The Role of Glycemic Variability in Cardiovascular Disorders.
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ABSTRACT:
SUBMITTER: Alfieri V
PROVIDER: S-EPMC8395057 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Glycemic control and its benefits in preventing microvascular diabetic complications are convincingly proved by various prospective trials. Diabetes control and complications trial (DCCT) had reported variable glycated hemoglobin (HbA1C) as a cause of increased microvascular complications in conventional glycemic control group versus intensive one. However, in spite of several indirect evidences, its link with cardiovascular events or macrovascular complications is still not proved. Glycemic variability (GV) is one more tool to explain relation between hyperglycemia and increased cardiovascular risk in diabetic patients. In fact GV along with fasting blood sugar, postprandial blood sugar, HbA1C, and quality of life has been proposed to form glycemic pentad, which needs to be considered in diabetes management. Postprandial spikes in blood glucose as well as hypoglycemic events, both are blamed for increased cardiovascular events in Type 2 diabetics. GV includes both these events and hence minimizing GV can prevent future cardiovascular events. Modern diabetes management modalities including improved sulfonylureas, glucagon like peptide-1 (GLP-1)-based therapy, newer basal insulins, and modern insulin pumps address the issue of GV effectively. This article highlights mechanism, clinical implications, and measures to control GV in clinical practice.
| S-EPMC3743360 | biostudies-other
Project description:The growing popularity of medical and recreational consumption of cannabis, especially among the youth, raises immediate concerns regarding its safety and long-terms effects. The cardiovascular effects of cannabis are not well known. Cannabis consumption has been shown to cause arrhythmia including ventricular tachycardia, and potentially sudden death, and to increase the risk of myocardial infarction (MI). These effects appear to be compounded by cigarette smoking and precipitated by excessive physical activity, especially during the first few hours of consumption. Cannabinoids, or the active compounds of cannabis, have been shown to have heterogeneous effects on central and peripheral circulation. Acute cannabis consumption has been shown to cause an increase in blood pressure, specifically systolic blood pressure (SBP), and orthostatic hypotension. Cannabis use has been reported to increase risk of ischemic stroke, particularly in the healthy young patients. The endocannabinoid system (ECS) is currently considered as a promising therapeutic target in the management of several disease conditions. Synthetic cannabinoids (SCs) are being increasingly investigated for their therapeutic effects; however, the value of their benefits over possible complications remains controversial. Despite the considerable research in this field, the benefits of cannabis and its synthetic derivatives remains questionable even in the face of an increasingly tolerating attitude towards recreational consumption and promotion of the therapeutic complications. More efforts are needed to increase awareness among the public, especially youth, about the cardiovascular risks associated with cannabis use and to disseminate the accumulated knowledge regarding its ill effects.
| S-EPMC5542986 | biostudies-other
Project description:BackgroundHbA1c variability has emerged as risk factor for cardiovascular diseases in diabetes. However, the impact of HbA1c variability on cardiovascular diseases in subjects within the recommended HbA1c target has been relatively unexplored.MethodsUsing data from a large database, we studied 101,533 people with type 2 diabetes without cardiovascular diseases. HbA1c variability was expressed as quartiles of the standard deviation of HbA1c during three years (exposure phase). The primary composite outcome included non-fatal myocardial infarction, non-fatal stroke, all-cause mortality and was assessed during five years following the first three years of exposure to HbA1c variability (longitudinal phase). An expanded composite outcome including non-fatal myocardial infarction, non-fatal stroke, coronary revascularization/reperfusion procedures, peripheral revascularization procedures, and all-cause mortality was also considered, as well as a series of specific cardiovascular complications. Cox models were adjusted for a large range of risk factors and results were expressed as adjusted hazard ratios.ResultsAn association between HbA1c variability and all the outcomes considered was found. The correlation between HbA1c variability and cardiovascular complications development was confirmed in both the subgroups of subjects with a mean HbA1c ≤ 53 mmol/mol (recommended HbA1c target) or > 53 mmol/mol during the exposure phase. The risk related to HbA1c variability was higher in people with mean HbA1c ≤ 53 mmol/mol for the primary outcome (p for interaction 0.004), for the expanded secondary outcome (p for interaction 0.001) and for the stroke (p for interaction 0.001), even though HbA1c remained at the target during the follow-up.ConclusionsThese findings suggest that HbA1c variability may provide additional information for an optimized management of diabetes, particularly in people within the target of HbA1c.
