Glycemic Instability Research Articles

Pancreatic islet transplantation

BackgroundNo formulation of exogenous insulin available to date has yet been able to mimic the physiological nictemeral rhythms of this hormone, and despite all engineering advancements, the theoretical proposal of developing a mechanical replacement for pancreatic β cell still has not been reached. Thus, the replacement of β cells through pancreas and pancreatic islet transplantation are the only concrete alternatives for re-establishing the endogenous insulin secretion in type 1 diabetic patients. Since only 1 to 1.5% of the pancreatic mass corresponds to endocrine tissue, pancreatic islets transplantation arises as a natural alternative. Data from the International Islet Transplant Registry (ITR) from 1983 to December 2000 document a total of 493 transplants performed around the world, with progressively worse rates of post-transplant insulin independence. In 2000, the "Edmonton Protocol" introduced several modifications to the transplantation procedure, such as the use of a steroid-free immunosuppression regimen and transplantation of a mean islet mass of 11,000 islet equivalents per kilogram, which significantly improved 1-year outcomes. Although the results of a 5-year follow-up in 65 patients demonstrated improvement in glycemic instability in a significant portion of them, only 7.5% of the patients have reached insulin independence, indicating the need of further advances in the preservation of the function of transplanted islet. In addition to the scarcity of organs available for transplantation, islets transplantation still faces major challenges, specially those related to cell loss during the process of islet isolation and the losses related to the graft site, apoptosis, allorejection, autoimmunity, and immunosuppression. The main strategies to optimize islet transplantation aim at improving all these aspects.ConclusionHuman islet transplantation should be regarded as an intervention that can decrease the frequency of severe hypoglycemic episodes and improve glycemic control in selected patient for whom benefits of 4-5 years duration would be very valuable. Its limitations, however, indicate that the procedure in its current format is not suitable for all patients with type 1 diabetes.

Effect of Glucose Variability on the Long-Term Risk of Microvascular Complications in Type 1 Diabetes

OBJECTIVEThis study analyzed data from the Epidemiology of Diabetes Interventions and Complications (EDIC) study to see whether longer-term follow-up of Diabetes Control and Complications Trial (DCCT) patients reveals a role for glycemic instability in the development of microvascular complications.RESEARCH DESIGN AND METHODSThe mean area under the curve glucose and the within-day glucose variability (SD and mean amplitude of glycemic excursions [MAGE]) during the DCCT were assessed to see whether they contributed to the risk of retinopathy and nephropathy by year 4 of the EDIC.RESULTSLogistic regression analysis showed that mean glucose during the DCCT and mean A1C during EDIC were independently predictive of retinopathy (each P < 0.001) as well as A1C during EDIC of nephropathy (P = 0.001) development by EDIC year 4. Glucose variability did not add to this (all P > 0.25 using SD or MAGE).CONCLUSIONSGlucose variability in the DCCT did not predict the development of retinopathy or nephropathy by EDIC year 4.

Long-term glycemic instability increases risk of microvascular damage in T1DM

Long-term glycemic instability increases risk of microvascular damage in T1DM

Treatment of diabetes mellitus using an external insulin pump: the state of the art

The aim of diabetes treatment is to achieve tight glucose control to avoid the development of chronic diabetic complications while reducing the frequency of hypoglycaemic episodes. Continuous subcutaneous insulin infusion (CSII) using an external pump is an intensive diabetes therapy recognized to improve metabolic control and glycaemic instability, and to reduce the frequency of severe hypoglycaemia. For years, the theoretical advantages of the insulin pump (constancy of basal delivery, adjustable basal rates, and low insulin depots allowing the reduction of glycaemic variability) have contributed to its reported superiority compared with multiple daily injections (MDI). However, insulin pump therapy is now challenged by new MDI regimens based on long-acting insulin analogues that could replace the use of CSII. As a consequence, health professionals now have to determine which patients are likely to benefit the most from CSII. Recently, several studies reported that children and adolescents, and patients whose blood glucose imbalance was initially the most pronounced with basal-bolus regimens, would particularly benefit from CSII. Other indications were also proposed in marginal clinical situations with highly selected patients in whom a significant improvement of blood glucose was demonstrated. Finally, the use of CSII in type 2 diabetic patients now appears to be a good alternative to the ineffective MDI regimens observed in some of these patients. However, past experience with CSII indicates that candidates for insulin pump therapy must be carefully selected and strongly motivated to improve their glucose control. Use of CSII also requires strict medical supervision by physicians and a regular programme of patient education by paramedical teams, to ensure optimal responsible use of this technique by healthcare professionals.

