Sarah E. Siegelaar

Glucose variability; does it matter?

Overall lowering of glucose is of pivotal importance in the treatment of diabetes, with proven beneficial effects on microvascular and macrovascular outcomes. Still, patients with similar glycosylated hemoglobin levels and mean glucose values can have markedly different daily glucose excursions. The role of this glucose variability in pathophysiological pathways is the subject of debate. It is strongly related to oxidative stress in in vitro, animal, and human studies in an experimental setting. However, in real-life human studies including type 1 and type 2 diabetes patients, there is neither a reproducible relation with oxidative stress nor a correlation between short-term glucose variability and retinopathy, nephropathy, or neuropathy. On the other hand, there is some evidence that long-term glycemic variability might be related to microvascular complications in type 1 and type 2 diabetes. Regarding mortality, a convincing relationship with short-term glucose variability has only been demonstrated in nondiabetic, critically ill patients. Also, glucose variability may have a role in the prediction of severe hypoglycemia. In this review, we first provide an overview of the various methods to measure glucose variability. Second, we review current literature regarding glucose variability and its relation to oxidative stress, long-term diabetic complications, and hypoglycemia. Finally, we make recommendations on whether and how to target glucose variability, concluding that at present we lack both the compelling evidence and the means to target glucose variability separately from all efforts to lower mean glucose while avoiding hypoglycemia.

A decrease in glucose variability does not reduce cardiovascular event rates in type 2 diabetic patients after acute myocardial infarction: a reanalysis of the HEART2D study

OBJECTIVE To assess the effect of intraday glucose variability (GV) on cardiovascular outcomes in a reanalysis of Hyperglycemia and Its Effect After Acute Myocardial Infarction on Cardiovascular Outcomes in Patients With Type 2 Diabetes Mellitus (HEART2D) study data. RESEARCH DESIGN AND METHODS Type 2 diabetic patients after acute myocardial infarction were randomized to an insulin treatment strategy targeting postprandial (PRANDIAL; n = 557) or fasting/interprandial (BASAL; n = 558) hyperglycemia. GV was calculated as mean amplitude of glycemic excursions (MAGE), mean absolute glucose (MAG) change, and SD. RESULTS The PRANDIAL strategy resulted in an 18% lower MAG than BASAL (mean [SEM] difference 0.09 [0.04] mmol/L/h, P = 0.02). In addition, MAGE and SD were lower in the PRANDIAL group, however, not significantly. HbA1c levels and cardiovascular event rates were comparable between groups. CONCLUSIONS A PRANDIAL strategy demonstrated lower intraday GV vs. a BASAL strategy with similar overall glycemic control but did not result in a reduction in cardiovascular outcomes. This does not support the hypothesis that targeting GV would be beneficial in reducing subsequent secondary cardiovascular events.

The effect of diabetes mellitus on the association between measures of glycaemic control and ICU mortality: a retrospective cohort study

IntroductionIn critical illness, four measures of glycaemic control are associated with ICUmortality: mean glucose concentration, glucose variability, the incidence ofhypoglycaemia (≤ 2.2 mmol/l) or low glucose (2.3 to 4.7 mmol/l). Underlyingdiabetes mellitus (DM) might affect these associations. Our objective was to studywhether the association between these measures of glycaemic control and ICUmortality differs between patients without and with DM and to explore the cutoffvalue for detrimental low glucose in both cohorts.MethodsThis retrospective database cohort study included patients admitted betweenJanuary 2004 and June 2011 to a 24-bed medical/surgical ICU in a teachinghospital. We analysed glucose and outcome data from 10,320 patients: 8,682 withoutDM and 1,638 with DM. The cohorts were subdivided into quintiles of mean glucoseand quartiles of glucose variability. Multivariable regression models were used toexamine the independent association between the four measures of glycaemic controland ICU mortality, and for defining the cutoff value for detrimental lowglucose.ResultsRegarding mean glucose, a U-shaped relation was observed in the non-DM cohort withan increased ICU mortality in the lowest and highest glucose quintiles (odds ratio= 1.4 and 1.8, P < 0.001). No clear pattern was found in the DMcohort. Glucose variability was related to ICU mortality only in the non-DMcohort, with highest ICU mortality in the upper variability quartile (odds ratio =1.7, P < 0.001). Hypoglycaemia was associated with ICU mortality inboth cohorts (odds ratio non-DM = 2.5, P < 0.001; odds ratio DM = 4.2,P = 0.001), while low-glucose concentrations up to 4.9 mmol/l wereassociated with an increased risk of ICU mortality in the non-DM cohort and up to3.5 mmol/l in the DM cohort.ConclusionMean glucose and high glucose variability are related to ICU mortality in thenon-DM cohort but not in the DM cohort. Hypoglycaemia (≤ 2.2 mmol/l) wasassociated with ICU mortality in both. The cutoff value for detrimental lowglucose is higher in the non-DM cohort (4.9 mmol/l) than in the DM cohort (3.5mmol/l). While hypoglycaemia (≤ 2.2 mmol/l) should be avoided in bothgroups, DM patients seem to tolerate a wider glucose range than non-DMpatients.

