Nocturnal hypoglycaemia in Type 1 diabetic patients, assessed with continuous glucose monitoring: frequency, duration and associations

Modifiable self-management practices impact nocturnal and morning glycaemia in type 1 diabetes

AIMS

To identify risk factors for nocturnal/morning hypo- and hyperglycaemia in type 1 diabetes.

METHODS

Data on self-management practices were obtained from 3-day records. We studied the associations between self-management practices on the first recording day and the self-reported blood glucose (BG) concentrations on the subsequent night/morning.

RESULTS

Of the 1025 participants (39 % men, median age 45 years), 4.4 % reported nocturnal hypoglycaemia (<3.9 mmol/l), 9.8 % morning hypoglycaemia, 51.5 % morning euglycaemia, and 34.3 % morning hyperglycaemia (≥8.9 mmol/l). Within hypoglycaemic range, insulin pump use was associated with higher nocturnal BG concentration (B=0.486 [95 % Confidence Interval=0.121-0.852], p=0.009). HbA1c was positively (0.046 [0.028-0.065], p<0.001), while antecedent fibre intake (-0.327 [-0.543 - -0.111], p=0.003) and physical activity (PA) (-0.042 [-0.075 - -0.010], p=0.010) were inversely associated with morning BG concentration. The odds of morning hypoglycaemia were increased by previous day hypoglycaemia (OR=2.058, p=0.002) and alcohol intake (1.031, p=0.001). Previous day PA (0.977, p=0.031) and fibre intake (0.848, p=0.017) were inversely, while HbA1c (1.027, p<0.001) was positively associated with the risk of morning hyperglycaemia.

CONCLUSIONS

Alcohol avoidance may prevent nocturnal hypoglycaemia, while PA and fibre intake may reduce hyperglycaemia risk. Avoidance of daytime hypoglycaemia and keeping HbA1c in control may help maintain normoglycaemia also at night-time.

Prevalence of nocturnal hypoglycemia in free-living conditions in adults with type 1 diabetes: What is the impact of daily physical activity?

Objective

Studies investigating strategies to limit the risk of nocturnal hypoglycemia associated with physical activity (PA) are scarce and have been conducted in standardized, controlled conditions in people with type 1 diabetes (T1D). This study sought to investigate the effect of daily PA level on nocturnal glucose management in free-living conditions while taking into consideration reported mitigation strategies to limit the risk of nocturnal hyoglycemia in people with T1D.

Methods

Data from 25 adults (10 males, 15 females, HbA1c: 7.6 ± 0.8%), 20-60 years old, living with T1D, were collected. One week of continuous glucose monitoring and PA (assessed using an accelerometer) were collected in free-living conditions. Nocturnal glucose values (midnight-6:00 am) following an active day "ACT" and a less active day "L-ACT" were analyzed to assess the time spent within the different glycemic target zones (<3.9 mmol/L; 3.9 - 10.0 mmol/L and >10.0 mmol/L) between conditions. Self-reported data about mitigation strategies applied to reduce the risk of nocturnal hypoglycemia was also analyzed.

Results

Only 44% of participants reported applying a carbohydrate- or insulin-based strategy to limit the risk of nocturnal hypoglycemia on ACT day. Nocturnal hypoglycemia occurrences were comparable on ACT night versus on L-ACT night. Additional post-meal carbohydrate intake was higher on evenings following ACT (27.7 ± 15.6 g, ACT vs. 19.5 ± 11.0 g, L-ACT; P=0.045), but was frequently associated with an insulin bolus (70% of participants). Nocturnal hypoglycemia the night following ACT occurred mostly in people who administrated an additional insulin bolus before midnight (3 out of 5 participants with nocturnal hypoglycemia).

Conclusions

Although people with T1D seem to be aware of the increased risk of nocturnal hypoglycemia associated with PA, the risk associated with additional insulin boluses may not be as clear. Most participants did not report using compensation strategies to reduce the risk of PA related late-onset hypoglycemia which may be because they did not consider habitual PA as something requiring treatment adjustments.

Is it possible to predict the onset of nocturnal asymptomatic hypoglycemia in patients with type 1 diabetes receiving insulin degludec? Potential role of previous day and next morning glucose values

AIMS/INTRODUCTION

To determine whether the occurrence of nocturnal asymptomatic, serious, clinically important hypoglycemia (NSH) could be predicted based on glucose values on the previous day and the following morning of the day of onset.

MATERIALS AND METHODS

This study examined patients with type 1 diabetes who underwent continuous glucose monitoring assessments and received insulin degludec. NSH was defined as glucose level <54 mg/dL detected between 24.00 and 06.00 hours. The participants were evaluated to determine the following: (i) glucose level at bedtime (24.00 hours) on the previous day (BG); (ii) fasting glucose level (FG); and (iii) the range of post-breakfast glucose elevation. The patients were divided into those with NSH and those without, and compared using t-tests. Optimal cut-off values for relevant parameters for predicting NSH were determined using receiver operating characteristic analysis.

