Management of Daily Glycemic Fluctuations in Patients With Type 2 Diabetes

Abstract

Traditional measures of overall glucose control, such as glycated hemoglobin (A1C), may not fully capture short-term, rapid changes in blood glucose. With the availability of multiple options to control A1C, glycemic fluctuations have emerged as an additional therapeutic goal for the management of type 2 diabetes (T2D). Glycemic fluctuations can be measured in various ways: self-monitoring of blood glucose provides measures at specific points throughout the day, whereas continuous glucose monitoring systems provide a more detailed description of glycemic fluctuations. Glycemic fluctuations have been associated with complications of T2D such as reduced cognitive function, an increased risk for cardiovascular events, and an increased risk of cardiovascular and all-cause death. These complications are often associated with increased reactive oxygen species. Although different treatments may result in expected improvements in A1C, they often have distinct effects on glycemic fluctuations. Therefore, for clinicians managing T2D, the choice of prescribed therapy should address both daily and long-term glycemic control, while also considering each patient’s needs and preferences.

For patients with type 2 diabetes (T2D), quantifying an individual’s level of glycemic control is complex and can be assessed in a number of different ways. The American Diabetes Association (ADA) recommends diagnosing T2D based on 1 of 4 criteria:

1. fasting plasma glucose (FPG; ≥126 mg/dL after no caloric intake for at least 8 hours)
2. 2-hour postprandial glucose (PPG; ≥200 mg/dL after a 75-g oral glucose load)
3. glycated hemoglobin (A1C) criteria (≥6.5%)
4. a random plasma glucose measure (≥200 mg/dL) in patients with classic symptoms of hyperglycemia.¹

Both FPG and PPG reflect blood glucose at a particular moment in time, while A1C reflects an average of blood glucose levels over the 2 to 3 months before the assessment. FPG and PPG contribute to A1C, but do so differentially, and the relationship between these measures can vary across individual patients. Over 10 years ago, Monnier et al noted that, as a patient’s A1C increased from approximately 7% to 10%, the relative contribution of PPG to A1C decreased, whereas the contribution of FPG increased.² The interplay between A1C, FPG, and PPG is complex, and the relationship between these measures and the risks of diabetes complications is not entirely clear. Complications may be related to multiple glycemic measures, as shown by the UK Prospective Diabetes Study (UKPDS) and the Diabetes Control and Complications Trial.^3-5 These studies demonstrated that improving A1C for patients with type 1 diabetes or T2D cut the risk of microvascular complications, with a 0.9% reduction in A1C reducing the risk by 25% in the UKPDS.⁵

Rapid changes in blood glucose (both peaks and troughs) are termed glycemic fluctuations and have emerged as a potential therapeutic target when managing T2D.⁶ In healthy individuals, nutrient intake (ie, a meal) produces a short-term increase in blood glucose to a level greater than basal FPG (Figure 1).⁷ However, in patients with T2D, basal glucose concentrations are typically elevated due to fasting hyperglycemia, while loss of PPG control results in additional blood glucose elevations (excursions) following meals.⁸ For these patients, blood glucose can fluctuate dramatically throughout the course of a day, even if A1C targets have been achieved. In a review of 7 patients with well-controlled T2D (A1C of 6.5%) on oral glucose-lowering treatments, 24-hour glucose traces showed that each patient had a unique glucose pattern, with most experiencing marked glycemic fluctuations exceeding the target glucose range at a number of time points (Figure 2).⁹ Additionally, variations in a patient’s diet may impact glycemic fluctuations, with evidence suggesting that high-fiber, low-glycemic index foods reduce PPG and may reduce glycemic fluctuations.¹⁰ This newsletter reviews glycemic fluctuations, including how they are assessed, the risks that they can confer to patients with T2D, and potential clinical approaches for managing them.