Glycemic Instability and Spontaneous Energy Intake: Association With Knowledge-Based Work

To further document the impact of knowledge-based work (KBW) on spontaneous energy intake and glucose homeostasis. We used a within-subjects experimental design, in which each participant was engaged in each of the three 45-minute conditions followed by an ad libitum buffet, 1) resting in a sitting position; 2) reading a document and writing a summary; or 3) performing a battery of computerized tests. Fourteen female students (mean age: 22.8 +/- 2.3 years, mean body mass index: 22.4 +/- 2.5 kg/m(2)) were recruited to participate. Plasma glucose, insulin, and cortisol levels at seven time-points, and appetite sensation markers were measured at each experimental condition. The mean ad libitum energy intake after the reading-writing and the automated test-battery conditions exceeded that measured after rest by 848 kJ and 1057 kJ, respectively (p < .05). No specific dietary preference was detected, as reflected by the comparable percent of energy from each macronutrient in the three conditions. No significant difference in appetite sensation markers was observed among the three conditions. Mean cortisol level over 45 minutes in the two KBW conditions was significantly higher (p < .05) compared with the control condition. Finally, a significant increase in variations in plasma glucose and insulin levels was observed as compared with the control condition (p < .01). This study showed that KBW acutely induces an increase in spontaneous energy intake, and promotes an increased fluctuation in plasma glucose and insulin levels. This study contributes to the documentation of a new risk factor for a positive energy balance, with the potential to lead to overweight in the long-term.

A1C Variability and the Risk of Microvascular Complications in Type 1 Diabetes

OBJECTIVE—Debate remains as to whether short- or long-term glycemic instability confers a risk of microvascular complications in addition to that predicted by mean glycemia alone. In this study, we analyzed data from the Diabetes Control and Complications Trial (DCCT) to assess the effect of A1C variability on the risk of retinopathy and nephropathy in patients with type 1 diabetes.RESEARCH DESIGN AND METHODS—A1C was collected quarterly during the DCCT in 1,441 individuals. The mean A1C and the SD of A1C variability after stabilization of glycemia (from 6 months onwards) were compared with the risk of retinopathy and nephropathy with adjustments for age, sex, disease duration, treatment group, and baseline A1C.RESULTS—Multivariate Cox regression showed that the variability in A1C added to mean A1C in predicting the risk of development or progression of both retinopathy (hazard ratio 2.26 for every 1% increase in A1C SD [95% CI 1.63–3.14], P < 0.0001) and nephropathy (1.80 [1.37–2.42], P < 0.0001), with the relationship a feature in conventionally treated patients in particular.CONCLUSIONS—This study has shown that variability in A1C adds to the mean value in predicting microvascular complications in type 1 diabetes. Thus, in contrast to analyses of DCCT data investigating the effect of short-term glucose instability on complication risk, longer-term fluctuations in glycemia seem to contribute to the development of retinopathy and nephropathy in type 1 diabetes.

