Reproducibility and reliability of hypoglycaemic episodes recorded with Continuous Glucose Monitoring System (CGMS) in daily life

Impaired Awareness of Hypoglycemia in Type 1 Diabetes: A Report of An NIDDK Workshop in October 2021

Hypoglycemia remains a limiting factor in the optimal treatment of type 1 diabetes. Repeated episodes of hypoglycemia result in impaired awareness of subsequent hypoglycemic events, inducing a vicious feed-forward cycle and increasing the risk of morbidity and mortality. Why this occurs and how to manage the problem in clinical practice remain uncertain. To address the obstacles and barriers that have hindered progress in this clinically important area, the National Institute of Diabetes and Digestive and Kidney Diseases convened a workshop on 14-15 October 2021. This perspective offers a summary of this outstanding meeting, which brought clinical and basic scientists from the fields of diabetes, neuroscience, psychology, psychiatry, and imaging together, on how to best advance the field of impaired awareness of hypoglycemia and hypoglycemia in general in patients with diabetes.

Continuous glucose monitoring detected hypoglycaemia in the Treating to Target in Type 2 Diabetes Trial (4-T)

AIMS

Hypoglycaemia is a significant risk in insulin treated type 2 diabetes and has been associated with future risk of cardiovascular events. We compared the frequency of low-glucose events using continuous glucose monitoring (CGM) with that of self-reported hypoglycemic events at the end of the first and third years of the Treating to Target in Type 2 Diabetes Trial (4-T), which compared biphasic, prandial and basal insulin regimens added to sulfonylurea and metformin.

METHODS

CGM using a Medtronic Gold system was performed in a subgroup of 4-T participants. CGM detected low-glucose events were defined at thresholds of ≤3.0 (CGM3.0) and ≤2.2 (CGM2.2) mmol/l.

RESULTS

Of the 110 participants, 106 and 70 had CGM analysable data at the end of years 1 and 3 respectively. In both years, the frequency of CGM detected low glucose events was several fold higher than that of self-reported hypoglycaemia (symptoms with blood glucose less than 3.1mmol/l [<56mg/dl]). At the end of the first year, CGM3.0 and CGM2.2 mean (95%CI) event frequencies, expressed at events per participant per year, were 120 (85, 155) and 41 (21, 61) compared with 17 (8, 29) self-reported events during CGM, each p=0.001. The disparity at the end of the third year was similar.

CONCLUSIONS

These data demonstrate the likely under-reporting of hypoglycaemia and of potential hypoglycaemia unawareness in clinical trials. The clinical implications of these findings need to be explored further (ISRCTN No ISRCTN51125379).

Changes in cardiac repolarisation during spontaneous nocturnal hypoglycaemia in subjects with type 1 diabetes: a preliminary report

AIMS

Experimental studies have revealed that hypoglycaemia can result in morphological changes in electrocardiographic repolarisation in subjects with type 1 diabetes. However, the influence of spontaneous nocturnal hypoglycaemia on repolarisation morphology in a 'real life' situation is not clear.

METHODS

Adults with type 1 diabetes (n = 11) underwent continuous glucose monitoring with a subcutaneous sensor and digital 12-lead ECG recording for three nights. T-wave morphology was analysed with custom-made software during both hypoglycaemia (glucose <3.5 mmol/l at least 20 min) from ten consecutive heart beats in the middle of the deepest hypoglycaemia and from a control nonhypoglycaemic period (glucose ≥5.0 mmol/l) from the same recording.

RESULTS

In the comparison of 10 hypoglycaemia-control pairs, heart rate (65 ± 12 beats/min during normoglycaemia versus 85 ± 19 beats/min during hypoglycaemia, p = 0.028) increased and the QT_c interval (439 ± 5 vs. 373 ± 5 ms, respectively, p = 0.025) decreased significantly during hypoglycaemia. The spatial QRS-T angle (TCRT) was reduced, and the roughness of the T-wave loop (T-E) increased significantly (p = 0.037 for both) in the patients during hypoglycaemia.

CONCLUSIONS

In adults with type 1 diabetes, spontaneous nocturnal hypoglycaemia results in morphological changes and increased heterogeneity of global cardiac repolarisation. These changes may contribute to the risk of 'dead in bed' syndrome encountered in young individuals with type 1 diabetes.