RESULTS

The study included a total of 31 patients with type 1 diabetes (mean glycated hemoglobin value 7.8 ± 0.7%). NSH occurred in eight patients (26%). BG and FG were significantly lower in those with NSH than in those without (P = 0.044, P < 0.001). The range of post-breakfast glucose elevation was significantly greater in those with NSH than in those without. The cut-off glucose values for predicting NSH were as follows: BG = 90 mg/dL (sensitivity 0.83/specificity 0.75/area under the curve 0.79, P = 0.017) and FG = 69 mg/dL (0.83/0.75/0.86, P = 0.003).

CONCLUSIONS

The results showed that in patients with type 1 diabetes receiving insulin degludec, BG <90 mg/dL and FG <69 mg/dL had an approximately 80% probability of predicting the occurrence of NSH.

Asymptomatic hypoglycaemia in Type 1 diabetes: incidence and risk factors

AIM

The epidemiology of asymptomatic (silent) hypoglycaemia is not well-described. We investigated incidence and risk factors for asymptomatic hypoglycaemia in Type 1 diabetes.

METHODS

A cohort of 153 people with Type 1 diabetes participated in 6 days of blinded continuous glucose monitoring (CGM) and recording of hypoglycaemia symptoms. At entry, hypoglycaemia awareness was classified (by three different methods) and HbA_1c and C-peptide were measured. Hypoglycaemic episodes were defined as interstitial glucose ≤ 3.9 mmol/l (IG_3.9 ) or ≤ 3.0 mmol/l (IG_3.0 ) for ≥ 15 min, and were considered asymptomatic if no hypoglycaemic symptoms were reported.

RESULTS

At thresholds IG_3.9 and IG_3.0 , the incidence rates of hypoglycaemic episodes were 5.0 (7.9) [median (IQR)] and 1.3 (3.4) episodes/person-week, respectively. Three-quarters of episodes were asymptomatic. In total, 77% and 52% of participants experienced one or more episode of asymptomatic hypoglycaemia at IG_3.9 and IG_3.0 [3.0 (6.2) and 1.0 (2.3) asymptomatic episodes/person-week]. At multivariate analysis, reduced awareness was positively associated with asymptomatic hypoglycaemia, particularly nocturnal events, and negatively with symptomatic hypoglycaemia. High insulin dose was associated with increased risk of both asymptomatic and symptomatic hypoglycaemia, whereas low HbA_1c and long diabetes duration were risk factors only for symptomatic hypoglycaemia.

CONCLUSIONS

Asymptomatic hypoglycaemia constitutes the majority of hypoglycaemic events in Type 1 diabetes. Reduced hypoglycaemia awareness and high insulin dose are risk factors for asymptomatic hypoglycaemia but other conventional risk factors for severe hypoglycaemia do not correlate with risk of asymptomatic episodes.

The risks of nocturnal hypoglycaemia in insulin-treated diabetes

Over half of all episodes of severe hypoglycaemia (requiring external help) occur during sleep, but nocturnal hypoglycaemia is often asymptomatic and unrecognised. The precise incidence of nocturnal hypoglycaemia is difficult to determine with no agreed definition, but continuous glucose monitoring has shown that it occurs frequently in people taking insulin. Attenuation of the counter-regulatory responses to hypoglycaemia during sleep may explain why some episodes are undetected and more prolonged, and modifies cardiovascular responses. The morbidity and mortality associated with nocturnal hypoglycaemia is probably much greater than realised, causing seizures, coma and cardiovascular events and affecting quality of life, mood and work performance the following day. It may induce impaired awareness of hypoglycaemia. Cardiac arrhythmias that occur during nocturnal hypoglycaemia include bradycardia and ectopics that may provoke dangerous arrhythmias. Treatment strategies are discussed that may help to minimise the frequency of nocturnal hypoglycaemia.

Prediction of nocturnal hypoglycemia unawareness by fasting glucose levels or post-breakfast glucose fluctuations in patients with type 1 diabetes receiving insulin degludec: A pilot study

OBJECTIVE

To evaluate whether nocturnal asymptomatic hypoglycemia (NAH) can be predicted by fasting glucose levels or post-breakfast glucose fluctuations in patients with type 1 diabetes (T1D) receiving insulin degludec.

METHODS

Patients with T1D receiving insulin degludec underwent at-home CGM assessments. Indices for glycemic variability before and after breakfast included fasting glucose levels and the range of post-breakfast glucose elevation. For comparison, the patients were classified into those with NAH and those without. The optimal cut-off values for the relevant parameters were determined to predict NAH using ROC analysis.

RESULTS

The study included a total of 31 patients (mean HbA1c values, 7.8 ± 0.7%), and 16 patients (52%) had NAH. Those with NAH had significantly lower fasting glucose levels than did those without (82 ± 48 mg/dL vs. 144 ± 69 mg/dL; P = 0.009). The change from pre- to post-breakfast glucose levels was significantly greater among those with NAH (postprandial 1-h, P = 0.028; postprandial 2-h, P = 0.028). The cut-off values for prediction of NAH were as follows: fasting glucose level <84 mg/dL (sensitivity 0.80/specificity 0.75/AUC 0.80; P = 0.004), 1-h postprandial elevation >69 mg/dL (0.75/0.67/0.73; P = 0.033), and 2-h postprandial elevation >99 mg/dL (0.69/0.67/0.71; P = 0.044).