| S-EPMC8788128 | biostudies-literature
Project description:BACKGROUND:High levels of glycemic variability are still observed in most patients with diabetes with severe insulin deficiency. Glycemic variability may be an important risk factor for acute and chronic complications. Despite its clinical importance, there is no consensus on the optimum method for characterizing glycemic variability. METHOD:We developed a simple new metric, the glycemic variability percentage (GVP), to assess glycemic variability by analyzing the length of the continuous glucose monitoring (CGM) temporal trace normalized to the duration under evaluation. The GVP is similar to other recently proposed glycemic variability metrics, the distance traveled, and the mean absolute glucose (MAG) change. We compared results from distance traveled, MAG, GVP, standard deviation (SD), and coefficient of variation (CV) applied to simulated CGM traces accentuating the difference between amplitude and frequency of oscillations. The GVP metric was also applied to data from clinical studies for the Dexcom G4 Platinum CGM in subjects without diabetes, with type 2 diabetes, and with type 1 diabetes (adults, adolescents, and children). RESULTS:In contrast to other metrics, such as CV and SD, the distance traveled, MAG, and GVP all captured both the amplitude and frequency of glucose oscillations. The GVP metric was also able to differentiate between diabetic and nondiabetic subjects and between subjects with diabetes with low, moderate, and high glycemic variability based on interquartile analysis. CONCLUSION:A new metric for the assessment of glycemic variability has been shown to capture glycemic variability due to fluctuations in both the amplitude and frequency of glucose given by CGM data.
| S-EPMC5846572 | biostudies-literature
Project description:ObjectiveFor patients with diabetes, high-frequency and -amplitude glycemic variability may be more harmful than continuous hyperglycemia; however, there is still a lack of screening indicators that can quickly and easily assess the level of glycemic variability. The aim of this study was to investigate whether the glycemic dispersion index is effective for screening high glycemic variability.MethodsA total of 170 diabetes patients hospitalized in the Sixth Affiliated Hospital of Kunming Medical University were included in this study. After admission, the fasting plasma glucose, 2-hour postprandial plasma glucose, and glycosylated hemoglobin A1c were measured. The peripheral capillary blood glucose was measured seven times in 24 h, before and after each of three meals and before bedtime. The standard deviation of the seven peripheral blood glucose values was calculated, and a standard deviation of > 2.0 was used as the threshold of high glycemic variability. The glycemic dispersion index was calculated and its diagnostic efficacy for high glycemic variability was determined by the Mann-Whitney U test, receiver operating characteristic (ROC) curve and, Pearson correlation analysis.ResultsThe glycemic dispersion index of patients with high glycemic variability was significantly higher than that of those with low glycemic variability (p < 0.01). The best cutoff value of the glycemic dispersion index for screening high glycemic variability was 4.21. The area under the curve (AUC) was 0.901 (95% CI: 0.856-0.945) and had a sensitivity of 0.781 and specificity of 0.905. It was correlated with the standard deviation of blood glucose values (r = 0.813, p < 0.01).ConclusionsThe glycemic dispersion index had good sensitivity and specificity for screening high glycemic variability. It was significantly associated with the standard deviation of blood glucose concentration and is simple and easy to calculate. It was an effective screening indicator of high glycemic variability.