Characteristics of glucose metabolism indexes and continuous glucose monitoring system (CGMS) in patients with insulinoma

AIMS

Analyze the clinical applicability of glucose metabolism indexes and continuous glucose monitoring data on the qualitative diagnosis of insulinoma.

METHODS

Involve 22 patients with insulinoma (insulinoma group), 11 patients with hypoglycemia (hypoglycemia group) and 31 people with normal glucose tolerance (control group). HbA1c, fasting blood glucose (FBG), insulin (FINS) and C-peptide (FCP) was tested. Using CGMS to monitor the blood glucose for three consecutive days and selecting the monitoring data of 24 h thereof, figuring out, with the aid of EasyGV Version 9.0, the mean glucose (MG), the standard deviation (SD) of blood glucose, CONGA (continuous overall net glycemic action), J-Index, LI (Lability Index), LBGI (Low Blood Glucose Index), HBGI (High Blood Glucose Index), GRADE (glycaemic risk assessment diabetes equation), MAGE (mean aplitude of glycaemic excursions), M value, MAG (mean absolute glucose).

RESULTS

(1) FBG and LBG of insulinoma group are lower than those of control group and those of hypoglycemia group while FINS and FCP of insulinoma group are markedly higher than those of the other two groups; (2) the MG and CONGA of insulinoma group are lower than those of control group and its indexes like ST, LI, LBGI, GRADE, MAGE, M value and MAG are higher than those of control group; there are differences between the indexes of insulinoma group and those of hypoglycemia group in CONGA (lower than that of hypoglycemia group), LBGI (higher than that of hypoglycemia group), and M value (higher than that of hypoglycemia group). By drawing the ROC curve and calculating Youden index, the cut-off values of LBGI, M value, CONGA are respectively as 4.06, 7.79, 4.38, and the best index of differential diagnosis is LBGI.

CONCLUSION

Continuous glucose monitoring data can be used to diagnose insulinoma and blood glucose fluctuation indicators such as LBGI, M value, CONGA might be useful to identify insulinoma.

Self-reported discrimination, diabetes distress, and continuous blood glucose in women with type 2 diabetes

We investigated whether self-reported racial discrimination was associated with continuous glucose levels and variability in individuals with diabetes, and whether diabetes distress mediated these associations. Seventy-four Black and White women with type 2 diabetes completed the Experience of Discrimination scale, a measure of lifetime racial discrimination, and the Problem Areas in Diabetes, a measure of diabetes distress. Participants wore a continuous glucose monitor for 24 h after 8 h of fasting, a standard meal, and a 4-h run in period. Higher discrimination predicted higher continuous mean glucose and higher standard deviation of glucose. For both mean and standard deviation of glucose, a race × discrimination interaction indicated a stronger relationship between discrimination and glucose for Whites than for Blacks. Diabetes distress mediated the discrimination-mean glucose relationship. Whites who report discrimination may be uniquely sensitive to distress. These preliminary findings suggest that racial discrimination adversely affects glucose control in women with diabetes, and does so indirectly through diabetes distress. Diabetes distress may be an important therapeutic target to reduce the ill effects of racial discrimination in persons with diabetes.

Continuous glucose monitoring system and new era of early diagnosis of diabetes in high risk groups

Continuous glucose monitoring (CGM) systems are an emerging technology that allows frequent glucose measurements to monitor glucose trends in real time. Their use as a diagnostic tool is still developing and appears to be promising. Combining intermittent glucose self-monitoring (SGM) and CGM combines the benefits of both. Significant improvement in the treatment modalities that may prevent the progress of prediabetes to diabetes have been achieved recently and dictates screening of high risk patients for early diagnosis and management of glycemic abnormalities. The use of CGMS in the diagnosis of early dysglycemia (prediabetes) especially in high risk patients appears to be an attractive approach. In this review we searched the literature to investigate the value of using CGMS as a diagnostic tool compared to other known tools, namely oral glucose tolerance test (OGTT) and measurement of glycated hemoglobin (HbA1C) in high risk groups. Those categories of patients include adolescents and adults with obesity especially those with family history of type 2 diabetes mellitus, polycystic ovary syndrome (PCO), gestational diabetes, cystic fibrosis, thalassemia major, acute coronary syndrome (ACS), and after renal transplantation. It appears that the ability of the CGMS for frequently monitoring (every 5 min) glucose changes during real-life settings for 3 to 5 days stretches the chance to detect more glycemic abnormalities during basal and postprandial conditions compared to other short-timed methods.