Glycemic instability in type 1 diabetic patients: Possible role of ketosis or ketoacidosis at onset of diabetes

Aims In type 1 diabetic patients, some have glycemic instability while others glycemic stability. We have developed criteria for evaluating glycemic instability and investigated the factors responsible. Methods Glycemic instability in 52 type 1 diabetic patients was assessed by the mean amplitude of glycemic excursions (MAGE) and M-value, and clinical characteristics of good, fair and poor control groups were compared. Results The median MAGE and M-value was 6.6 mmol/L and 18.7, respectively. Then MAGE ≥6.6 mmol/L and M-value ≥18.7 was defined as poor control. In the 32 patients without detectable C-peptide levels, 18 patients (56%) showed poor control. The frequency of ketosis or ketoacidosis at onset of diabetes was dramatically higher in the poor control group not only in the patients as a whole but also in those without detectable C-peptide levels. Conclusions A decreased level of C-peptide is a significant factor in glycemic instability. However, some patients have glycemic stability though β-cell function is completely depleted. The presence of ketosis or ketoacidosis at onset of diabetes may be a factor in later glycemic instability, suggesting the importance of examining patients in detail at onset of diabetes for careful follow-up to prevent progression of acute and chronic complications of diabetes.

Altered Kinetics of Interleukin-6 and Other Inflammatory Mediators During Exercise in Children With Type 1 Diabetes

BackgroundLeukocyte mobilization and secretions of cytokines, chemokines, and growth factors in children during exercise are necessary biochemical signals for physiological growth and long-term cardiovascular protection. Because of glycemic instability, altered...

High Rates of Nocturnal Hypoglycemia in a Unique Sports Camp for Athletes with Type 1 Diabetes: Lessons Learned from Continuous Glucose Monitoring Systems

BACKGROUND Glycemic instability related to exercise in people with type 1 diabetes mellitus is most often studied using short-term laboratory investigation. However, such acute laboratory sessions do not provide an "everyday" depiction of the frequency of blood glucose excursions during training. Continuous glucose monitoring systems (CGMS) provide a unique method of observing both the immediate and long-term effects of exercise on glycemic control in this active population. The purpose of this observational study was to quantify episodes of both hypo- and hyperglycemia during a 5-day training camp for athletes with type 1 diabetes METHODS Twelve subjects from the Diabetes Training Camp were randomly selected and fitted with CGMS and were instructed to maintain their usual insulin and blood capillary sampling regimens for exercise. A support team consisting of an endocrinologist, exercise physiologists, physician assistants, professional athletes and coaches, dietitians and sport psychologists were continuously involved in the athletes' care and training throughout the camp. RESULTS All 12 subjects had at least 1 hypoglycemic event during the ~60 hours of data collection. Seventy-five episodes of hypoglycemia (interstitial glucose <4 mmol/L) were detected in total; 45 of these episodes (60%) occurred at night during sleep, with the remainder occurring during waking hours. CGMS nighttime glucose nadirs (6.0+2.4 mmol/L) occurred at 3:45 AM and were modestly related to pre-bedtime blood glucose levels (r2=0.44, p<0.01, n=36 data pairs). The timing of the glucose nadir during sleep was reproducible on 2 separate camp days. CONCLUSION This field study illustrates that hypoglycemia is extremely common in regularly active individuals with type 1 diabetes, despite regular glucose testing, continuous carbohydrate availability and on-location support. Nocturnal hypoglycemia was particularly prevalent, regardless of the level of bedtime glycemia, with the lowest nighttime values typically occurring around 3:45 AM when subjects were asleep. We conclude that active persons with type 1 diabetes are highly susceptible to hypoglycemia, especially during sleeping hours. As such, CGMS may be the only practical method of detecting both asymptomatic and nocturnal episodes of hypoglycemia. These results also suggest that athletes may benefit from reductions in insulin or a slow-release carbohydrate bedtime snack during training.