Figure 1. Mean continuous blood glucose profile from 434 healthy participants

The mean profile is indicated by the thick center line; the thinner lines represent the 5th and 95th percentiles as indicated. Arrows indicate meal time.
Adapted from: Zhou J, et al, Reference values for continuous glucose monitoring in Chinese subjects, Diabetes Care, American Diabetes Association, 2009. Copyright and all rights reserved. Material from this publication has been used with the permission of American Diabetes Association.⁷

Figure 2. Continuous glucose monitoring from 7 patients with well-controlled T2D
(A1C of 6.5%)

Measuring Glycemic Fluctuations

Various methods exist to quantify and record glycemic fluctuations. Self-monitoring of blood glucose (SMBG) measures blood glucose concentrations at up to 8 strategic points throughout the day.¹¹ In contrast, continuous glucose monitoring (CGM) systems provide a more detailed description of glycemic fluctuations via more frequent assessment of glucose levels (ie, sampling frequencies in the order of minutes).⁹

Experts at the International Diabetes Center discussed recommendations for standardizing the quantification of glycemic fluctuations and noted that SMBG data can often miss critical glucose excursions or hypoglycemia, especially overnight.¹² Consequently, the panel favored finding appropriate ways to expand the use of CGM to record daily glucose profiles in clinical practice, and they specified the target glucose range of 70 to 180 mg/dL (Figure 3),¹² which is not an ideal or normal glucose range as it includes elevations in FPG and PPG present in T2D.¹² However, this target range is commonly used in clinical practice and aligns with safe and realistic expectations. The panel acknowledged that there are multiple ways to analyze the measured glucose data and suggested metrics such as the mean amplitude of glucose excursion (MAGE) and standard deviation (SD) for quantification of glycemic fluctuations.

Figure 3. Blood glucose target ranges and categories

Abbreviations: DKA, diabetic ketoacidosis; ED, emergency department.
Adapted from: Bergenstal RM, et al. J Diabetes Sci Technol. 7(2):562–578, copyright © 2013 by International Diabetes Center at Park Nicollet, Minneapolis, MN. Reprinted by Permission of SAGE Publications, Inc.¹²

Hypoglycemia

Glycemic fluctuations include periods of hyperglycemia, but also hypoglycemia, the most well-recognized risk associated with glucose fluctuations. Among 29 patients with well-controlled T2D (A1C ≤7.0%) being treated with metformin ± sulfonylurea, CGM over 5 days showed that 18 (62%) of these patients experienced a total of 65 silent hypoglycemic episodes (asymptomatic episodes of hypoglycemia).¹³ An additional study of 108 patients with T2D monitored over 5 days found that, of the 49% of patients experiencing a hypoglycemic episode, the majority (75%) also experienced at least one silent hypoglycemic episode.¹⁴ Accumulating evidence has established a link between severe hypoglycemia and excessive morbidity and mortality, such as increased risk of major microvascular events, major macrovascular events, cardiovascular death, and death from any cause.^15-18 Risks associated with silent hypoglycemia are less clear, although asymptomatic hypoglycemia has been linked to cardiac arrhythmias.¹⁹ Chow and colleagues reported that patients with T2D and a history of cardiovascular disease (coronary artery disease, peripheral vascular disease, or cerebrovascular disease) and/or cardiovascular risk factors had an increase in bradycardia and atrial and ventricular ectopic activity that coincided with hypoglycemic periods.¹⁹ As such, treatment and management of glycemic fluctuations should consider the risks of hypoglycemia.

Neuropathic Complications

Glycemic fluctuations can also affect a patient’s cognitive abilities. Two studies that included older patients with T2D found that MAGE was negatively correlated with performance on the Mini–Mental State Examination,^20,21 as well as with a composite score of several standardized cognitive assessments designed to evaluate attention and executive function.²⁰ In 43 patients with T2D and 26 age-matched, healthy controls, increased glycemic fluctuations were found to correlate with gray matter atrophy of the limbic system and central autonomic networks.²² Among the patients with T2D, increased glycemic fluctuations were also associated with worse scores on tests of learning and memory.