Severe hypoglycaemia in type 1 diabetes mellitus: underlying drivers and potential strategies for successful prevention

Hypoglycaemia remains an over-riding factor limiting optimal glycaemic control in type 1 diabetes. Severe hypoglycaemia is prevalent in almost half of those with long-duration diabetes and is one of the most feared diabetes-related complications. In this review, we present an overview of the increasing body of literature seeking to elucidate the underlying pathophysiology of severe hypoglycaemia and the limited evidence behind the strategies employed to prevent episodes. Drivers of severe hypoglycaemia including impaired counter-regulation, hypoglycaemia-associated autonomic failure, psychosocial and behavioural factors and neuroimaging correlates are discussed. Treatment strategies encompassing structured education, insulin analogue regimens, continuous subcutaneous insulin infusion pumps, continuous glucose sensing and beta-cell replacement therapies have been employed, yet there is little randomized controlled trial evidence demonstrating effectiveness of new technologies in reducing severe hypoglycaemia. Optimally designed interventional trials evaluating these existing technologies and using modern methods of teaching patients flexible insulin use within structured education programmes with the specific goal of preventing severe hypoglycaemia are required. Individuals at high risk need to be monitored with meticulous collection of data on awareness, as well as frequency and severity of all hypoglycaemic episodes.

Arrhythmogenic effects of hypoglycemia in children and adolescents with type 1 diabetes mellitus

Aim. To determine the effects of hypoglycemia on the duration of QT interval, heart rate variability (HRV) and frequency of arrhythmic events, as well as to closer investigate the factors associated with the development of various heart rhythm disorders in children and adolescents with type 1 diabetes mellitus (T1DM). Materials and methods.  The study included 150 children and adolescents with T1DM at the age of 6?18 years. All participants underwent Holter monitoring and continuous glucose monitoring (CGM) for 24 hours. QTc and HRV parameters (SDNN, RMSSD, SVVR) were calculated automatically. Data was averaged for 5?-interval and juxtaposed with CGM. Patients identified with hypoglycemic events (blood glucose

Do high fasting glucose levels suggest nocturnal hypoglycaemia? The Somogyi effect-more fiction than fact?

AIMS

The Somogyi effect postulates that nocturnal hypoglycaemia causes fasting hyperglycaemia attributable to counter-regulatory hormone release. Although most published evidence has failed to support this hypothesis, this concept remains firmly embedded in clinical practice and often prevents patients and professionals from optimizing overnight insulin. Previous observational data found lower fasting glucose was associated with nocturnal hypoglycaemia, but did not assess the probability of infrequent individual episodes of rebound hypoglycaemia. We analysed continuous glucose monitoring data to explore its prevalence.

METHODS

We analysed data from 89 patients with Type 1 diabetes who participated in the UK Hypoglycaemia study. We compared fasting capillary glucose following nights with and without nocturnal hypoglycaemia (sensor glucose < 3.5 mmol/l).

RESULTS

Fasting capillary blood glucose was lower after nights with hypoglycaemia than without [5.5 (3.0) vs. 14.5 (4.5) mmol/l, P < 0.0001], and was lower on nights with more severe nocturnal hypoglycaemia [5.5 (3.0) vs. 8.2 (2.3) mmol/l; P = 0.018 on nights with nadir sensor glucose of < 2.2 mmol/l vs. 3.5 mmol/l]. There were only two instances of fasting capillary blood glucose > 10 mmol/l after nocturnal hypoglycaemia, both after likely treatment of the episode. When fasting capillary blood glucose is < 5 mmol/l, there was evidence of nocturnal hypoglycaemia on 94% of nights.

CONCLUSION

Our data indicate that, in clinical practice, the Somogyi effect is rare. Fasting capillary blood glucose ≤ 5 mmol/l appears an important indicator of preceding silent nocturnal hypoglycaemia.