Continuous Subcutaneous Insulin Infusion Attenuated Glycemic Instability in Preschool Children with Type 1 Diabetes Mellitus

Continuous subcutaneous insulin infusion (CSII) is believed to decrease glycemic instability and hypoglycemia while increasing quality of life compared to insulin injection regimens. To evaluate indices of glycemic control and impact on quality of life, we studied a group of preschool children with type 1 diabetes mellitus (DM) on CSII. Fourteen patients (eight girls and six boys) 3.9 +/- 0.8 years old with DM duration of 2.0 +/- 0.8 years were transitioned from flexible multiple daily insulin (FMDI) (pre-meal aspart and bedtime glargine) to CSII. Patients were evaluated with hemoglobin A(1c) (HbA(1c)) and continuous glucose monitoring quarterly for 1 year. Mean blood glucose (MBG), mean amplitude of glycemic excursion (MAGE), and hypoglycemic events (blood glucose <60 mg/dL) were determined. Patients' parents completed quality of life [TNO-AZL Preschool Children Quality of Life (TAPQoL)] questionnaires for their children at baseline and 1.0 year. The total daily insulin and the bolus:basal ratio did not change during CSII (0.72 +/- 0.21 vs. 0.74 +/- 0.16 U/kg/day and 2.1 +/- 0.61 vs. 2.40 +/- 0.58 U/kg/day, respectively). There was no change in HbA(1c) (8.0 +/- 0.50% vs. 7.8 +/- 0.40%) or frequency of hypoglycemia (moderate, 92.3 vs. 73.1 events/100 patient-years; severe, 22.5 vs. 17.5 events/100 patient-years). The MBG (213 +/- 94 vs. 185 +/- 79 mg/dL) and frequency (1.9 +/- 1.6 vs. 2.1 +/- 2.2) and duration (nocturnal, 135 +/- 141 vs. 120 +/- 103 min; total, 267 +/- 222 vs. 189 +/- 148 min) of hypoglycemic events did not decrease, whereas MAGE was reduced on CSII (210 +/- 31 vs. 168 +/- 22 mg/dL, P < 0.005). The quality of life subscales on the TAPQoL questionnaire did not change on CSII. CSII improved glycemic instability without reducing HbA(1c) or frequency and duration of hypoglycemic events and altering the parent's perception of his or her child's quality of life. CSII improves glycemic instability and is an effective alternative to FMDI therapy in young children with type 1 DM.

Glycaemic instability is an underestimated problem in Type II diabetes

The aim of the present study was to assess the level of glycaemic control by the measurement of 24 h blood glucose profiles and standard blood analyses under identical nutritional and physical activity conditions in patients with Type II diabetes and healthy normoglycaemic controls. A total of 11 male patients with Type II diabetes and 11 healthy matched controls participated in a 24 h CGMS (continuous subcutaneous glucose-monitoring system) assessment trial under strictly standardized dietary and physical activity conditions. In addition, fasting plasma glucose, insulin and HbA(1c) (glycated haemoglobin) concentrations were measured, and an OGTT (oral glucose tolerance test) was performed to calculate indices of whole-body insulin sensitivity, oral glucose tolerance and/or glycaemic control. In the healthy control group, hyperglycaemia (blood glucose concentration >10 mmol/l) was hardly present (2+/-1% or 0.4+/-0.2/24 h). However, in the patients with Type II diabetes, hyperglycaemia was experienced for as much as 55+/-7% of the time (13+/-2 h over 24 h) while using the same standardized diet. Breakfast-related hyperglycaemia contributed most (46+/-7%; P<0.01 as determined by ANOVA) to the total amount of hyperglycaemia and postprandial glycaemic instability. In the diabetes patients, blood HbA(1c) content correlated well with the duration of hyperglycaemia and the postprandial glucose responses (P<0.05). In conclusion, CGMS determinations show that standard measurements of glycaemic control underestimate the amount of hyperglycaemia prevalent during real-life conditions in Type II diabetes. Given the macro- and micro-vascular damage caused by postprandial hyperglycaemia, CGMS provides an excellent tool to evaluate alternative therapeutic strategies to reduce hyperglycaemic blood glucose excursions.

