Asymptomatic Nocturnal Hypoglycemia Research Articles

Mixed Meal Tolerance Test Versus Continuous Glucose Monitoring for an Effective Diagnosis of Persistent Post-Bariatric Hypoglycemia.

Gastric bypass determines an increase in incretin secretion and glucose excursions throughout the day and may sometimes entail the development of severe post-bariatric hypoglycemia (PBH). However, there is no consensus on the gold standard method for its diagnosis. In this study, we evaluated the usefulness of a mixed meal tolerance test (MMTT) and continuous glucose monitoring (CGM) for the diagnosis of PBH, defined as glucose levels <54 mg/dL (3.0 mmol/L). We found that hypoglycemia occurred in 60% of patients after the MMTT and in 75% during CGM, and it was predominantly asymptomatic. The MMTT confirmed the diagnosis of PBH in 88.9%of patients in whom surgery had been performed more than three years ago, in comparison to 36.4% in cases with a shorter postsurgical duration. CGM diagnosed nocturnal asymptomatic hypoglycemia in 70% of patients, and daytime postprandial hypoglycemia in 25% of cases. The mean duration of asymptomatic hypoglycemia was more than 30 min a day. Patients with ≥2% of their CGM readings with hypoglycemia exhibited a higher degree of glucose variability than those with <1% of the time in hypoglycemia. Our results show that the MMTT may be a useful dynamic test to confirm the occurrence of hypoglycemia in a large number of patients with persistent and recurrent PBH during long-term follow-up after gastric bypass. CGM, on its part, helps identify hypoglycemia in the real-world setting, especially nocturnal asymptomatic hypoglycemia, bringing to light that PBH is not always postprandial.

Association between the severity of nocturnal asymptomatic hypoglycemia and heart rate variability change in patients with type 2 diabetes

Association between the severity of nocturnal asymptomatic hypoglycemia and heart rate variability change in patients with type 2 diabetes

Hypoglycemia unawareness identified by continuous glucose monitoring system is frequent in outpatients with type 2 diabetes without receiving intensive therapeutic interventions

BackgroundPatients with diabetes are prone to asymptomatic hypoglycemia (AH) due to diminished ability to perceive the onset of hypoglycemia. However, the actual prevalence and influencing factors of AH in outpatients with type 2 diabetes (T2DM) have not been well investigated.MethodsA total of 351 outpatients with T2DM underwent glucose monitoring by continuous glucose monitoring system (CGMS) for consecutive 72 h without changing their lifestyle and treatment regimens. Hypoglycemia is defined as a blood glucose level less than 3.9 mmol/L, which was further divided into Level 1 hypoglycemia (blood glucose 3.0–3.9 mmol/L) and Level 2 hypoglycemia (blood glucose < 3.0 mmol/L). Univariate and multivariate logistic regression analyses were used to determine the possible risk factors of AH.ResultsIn all 351 subjects studied, 137 outpatients (39.0%) were captured AH events, in which Level 1 AH and Level 2 AH accounted for 61.3% and 38.7%, respectively. 85 (62.0%) of the AH patients experienced nocturnal asymptomatic hypoglycemia (NAH) and 25 (18.2%) exclusively NAH. Multivariate logistic regression analysis demonstrated that patients with younger age, lower hemoglobin A1c (HbA1c), and higher systolic blood pressure (SBP) levels were associated with increased risk of AH. While after further grading of AH, male sex and Dipeptidylpeptidase-4 inhibitors (DPP4i) regime were shown to be associated with lower risk of Level 2 AH.ConclusionsHypoglycemia unawareness could be frequently observed at either daytime or nighttime, although NAH was more common, in outpatients with T2DM. Relative relax HbA1c targets should be considered for patients who are prone to AH.

Confirmation of the Absence of Somogyi Effect in Patients with Type 2 Diabetes by Retrospective Continuous Glucose Monitoring Systems.