Autonomic cardiac regulation during spontaneous nocturnal hypoglycemia in patients with type 1 diabetes

OBJECTIVE

Experimental clamp studies have suggested that hypoglycemia evokes a reduction of cardiac vagal control in patients with type 1 diabetes. However, there are limited data on the influence of spontaneous nocturnal hypoglycemia on cardiac autonomic regulation.

RESEARCH DESIGN AND METHODS

Adults with type 1 diabetes (n = 37) underwent continuous glucose monitoring via a subcutaneous sensor as well as recording of R-R interval or electrocardiogram for 3 nights. Heart rate (HR) variability was analyzed during periods of hypoglycemia (glucose <3.5 mmol/L) (minimum length of 20 min) and a control nonhypoglycemic period (glucose >3.9 mmol/L) of equal duration and at the same time of night.

RESULTS

The duration of hypoglycemic and control episodes (n = 18) ranged from 20 to 190 min (mean 71 min). HR (62 ± 7 vs. 63 ± 9 beats per min; P = 0.30) or the high-frequency component of HR power spectrum (2,002 ± 1,965 vs. 1,336 ± 1,506 ms(2); P = 0.26) did not change during hypoglycemia. Hypoglycemia resulted in a significant decrease in the low-frequency component of HR variability (2,134 ± 1,635 vs. 1,169 ± 1,029 ms(2), respectively; P = 0.006). The decline in the glucose concentration displayed a significant positive correlation with the decrease of the low-frequency component of HR variability (r = 0.48; P = 0.04). The latter was closely related to an increase in muscle sympathetic nerve activity recorded in 10 subjects during controlled sympathetic activation.

CONCLUSIONS

Spontaneous nocturnal hypoglycemia in patients with type 1 diabetes results in a reduction of the low-frequency component of HR, which is best explained by excessive sympathetic activation without a concomitant withdrawal of vagal outflow.

Continuous glucose monitoring system during physical exercise in adolescents with type 1 diabetes

AIM

Continuous glucose monitoring system (CGMS) provides detailed information on glucose fluctuations. The aim was to establish whether CGMS could be used during physical exercise and whether it detects more episodes of hypoglycaemia and hyperglycaemia than frequent blood glucose measurements.

METHODS

Adolescents with type 1 diabetes (12 girls and 47 boys) participated in three annual sports camps that lasted for 3-4 days and included different types of exercise: soccer, floorball + cross-country skiing and golf. During the study, blood glucose values, mean 8.7 ± 3.3 per day, were obtained with Hemocue in parallel with the CGMS.

RESULTS

Ninety-eight per cent of the participants used the sensor at all times during the camps. Eighty-seven per cent of the sensors gave adequate signals for 24 h and 66% for 48 h. Median durations of hypoglycaemia and hyperglycaemia were 1.7 h per day and 3.8 h per day, respectively. The CGMS identified significantly more episodes of hypoglycaemia (p < 0.005) and hyperglycaemia (p < 0.005) during the day and night than frequent blood glucose tests.

CONCLUSION

We demonstrate that, even during days that included episodic strenuous physical exercise, CGMS could provide useful information on glucose fluctuations during day and night, albeit with significant failure rates.

Hypoglycemia impairs quality of blood glucose simulation in a clinical decision support system

BACKGROUND

Clinical decision support systems allow for decisions based on blood glucose simulations. The DiasNet simulation tool is based on accepted principles of physiology and simulates blood glucose concentrations accurately in type 1 diabetes mellitus (T1DM) patients during periods without hypoglycemia, but deviations appear after hypoglycemia, possibly because of the long-term glucose counter-regulation to hypoglycemia. The purpose of this study was to evaluate the impact of hypoglycemia on blood glucose simulations.

METHOD

Continuous glucose monitoring (CGM) data and diary data (meals, insulin, self-monitored blood glucose) were collected for 2 to 5 days from 17 T1DM patients with poor glycemic control. Hypoglycemic episodes [CGM glucose <63 mg/dl (3.5 mmol/liter) for ≥20 min] were identified in valid (well-calibrated) CGM data. For 24 hours after each hypoglycemic episode, a simulated (DiasNet) glucose profile was compared to the CGM glucose.