The Effect of Glucose Variability on the Risk of Microvascular Complications in Type 1 Diabetes

It is not known whether glycemic instability may confer a risk of microvascular complications that is in addition to that predicted by the mean blood glucose (MBG) value alone. This study has analyzed data from the Diabetes Control and Complications Trial (DCCT) to assess the effect of glucose variability on the risk of retinopathy and nephropathy in patients with type 1 diabetes. Pre- and postprandial seven-point glucose profiles were collected quarterly during the DCCT in 1,441 individuals. The mean area under the curve glucose and the SD of glucose variability within 24 h and between visits were compared with the risk of retinopathy and nephropathy, having adjusted for age, sex, disease duration, treatment group, prevention cohort, and phase of treatment. Multivariate Cox regression showed that within-day and between-day variability in blood glucose around a patient's mean value has no influence on the development or progression of either retinopathy (P = 0.18 and P = 0.72, respectively) or nephropathy (P = 0.32 and P = 0.57). Neither preprandial (P = 0.18) nor postprandial (P = 0.31) glucose concentrations preferentially contribute to the probability of retinopathy. This study has shown that blood glucose variability does not appear to be an additional factor in the development of microvascular complications. Also, pre- and postprandial glucose values are equally predictive of the small-vessel complications of type 1 diabetes.

Activation of Oxidative Stress by Acute Glucose Fluctuations Compared With Sustained Chronic Hyperglycemia in Patients With Type 2 Diabetes

Glycemic disorders, one of the main risk factors for cardiovascular disease, are associated with activation of oxidative stress. To assess the respective contributions of sustained chronic hyperglycemia and of acute glucose fluctuations to oxidative stress in type 2 diabetes. Case-control study of 21 patients with type 2 diabetes (studied 2003-2005) compared with 21 age- and sex-matched controls (studied in 2001) in Montpellier, France. Oxidative stress, estimated from 24-hour urinary excretion rates of free 8-iso prostaglandin F2alpha (8-iso PGF2alpha). Assessment of glucose fluctuations was obtained from continuous glucose monitoring system data by calculating the mean amplitude of glycemic excursions (MAGE). Postprandial contribution to glycemic instability was assessed by determining the postprandial increment of glucose level above preprandial values (mean postprandial incremental area under the curve [AUCpp]). Long-term exposure to glucose was estimated from hemoglobin A1c, from fasting glucose levels, and from mean glucose concentrations over a 24-hour period. Mean (SD) urinary 8-iso PGF2alpha excretion rates were higher in the 21 patients with diabetes (482 [206] pg/mg of creatinine) compared with controls (275 [85] pg/mg of creatinine). In univariate analysis, only MAGE (r = 0.86; P<.001) and AUCpp (r = 0.55; P = .009) showed significant correlations with urinary 8-iso PGF2alpha excretion rates. Relationships between 8-iso PGF2alpha excretion rates and either MAGE or AUCpp remained significant after adjustment for the other markers of diabetic control in multiple linear regression analysis (multiple R2 = 0.72 for the model including MAGE and multiple R2 = 0.41 for the model including AUCpp). Standardized regression coefficients were 0.830 (P<.001) for MAGE and 0.700 (P = .003) for AUCpp. Glucose fluctuations during postprandial periods and, more generally, during glucose swings exhibited a more specific triggering effect on oxidative stress than chronic sustained hyperglycemia. The present data suggest that interventional trials in type 2 diabetes should target not only hemoglobin A1c and mean glucose concentrations but also acute glucose swings.

A case of slowly progressive type 1 diabetes with unstable glycemic control caused by unusual insulin antibody and successfully treated with steroid therapy