CONCLUSIONS

The results suggest that fasting glucose level of < 84 mg/dL had approximately 80% probability of predicting the occurrence of NAH in T1D receiving insulin degludec. It was also shown that the occurrence of hypoglycemia led to greater post-breakfast glucose fluctuations and steeper post-breakfast glucose gradients.

Glucose variability indices predict the episodes of nocturnal hypoglycemia in elderly type 2 diabetic patients treated with insulin

AIM

O determine the applicability of glucose variability (GV) indices derived from continuous glucose monitoring (CGM) data for prediction of nocturnal hypoglycemia (NH) in elderly patients with type 2 diabetes treated with insulin.

METHODS

We observed 83 insulin-treated in-patients, 65-80 years of age. Blinded CGM data for 176 nights were analyzed. Daytime (06:00-22:59) mean glucose, Standard Deviation (SD), 2-h Continuous Overlapping Net Glycemic Action (CONGA2) and Mean Absolute Glucose (MAG), pre-midnight (23:00-23:59) mean glucose, SD and MAG, 24-h Mean Amplitude of Glucose Excursions (MAGE), were estimated. Pre-midnight glucose trends were estimated as the absolute difference between glucose values at 23:00 and 23:59 (deltaG). Episode of interstitial glucose ≤70mg/dL observed from 0:00 to 5:59 was considered as NH.

RESULTS

NH was present in 68 out of 176 24-h recordings (39%). Lower daytime mean glucose and CONGA2, and higher MAG values were found in patients with NH as compared to those without (p=0.0002, p=0.0001 and p=0.02, respectively). Pre-midnight mean glucose was lower, while pre-midnight deltaG was higher in patients with NH (p<0.0001 and p=0.02). Antecedent daytime hypoglycemia increased the risk of NH (p<0.0001). In logistic regression analysis, the combination of daytime MAG and pre-midnight mean glucose was the most reliable predictor of subsequent NH (accuracy 75.6%, p=0.0004).

CONCLUSION

The analysis of CGM-derived GV parameters could improve prediction of NH in elderly patients with type 2 diabetes treated with insulin.

Continuous Glucose Monitoring: Impact on Hypoglycemia

The necessity of strict glycemic control is unquestionable. However, hypoglycemia remains a major limiting factor in achieving satisfactory glucose control, and evidence is mounting to show that hypoglycemia is not benign. Over the past decade, evidence has consistently shown that real-time continuous glucose monitoring improves glycemic control in terms of lowering glycated hemoglobin levels. However, real-time continuous glucose monitoring has not met the expectations of the diabetes community with regard to hypoglycemia prevention. The earlier trials did not demonstrate any effect on either mild or severe hypoglycemia and the effect of real-time continuous glucose monitoring on nocturnal hypoglycemia was often not reported. However, trials specifically designed to reduce hypoglycemia in patients with a high hypoglycemia risk have demonstrated a reduction in hypoglycemia, suggesting that real-time continuous glucose monitoring can prevent hypoglycemia when it is specifically used for that purpose. Moreover, the newest generation of diabetes technology currently available commercially, namely sensor-augmented pump therapy with a (predictive) low glucose suspend feature, has provided more convincing evidence for hypoglycemia prevention. This article provides an overview of the hypoglycemia outcomes of randomized controlled trials that investigate the effect of real-time continuous glucose monitoring alone or sensor-augmented pump therapy with a (predictive) low glucose suspend feature. Furthermore, several possible explanations are provided why trials have not shown a reduction in severe hypoglycemia. In addition, existing evidence is presented of real-time continuous glucose monitoring in patients with impaired awareness of hypoglycemia who have the highest risk of severe hypoglycemia.

Can Fasting Glucose Levels or Post-Breakfast Glucose Fluctuations Predict the Occurrence of Nocturnal Asymptomatic Hypoglycemia in Type 1 Diabetic Patients Receiving Basal-Bolus Insulin Therapy with Long-Acting Insulin?

Objective

To investigate whether the occurrence of nocturnal asymptomatic hypoglycemia may be predicted based on fasting glucose levels and post-breakfast glucose fluctuations.

Patients and Methods

The study subjects comprised type 1 diabetic patients who underwent CGM assessments and received basal-bolus insulin therapy with long-acting insulin. The subjects were evaluated for I) fasting glucose levels and II) the range of post-breakfast glucose elevation (from fasting glucose levels to postprandial 1- and 2-hour glucose levels). The patients were divided into those with asymptomatic hypoglycemia during nighttime and those without for comparison. Optimal cut-off values were also determined for relevant parameters that could predict nighttime hypoglycemia by using ROC analysis.

Results

64 patients (mean HbA1c 8.7 ± 1.8%) were available for analysis. Nocturnal asymptomatic hypoglycemia occurred in 23 patients (35.9%). Fasting glucose levels (I) were significantly lower in those with hypoglycemia than those without (118 ± 35 mg/dL vs. 179 ± 65 mg/dL; P < 0.001). The range of post-breakfast glucose elevation (II) was significantly greater in those with hypoglycemia than in those without (postprandial 1-h, P = 0.003; postprandial 2-h, P = 0.005). The cut-off values determined for relevant factors were as follows: (I) fasting glucose level < 135 mg/dL (sensitivity 0.73/specificity 0.83/AUC 0.79, P < 0.001); and (II) 1-h postprandial elevation > 54 mg/dL (0.65/0.61/0.71, P = 0.006), 2-h postprandial elevation > 78 mg/dL (0.65/0.73/0.71, P = 0.005).