RESULTS

A total of 52 episodes of hypoglycemia were identified in valid data. All subjects had at least one hypoglycemic episode. Ten episodes of hypoglycemia from nine subjects were eligible for analysis. The CGM glucose was significantly (p < .05) higher than simulated blood glucose for a period of 13 h, beginning 8 h after hypoglycemia onset.

CONCLUSIONS

The present data show that hypoglycemia introduces substantial and systematic simulation errors for up to 24 h after hypoglycemia. This underlines the need for further evaluation of mechanisms behind this putative long-term glucose counter-regulation to hypoglycemia. When using blood glucose simulations in decision support systems, the results indicate that simulations for several hours following a hypoglycemic event may underestimate glucose levels by 100 mg/dl (5.6 mmol/liter) or more.

Frequency of biochemical hypoglycaemia in adults with Type 1 diabetes with and without impaired awareness of hypoglycaemia: no identifiable differences using continuous glucose monitoring

OBJECTIVE

Impaired awareness of hypoglycaemia (IAH) is a major risk factor for severe hypoglycaemia in Type 1 diabetes. Although biochemical hypoglycaemia is asserted to be more frequent in IAH, this has not been estimated accurately. The aim of this study was to use Continuous Glucose Monitoring (CGM) to quantify hypoglycaemia in IAH and evaluate its use in identifying impaired awareness of hypoglycaemia.

METHODS

Ninety-five patients with Type 1 diabetes were classified as having normal (n = 74) or impaired awareness (n = 21) using an established method of assessing hypoglycaemia awareness. Hypoglycaemia exposure was assessed prospectively over 9-12 months using weekly 4-point capillary home blood glucose monitoring (HBGM), 5 days of CGM and prospective reporting of severe hypoglycaemia. The frequencies of biochemical and severe hypoglycaemia were compared in patients with normal and impaired awareness of hypoglycaemia.

RESULTS

Patients with impaired awareness had a 3-fold higher incidence of severe hypoglycaemia than those with normal awareness [incidence rate ratio (IRR) 3.37 (95% CI 1.30-8.7); P = 0.01] and 1.6-fold higher incidence of hypoglycaemia on weekly HBGM [IRR 1.63 (95% CI 1.09-2.44); P = 0.02]. No significant differences were observed with CGM [IRR for sensor glucose < or = 3.0 mmol/l 1.47 (95% CI 0.91-2.39); P = 0.12; IRR for sensor glucose < or = 2.2 mmol/l 1.23 (95% CI 0.76-1.98); P = 0.40].

CONCLUSIONS

Patients with Type 1 diabetes with impaired awareness had a 3-fold higher risk of severe hypoglycaemia and 1.6-fold higher incidence of biochemical hypoglycaemia measured with weekly glucose monitoring compared with normal awareness, but 5 days of CGM did not differentiate those with impaired from those with normal awareness.

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.

Hypoglycaemia: an overview

Hypoglycaemia is a frequent side-effect of treatment with insulin and sulfonylureas for people with diabetes, threatening potentially serious morbidity and preventing optimal glycaemic control. Fear of hypoglycaemia and development of syndromes such as impaired awareness and counterregulatory deficiency provide additional hazards for intensification of treatment. Rapid lowering of HbA1c may be potentially dangerous in type 2 diabetes because of the adverse cardiovascular effects induced by hypoglycaemia. Hypoglycaemia can disrupt many everyday activities such as driving, work performance and recreational pursuits. Measures to reduce the risk of hypoglycaemia are labour-intensive and require substantial resources.

Comparing hormonal and symptomatic responses to experimental hypoglycaemia in insulin- and sulphonylurea-treated Type 2 diabetes

AIMS

Patients with diabetes rely on symptoms to identify hypoglycaemia. Previous data suggest patients with Type 2 diabetes develop greater symptomatic and hormonal responses to hypoglycaemia at higher glucose concentrations than non-diabetic controls and these responses are lowered by insulin treatment. It is unclear if this is as a result of insulin therapy itself or improved glucose control. We compared physiological responses to hypoglycaemia in patients with Type 2 diabetes patients treated with sulphonylureas (SUs) or insulin (INS) with non-diabetic controls (CON).