Background The Somogyi effect is defined as fasting hyperglycemia secondary to nocturnal hypoglycemia. In past decades, this effect proved to be rare or absent. However, many endocrinologists still believe in this phenomenon in clinical practice. Does the Somogyi effect truly exist? We aimed to answer this question with a study based on a larger sample size. Methods We collected retrospective CGMs data from 2,600 patients with type 2 diabetes with stable treatment of insulin. Nocturnal hypoglycemia was defined as a CGMs sensor glucose of less than 3.9 mmol/L for at least 15 min between 24:00 and 06:00. Morning fasting glucose was compared between people with nocturnal hypoglycemia and without nocturnal hypoglycemia. Results Valid CGMs data were obtained on 4,705 of 5,200 nights. Morning fasting glucose was observed lower after nights with nocturnal hypoglycemia compared with nights without hypoglycemia (P < 0.001). 84 cases presented fasting glucose of more than 7 mmol/L after nocturnal glucose of less than 3.9 mmol/L. Only 27 cases presented fasting glucose of more than 7 mmol/L after nocturnal glucose of less than 3.0 mmol/L. Fasting glucose values below 3.9 mmol/l in the morning were associated with a 100% risk of nocturnal hypoglycemia, while fasting glucose values over 9.6 mmol/l in the morning were associated with no risk of nocturnal hypoglycemia. Correlation analysis showed that the nocturnal glucose nadir was significantly correlated with fasting glucose levels (r = 0.613, P < 0.001). Conclusions Our data provided no support for the existence of the Somogyi effect. If fasting glucose exceeds 9.6 mmol/L, we do not have to worry about asymptomatic nocturnal hypoglycemia in patients with type 2 diabetes.

Largest Amplitude of Glycemic Excursion Calculating from Self-Monitoring Blood Glucose Predicted the Episodes of Nocturnal Asymptomatic Hypoglycemia Detecting by Continuous Glucose Monitoring in Outpatients with Type 2 Diabetes.

AimsNocturnal asymptomatic hypoglycemia (NAH) is a serious complication of diabetes, but it is difficult to be detected clinically. This study was conducted to determine the largest amplitude of glycemic excursion (LAGE) to predict the episodes of NAH in outpatients with type 2 diabetes.MethodsData were obtained from 313 outpatients with type 2 diabetes. All subjects received continuous glucose monitoring (CGM) for consecutive 72 hours. The episodes of NAH and glycemic variability indices (glucose standard deviation [SD], mean amplitude of plasma glucose excursion [MAGE], mean blood glucose [MBG]) were accessed via CGM. LAGE was calculated from self-monitoring blood glucose (SMBG).ResultsA total of 76 people (24.3%) had NAH. Compared to patients without NAH, patients with NAH showed higher levels of glucose SD (2.4 ± 0.9 mmol/L vs 1.7 ± 0.9 mmol/L, p <0.001), MAGE (5.2 ± 2.1 mmol/L vs 3.7 ± 2.0, p<0.001) and LAGE (4.6 ± 2.3 mmol/L vs 3.8 ± 1.9 mmol/L, p=0.007), and lower level of MBG (7.5 ± 1.5 mmol/L vs 8.4 ± 2.2 mmol/L, p=0.002). LAGE was significantly associated with the incidence of NAH and time below rang (TBR) in model 1 [NAH: 1.189 (1.027-1.378), p=0.021; TBR: 0.008 (0.002-0.014), p=0.013] with adjustment for age, BMI, sex, work, hyperlipidemia, complication and medication, and in model 2 [NAH: 1.177 (1.013-1.367), p=0.033; TBR: 0.008 (0.002-0.014), p=0.012] after adjusting for diabetes duration based on model 1, as well as in model 3 [NAH: 1.244 (1.057-1.464), p=0.009; TBR: 0.009 (0.002-0.016), p=0.007] with further adjustment for HbA1c based on model 2. In addition, no significant interactions were found between LAGE and sex, age, HbA1c, duration of diabetes, BMI and insulin therapy on the risk of NAH. The receiver operator characteristic (ROC) curve shows the ideal cutoff value of LAGE for the prediction of NAH was 3.48 mmol/L with 66.7% sensitivity, 50% specificity and 0.587 (95% CI: 0.509-0.665) of area under the ROC curve.ConclusionsHigh glycemic variability is strongly associated with the risk of NAH. The LAGE based on SMBG could be an independent predictor of NAH for outpatients with type 2 diabetes, and LAGE greater than 3.48 mmol/L could act as a warning alarm for high risk of NAH in daily life.