Conclusions

Nocturnal asymptomatic hypoglycemia was associated with increases in post-breakfast glucose levels in type 1 diabetes. Study findings also suggest that fasting glucose levels and the range of post-breakfast glucose elevation could help predict the occurrence of nocturnal asymptomatic hypoglycemia.

Hypoglycemia in Patients with Diabetes and Renal Disease

This article summarizes our current knowledge of the epidemiology, pathogenesis, and morbidity of hypoglycemia in patients with diabetic kidney disease and reviews therapeutic limitations in this situation.

Association between post-dinner dietary intakes and nocturnal hypoglycemic risk in adult patients with type 1 diabetes

AIMS

To describe (i) current bedtime nutritional practices and (ii) the association between post-dinner dietary intake and the occurrence of non-severe nocturnal hypoglycemia (NH) in real-life conditions among adult patients with type 1 diabetes using insulin analogs.

METHODS

One hundred adults (median [interquartile range]: age 46.4 [36.0-55.8] years, HbA1c 7.9 [7.3-8.6] % (63 [56-70] mmol/mol)) using multiple daily injections (n=67) or insulin pump (n=33) wore a blinded continuous glucose monitoring system and completed a food diary for 72-h.

RESULTS

NH occurred on 28% of 282 nights analyzed. (i) Patients reported post-dinner dietary intakes on 63% of the evenings. They injected rapid-acting insulin boluses on 64 occasions (23% of 282 evenings). These insulin boluses were mostly injected with (n=37) dietary intakes. (ii) Post-dinner dietary intake was not associated with NH occurrence in univariate analyses. In multivariate analyses, the injection of rapid-acting insulin modulated the association between post-dinner dietary intake and NH: with insulin, post-dinner carbohydrate intake was positively associated with NH (odds ratio (OR): 1.16 [95% confidence interval, CI: 1.04-1.29] per 5g increase, p=0.008); without insulin, post-dinner protein intake was inversely associated with NH occurrence (OR [95% CI]: 0.88 [0.78-1.00] per 2g increase, p=0.048).

CONCLUSIONS

NH remains frequent in adults with type 1 diabetes. There is a complex relationship between post-dinner dietary intake and NH occurrence, including the significant role of nutrient content and rapid-acting insulin injection that requires further investigation.

Hypoglycemia, chronic kidney disease, and diabetes mellitus

Hypoglycemia is a major problem associated with substantial morbidity and mortality in patients with diabetes and is often a major barrier to achieving optimal glycemic control. Chronic kidney disease not only is an independent risk factor for hypoglycemia but also augments the risk of hypoglycemia that is already present in people with diabetes. This article summarizes our current knowledge of the epidemiology, pathogenesis, and morbidity of hypoglycemia in patients with diabetes and chronic kidney disease and reviews therapeutic considerations in this situation. PubMed and MEDLINE were searched for literature published in English from January 1989 to May 2014 for diabetes mellitus, hypoglycemia, chronic kidney disease, and chronic renal insufficiency.

When hypoglycemia is not obvious: diagnosing and treating under-recognized and undisclosed hypoglycemia

Hypoglycemia continues to be a significant problem for patients with diabetes. The incidence remains high but patients may also be under-reporting hypoglycemic events for various reasons, including hypoglycemia unawareness and deliberate non-reporting. This restricts the ability of healthcare professionals to manage treatment effectively. The aim of this article is to focus specifically on the issues associated with hypoglycemia unawareness and undisclosed hypoglycemia. The article provides general practice teams with an overview of these problems and, through patient narratives, suggests ways to mitigate them.

Hypoglycemia

Hypoglycemia remains a common problem for patients with diabetes and is associated with substantial morbidity and mortality. This article summarizes our current knowledge of the epidemiology, pathogenesis, risk factors, and complications of hypoglycemia in patients with diabetes and discusses prevention and treatment strategies.

Susceptibility of interstitial continuous glucose monitor performance to sleeping position

BACKGROUND

Developing a round-the-clock artificial pancreas requires accurate and stable continuous glucose monitoring. The most widely used continuous glucose monitors (CGMs) are percutaneous, with the sensor residing in the interstitial space. Inaccuracies in percutaneous CGM readings during periods of lying on the devices (e.g., in various sleeping positions) have been anecdotally reported but not systematically studied.

METHODS

In order to assess the impact of sleep and sleep position on CGM performance, we conducted a study in human subjects in which we measured the variability of interstitial CGM data at night as a function of sleeping position. Commercially available sensors were placed for 4 days in the abdominal subcutaneous tissue in healthy, nondiabetic volunteers (four sensors per person, two per side). Nocturnal sleeping position was determined from video recordings and correlated to sensor data.

RESULTS

We observed that, although the median of the four sensor readings was typically 70-110 mg/dl during sleep, individual sensors intermittently exhibited aberrant glucose readings (&gt;25 mg/dl away from median) and that these aberrant readings were strongly correlated with subjects lying on the sensors. We expected and observed that most of these aberrant sleep-position-related CGM readings were sudden decreases in reported glucose values, presumably due to local blood-flow decreases caused by tissue compression. Curiously, in rare cases, the aberrant CGM readings were elevated values.