METHODS

Stepped hyperinsulinaemic hypoglycaemic clamps were performed on 20 subjects with Type 2 diabetes, 10 SU-treated and 10 treated with twice-daily premixed insulin, and 10 age- and weight-matched non-diabetic controls. Diabetic subjects were matched for diabetes duration, glycated haemoglobin (HbA(1c)) and hypoglycaemia experience. We measured symptoms, counterregulatory hormones and cognitive function at glucose plateaux of 5, 4, 3.5, 3 and 2.5 mmol/l.

RESULTS

Symptomatic responses to hypoglycaemia occurred at higher blood glucose concentrations in SU-treated than INS-treated patients [3.5 (0.4) vs. 2.6 (0.5) mmol/l SU vs. INS; P = 0.001] or controls [SU vs. CON 3.5 (0.4) vs. 3.0 (0.6) mmol/l; P = 0.05]. They also had a greater increase in symptom scores at hypoglycaemia [13.6 (11.3) vs. 3.6 (6.1) vs. 5.1 (4.3) SU vs. INS vs. CON; P = 0.017]. There were no significant differences in counterregulatory hormone responses or impairment of cognitive function among groups.

CONCLUSIONS

Sulphonylurea-treated subjects are more symptomatic of hypoglycaemia at a higher glucose level than insulin-treated subjects. This may protect them from severe hypoglycaemia but hinder attainment of glycaemic goals.

Decreasing concentration of interstitial glucose in REM sleep in subjects with normal glucose tolerance

AIMS

Sleep is divided into two major stages, non-rapid eye movement (NREM) and rapid eye movement (REM), which are distinct in various neuroendocrine respects. NREM/REM cycles influence insulin and glucagon secretion; however, glucose concentrations in REM compared with NREM have not been directly explored. The aim was to investigate the differences in glucose concentrations in interstitial fluid (IGC) between NREM/REM cycles using a continuous glucose monitoring system (CGMS).

METHODS

Thirteen subjects were eligible for analysis out of the 28 enrolled. All underwent standard polysomnography for the assessment of sleep stages and the exclusion of sleep apnoea syndrome with CGMS and subsequent morning oral glucose tolerance test (exclusion of glucose intolerance or diabetes).

RESULTS

The IGC in REM fell in 12 out of the 13 subjects, whereas the IGC in NREM increased in eight out of the 13 subjects. Therefore, the mean change of IGC differed in direction between sleep stages: -0.028 (-0.045 to -0.011) for REM vs. 0.005 (-0.012 to 0.017) for NREM [median (QR), P = 0.007, n = 13], with the mean difference of 0.038 mmol/l x 5 min(-1) (95% confidence interval 0.012, 0.064). The mean glucose concentration in REM sleep was lower than in NREM: 4.29 +/- 1.00 vs. 4.53 +/- 0.90 mmol/l (mean +/- sd, P = 0.003, n = 13).

CONCLUSIONS

The decrease in IGC in REM compared with NREM sleep, with lower absolute values, may arise from different physiological events observed in these sleep stages. The REM-related decline in glucose concentrations may be a risk factor for nighttime hypoglycaemia.

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.

Continuous glucose monitoring in patients with insulinoma

BACKGROUND

Insulinomas are rare neuroendocrine tumours that are usually small and may take time to localize. They cause recurrent life-threatening spontaneous hypoglycaemia. Recurrent hypoglycaemia causes loss of hypoglycaemia awareness, putting the patient at further risk, but this has rarely been described in insulinoma. We describe the utility of continuous glucose monitoring (CGM) in patients with insulinoma.

PATIENTS AND METHODS

Three patients, aged 72 years (patient 1), 37 years (patient 2) and 24 years (patient 3), with suspected insulinoma attended our investigation unit, in a university teaching hospital. Biochemical diagnosis was confirmed by elevated plasma insulin and C-peptide during biochemical hypoglycaemia [plasma glucose < 2.2 mM (40 mg/dl)]. Surgery confirmed histology in all. CGM was used to monitor frequency and time of hypoglycaemia during diagnosis and medical treatment, and after definitive surgical treatment.