Is it possible to predict the onset of nocturnal asymptomatic hypoglycemia in patients with type1 diabetes receiving insulin degludec? Potential role of previous day and next morning glucose values.

Aims/IntroductionTo 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 MethodsThis 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.ResultsThe 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).ConclusionsThe 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.

270-OR: Nocturnal Hypoglycemia with Insulin Degludec and Glargine U100 in Patients with Type 1 Diabetes Prone to Severe Nocturnal Hypoglycemia (HypoDeg): A CGM Substudy

Background and Aims: Nocturnal hypoglycemia is a major source of concern of people with type 1 diabetes (T1D) and may result in suboptimal glycemic control due to avoidance behavior. Optimal basal insulin therapy may reduce nocturnal hypoglycemia. Insulin degludec is associated with lower risk of nocturnal hypoglycemia in T1D. However, it has not been studied in people specifically prone to severe nocturnal hypoglycemia. We report frequencies of CGM-recorded nocturnal non-severe hypoglycemia (NSH) from the HypoDeg trial, which compared insulin degludec with insulin glargine in people with T1D and previous severe nocturnal hypoglycemia. Materials and Methods: Seventy-four people completed 4 x 6 days of blinded CGM (Medtronic iPro) during a 2-year randomized cross-over study. CGM traces were reviewed for clinically important hypoglycemic events ≤ 3.0 mmol/L according to current international consensus. Results: When defining night-time from 23-06:59 a total of 193 episodes of nocturnal NSH were found at the glucose threshold ≤ 3.0 mmol/L. A 53% (95% confidence interval [CI] 35%-64%; p&amp;lt;0.001) relative risk reduction (RRR) in nocturnal NSH during treatment with insulin degludec (0.6 episodes/person-week) was observed as compared to insulin glargine (1.3 episodes/person-week). The reduction in nocturnal NSH was mainly due to a 52% (95%[CI]:32-70%; p&amp;lt;0.001) RRR in nocturnal asymptomatic hypoglycemia with insulin degludec (0.4 episodes/person-week) as compared to insulin glargine (0.9 episodes/person-week). Similar results were found when defining night-time from 00-05:59. Conclusion: People with T1D prone to nocturnal severe hypoglycemia have lower rates of CGM-recorded nocturnal hypoglycemia with insulin degludec as compared to insulin glargine. Disclosure J.M. Brøsen: None. R.M. Agesen: Employee; Self; Novo Nordisk A/S. A. Alibegovic: Employee; Self; Novo Nordisk A/S. H.U. Andersen: Advisory Panel; Self; Novo Nordisk A/S. Stock/Shareholder; Self; Novo Nordisk A/S. P. Gustenhoff: Advisory Panel; Self; Abbott Laboratories, AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Novo Nordisk A/S, Sanofi-Aventis. T.K. Hansen: None. T. Jensen: Stock/Shareholder; Self; Novo Nordisk A/S. C.B. Juhl: None. S. Lerche: None. K. Nørgaard: Advisory Panel; Self; Abbott, Medtronic. Research Support; Self; Novo Nordisk A/S. Speaker’s Bureau; Self; Medtronic, Novo Nordisk A/S. Stock/Shareholder; Self; Novo Nordisk Inc. H.D. Parving: None. L. Tarnow: None. B. Thorsteinsson: None. U. Pedersen-Bjergaard: Advisory Panel; Self; Novo Nordisk A/S, Sanofi. Research Support; Self; Novo Nordisk A/S.