CONCLUSIONS

These findings highlight limitations in our understanding of interstitial fluid physiology in the subcutaneous space and have significant implications for the utilization of sensors in the construction of an artificial pancreas.

Nocturnal continuous glucose monitoring: accuracy and reliability of hypoglycemia detection in patients with type 1 diabetes at high risk of severe hypoglycemia

BACKGROUND

A reliable method to detect biochemical nocturnal hypoglycemia is highly needed, especially in patients with recurrent severe hypoglycemia. We evaluated reliability of nocturnal continuous glucose monitoring (CGM) in patients with type 1 diabetes at high risk of severe hypoglycemia.

PATIENTS AND METHODS

Seventy-two type 1 diabetes patients with recurrent severe hypoglycemia (two or more events within the last year) participated for 4 nights in blinded CGM recordings (Guardian(®) REAL-Time CGMS and Sof-Sensor(®); Medtronic MiniMed, Northridge, CA). Blood was drawn hourly from 23:00 to 07:00 h for plasma glucose (PG) measurements (gold standard).

RESULTS

Valid data were obtained in 217 nights. The sensitivity of CGM was 65% (95% confidence interval, 53-77%) below 4 mmol/L, 40% (24-56%) below 3 mmol/L, and 17% (0-47%) below 2.2 mmol/L. PG and CGM readings correlated in the total measurement range (Spearman's ρ=0.82; P<0.001). In the normo- and hyperglycemic ranges CGM underestimated PG by 1.1 mmol/L (0.9-1.2 mmol/L) (P<0.001); in contrast, in the hypoglycemic range (PG<4 mmol/L) CGM overestimated PG levels by 1.0 mmol/L (P<0.001). The mean absolute relative differences in the hypo- (≤3.9 mmol/L), normo- (4-9.9 mmol/L), and hyperglycemic (≥10 mmol/L) ranges were 45% (37-53%), 23% (22-25%), and 20% (19-21%), respectively. Continuous glucose error grid analysis indicated a clinical accuracy of 56%, 99%, and 93% in the hypo-, normo-, and hyperglycemic ranges, respectively.

CONCLUSIONS

The accuracy in the hypoglycemic range of nocturnal CGM data using Sof-Sensor is suboptimal in type 1 diabetes patients at high risk of severe hypoglycemia. To ensure clinical useful sensitivity in detection of nocturnal hypoglycemic episodes, an alarm threshold should not be lower than 4 mmol/L.

Italian contributions to the development of continuous glucose monitoring sensors for diabetes management

Monitoring glucose concentration in the blood is essential in the therapy of diabetes, a pathology which affects about 350 million people around the World (three million in Italy), causes more than four million deaths per year and consumes a significant portion of the budget of national health systems (10% in Italy). In the last 15 years, several sensors with different degree of invasiveness have been proposed to monitor glycemia in a quasi-continuous way (up to 1 sample/min rate) for relatively long intervals (up to 7 consecutive days). These continuous glucose monitoring (CGM) sensors have opened new scenarios to assess, off-line, the effectiveness of individual patient therapeutic plans from the retrospective analysis of glucose time-series, but have also stimulated the development of innovative on-line applications, such as hypo/hyper-glycemia alert systems and artificial pancreas closed-loop control algorithms. In this review, we illustrate some significant Italian contributions, both from industry and academia, to the growth of the CGM sensors research area. In particular, technological, algorithmic and clinical developments performed in Italy will be discussed and put in relation with the advances obtained in the field in the wider international research community.

Sensor-augmented pump therapy lowers HbA(1c) in suboptimally controlled Type 1 diabetes; a randomized controlled trial

AIMS

To investigate the efficacy of sensor-augmented pump therapy vs. multiple daily injection therapy in patients with suboptimally controlled Type 1 diabetes.

METHODS

In this investigator-initiated multi-centre trial (the Eurythmics Trial) in eight outpatient centres in Europe, we randomized 83 patients with Type 1 diabetes (40 women) currently treated with multiple daily injections, age 18-65 years and HbA(1c) ≥ 8.2% (≥ 66 mmol/mol) to 26 weeks of treatment with either a sensor-augmented insulin pump (n = 44) (Paradigm(®) REAL-Time) or continued with multiple daily injections (n = 39). Change in HbA(1c) between baseline and 26 weeks, sensor-derived endpoints and patient-reported outcomes were assessed.

RESULTS

The trial was completed by 43/44 (98%) patients in the sensor-augmented insulin pump group and 35/39 (90%) patients in the multiple daily injections group. Mean HbA(1c) at baseline and at 26 weeks changed from 8.46% (SD 0.95) (69 mmol/mol) to 7.23% (SD 0.65) (56 mmol/mol) in the sensor-augmented insulin pump group and from 8.59% (SD 0.82) (70 mmol/mol) to 8.46% (SD 1.04) (69 mmol/mol) in the multiple daily injections group. Mean difference in change in HbA(1c) after 26 weeks was -1.21% (95% confidence interval -1.52 to -0.90, P < 0.001) in favour of the sensor-augmented insulin pump group. This was achieved without an increase in percentage of time spent in hypoglycaemia: between-group difference 0.0% (95% confidence interval -1.6 to 1.7, P = 0.96). There were four episodes of severe hypoglycaemia in the sensor-augmented insulin pump group and one episode in the multiple daily injections group (P = 0.21). Problem Areas in Diabetes and Diabetes Treatment Satisfaction Questionnaire scores improved in the sensor-augmented insulin pump group.