Evidence also exists for a relationship between glycemic fluctuations and neuropathic complications resulting from compromised microvascular integrity in T2D. In a study of patients with well-controlled T2D (A1C <7.0%), 45 patients with and 45 patients without diabetic peripheral neuropathy were evaluated over 72 hours with CGM.²³ Multivariate regression analysis showed that MAGE was the most significant predictor of diabetic peripheral neuropathy. A separate multivariate analysis of 110 patients with T2D found that the coefficient of variation—a measure of glycemic fluctuations—but not SD or MAGE, predicted the presence of cardiovascular autonomic neuropathy.²⁴

Macrovascular Complications of T2D

Glycemic fluctuations have been reported to impact cardiovascular complications of T2D. The DECODE (Diabetes Epidemiology: Collaborative Analysis of Diagnostic Criteria in Europe) study group analyzed more than 20,000 patients with T2D and found that impaired glucose tolerance, determined by 2-hour PPG criteria (a key contributor to glycemic fluctuations), increased the risk of cardiovascular and all-cause death.²⁵ Similarly, the Framingham Offspring Study found that increased 2-hour PPG levels increased the risk for cardiovascular events among 3370 patients with T2D,²⁶ and the Diabetes Intervention Study found a significant association between poor PPG control and increased risk for myocardial infarction and death among 994 patients.²⁷

Newer measures of glycemic fluctuations have also been reported to affect macrovascular complications. In patients with T2D and chest pain who underwent coronary angiography, MAGE and PPG excursions were significantly greater in patients with coronary artery disease, whereas A1C and FPG were not significantly different.²⁸

Oxidative Stress as a Mechanism of Vascular Damage

Glycemic fluctuations can produce detrimental effects at a molecular level through the overproduction of reactive oxygen species and subsequent damage via oxidative stress. This increase in reactive oxygen species occurs through the mitochondrial electron transport chain and can lead to vascular damage.²⁹ Several studies have found that glycemic fluctuations were correlated with markers of oxidative stress, chronic inflammation, and vascular damage; of note, the more traditional measures of glycemic control, such as A1C and FPG, were not associated with these indicators.^30,31 Thus, oxidative stress resulting from glycemic fluctuations may be an upstream contributor to vascular complications of T2D.

Managing Glycemic Fluctuations

While different treatments may result in expected improvements in the traditional measures of glucose control (eg, A1C), they may have distinct effects on measures of glycemic fluctuations.

The sodium-glucose cotransporter-2 inhibitors dapagliflozin and empagliflozin have both been shown to reduce glycemic fluctuations. A 4-week placebo-controlled study among 100 patients with T2D found that dapagliflozin 10 mg added to metformin alone or insulin plus oral glucose-lowering medications significantly reduced 24-hour mean glucose, MAGE, FPG, and PPG compared with placebo (P<.001 for all except MAGE [P=.01]).³² In addition, dapagliflozin reduced the proportion of time that patient glucose concentrations were in the hyperglycemic range (>180 mg/dL) and increased the time with glucose concentrations in the target glycemic range (70–180 mg/dL; both P<.001). There was a small increase in the proportion of time that patient glucose concentrations were in the hypoglycemic range (<70 mg/dL) with dapagliflozin vs placebo (P=.023), which was driven by the combination of dapagliflozin plus insulin. Empagliflozin (dosed at 10 mg and 25 mg for 28 days) was evaluated in 60 patients with T2D and while it reduced A1C by –0.46% and –0.63%, respectively (P<.001 vs placebo for both), MAGE was not significantly reduced relative to placebo.³³ However, the 24-hour glucose profile shifted downward, increasing the amount of time spent within the target range of 70 to 140 mg/dL, without increasing the time spent in the hypoglycemic range (<70 mg/dL).

The addition of the dipeptidyl peptidase-4 inhibitor saxagliptin to metformin was examined in a phase 3b study involving 93 patients with T2D that was inadequately controlled with metformin.³⁴ Compared with metformin alone, the addition of saxagliptin 5 mg was associated with significant reductions from baseline in 24-hour mean glucose (P=.0001), as well as 4-hour mean weighted PPG, 2-hour PPG, 3-day average mean daily glucose, and 2-day average FPG (all P≤.001). The proportion of adverse events in the monotherapy and combination treatment groups was similar, and no reports of hypoglycemia were observed in the saxagliptin group.