The effect of diabetes on mortality in critically ill patients: a systematic review and meta-analysis

IntroductionCritically ill patients with diabetes are at increased risk for the development of complications, but the impact of diabetes on mortality is unclear. We conducted a systematic review and meta-analysis to determine the effect of diabetes on mortality in critically ill patients, making a distinction between different ICU types.MethodsWe performed an electronic search of MEDLINE and Embase for studies published from May 2005 to May 2010 that reported the mortality of adult ICU patients. Two reviewers independently screened the resultant 3,220 publications for information regarding ICU, in-hospital or 30-day mortality of patients with or without diabetes. The number of deaths among patients with or without diabetes and/or mortality risk associated with diabetes was extracted. When only crude survival data were provided, odds ratios (ORs) and standard errors were calculated. Data were synthesized using inverse variance with ORs as the effect measure. A random effects model was used because of anticipated heterogeneity.ResultsWe included 141 studies comprising 12,489,574 patients, including 2,705,624 deaths (21.7%). Of these patients, at least 2,327,178 (18.6%) had diabetes. Overall, no association between the presence of diabetes and mortality risk was found. Analysis by ICU type revealed a significant disadvantage for patients with diabetes for all mortality definitions when admitted to the surgical ICU (ICU mortality: OR [95% confidence interval] 1.48 [1.04 to 2.11]; in-hospital mortality: 1.59 [1.28 to 1.97]; 30-day mortality: 1.62 [1.13 to 2.34]). In medical and mixed ICUs, no effect of diabetes on all outcomes was found. Sensitivity analysis showed that the disadvantage in the diabetic surgical population was attributable to cardiac surgery patients (1.77 [1.45 to 2.16], P < 0.00001) and not to general surgery patients (1.21 [0.96 to 1.53], P = 0.11).ConclusionsOur meta-analysis shows that diabetes is not associated with increased mortality risk in any ICU population except cardiac surgery patients.

No Relevant Relationship between Glucose Variability and Oxidative Stress in Well-Regulated Type 2 Diabetes Patients

Background: A strong relationship between glycemic variability and oxidative stress in poorly regulated type 2 diabetes (T2DM) on oral medication has been reported. However, this relationship was not seen in type 1 diabetes. The purpose of this study is to reexamine the relation between glycemic variability and oxidative stress in a cohort of T2DM patients on oral medication. Methods: Twenty-four patients with T2DM on oral glucose lowering treatment underwent 48 hours of continuous glucose monitoring (CGMS® System Gold™, Medtronic MiniMed) and simultaneous collection of two consecutive 24-hour urine samples for determination of 15(S)-8-iso-prostaglandin F2α (PGF2α) using high-performance liquid chromatography tandem mass spectrometry. Standard deviation (SD) and mean amplitude of glycemic excursions (MAGE) were calculated as markers of glycemic variability. Results: Included in the study were 66.7% males with a mean age (range) of 59 (36–76) years and a mean (SD) HbA1c of 6.9% (0.7). Median [interquartile range (IQR)] urinary 15(S)-8-iso-PGF2α excretion was 176.1 (113.6–235.8) pg/mg creatinine. Median (IQR) SD was 31 (23–40) mg/dl and MAGE 85 (56–106) mg/dl. Spearman correlation did not show a significant relation for SD (ρ = 0.15, p = .49) or MAGE (ρ = 0.23, p = .29) with 15(S)-8-iso-PGF2α excretion. Multivariate regression analysis adjusted for age, sex, HbA1c, and exercise did not alter this observation. Conclusions: We did not find a relevant relationship between glucose variability and 15(S)-8-iso-PGF2α excretions in T2DM patients well-regulated with oral medication that would support an interaction between hyperglycemia and glucose variability with respect to the formation of reactive oxygen species.