A 75-year-old man with type 1 diabetes and history of insulin therapy for previous 3 years using only human recombinant ones was suffering from unstable glycemic control. He had a high level of total insulin and a high titer of insulin antibodies (IA) (bound/total ratio: 89.8%). Low affinity constant ( k 1: 0.0312 × 10 8 M −1) and high binding capacity ( b 1: 51.8 × 10 −8 M) of IA in the patient detected by the Scatchard analysis were not compatible with those of IA associated with exogenous insulin injections in the diabetic patients, but compatible with those of the insulin autoantibodies found in patients with insulin autoimmune syndrome (IAS), although he had DRB1*0405, which may have protection against IAS development. The glucose infusion rate during hyperinsulinemic euglycemic clamp was 2.84 mg/kg/min, suggesting a high level of insulin resistance. Steroid pulse therapy (1000 mg for 3 days) aimed at reducing the possible effect of the IA on his insulin resistance and glycemic instability successfully decreased IA titer (from 89.8 to 58.3%), lowered its binding capacity (51.8–9.8 × 10 −8 M), increased glucose infusion rate (from 2.84 to 5.55 mg/kg/min) and improved glycemic control (HbA 1c: from 10.0 to 7.4%) with reduced blood glucose excursion. In conclusion, the alteration in insulin pharmacokinetics induced by IA seemed to be the cause of the brittle diabetes of the present case. Steroid treatment might be useful for the improvement of glycamic control in such patients with high IA levels and unstable blood glucose.

Palm Glucose Readings Compared with Fingertip Readings Under Steady and Dynamic Glycemic Conditions, Using the OneTouch® Ultra® Blood Glucose Monitoring System

Past studies have suggested the absence of lag between palm glucose and fingertip glucose, even when glucose levels are changing rapidly. However, at any given time point, there may be differences between palm and fingertip glucose values because of glycemic instability and/or test methodology. The objectives of this study included assessing the variability in fingertip blood glucose test results between two fingers, and establishing whether the variability in blood glucose test results obtained from the palm was clinically equivalent to that observed in fingertip-to-fingertip comparisons. This multicenter trial was conducted on patients under both steady-state glycemic conditions and after meal and exercise challenges (to promote rapidly changing glucose). Sequential capillary glucose testing, performed with the One Touch Ultra Blood Glucose Monitoring System (LifeScan, Inc., Milpitas, CA), was allocated to two of four fingertip sites and one of two palm sites in each subject using a randomized, balanced, incomplete block design. One of the fingertips was designated the reference site. Fingertip-to-fingertip variability and fingertip- to-palm variability were assessed under these steady-state and dynamic testing conditions using error grid analysis and by comparing the proportion of clinically acceptable blood glucose tests at the palm site versus the fingertip site. Clinically acceptable agreement was defined as pairs of values (fingertip to reference, or palm to reference) within 15 mg/dL when reference glucose was < or = 75 mg/dL or within 20% when reference glucose was >75 mg/dL. One hundred eighty-one subjects with type 1 [n = 74 (40.9%)] or type 2 [n = 107 (59.1%)] diabetes at eight clinical sites completed the study. Overall, the proportion of clinically acceptable agreement was high for both palm (95.1%) and fingertip (97.5%) testing. The mean difference between palm and fingertip clinically acceptable agreement when done by healthcare professionals was -1.3% and -4.4%, under steady-state and dynamic glycemic conditions, respectively. Error grid analysis showed >97% of all palm and fingertip measurements fell in Zone A. This study demonstrated that variability between fingertip-to-fingertip and palm-to-fingertip measurements was in the clinically acceptable range during steady-state conditions and when glucose was rapidly changing.

Continuous Subcutaneous Insulin Infusion and Multiple Dose of Insulin Regimen Display Similar Patterns of Blood Glucose Excursions in Pediatric Type 1 Diabetes