| S-EPMC10169464 | biostudies-literature
Project description:ObjectiveThe prognostic value of long-term glycemic variability is incompletely understood. We evaluated the influence of visit-to-visit variability (VVV) of fasting blood glucose (FBG) on incident cardiovascular disease (CVD) and mortality.Research design and methodsWe conducted a prospective cohort analysis including 4,982 participants in the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT) who attended the baseline, 24-month, and 48-month visits. VVV of FBG was defined as the SD or variability independent of the mean (VIM) across FBG measurements obtained at the three visits. Participants free of CVD during the first 48 months of the study were followed for incident CVD (coronary heart disease [CHD], stroke, and heart failure [HF]) and all-cause mortality.ResultsOver a median follow-up of 5 years, there were 305 CVD events (189 CHD, 45 stroke, and 81 HF) and 154 deaths. The adjusted hazard ratio (HR) comparing participants in the highest versus lowest quartile of SD of FBG (≥26.4 vs. <5.5 mg/dL) was 1.43 (95% CI 0.93-2.19) for CVD and 2.22 (95% CI 1.22-4.04) for all-cause mortality. HR for VIM was 1.17 (95% CI 0.84-1.62) for CVD and 1.89 (95% CI 1.21-2.93) for all-cause mortality. Among individuals without diabetes, the highest quartile of SD of FBG (HR 2.67 [95% CI 0.14-6.25]) or VIM (HR 2.50 [95% CI 1.40-4.46]) conferred a higher risk of death.ConclusionsGreater VVV of FBG is associated with increased mortality risk. Our data highlight the importance of achieving normal and consistent glycemic levels for improving clinical outcomes.
| S-EPMC6463548 | biostudies-literature
Project description:BackgroundThe role of glycemic variability (GV) in development of cardiovascular diseases remains controversial, and factors that determine glucose fluctuation in patients with diabetes are unknown. We investigated relationships between GV indices, kinds of oral hypoglycemic agents (OHAs), and cardiovascular risk factors in patients with type 2 diabetes mellitus (T2DM).MethodsWe analyzed 209 patients with T2DM. The GV index (standard deviation [SD] and mean absolute glucose change [MAG]) were calculated from 7-point self-monitoring of blood glucose profiles. The patients were classified into four groups according to whether they take OHAs known as GV-lowering (A) and GV-increasing (B): 1 (A only), 2 (neither), 3 (both A and B), and 4 (B only). The 10-year risk for atherosclerotic cardiovascular disease (ASCVD) was calculated using the Pooled Cohort Equations.ResultsGV indices were significantly higher in patients taking sulfonylureas (SUs), but lower in those taking dipeptidyl peptidase-4 inhibitors. In hierarchical regression analysis, the use of SUs remained independent correlates of the SD (?=0.209, P=0.009) and MAG (?=0.214, P=0.011). In four OHA groups, GV indices increased progressively from group 1 to group 4. However, these did not differ according to quartiles of 10-year ASCVD risk.ConclusionGV indices correlated significantly with the use of OHAs, particularly SU, and differed significantly according to combination of OHAs. However, cardiovascular risk factors and 10-year ASCVD risk were not related to GV indices. These findings suggest that GV is largely determined by properties of OHAs and not to cardiovascular complications in patients with T2DM.