RESULTS

All patients had evidence of hypoglycaemia unawareness. At diagnosis in patients 1-3, CGM revealed 6.1%, 21.9% and 71.0% of time spent in moderate hypoglycaemia (plasma glucose 2.2-3.0 mM), and 1.4%, 11.4% and 48.1% of time in severe hypoglycaemia (plasma glucose < 2.2 mM), respectively. On diazoxide this reduced to 0.6%, 5.4% and 5.7% time in moderate hypoglycaemia, and no severe hypoglycaemia in patients 1 and 3, and 0.5% in patient 2. Octreotide therapy in patients 2 and 3 resulted in 5.8% and 0% of time in moderate hypoglycaemia, respectively, and no severe hypoglycaemia. After surgical excision CGM confirmed cure in all.

CONCLUSIONS

CGM in insulinoma is useful in detecting hypoglycaemia, and hypoglycaemia unawareness, monitoring response to medical therapy and for confirming cure postoperatively, and is useful in the management of this uncommon but dangerous condition.

Glargine versus NPH insulin: efficacy in comparison with insulin aspart in a basal bolus regimen in type 1 diabetes--the glargine and aspart study (GLASS) a randomised cross-over study

The aim of the study was to compare the efficacy of insulin glargine and aspart with NPH insulin and aspart in a basal bolus regimen in type 1 diabetes. In this 36-week randomised open-label two-period cross-over trial, subjects received 16 weeks' treatment with either once-daily insulin glargine or twice-daily NPH insulin after 4-week run-in. Primary outcome was HbA1c and secondary outcomes were fasting plasma glucose (FPG), weight change, incidence of hypoglycaemia, effect on lipid profile and patient satisfaction. Sixty patients with type 1 diabetes were recruited (33 male, mean age 42.7 years, mean HbA1c 8.53%) with 53 completing the study. At completion, HbA1c was lower with glargine and aspart than with NPH and aspart (8.07% versus 8.26%, difference -0.19 [95% CI 0.37-0.01]%, p=0.04). FPG was significantly different between glargine and NPH (p=0.002), with mean FPG on glargine 3mmol/L lower than on NPH at the end of the study. There were no differences in hypoglycaemia rate (p=0.63), weight (p=0.45) or lipid profile (p=0.18). Patient satisfaction was greater with glargine (DTSQ, p=0.001). Three patients discontinued as they wished to remain on glargine. We suggest that glargine combined with aspart is an effective basal bolus regimen in type 1 diabetes.

Using continuous glucose monitoring to measure the frequency of low glucose values when using biphasic insulin aspart 30 compared with biphasic human insulin 30: a double-blind crossover study in individuals with type 2 diabetes

OBJECTIVE

Rapid-acting insulin analogs in basal-bolus regimens can reduce nocturnal hypoglycemia, so it is conceivable that twice-daily biphasic insulin analogs might reduce hypoglycemia in patients with insulin-treated type 2 diabetes. We used a continuous glucose monitoring system (CGMS) and self-reported episodes to investigate differences in the frequency of low glucose values in patients with type 2 diabetes, using either biphasic insulin aspart 30 (BIAsp 30) or biphasic human insulin 30 (BHI 30).

RESEARCH DESIGN AND METHODS

This was a double-blind, two-period, crossover trial involving 160 subjects. After 8 weeks' run-in, subjects were randomized to the first of two 16-week treatment periods.

RESULTS

No differences in overall incidence of low interstitial glucose (IG) were found. Twenty-four-hour plots of CGMS showed low IG was more frequent at night than during the day and was unrecognized by patients. At night, subjects spent significantly less time (percentage of total CGMS recorded) with IG <3.5 and <2.5 mmol/l during BIAsp 30 than during BHI 30 treatment, respectively (<3.5 mmol/l: 6.36 vs. 7.93% [mean], 0.67 vs. 2.43% [median], P = 0.018; <2.5 mmol/l: 2.35 vs. 2.86% [mean], 0 vs. 0% [median], P = 0.0467). No treatment difference in A1C was observed.