Continuous subcutaneous insulin infusion (CSII) is believed to decrease glycemic variability and clinical hypoglycemia compared with the multiple daily insulin (MDI) regimen. To compare the indices of glycemic instability between CSII and MDI, we analyzed the continuous glucose monitoring system (CGMS) (Medtronic MiniMed, Northridge, CA) profiles of a group of children with type 1 diabetes mellitus with history of frequent blood glucose (BG) fluctuations and hypoglycemia. Data from 14 (nine girls, five boys) patients (3.9-16.8 years old) on CSII and 14 age- and sex-matched (nine girls, five boys) patients (3.9-16.0 years old) on MDI with similar glycemic control (hemoglobin A1c: 7.9 +/- 1.0% vs. 7.9 +/- 1.5%) and body mass index (BMI) (20.1 +/- 4.3 vs. 19.9 +/- 4.1 kg/m(2)) were evaluated by the CGMS. Mean BG (MBG), absolute means of daily differences (MODD), mean amplitude of glycemic excursion (MAGE), and number of hypoglycemic events (BG <60 mg/dL) for 48 h were calculated. The MBG, MODD, MAGE, and number and mean duration of hypoglycemia events in the CSII group were similar to those in the MDI group. The MAGE had an inverse correlation with age (CSII: r (2) = 0.52, P = 0.003; MDI: r (2) = 0.29, P < 0.04) and BMI (CSII: r (2) = 0.38, P < 0.02; MDI: r (2) = 0.71, P < 0.0002). However, there was a positive relationship between MAGE and bolus:basal insulin ratio in the CSII (r (2) = 0.28, P < 0.05) and MDI (r (2) = 0.33, P < 0.03) groups. Also, the MAGE had a positive correlation with frequency of hypoglycemic events in the CSII (r (2) = 0.44, P < 0.01) and MDI (r (2) = 0.35, P < 0.03) groups. The CSII and MDI regimens in children and adolescents with comparable glycemic control displayed similar patterns of glycemic excursions, implying that factors influencing glycemic instability in pediatric type 1 diabetes mellitus appear to be independent of treatment modality.

Rates of glucose change measured by blood glucose meter and the GlucoWatch Biographer during day, night, and around mealtimes.

The purpose of this study was to characterize the distribution of the rate of change of blood glucose for a diabetic population. The study population consisted of 124 adults with type 1 or type 2 diabetes requiring insulin. Study participants applied a GlucoWatch Biographer during the day at home for 5 consecutive days and took finger-prick blood glucose measurements hourly. Subjects kept a diary of meals. The Biographer frequently and automatically measured glucose up to three times per hour for up 12 h. Rates of glucose change were calculated for both Biographer and blood glucose measurements. Rates of glucose change during a separate study of 134 subjects were determined for daytime and nighttime use. -Mean (+/-SD) rates of change of glucose of -0.36 +/- 0.95 and 0.36 +/- 0.99 mg. dl(-1). min(-1) were found before and after lunch using blood glucose data and -0.31 +/- 1.23 and 0.43 +/- 1.26 using Biographer data. For both types of diabetes, rates of glucose change exceeded 2 mg. dl(-1). min(-1) before and after meals approximately 10% of the time. Periprandial glucose patterns showed some significant differences between type 1 and type 2 diabetic subjects. Glucose levels changed more gradually at night than during the day. Glucose values were almost equally unstable before and after meals. Glycemic instability around dinner was different in type 1 and type 2 diabetes. The GlucoWatch Biographer was found to be effective in tracking trends in glucose levels and yielded similar results as obtained by finger-prick blood samples.

Is HbA(1c) affected by glycemic instability?

HbA(1c) is a standard clinical assessment of glycemia and the basis of most data relating glycemic control to complications. It remains unclear, however, whether HbA(1c) is affected by glycemic variation and mean glycemia. To test this question, we analyzed the statistical relationship between HbA(1c) levels and glycemic variability as measured by self-monitoring of blood glucose (SMBG). The records of 256 subjects were studied. SMBG data for the preceding 3 months were downloaded, and HbA(1c) was measured by ion-exchange high-performance liquid chromatography. Simple- and random-effects linear regression models were used to assess the independent contributions of mean blood glucose (BG) and SD of BG to HbA(1c), after adjusting for the mean BG. Mean +/- SD for HbA(1c) was 7.66 +/- 1.11% and for BG was 8.5 +/- 1.9 mmol/l (153.3 +/- 34.9 mg/dl); SD of BG for individual subjects was 3.5 mmol/l (63.3 mg/dl), varying from 0.4 mmol/l (8.1 mg/dl; very stable glycemia) to 8.4 mmol/l (152.5 mg/dl; very unstable glycemia). A close correlation between mean BG and HbA(1c) was demonstrated (r = 0.62). Also, within-subject SD of BG correlated with HbA(1c) (r = 0.375), indicating that people with poorer glycemic control had higher BG variance. After adjusting for mean BG in a linear regression model, however, the effect of the within-subject SD of BG on the HbA(1c) was insignificant. Several further analyses confirmed the strength of the observation. HbA(1c) reflects mean glycemia and is not meaningfully affected by glycemic instability after adjusting for mean BG.