| S-EPMC4595361 | biostudies-literature
Project description:BACKGROUND:Glycemic variability is associated with worse outcomes after cardiac surgery, but the prognosis value of early glycemic variability after transcatheter aortic valve implantation is not known. This study was therefore designed to analyze the prognosis significance of post-procedural glycemic variability within 30 days after transcatheter aortic valve implantation. METHODS:A post hoc analysis of patients from our center included in the FRANCE and FRANCE-2 registries was conducted. Post-procedural glycemic variability was assessed by calculating the mean daily ? blood glucose during the first 2 days after transcatheter aortic valve implantation. Major complications within 30 days were death, stroke, myocardial infarction, acute heart failure, and life-threatening cardiac arrhythmias. RESULTS:We analyzed 160 patients (age (median [interquartile]?=?84 [80-88] years; diabetes mellitus (n)?=?41 (26%) patients; logistic Euroscore?=?20 [12-32]). The median value of mean daily ? blood glucose was 4.3 mmol l-1. The rate of major complications within 30 days after procedure among patients with the lowest quartile of glycemic variability was 12%, increasing from 12 to 26%, and 39% in the second, third, and fourth quartiles, respectively. In multivariate analysis, glycemic variability was independently associated with an increased risk of major complications within 30 days after the procedure (odds ratio [95% CI]?=?1.83 [1.19-2.83]; p?=?0.006). CONCLUSIONS:This study showed that post-procedural glycemic variability was associated with an increased risk of major complications within 30 days after transcatheter aortic valve implantation. Trial registration Clinical trial registration number https://www.clinicaltrials.gov/ ; identifier: NCT02726958; date: April 4th, 2016.
| S-EPMC6410509 | biostudies-literature
Project description:Increased glycemic variability (GV) is an independent risk factor for cardiovascular complications in patients with diabetes. We evaluated the risk of future development of cardiovascular disease (CVD) and death according to GV in a general population without diabetes.We used the National Health Insurance Service, providing a population-based, nationwide database of Koreans. We included individuals without diabetes who underwent glucose measurement at least 3 times during 2002 to 2006. GV was calculated as standard deviation (SD) of fasting plasma glucose (FPG) levels. We observed development of CVD or all-cause death from 2007 to 2015, and also evaluated the mortality within 1 year after CVD.Among 3,211,319 people, we found 23,374 incident cases of myocardial infarction (MI), 27,705 cases of stroke, and 63,275 deaths during 8.3 years of follow-up. After multivariate adjustment, GV was found to be a significant predictor of MI, stroke and all-cause death for their highest quartile, with corresponding hazard ratios (HR) of 1.08 (95% confidence interval, CI 1.04-1.11), 1.09 (95% CI 1.06-1.13), and 1.12 (95% CI 1.10-1.15), respectively. The risk of death increased more in those who had both impaired fasting glucose and the highest quartile of GV (HR 1.24 [95% CI 1.21-1.28]). Moreover, early death rate after 1 year of CVD was higher in the highest quartile of GV compared to the lowest quartile (HR 1.21 [95% CI 1.03-1.41]).Long-term FPG variation was independently associated with CVD and mortality in a general population without diabetes.
| S-EPMC6709246 | biostudies-literature
Project description:People with diabetes are two times more likely to die from influenza than people with no underlying medical condition. The mechanisms underlying this susceptibility are poorly understood. In healthy individuals, small and short-lived postprandial peaks in blood glucose levels occur. In diabetes mellitus, these fluctuations become greater and more frequent. This glycemic variability is associated with oxidative stress and hyperinflammation. However, the contribution of glycemic variability to the pathogenesis of influenza A virus (IAV) has not been explored. Here, we used an in vitro model of the pulmonary epithelial-endothelial barrier and novel murine models to investigate the role of glycemic variability in influenza severity. In vitro, a history of glycemic variability significantly increased influenza-driven cell death and destruction of the epithelial-endothelial barrier. In vivo, influenza virus-infected mice with a history of glycemic variability lost significantly more body weight than mice with constant blood glucose levels. This increased disease severity was associated with markers of oxidative stress and hyperinflammation both in vitro and in vivo Together, these results provide the first indication that glycemic variability may help drive the increased risk of severe influenza in people with diabetes mellitus.IMPORTANCE Every winter, people with diabetes are at increased risk of severe influenza. At present, the mechanisms that cause this increased susceptibility are unclear. Here, we show that the fluctuations in blood glucose levels common in people with diabetes are associated with severe influenza. These data suggest that glycemic stability could become a greater clinical priority for patients with diabetes during outbreaks of influenza.
| S-EPMC7157527 | biostudies-literature