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.

IntroductionIn critical illness, four measures of glycaemic control are associated with ICU mortality: mean glucose concentration, glucose variability, the incidence of hypoglycaemia (≤ 2.2 mmol/l) or low glucose (2.3 to 4.7 mmol/l). Underlying diabetes mellitus (DM) might affect these associations. Our objective was to study whether the association between these measures of glycaemic control and ICU mortality differs between patients without and with DM and to explore the cutoff value for detrimental low glucose in both cohorts.MethodsThis retrospective database cohort study included patients admitted between January 2004 and June 2011 to a 24-bed medical/surgical ICU in a teaching hospital. We analysed glucose and outcome data from 10,320 patients: 8,682 without DM and 1,638 with DM. The cohorts were subdivided into quintiles of mean glucose and quartiles of glucose variability. Multivariable regression models were used to examine the independent association between the four measures of glycaemic control and ICU mortality, and for defining the cutoff value for detrimental low glucose.ResultsRegarding mean glucose, a U-shaped relation was observed in the non-DM cohort with an 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 DM cohort. Glucose variability was related to ICU mortality only in the non-DM cohort, with highest ICU mortality in the upper variability quartile (odds ratio = 1.7, P < 0.001). Hypoglycaemia was associated with ICU mortality in both 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 were associated with an increased risk of ICU mortality in the non-DM cohort and up to 3.5 mmol/l in the DM cohort.ConclusionMean glucose and high glucose variability are related to ICU mortality in the non-DM cohort but not in the DM cohort. Hypoglycaemia (≤ 2.2 mmol/l) was associated with ICU mortality in both. The cutoff value for detrimental low glucose is higher in the non-DM cohort (4.9 mmol/l) than in the DM cohort (3.5 mmol/l). While hypoglycaemia (≤ 2.2 mmol/l) should be avoided in both groups, DM patients seem to tolerate a wider glucose range than non-DM patients.

OBJECTIVETo 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 METHODSType 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.RESULTSThe 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.CONCLUSIONSA 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.

IntroductionLowering of hyperglycemia in the intensive care unit (ICU) is widely practiced. We investigated in which way glucose regulation, defined as mean glucose concentration during admission, is associated with ICU mortality in a medical and a surgical cohort.MethodsRetrospective database cohort study including patients admitted between January 2004 and December 2007 in a 20-bed medical/surgical ICU in a teaching hospital. Hyperglycemia was treated using a computerized algorithm targeting for glucose levels of 4.0-7.0 mmol/l. Five thousand eight hundred twenty-eight patients were eligible for analyses, of whom 1,339 patients had a medical and 4,489 had a surgical admission diagnosis.ResultsThe cohorts were subdivided in quintiles of increasing mean glucose. We examined the relation between these mean glucose strata and mortality. In both cohorts we observed the highest mortality in the lowest and highest strata. Logistic regression analysis adjusted for age, sex, Acute Physiology and Chronic Health Evaluation II (APACHE II) score, admission duration and occurrence of severe hypoglycemia showed that in the medical cohort mean glucose levels <6.7 mmol/l and >8.4 mmol/l and in the surgical cohort mean glucose levels < 7.0 mmol/l and >9.4 mmol/l were associated with significantly increased ICU mortality (OR 2.4-3.0 and 4.9-6.2, respectively). Limitations of the study were its retrospective design and possible incomplete correction for severity of disease.ConclusionsMean overall glucose during ICU admission is related to mortality by a U-shaped curve in medical and surgical patients. In this cohort of patients a 'safe range' of mean glucose regulation might be defined approximately between 7.0 and 9.0 mmol/l.

Abbreviations EMG Electromyography MAGE Mean amplitude of glycaemic excursionsTo the Editor: While it is suggested that, in addition to hyperglycaemia, glucose variability can contribute to the severity and development of diabetic neuropathy [1], it is not related to the development of retinopathy and nephropathy in type 1 diabetes [1,2]. To determine any additional effect of glucose variability-above that assessed by HbA 1c and mean glucose-on peripheral and autonomic diabetic neuropathy, we used the datasets collected during the DCCT (available at www.gcrc.med.umn.edu/gcrc/downloads/dcct.html, accessed 23-27 January 2009) [3].We studied the effect of glucose variability on the main neurological endpoint of the DCCT, i.e. confirmed clinical neuropathy, and on the DCCT-defined secondary endpoints separately: clinical neuropathy, abnormal nerve conduction studies, and abnormal autonomic function [4]. In addition, we determined its effect on the subvariables median motor F-wave latency, sural amplitude, sensory signs and beat-tobeat heart-rate variation (with Valsalva ratio <1.5), as these variables tend to be the first affected by diabetes. We included only data from baseline to 4 years (autonomic function data) or 5 years of follow-up in the analyses as more than 50% of the patients did not have records of glucose data after 5 years of follow-up.We assessed glycaemic variables from seven-point blood glucose profiles collected every 3 months. We included all glucose profiles with five observations or more during the 24 h period, extrapolating missing values from the surrounding points [5]. Mean blood glucose was calculated by the AUC using the trapezoidal rule [6]. Variability of blood glucose (within-day SD) was calculated as the SD of daily blood glucose around the mean from each quarterly visit and the mean amplitude of glycaemic excursions (MAGE) [7]. Last, we calculated the mean SD from individual glucose data transformed to a symmetric distribution according to Kovatchev [8]. Glucose variability from baseline to 4 or 5 years was assessed as the mean SD and mean MAGE from the first quarter to the 16th or 20th quarter of follow-up, respectively.The main characteristics of the patients in the group analysed for confirmed clinical neuropathy are listed in Table 1. Of the 1,441 patients in total, 1,160 were included in this specific analysis. Ninety-two patients were excluded from the analysis because they had a positive score at baseline and 189 patients had missing data on confirmed clinical neuropathy at baseline (n=3) or at 5 years (n=186).