Cardiac Autonomic Neuropathy and Hypoglycemia as Independent Predictors of QTc Elongation at Night in Adolescents With Type 1 Diabetes: Cohort Study

Background. QTc elongation is the risk factor of sudden cardiac death. Patients with type 1 diabetes (T1D) can have QTc elongation due to hypoglycemia and cardiac autonomic neuropathy (CAN). The separate role of this two factors in QTc elongation development in T1D patients is still unknown. Objective. The aim was to study the role of cardiac autonomic neuropathy and hypoglycemia as independent risk factors of QTc elongation at night in adolescents with T1D. Methods. Patients at the age of 10-17 years old with T1D were enrolled in the cohort study. All patients have undergone simultaneous 24-hour monitoring of electrocardiogram and glycemia. Results of nocturnal monitoring (23:00-07:00) were estimated. QTc elongation &gt; 450 ms was regarded pathological. CAN was diagnosed at decrease of ≥ 2 time domain parameters (SDNN &lt; 101 ms, SDNNi &lt; 48 ms, SDANN &lt; 85 ms, rMSSD &lt; 25 ms). Hypoglycemia was classified as 1st ( ≥ 3.0 and ≤ 3.9 mmol/L), 2nd (≥ 2.2 and &lt; 3.0 mmol/L) or 3rd (≤ 3.9 mmol/L along with cognitive defects and the need of acute hypoglycemia treatment) level. We also have distinguished prolonged (&lt; 3.0 mmol/L and ≥ 120 min) and asymptomatic ( ≤ 3.9 mmol/L and no adrenergic symptoms) nocturnal hypoglycemia. We didn’t analyse hypoglycemia periods with &gt; 9.0 mmol/L. Results. QTc elongation &gt; 450 ms was revealed in 28 out of 100 patients. All patients with QTc &gt; 450 ms were similar on gender, age, HbA1C level with patients without any QTc elongation but they have longer history of T1D and higher frequency of 2nd level hypoglycemia and asymptomatic nocturnal hypoglycemia. According to the data from multivariate regression analysis independent predictors of QTc elongation were the following: CAN — odds ratio (OR) 9.0 (95% confidential interval [CI] 3.3-24.2), 2nd level hypoglycemia — OR 4.4 (95% CI 1.4-14.2), asymptomatic nocturnal hypoglycemia — OR 2.9 (95% CI 1.1-7.7) and T1D duration — OR 1.3 (95% CI 1.0-1.5). Conclusion. CAN and hypoglycemia (both clinically significant and asymptomatic nocturnal) are independent predictors of QTc elongation in adolescents with T1D.

682-P: Early Detection and Prevention of Dulaglutide-Induced Asymptomatic Nocturnal and Persistent Hypoglycemia in Patients with Advanced Diabetic Kidney Disease

Purpose: Dulaglutide, a long acting GLP-1 receptor agonist (GLP-1 RA) is reported to reduce decline in eGFR in patients with diabetic kidney disease (DKD). Dulaglutide has been applied to the treatment and prevention of advanced DKD. GLP-1RA is well known to suppress glucagon secretion from the pancreas. In advanced DKD, renal gluconeogenesis is reduced due to the progression of DKD, and thereby the incidence of hypoglycemia is increased in advanced DKD. However, hypoglycemia due to GLP-1RA is rarely reported in advanced DKD. The present study was performed in order to get further insight into the risk management of hypoglycemia in advanced DKD patients treated with GLP-RA using continuous glucose monitoring (CGM). Methods: Eleven patients with advanced DKD (eGFR&amp;lt;45) were included in the present study. Whole patients were treated with dulaglutide over 1 year and no other hypoglycemic agents were administered. Two weeks CGM was performed using Free Style Libre Pro. In the case of nocturnal hypoglycemia, the effect of oral administration of medium-chain triglyceride (MCT), which directly stimulates hepatic glucose production, was studied. Results: Two weeks CGM revealed that asymptomatic nocturnal and persistent hypoglycemia lasting 4 to 6 hours occurred in patients with advanced DKD during dulaglutide monotherapy. Late evening oral administration of a small amount (10-15g) of MCT is effective to avoid dulaglutide-induced nocturnal and persistent hypoglycemia. Discussion: Dulaglutide-induced nocturnal hypoglycemia in advanced DKD may be attributed to reduced hepatic glycogenolysis and renal gluconeogenesis. Conclusion: The present study firstly demonstrated that dulaglutide produced asymptomatic nocturnal and persistent hypoglycemia in patients with advanced DKD, which can be prevented by the administration of MCT. CGM is essential for early detection and prevention of dulaglutide-induced hypoglycemia. Disclosure H. Nishihara: None. M. Inoue: None. J. Umezu: None. K. Arai: None. T. Sudo: None. J. Sasaki: None. C. Koizumi: None. M. Saito: None. H. Sunagawa: None. A. Hirai: None.