CONCLUSIONS

Sensor augmented pump therapy effectively lowers HbA(1c) in patients with Type 1 diabetes suboptimally controlled with multiple daily injections.

Sleep and the response to hypoglycaemia

Undetected nocturnal hypoglycaemia frequently occurs in patients with diabetes, having a negative influence on well-being, counterregulation against and awareness of subsequent hypoglycaemia, and even causing sudden death in some cases most likely by inducing cardiac arrhythmia. Sleep markedly weakens the neuroendocrine defence mechanism against hypoglycaemia by shifting the glycaemic threshold for counterregulatory activation to lower levels. While hypoglycaemia triggers awakening in healthy subjects, patients with type 1 diabetes frequently fail to awake in the presence of low plasma glucose levels. Little is known about the frequency of and responses to nocturnal hypoglycaemia in patients with type 2 diabetes. Unfortunately, effective strategies to prevent or even safely detect nocturnal hypoglycaemia are still lacking. Taken together, hypoglycaemia occurring during sleep presents a major, often neglected problem in the management of diabetic patients. Different aspects of this phenomenon such as responses to and consequences of nocturnal hypoglycaemia as well as strategies for its prevention are highlighted in this review.

Patients' perception and future acceptance of an artificial pancreas

BACKGROUND

Little is known of patient acceptance of an artificial pancreas (AP). The purpose of this study was to investigate future acceptance of an AP and its determinants.

METHODS

Patients with type 1 diabetes treated with insulin pump therapy were interviewed using questions based on the technology acceptance model and completed the diabetes treatment and satisfaction questionnaire (DTSQ).

RESULTS

Twenty-two adults with type 1 diabetes participated. Half of the patients were followed in a university hospital, and the others were under treatment in an affiliated teaching hospital. Half of the patients were male. The mean DTSQ score was 29 (range 23-33). The AP was perceived as likely to be useful. Perceived advantages were a stable glucose regulation, less need for self-monitoring of blood glucose, relief of daily concerns, and time saving. Participants were confident in their capability to use the system. Although many participants (58%) had been reluctant to start continuous subcutaneous insulin infusion, the majority (79%) felt they would have no barriers to start using the AP. Trust in the AP was related to the quality of glucose control it would provide. Almost everyone expressed the intention to use the new system when available, even if it would initially not cover 24/24 hours.

CONCLUSION

The overall attitude on the AP was positive. Intention to use was dependent on trust in the AP, which was related to the quality of glucose control provided by the AP.

Prolonged nocturnal hypoglycemia is common during 12 months of continuous glucose monitoring in children and adults with type 1 diabetes

OBJECTIVE

To characterize the amount of nocturnal hypoglycemia and evaluate factors associated with nocturnal hypoglycemia assessed with continuous glucose monitoring (CGM) in adults and children with type 1 diabetes who participated in the Juvenile Diabetes Research Foundation CGM randomized clinical trial.

RESEARCH DESIGN AND METHODS

The analysis included 36,467 nights with >or=4 h of CGM glucose readings between 12 midnight and 6:00 a.m. from 176 subjects assigned to the CGM group of the trial. The percentage of nights in which hypoglycemia occurred (two consecutive CGM readings <or=60 mg/dl in 20 min) was computed for each subject. Associations with baseline characteristics and clinical factors were evaluated using a multivariate regression model.

RESULTS

Hypoglycemic events occurred during 8.5% of nights, with the median percentage of nights with hypoglycemia per subject being 7.4% (interquartile range 3.7-12.1%). The duration of hypoglycemia was >or=2 h on 23% of nights with hypoglycemia. In a multivariate model, a higher incidence of nocturnal hypoglycemia was associated with 1) lower baseline A1C levels (P < 0.001) and 2) the occurrence of hypoglycemia on one or more nights during baseline blinded CGM (P < 0.001). The hypoglycemia frequency was not associated with age or with insulin modality (pump versus multiple daily injections).

CONCLUSIONS

Nocturnal hypoglycemia is frequent and often prolonged in adults and children with type 1 diabetes. Patients with low A1C levels are at an increased risk for its occurrence. One week of blinded CGM can identify patients who are at greater risk for nocturnal hypoglycemia.

Sense and nonsense in sensors

Continuous subcutaneous glucose monitoring (CGM) is a developing technology in the treatment of diabetes mellitus. The first randomised controlled trials on its efficacy have been performed. In several studies, CGM lowered HbA1c in adult patients with suboptimally controlled type 1 diabetes mellitus, when selecting compliant patients who tolerate the device. However, as a preventive tool for hypoglycaemia, CGM has not fulfilled the great expectations. Increasing reimbursement of CGM is expected in the near future, awaiting studies on cost-effectiveness.

Nocturnal hypoglycaemia in type 1 diabetes--frequency and predictive factors

BACKGROUND

Nocturnal hypoglycaemia (NH) remains a problem in type 1 diabetes and spontaneous asymptomatic NH may be a risk factor for sudden death ('Dead in Bed' syndrome).