La variabilité glycémique asymptomatique: comment l'évaluer et quelle est son incidence clinique ?

The glycemic variations observed in nondiabetic subjects are primarily related to the post-prandial metabolic responses generated by the food intake. This physiological glycemic variability is reproducible between two successive days under conditions of similar meals and activities. In insulin-treated diabetic patients, glycemic instability is directly related to loss of glucose homeostasis due to the failure then the deficiency of endogenous insulin secretion, but its physiopathological implication in term of diabetic angiopathy risk remains to be determined. Other exogenous glycemic instability factors are known and have to be corrected (not adapted repartition of the meals and/or the insulin doses during the day, inappropriate choices in insulin regimens, errors in insulin adjustments, inadequate insulin injection). Classical glycemic measurements used to appreciate the quality of the glycemic control do not provide or give partial and erroneous information on quality of glycemic stability. It's particularly the case for glycated hemoglobin and glycemic average. In order to exactly quantify glycemic variability, specific tools of measurement or calculation can evaluate the intra-day glycemic variations or excursions (MAGE), the day-to-day glycemic variations or excursions (MODD), the meal-related glycemic excursions (MIME) or the risk of severe hypoglycemia (LBGI). Some of these tools are easy to use, other much complex or difficult to apply in clinical practice, even by using new methods such as the continuous glucose monitoring system (CGMS). Thus, asymptomatic glycemic variability is related to loss of glucose homeostasis, but also to irrelevant or incompatibility of the treatments used to obtain glucose control in insulin-treated diabetic patients. The evaluation of glucose instability can be provided using new methods of glucose monitoring and could be useful to optimize the therapeutic regimens in some of these diabetic patients.

Glucose sensor evaluation of glycemic instability in pediatric type 1 diabetes mellitus.

Maintaining blood glucose (BG) levels within the target range can be an elusive goal in children with type 1 diabetes mellitus (DM). To identify factor(s) that may contribute to glycemic instability, we analyzed the Continuous Glucose Monitoring System (CGMS) (Medtronic MiniMed, Northridge, CA) profiles of a group of children with type 1 DM and a history of frequent BG fluctuations and hypoglycemia. A total of 30 (17 girls, 13 boys) pediatric patients with a history of frequent BG fluctuations and hypoglycemia (mean age, 10.5 +/- 0.7 years; duration, 5.0 +/- 0.6 years), on three to four injections of insulin daily or insulin pump therapy, were evaluated by the CGMS. The mean BG (MBG), absolute means of daily differences (MODD), mean amplitude of glycemic excursion (MAGE), and number of hypoglycemic events (BG <60 mg/dL) for 48 h were calculated in each patient. There was a significant correlation between MBG and glycosylated hemoglobin (HbA1c) (r(2) = 0.22, p < 0.009). There was also a significant correlation between severity of lipohypertrophy and glycemic control (HbA1c) (r(2) = 0.20, p < 0.01). The MODD values had a positive correlation with the severity of injection site lipohypertrophy (r(2) = 0.37, p < 0.0003). The MAGE values had a positive correlation with bolus:basal insulin ratio (r(2) = 0.22, p < 0.009) and number of hypoglycemic events (r(2) = 0.21, p < 0.008), independent of age, MBG, and glycemic control. The 48-h CGMS profile can help characterize day-to-day and within-day BG variability and identify factors influencing glycemic instability in pediatric type 1 DM.