Prediction of Nonsevere Hypoglycemia—The Influence of Glycemic Variability in the HypoAna Study

Introduction: In the struggle for tight glycemic control many type 1 diabetes patients daily experience large blood glucose fluctuations. It has been demonstrated that increased glucose variability is a predictor of hypoglycemia, which is the main limiting factor for achieving the recommended HbA1c target. The relationship between glucose variability and hypoglycemia might seem intuitive, but the exact nature of the relationship is difficult to elucidate. In this study we wanted to clarify the relationship between occurrence of non-severe hypoglycemia and glycemic variability in type 1 diabetic patients at high risk of severe hypoglycemia. Material and Methods: 72 patients participated for 4 x 3 days of blinded CGM recordings during a 2-year randomized balanced cross-over study with human insulins (regular/NPH) and insulin analogs (aspart/detemir). CGM recordings were used to calculate the coefficient of variation (CV) in glucose. Results: Treatment with insulin analogs resulted in a significant lower nocturnal CV (mean 29.2%, SD 9.1) than treatment with human insulin (mean 36.9%, SD 9.1) (p&amp;lt;0.0001). CV was a significant risk marker of nocturnal asymptomatic hypoglycemia ?3.9 mmol/l in a multivariate analysis. A 1% increase in CV corresponds to a 5% (p&amp;lt;0.0001) increase in asymptomatic hypoglycemia. CV did not predict hypoglycemia during daytime at this threshold. Conclusion: Treatment with insulin analogs provides less glycemic variability during night-time. The coefficient of variation in patients suffering from recurrent severe hypoglycemia predicts the occurrence of especially nocturnal hypoglycemia. Disclosure R.M. Agesen: None. P.L. Kristensen: Other Relationship; Self; Eli Lilly and Company. H. Beck-Nielsen: None. K. Nørgaard: Research Support; Self; Roche Diabetes Care Health and Digital Solutions. Advisory Panel; Self; Novo Nordisk A/S. Stock/Shareholder; Self; Novo Nordisk A/S. Research Support; Self; Novo Nordisk A/S. Advisory Panel; Self; Medtronic. Speaker's Bureau; Self; Medtronic, Zealand Pharma A/S, Novo Nordisk A/S. Research Support; Self; Zealand Pharma A/S. T. Jensen: Stock/Shareholder; Self; Novo Nordisk A/S. B. Thorsteinsson: None. L. Tarnow: Stock/Shareholder; Self; Novo Nordisk A/S. U. Pedersen-Bjergaard: Advisory Panel; Self; Novo Nordisk A/S. Consultant; Self; Novo Nordisk A/S. Research Support; Self; Novo Nordisk A/S. Advisory Panel; Self; Sanofi-Aventis. Consultant; Self; Medtronic.

Effect of Insulin Analogs on Frequency of Non–Severe Hypoglycemia in Patients with Type 1 Diabetes Prone to Severe Hypoglycemia: Much Higher Rates Detected by Continuous Glucose Monitoring than by Self-Monitoring of Blood Glucose—The HypoAna Trial