AIMS

To explore whether any predictive relationship exists between the average or time-specific glycaemia and the occurrence of NH.

METHODS

Twenty-five healthy patients with type 1 diabetes underwent two separate overnight periods of continuous glucose monitoring (CGM) using a MMT-7002 Medtronic MiniMed System. There was a 6-week interval before the second monitoring period. CGM glucose levels recorded between 23:00 and 08:00 h defined the nocturnal period and recorded glucose monitoring levels <3.5 mmol/l for at least 10 min during this time-defined NH. A CGM recording at 23:00 h and 08:00 h were taken as the bedtime and fasting glucose levels, respectively.

RESULTS

The mean +/- SD age was 37 +/- 7 years and duration of diabetes 13 +/- 7 years; 16 (64%) were on long-acting analogue insulin. Forty-nine CGM data sets were recorded. Fourteen episodes of NH occurred in 12 patients (Group 1), 13 patients (Group 2) had no NH. Group 1 (NH) had a lower mean bedtime glucose recorded compared with Group 2 (7.7 +/- 4.3 vs. 11.4 +/- 4.0 mmol/l, P = 0.0035). Fasting glucose level was also lower in Group 1 following the occurrence of NH (P = 0.014). There was no difference in the type of insulin used between the two groups.

CONCLUSION

Our data show that in normal day to day settings, NH is common and that the bedtime glucose level is a significant predictive factor.

TheClinical Research Tool: a high-performance microdialysis-based system for reliably measuring interstitial fluid glucose concentration

BACKGROUND

A novel microdialysis-based continuous glucose monitoring system, the so-called Clinical Research Tool (CRT), is presented. The CRT was designed exclusively for investigational use to offer high analytical accuracy and reliability. The CRT was built to avoid signal artifacts due to catheter clogging, flow obstruction by air bubbles, and flow variation caused by inconstant pumping. For differentiation between physiological events and system artifacts, the sensor current, counter electrode and polarization voltage, battery voltage, sensor temperature, and flow rate are recorded at a rate of 1 Hz.

METHOD

In vitro characterization with buffered glucose solutions (c(glucose) = 0 - 26 x 10(-3) mol liter(-1)) over 120 h yielded a mean absolute relative error (MARE) of 2.9 +/- 0.9% and a recorded mean flow rate of 330 +/- 48 nl/min with periodic flow rate variation amounting to 24 +/- 7%. The first 120 h in vivo testing was conducted with five type 1 diabetes subjects wearing two systems each. A mean flow rate of 350 +/- 59 nl/min and a periodic variation of 22 +/- 6% were recorded.

RESULTS

Utilizing 3 blood glucose measurements per day and a physical lag time of 1980 s, retrospective calibration of the 10 in vivo experiments yielded a MARE value of 12.4 +/- 5.7. Clarke error grid analysis resulted in 81.0%, 16.6%, 0.8%, 1.6%, and 0% in regions A, B, C, D, and E, respectively.

CONCLUSION

The CRT demonstrates exceptional reliability of system operation and very good measurement performance. The ability to differentiate between artifacts and physiological effects suggests the use of the CRT as a reference tool in clinical investigations.

Use of short-term real-time continuous glucose monitoring in type 1 diabetes patients on continuous intraperitoneal insulin infusion: a feasibility study

BACKGROUND

In diabetes, strict glycemic control reduces risk of complications. One mode of therapy is continuous intraperitoneal insulin infusion (CIPII). With CIPII, like all intensified treatment strategies, frequent assessment of glucose levels is mandatory. Real-time (RT)-continuous glucose monitoring (CGM) gives RT information without the need for multiple invasive measurements. In theory, CIPII combined with RT-CGM could provide near normal glucose profiles. The objective of this study is to investigate effectiveness and safety of RT-CGM in patients treated with intraperitoneal insulin through an implanted pump.

METHODS

In an open-label, crossover, randomized study, effects of 6-day open RT-CGM use were studied in 12 type 1 diabetes patients on CIPII, with blinded RT-CGM used as a control. Primary outcome was time in euglycemia. Secondary outcomes included time in other glucose ranges, incidence of adverse events, and patient satisfaction. Agreement of self-measurement of blood glucose (SMBG) and RT-CGM measurements was assessed.

RESULTS

Median time spent in euglycemia was 68.2% (55.9-72.3%) with open RT-CGM and 64.9% (55.3-71.2%) with blinded RT-CGM (P = 0.25). Time spent in other glucose ranges did not differ (P > 0.05). There were no serious adverse events. Patient satisfaction was good. Median relative absolute difference of SMBG and RT-CGM values was 13.9%. Bland-Altman analysis showed a mean difference of -0.31 mg/dL with lower and upper limits of agreement of -77.0 and +76.4 mg/dL, respectively.

CONCLUSIONS

Short-term use of RT-CGM, although safe and with good patient satisfaction, does not result in more time spent in euglycemia, nor does it change time spent in other glucose ranges in our population of type 1 diabetes patients receiving CIPII.