For patients needing further treatment in addition to oral medications, insulin and other injectable medications are used. In a crossover study comparing basal-bolus and premix analog insulin over two 12-week treatment periods, glycemic fluctuations were evaluated in 306 patients with T2D and 82 patients with type 1 diabetes at lead-in and at the end of each 12-week treatment period.³⁵ Compared with premix insulin, mean daily glucose, SD, and time spent with glucose concentrations >140 mg/dL decreased significantly more with basal-bolus insulin (P<.0001), as did baseline-adjusted A1C and FPG (P<.0001). Of note, reductions in SD and A1C were associated with significant increases in patient satisfaction (P<.013 and P<.0001, respectively). With either insulin regimen, ~11% to 12% of patients experienced severe hypoglycemia, a known adverse effect associated with insulin.

Newer injectables, such as glucagon-like peptide-1 receptor agonists (GLP-1RAs), have also shown positive effects on markers of glycemic fluctuations in patients with T2D. What sets these agents apart is that their glucose-lowering effects are dependent on blood glucose concentrations, as is seen with the dipeptidyl peptidase-4 inhibitor class. This mechanism of action lowers the risk of hypoglycemia when not used with a sulfonylurea or insulin. In a pilot study, treatment effects on glycemic fluctuations were compared among patients who received second-line treatment with the GLP-1RA exenatide twice daily (n=6) or the sulfonylurea glimepiride (n=6) for 16 weeks.³⁶ Although A1C and FPG were reduced in both groups, exenatide twice daily led to significant reductions vs baseline in mean daily glucose (P<.05), SD (P<.01), and MAGE (P<.05). In contrast, glimepiride was associated with numerical increases in mean daily glucose, SD, and a non-significant decrease in MAGE.

More recently, a prospective placebo-controlled study (n=116) showed that exenatide once weekly improved daily glucose control and reduced glycemic fluctuations in patients with T2D uncontrolled with metformin therapy.³⁷ After 10 weeks of treatment, exenatide once weekly significantly reduced 24-hour mean glucose (P<.001), as well as MAGE and SD, compared with placebo (both P<.001). Furthermore, exenatide once weekly significantly reduced the proportion of time that patient glucose concentrations were in the hyperglycemic range (>180 mg/dL; P<.001) and significantly increased the time with glucose concentrations in the target glycemic range (70–180 mg/dL; P<.001) compared with placebo, without increasing time spent in the hypoglycemic range (<70 mg/dL). In the exenatide once-weekly group, time spent in the target glycemic range increased from 53% at baseline to 77% at week 10.

Liraglutide (a once-daily GLP-1RA) and dulaglutide (a once-weekly GLP-1RA) have also shown favorable effects for reducing glycemic fluctuations. Among 63 patients with T2D treated with liraglutide or neutral protamine Hagedorn (NPH) insulin for 12 weeks, liraglutide was associated with a significantly greater decrease in MAGE and large amplitude of glycemic excursions compared with NPH insulin (both P<.05).³⁸ A substudy of 144 patients in the AWARD-4 (A Study in Participants With Type 2 Diabetes Mellitus) trial compared treatment with dulaglutide (0.75 or 1.5 mg) plus insulin glargine vs insulin glargine without dulaglutide, each added to prandial insulin lispro. This study found that all treatments similarly reduced mean 24-hour glucose from baseline after 26 weeks, while the percentage of time spent with glucose in the range of 70 to 180 mg/dL was significantly greater with dulaglutide 1.5 mg vs insulin glargine (P<.05).³⁹ Dulaglutide and insulin glargine both reduced all indices of glycemic fluctuations, with a significantly greater reduction in overall within-patient SD with dulaglutide 1.5 mg vs insulin glargine (P<.05).

These studies point to an effect of GLP-1RAs for reducing glycemic fluctuations and improving daily glycemic control among patients with T2D.

Conclusions

While measures of overall glycemic control (such as A1C) have historically been the focus of diabetes treatment, glycemic fluctuations have been implicated in mechanisms of diabetes complications, although their importance remains controversial.^40,41

Different treatments with established effects on A1C may have distinct effects on glycemic fluctuations. Emerging evidence with newer glucose-lowering agents—available with once-daily or once-weekly dosing—builds on the understanding of A1C improvement and supports the efficacy of these agents in controlling daily glycemic fluctuations. Importantly, some of the newer agents work in a glucose-dependent manner, thus minimizing the risk of hypoglycemia. Ultimately, for clinicians managing T2D, the choice of prescribed therapy should address both daily and long-term glycemic control, while also reflecting each patient’s needs and preferences.

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