Hypoglycemia is an increasingly important endpoint in clinical diabetes trials. The assessment of hypoglycemia should therefore be as complete as possible. Blinded continuous glucose monitoring (CGM) provides an improved opportunity to capture asymptomatic and nocturnal events. Here we report results from the HypoAna trial comparing all-analog-insulin therapy (aspart/detemir) with all-human-insulin therapy (neutral protamine Hagedorn/regular) on non-severe hypoglycemia (symptomatic and asymptomatic hypoglycemia) as assessed by blinded CGM and compared with data obtained by self-monitoring of blood glucose (SMBG) in patients with type 1 diabetes and recurrent severe hypoglycemia. Fifty-three patients completed a substudy of 4 × 3 days of blinded CGM. CGM traces were reviewed for hypoglycemic events lasting 15 min or longer. At the threshold ≤3.9 mmol/L, the per-protocol analysis demonstrated a 40% rate reduction (95% confidence interval [CI] 20%-60%; P = 0.002) in nocturnal non-severe hypoglycemia during analog treatment, mainly due to a 40% rate reduction (95% CI 0%-70%; P = 0.03) of nocturnal asymptomatic hypoglycemia. Similar nonsignificant trends were seen at the glucose threshold ≤3.0 mmol/L. Overall CGM-detected that nocturnal asymptomatic hypoglycemia ≤3.9 mmol/L was ∼17 times more frequent than SMBG-detected episodes (52 vs. 3 events/patient-year). This translates into a time needed to treat one patient with insulin analogs to prevent one episode that is 34 times shorter using CGM data than SMBG data (1.4 vs. 47 weeks). Capturing hypoglycemic events by the conventional method of SMBG in patients with impaired awareness reveals only a limited number of events. Blinded CGM can provide more complete data, particularly in terms of asymptomatic and nocturnal events.

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.

ObjectiveTo 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.MethodsPatients 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.ResultsThe 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).ConclusionsThe 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.

Effect of insulin analogues on frequency of non-severe hypoglycaemia in patients with type 1 diabetes prone to severe hypoglycaemia: The HypoAna trial

AimInsulin analogues reduce the risk of hypoglycaemia compared with human insulin in patients with type 1 diabetes (T1D) and minor hypoglycaemia problems. The HypoAna trial showed that, in patients with recurrent severe hypoglycaemia, treatment based on insulin analogues reduces the risk of severe hypoglycaemia. The present study aims to assess whether this also applies to non-severe hypoglycaemia events during the day and at night. MethodsThis 2-year investigator-initiated multicentre, prospective, randomized, open, blinded endpoint (PROBE) trial involved patients with T1D and at least two episodes of severe hypoglycaemia during the previous year. Using a balanced crossover design, patients were randomized to basal–bolus therapy based on analogue (detemir/aspart) or human (NPH/regular) insulins. A total of 114 participants were included. Endpoints were the number of severe hypoglycaemic events and non-severe events, including documented symptomatic and asymptomatic episodes occurring during the day and at night (ClinicalTrials.gov number: NCT00346996). ResultsAnalogue-based treatment resulted in a 6% (2–10%; P=0.0025) overall relative risk reduction of non-severe hypoglycaemia. This was due to a 39% (32–46%; P<0.0001) reduction of non-severe nocturnal hypoglycaemia, seen for both symptomatic (48% [36–57%]; P<0.0001) and asymptomatic (28% [14–39%]; P=0.0004) nocturnal hypoglycaemia episodes. No clinically significant differences in hypoglycaemia occurrence were observed between the insulin regimens during the day. The time needed to treat one patient with insulin analogues to avoid one episode (TNT1) of non-severe nocturnal hypoglycaemia was approximately 3 months. ConclusionIn T1D patients prone to severe hypoglycaemia, treatment with analogue insulin reduced the risk of non-severe nocturnal hypoglycaemia compared with human insulin.

In search of the Somogyi effect

The Somogyi phenomenon or rebound hyperglycaemia is known as the counterregulatory response to asymptomatic nocturnal hypoglycaemia; the Somogyi phenomenon occurs with high fasting blood glucose levels and hyperglycaemia the following morning. Most published trials, however, do not agree with this theory. Although data from some experimental studies may suggest a pathophysiological link. Perhaps, the differences in research results are caused by the evolution of blood glucose monitoring methods. Nevertheless, it cannot be excluded that the results of Michael Somogyi’s studies were misunderstood.

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?