CONCLUSIONS

Overall rates of low glucose over 24 h were not different but were twice as frequent at night than during the day in individuals with type 2 diabetes. Compared with BHI 30, BIAsp 30 was associated with similar low IG readings over 24 h but with fewer nocturnal episodes and less self-reported nocturnal hypoglycemia.

Defective awakening response to nocturnal hypoglycemia in patients with type 1 diabetes mellitus

BACKGROUND

Nocturnal hypoglycemia frequently occurs in patients with type 1 diabetes mellitus (T1DM). It can be fatal and is believed to promote the development of the hypoglycemia-unawareness syndrome. Whether hypoglycemia normally provokes awakening from sleep in individuals who do not have diabetes, and whether this awakening response is impaired in T1DM patients, is unknown.

METHODS AND FINDINGS

We tested two groups of 16 T1DM patients and 16 healthy control participants, respectively, with comparable distributions of gender, age, and body mass index. In one night, a linear fall in plasma glucose to nadir levels of 2.2 mmol/l was induced by infusing insulin over a 1-h period starting as soon as polysomnographic recordings indicated that stage 2 sleep had been reached. In another night (control), euglycemia was maintained. Only one of the 16 T1DM patients, as compared to ten healthy control participants, awakened upon hypoglycemia (p = 0.001). In the control nights, none of the study participants in either of the two groups awakened during the corresponding time. Awakening during hypoglycemia was associated with increased hormonal counterregulation. In all the study participants (from both groups) who woke up, and in five of the study participants who did not awaken (three T1DM patients and two healthy control participants), plasma epinephrine concentration increased with hypoglycemia by at least 100% (p < 0.001). A temporal pattern was revealed such that increases in epinephrine in all participants who awakened started always before polysomnographic signs of wakefulness (mean +/- standard error of the mean: 7.5 +/- 1.6 min).

CONCLUSIONS

A fall in plasma glucose to 2.2 mmol/l provokes an awakening response in most healthy control participants, but this response is impaired in T1DM patients. The counterregulatory increase in plasma epinephrine that we observed to precede awakening suggests that awakening forms part of a central nervous system response launched in parallel with hormonal counterregulation. Failure to awaken increases the risk for T1DM patients to suffer prolonged and potentially fatal hypoglycemia.

Performance of the continuous glucose monitoring system (CGMS) during development of ketosis in patients on insulin pump therapy

AIMS

Ketoacidosis is one of the most severe complications of Type 1 diabetes. Development of ketosis leads to substantial shifts in electrolyte and ion concentrations in the different fluid compartments of the body. This study was performed to investigate the performance of the continuous glucose monitoring device (CGMS) during ketoacidosis.

METHODS

Twelve patients with Type 1 diabetes using continuous subcutaneous insulin infusion (CSII) participated in this trial [10 women, two men; age (mean +/- sd) 34 +/- 9 years; disease duration 17 +/- 10 years; HbA(1c) 7.1 +/- 1.0%]. In the morning, patients ate breakfast and the insulin pump was stopped at 11.00 h and restarted after 8 h. Observation parameters during this experiment were: blood glucose (laboratory reference and CGMS), 3-hydroxy-butyrate (3-OHB), pH, Na, pCO(2), pO(2), free fatty acids, osmolarity, standard bicarbonate, and lactate.

RESULTS

Blood glucose increased and reached a plateau within 2 h after pump stop (from 6.2 +/- 2.56 to 16.7 +/- 4.44 mmol/l, P < 0.001). A constant increase in 3-OHB (from 0.0 to 0.8 +/- 0.5 mmol/l, P < 0.001) and decrease in pH (from 7.43 +/- 0.02 to 7.40 +/- 0.03, P < 0.05) indicated ketosis development. Na decreased from 141 +/- 1.4 to 138 +/- 2.8 mmol/l, P < 0.001). Free fatty acids increased from 0.577 +/- 0.330 to 1.330 +/- 0.462 mmol/l (P < 0.001). The CGMS values showed excellent agreement with the capillary blood laboratory method during the entire experiment, and a modified error grid analysis revealed that 99.5% of the values were in the clinically acceptable zones A and B.

CONCLUSION

The CGMS device was confirmed to be reliable and accurate during the development of hyperglycaemia and ketotic conditions.