Cardiac arrhythmia and nocturnal hypoglycaemia in type 1 diabetes--the 'dead in bed' syndrome revisited

AIMS/HYPOTHESIS

Sudden nocturnal death in type 1 diabetes ('dead in bed' syndrome) is thought to be due to ECG QT prolongation with subsequent ventricular tachyarrhythmia in response to nocturnal hypoglycaemia. We investigated this theoretical mechanism using continuous ECG and continuous glucose monitoring in a group of patients with type 1 diabetes.

METHODS

Twenty-five patients with type 1 diabetes (age 20-50 years) underwent two separate 24 h ECG and continuous glucose monitoring periods. Patients were fully ambulant and carried out normal daily activities.

RESULTS

There were 13 episodes (26% of recordings) of nocturnal hypoglycaemia, eight of <2.2 mmol/l and five of 2.2-3.4 mmol/l. Corrected QT interval (QTc) was longer during nocturnal hypoglycaemia compared with normoglycaemic control periods (445 +/- 40 vs 415 +/- 23 ms; p = 0.037). Cardiac rate and rhythm disturbances (excluding sinus tachycardia) were seen in eight of the 13 nocturnal hypoglycaemia episodes (62%). These were sinus bradycardia (<40 beats/min; three episodes), ventricular ectopics (three episodes), atrial ectopics (one) and P wave abnormalities (one).

CONCLUSIONS/INTERPRETATION

This study demonstrates QTc prolongation and cardiac rate/rhythm disturbances in response to episodes of nocturnal hypoglycaemia in ambulant patients with type 1 diabetes. This may support an arrhythmic basis for the 'dead in bed' syndrome.

Terbutaline and the prevention of nocturnal hypoglycemia in type 1 diabetes

OBJECTIVE

Bedtime administration of 5.0 mg of the beta(2)-adrenergic agonist terbutaline prevents nocturnal hypoglycemia but causes morning hyperglycemia in type 1 diabetes. We tested the hypothesis that 2.5 mg terbutaline prevents nocturnal hypoglycemia without causing morning hyperglycemia.

RESEARCH DESIGN AND METHODS

This was a randomized double-blind crossover pilot study (placebo, 2.5 mg terbutaline, and 5.0 mg terbutaline) in 15 patients with type 1 diabetes.

RESULTS

Mean +/- SE nadir nocturnal plasma glucose concentrations were 87 +/- 14 mg/dl following placebo, 100 +/- 14 mg/dl following 2.5 mg terbutaline, and 122 +/- 13 mg/dl following 5.0 mg terbutaline (P < 0.05 vs. placebo). Nadir levels were <50 mg/dl in 5, 2, and 0 patients (P < 0.05 vs. placebo), respectively. Morning levels were 113 +/- 18, 127 +/- 17, and 183 +/- 19 mg/dl (P < 0.02 vs. placebo), respectively.

CONCLUSIONS

Terbutaline may be shown to be effective and safe in the prevention of nocturnal hypoglycemia in type 1 diabetes in a suitably powered randomized controlled trial.

A review of current evidence with continuous glucose monitoring in patients with diabetes

Devices that measure glucose on a near-continuous basis may provide a better insight into glycemic profiles, allowing patients with diabetes to make therapeutic adjustments to improve metabolic control, thereby reducing the risk of diabetic complications. Motivated and technologically adept patients with brittle diabetes, hypoglycemia unawareness, diabetic pregnancy, or who use pumps might benefit.Current evidence of continuous glucose monitoring (CGM) on health outcome in patients with diabetes is critically reviewed. No data are available on chronic complications or mortality. Therefore, surrogate endpoints need to be investigated, particularly HbA1c, number of hypo- and hyperglycemic episodes, time within normal, high, or low glucose concentrations, glycemic variability, and quality of life.Randomized controlled trials (RCTs) using CGM in a retrospective way did not show metabolic improvement. In contrast, most RCTs applying real-time CGM showed a decrease in HbA1c, reduced glycemic variability, and a diminished number and length of hypo- and hyperglycemic events. Using accurate, real-time CGM devices improves quality of life by reducing the fear of unexpected hypoglycemic events. These beneficial effects were observed despite the fact that in most studies no clear treatment algorithm based on CGM results was provided to the patients. However, most trials were too short in duration, with a variable use of CGM, and were performed in small study samples.In conclusion, real-time CGM systems can improve metabolic control, reduce hypoglycemic episodes, and improve quality of life. Whether this holds true for longer time periods and in the majority of patients remains to be proven. In the long term, CGM might help to reduce chronic diabetes complications and perhaps also mortality, thereby reducing health care costs.

Continuous glucose monitors: the long-awaited watch dogs?

To date, several continuous glucose sensors have been developed and launched in the U.S. and European markets, though large-scale application in standard diabetes care still awaits its breakthrough. This report offers an overview of the current applications and clinically relevant aspects of continuous glucose monitors (CGMs), e.g., the calibration procedure, interpretation of continuous glucose data, and some important limitations. It is still difficult to state with certainty that CGMs allow effective improvement in glycemic control for the majority of patients with type 1 diabetes, in view of the paucity of controlled studies showing an impact on hemoglobin A1c or frequency of hypoglycemia, even if such a tendency seems to emerge from most non-controlled intervention trials. Future controlled trials should also take into account patient-related outcomes, to evaluate the effect of CGMs on health status, treatment satisfaction, and fear of hypoglycemia. Increased accuracy and reimbursement are key to further implementation of CGMs.