ObjectiveTo investigate whether the occurrence of nocturnal asymptomatic hypoglycemia may be predicted based on fasting glucose levels and post-breakfast glucose fluctuations.Patients and MethodsThe 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.Results64 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).ConclusionsNocturnal 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 Insulin-Treated Diabetes: A Case for Increased Vigilance

Studies have shown that effective diabetes management can delay or prevent the micro- and macrovascular complications of diabetes. Achieving optimal glycemic control often requires treatment with intensive insulin management. However, with intensive insulin management comes the risk of severe hypoglycemia. Hypoglycemia requiring emergency medical assistance is as common in patients with longstanding insulin-treated type 2 diabetes mellitus as in patients with type 1 diabetes mellitus, and is associated with a significant economic and personal burden; untreated, severe hypoglycemia can result in morbidity and death. Key contributors to severe hypoglycemia are asymptomatic hypoglycemia and nocturnal hypoglycemia; both conditions inhibit patients' ability to recognize hypoglycemia when it is occurring and take appropriate action. As a result, many patients with types 1 and 2 diabetes mellitus are reluctant to follow and/or adjust their insulin regimens as needed because of fear of hypoglycemia, resulting in exposure to chronic hyperglycemia, oxidative stress, and long-term complications. Severe hypoglycemia can be prevented through vigilance in identifying patients at risk, utilizing appropriate medications and medication regimens, and effective glucose monitoring strategies and technologies. The purpose of this article is to review our current understanding of hypoglycemia and its impact on diabetes management, and to provide guidance to health care providers when assisting patients who utilize insulin therapy to do so safely and effectively.

Correlations of Glucose Levels in Interstitial Fluid Estimated by Continuous Glucose Monitoring Systems and Venous Plasma

Continuous glucose monitoring systems (CGMS) are relatively new technology that measures interstitial glucose every 5 minute over a period of 72 hours [1]. Continuous glucose monitoring by CGMS provides accurate data to patients and physicians about blood glucose variability during the measurement period. Two types of CGMS devices, intended for professional and personal use, are available. Professional devices allow physicians to download and analyze data and for use in clinical decision making. Personal devices allow patients to monitor real time glucose data and use such data for self-monitoring and medication adjustments. For this reason, the American Association of Clinical Endocrinologists has recommended the use of personal devices for glucose control and prevention of hypoglycemia in patients with type 1 diabetes [2,3] and pregnancy with diabetes [4,5]. The article, correlation and accuracy of glucose levels between interstitial fluid and venous plasma by continuous glucose monitoring system [6] clearly showed a glucose time lag between blood levels and subcutaneous interstitial levels. Blood and interstitial fluid had different peak times and peak values after meal loading, but the trends of glucose excursion were very similar. In addition, CGMS data showed delayed peaks and lowered peak values compared to venous blood sugar levels after the ingestion of different kinds of food. These lags between the two compartments did not differ by food. The use of CGMS devices, which provide accurate control and monitoring of blood glucose levels, is suitable for use in uncontrolled diabetic patients and to help physicians make decisions regarding treatment modalities. In the treatment of diabetes, glucose variability, especially postprandial hyperglycemia, is a major risk factor for cardiovascular complications. By using CGMS devices, clinicians can easily access glucose variability in patients. Although patients more easily achieved target HbA1c levels when practicing self monitoring of glucose using the CGMS device than by other methods, systemic reviews comparing the results of CGMS use and intermittent fingertip glucose monitoring do not indicate significantly superior benefits of CGMS. However, they do support the improved detection of asymptomatic nocturnal hypoglycemia [7]. CGMS systems offer many advantages to patients and physicians. However, the sensitivity of glucose sensing decreases over time. After 3 to 5 days, the sensing amplitude of CGMS sensors becomes unreliable. The accuracy of sensors is affected by localized tissue reactions and fibrous encapsulation [8]. For these reasons, patients should calibrate sensing amplitudes through comparisons with fingertip glucose values regularly. Methods of blocking fibrous tissue aggregation and reducing tissue reactions, such as corticosteroid sprays or anticancer drug coatings, were used in attempts to address these problems [9,10]. Also, if we placed the sensor in subcutaneous space during continuous monitoring, small glucose diffusion gap from blood level to subcutaneous tissue fluid was another limitation. Recently, ubiquitous health systems have been introduced to help outpatients to control their blood sugar levels. If patients send their blood glucose profiles to physicians over the internet, their physicians can provide advice to meet their patients' needs. The use of CGMS systems connected to Internet networks has the potential to provide effective, evidence-based support to clinicians in their daily efforts to optimize glycemic control [11]. The closed loop pump is a state of the art technology [12,13]. But major pitfall of this closed loop pump is sensing problems of glucose sensor and limited space of insulin reservoir in transplanted pump. Closed loop pumps are expected to replace open loop pumps and decrease the pain associated with insulin injections. Permanent usable blood glucose sensors and interstitial glucose sensors are also expected to be developed [9,10]. Rapid development of information technology devices and techniques will solve the relevant technological problems, and closed loop systems will be available to patients in the future.

