular outcome has been largely unknown. This study attempted to evaluate whether initial glycemic variability increases cardiovascular events and mortality in diabetic patients with acute ischemic stroke.

METHODS

We recruited consecutive patients with acute ischemic stroke or transient ischemic attack from March 2005 to December 2014. A total of 674 patients with diabetes within 72 hours from stroke onset were included. The serum glucose levels were checked 4 times per day during the initial 3 hospital days. J-index, coefficients of variation and standard deviation were calculated for glycemic variability. Composite outcome (nonfatal stroke, nonfatal myocardial infarction, cardiovascular death) and all-cause mortality at 3 months were prospectively captured. Multivariable logistic regression analyses were done adjusting for covariates which can influence on cardiovascular outcomes.

RESULTS

Cardiovascular composite outcomes at 3 months were identified in 71 (10.5%): 11 (6.5%), 15 (8.9%), 18 (10.7%) and 27 (16.0%) in each J-index quartiles (P = .035). The highest quartile of J-index had significantly higher cardiovascular death (4.2%, 3.6%, 6.5% and 11.8%; P = .008). In multivariable logistic regression, age (odds ratio [OR] 1.045; 95% confidence interval [CI] 1.006-1.084), P = .021), NIH stroke scale (OR 1.078; 95% CI 1.024-1.134, P = .004), and the highest J-index (OR 12.058; 95% 1.890-76.912, P = .008) were significantly associated with 3-month cardiovascular composite outcome. Increased cardiovascular outcomes in highest J-index quartile were similar in both euglycemic and hyperglycemic groups.

CONCLUSION

The initial glycemic variability might increase cardiovascular events in acute ischemic stroke patients with diabetes.

Alpha2A adrenergic receptor genetic variation contributes to hyperglycemia after myocardial infarction

BACKGROUND

Acute myocardial infarction (AMI) is frequently associated with transient hyperglycemia even in patients without pre-existing diabetes. Acute stress can lead to increased blood glucose through the effect of catecholamines on alpha2A-adrenergic receptors (α2A-ARs) present in pancreatic islet β-cells. Variation in the gene (ADRA2A) that encodes the α2A-AR affects insulin release and glucose control and may play a particularly important role during times of stress.

METHODS

We performed a retrospective cohort study using de-identified electronic medical records linked to a DNA repository in 521 Caucasians and 55 African-American non-diabetic patients with AMI. We examined the association between admission blood glucose concentrations and ten selected ADRA2A SNPs in Caucasians.

RESULTS

Three ADRA2A SNPS were associated with stress-induced hyperglycemia in Caucasians. Individuals homozygous for the rs10885122 variant (n=9) had a 23% lower admission glucose (geometric mean [95% CI], 99 [83-118]mg/dl) compared with non-carriers (121 [118-125] mg/dl; n=401; P=0.001). Admission glucose was 14% higher in rs1800544 variant homozygotes (134 [119-150]mg/dl; n=36) compared to non-carriers (118 [115-121]mg/dl; n=290, P=0.046). Furthermore, homozygotes of the rs553668 variant (n=13) had a 13% higher glucose (133 [110-160]mg/dl) compared to non-carriers (118 [115-122]mg/dl; n=366; P=0.056). Haplotypes including these ADRA2A SNPs were associated with higher admission glucose levels.

CONCLUSIONS

Three ADRA2A genetic variants are associated with blood glucose and stress-induced hyperglycemia after AMI in Caucasians.

The Impact of Hypoglycemia on the Cardiovascular System: Physiology and Pathophysiology

Intensive glycemic control may increase cardiovascular (CV) risk and mortality due to hypoglycemia. The pathophysiology of glucose counter-regulation in patients with type 1 or type 2 diabetes for over 15 years is characterized by impairment of the defense mechanisms against hypoglycemia. Hypoglycemia causes pronounced physiological and pathophysiological effects on the CV system as consequences of autonomic system activation and counter regulatory hormones release. These effects provoke a series of hemodynamic changes that include an increase in heart rate and peripheral systolic blood pressure, a decrease in central blood pressure, reduced peripheral arterial resistance, and increased myocardial contractility and cardiac output. Cardiac electrophysiological changes including flattening or inversion of T waves, QT prolongation, and ST segment depression were observed in both insulin-induced and spontaneous hypoglycemia. Sympathoadrenal activation is the main cause of these changes through mechanisms that involve, but are not limited to, catecholamine-mediated hypokalemia. Hypoglycemia is also involved in platelet activation. There is growing concern about the long-term effects of hypoglycemia, especially as related to inflammation and atherogenesis.

Early glucose variability in cardiogenic shock following acute myocardial infarction: a pilot study

Background:

No data are so far available on the association between glycaemic variability and outcomes in patients with cardiogenic shock (CS) following ST elevation myocardial infarction (STEMI).

Methods:

We assessed the relationship between glycaemic variability and mortality, both short term and long term, in 67 consecutive patients with cardiogenic shock following STEMI admitted to our Intensive Cardiac Care Unit. Glycaemic variability was measured in the first 48 h by means of standard deviation (SD) of glucose values and the mean absolute glucose change per hour (MAGC) defined as the sum of all absolute glucose change divided by the time in hours.

Results:

Lower glycaemic variability was observed in survivors when compared with nonsurvivors, as indicated by lower values of SD and MAGC, respectively. In Cox regression analysis, MAGC and SD were independent predictors of death (MAGC: adjusted hazard ratio [HR]: 8.60, 95% confidence interval [CI]: 2.21–33.41, p = 0.002; SD: adjusted HR: 6.64, 95% CI: 1.92–22.99, p = 0.003), as well as peak glycaemia (adjusted HR: 1.95, 95% CI: 1.20–3.15, p = 0.007).

Conclusions:

According to our results, in patients with CS following acute myocardial infarction, early glycaemic variability is an independent predictor of mortality. Further studies are needed to confirm our results in larger cohorts and eventually to assess the effect of strategies specifically targeting glucose variability reduction on mortality.