Accuracy and Reliability of Continuous Glucose Monitoring in the Intensive Care Unit: A Head-to-Head Comparison of Two Subcutaneous Glucose Sensors in Cardiac Surgery Patients

Hyperglycemia, hypoglycemia, and glucose variability are common during intensive care unit (ICU) stay and are associated with increased mortality (1–3). Continuous glucose monitoring (CGM) is a promising tool to assist glucose control, but the accuracy and reliability of these devices in critically ill patients is uncertain (4,5). Therefore, we studied two different CGM devices postoperatively in cardiac surgery patients in an investigator-initiated trial. We placed two CGM devices (Guardian RT, Medtronic Minimed; FreeStyle Navigator, Abbott Diabetes Care) subcutaneously in the abdominal wall before surgery in 60 patients. This is the first time the Navigator has been studied in an ICU setting. Both devices were calibrated simultaneously upon arrival at the ICU after surgery. Further calibrations were performed according to manufacturers’ instructions. An arterial blood glucose value was measured with an AccuChek device (Performa II, …

Special considerations for the diabetic patient in the ICU; targets for treatment and risks of hypoglycaemia

Due to the diabetes pandemic the number of diabetic patients admitted to the intensive care unit (ICU) increases. Diabetic patients admitted to the ICU are more vulnerable for developing complications as compared to non-diabetic patients, but this does not directly translate into higher mortality rates. However, mortality might differ per admission diagnosis. Hyperglycaemia is common in diabetic as well as non-diabetic critically ill patients, but probably chronic hyperglycaemia is pathophysiologically different from acute hyperglycaemia. As opposed to non-diabetic patients, there is discussion about the association between hyperglycaemia and mortality in diabetic patients. They do not seem to benefit from strict glycaemic control and also glucose variability appears less harmful, although clinical trials in diabetic populations have not been performed yet. Diabetes is a risk factor for hypoglycaemia and evidence suggests that even near-normal glucose levels are associated with worse outcome. Taking this together, it is suggested to strive for moderate targets when treating hyperglycaemia in critically ill diabetic patients.

Patients with diabetes in the intensive care unit; not served by treatment, yet protected?

Diabetes is associated with severe complications and decreased life expectancy. However, in the previous issue of Critical Care, Vincent and colleagues report no difference in mortality between patients with insulin-treated diabetes and patients without diabetes in the intensive care unit (ICU), despite larger severity of illness in the diabetes group at admission. This study contributes to the growing evidence that diabetes in itself is not a risk factor for ICU mortality, although the mechanisms are not yet fully understood. On the other hand, patients with diabetes seem not to benefit from tight glycemic control during their ICU stay. Different treatment approaches may be needed for patients with diabetes and patients with stress hyperglycemia.

Response to the Need for Identifying Standardized Indices for Measuring Glucose Variability.

We thank Picconi and colleagues1 for their valuable comments on our study.2 They observe a lack of standardization for measurement of glycemic variability (GV) and suggest that there might be different outcomes with different GV measures. Furthermore, the authors suggest a possible confounding role for insulin secretagogues on GV and oxidative stress parameters. The lack of standardization of GV measurement methods is a problem we had discussed.3 This lack limits comparison between trials and we would highly support development of a consensus on, ideally, one measure. We agree that mean amplitude of glycemic excursions has several limitations: not measuring excursions smaller than the standard deviation as well as not taking the frequency of excursions into account. Therefore, our group has developed a new measure that we believe overcomes these limitations and has proven robust in diabetes4 and intensive care unit populations5: mean absolute glucose change (MAG). This is a simple summation of all changes in glucose per unit of time and can be taken from self-monitored blood glucose profiles, blood glucoses, and continuous glucose monitoring traces. To investigate the influence of different measurement methods, we also measured the relation between oxidative stress and continuous net glycemic action (reflected as CONGA-1, CONGA-2, CONGA-4) as well as mean of daily differences originally in the subject study.2 As expected, all GV measures were highly correlated and, also for these additional measures, we were not able to show a correlation with oxidative stress in our population. To improve readability, we decided not to include them in the paper. Picconi and colleagues suggest that our outcomes might have been influenced by insulin secretagogues and other drugs used in our study population. It could be that the formation of oxidative stress is prohibited by these medicaments but, as mentioned, our population showed optimal glycemic control. The results of our study therefore reflect the current situation of diabetes regulation, which relies on polypharmacy. Moreover, it is plausible that mean glucose is the main driver of oxidative stress6 and not the way by which that mean glucose is reached. Noteworthy in this perspective is that the patients in the original Monnier article7 were allowed to use insulin secretagogues, which did not seem to influence the positive correlation found between GV and oxidative stress. In conclusion, we support that future studies use standardized GV measures, for which we propose the MAG, and, in case of isoprostane measurement, high-performance liquid chromatography tandem mass spectrometry to measure oxidative stress.