The effect of continuous subcutaneous glucose monitoring (CGMS) versus intermittent whole blood finger-stick glucose monitoring (SBGM) on hemoglobin A1c (HBA1c) levels in Type I diabetic patients: A systematic review

Background and purpose Continuous glucose monitoring (CGMS) is a relatively new technology that measures interstitial glucose every 5 min for 72 h. The resulting profile provides a more comprehensive measure of glycemic excursions than intermittent self-blood finger-stick glucose monitoring (SBGM) and thus could potentially improve diabetes control. We performed a meta-analysis of randomized controlled trials comparing CGMS and SBGM in Type 1 diabetic patients. Our aim was to determine whether CGMS leads to better hemoglobin A1c (HBA1c) levels, a marker of long-term vascular risk. Methods Randomized controlled trials comparing CGMS and SBGM in Type 1 diabetic patients were identified using both manual and electronic searches of the literature in MEDLINE, EMBASE, PUBMED and Cochrane Central Registry of Controlled Trials from 1996 to March 2007. Relevant studies were independently selected by two reviewers, who also extracted data on study design, quality and effect on HBA1c levels. Data from all trials were pooled using a random effects model. Results Seven studies with a total of 335 patients fulfilled the inclusion criteria. Five studies were confined to the pediatric population (age < 18 years). Study duration varied from 12 to 24 weeks. Compared with SBGM, CGMS was associated with a non-significant reduction in HBA1c (0.22%; 95% CI: −0.439% to 0.004%, p = 0.055). Conclusions There is insufficient evidence to support the notion that CGMS provides a superior benefit over SBGM in terms of HBA1c reduction. There was some indication of improved detection of asymptomatic nocturnal hypoglycemia in the CGMS group.

Home Use of the GlucoWatch G2 Biographer in Children With Diabetes

To evaluate usability, accuracy, and hypoglycemia detection of the GlucoWatch G2 Biographer (GW2B) in children aged 1 to 17 years. After a 15-hour study of device accuracy, 46 children (15 <7 years, 31 > or =7 years) with type 1 diabetes were enrolled for an extended-wear outcome study: 2 daytime and 2 nighttime 15-hr wear periods each week and blood glucose monitoring 4 times daily for 3 months. A total of 531 paired GW2B/meter readings were available for accuracy assessment. The correlation coefficients were 0.58 and 0.74 (ages <7 and > or =7 years, respectively). There was no significant change in hemoglobin A1C)or weight-adjusted insulin dose at 3 months after biographer use. Forty-two episodes of hypoglycemia were detected by the GW2B, 33 of which were confirmed by blood glucose meters. Sensitivity and specificity of audible low-glucose alerts were approximately 79% and 83%, respectively. No significant side effects were reported. The GW2B is usable and safe in children who are <7 years or older in the home setting. The GW2B can detect asymptomatic nocturnal hypoglycemia in younger children.

Motor activity during asymptomatic nocturnal hypoglycemia in adolescents with type 1 diabetes mellitus.

Nocturnal hypoglycemia is reported in 13%-56% of adolescents with type 1 diabetes mellitus. It may be asymptomatic in more than 50% of patients. No noninvasive method for detecting asymptomatic nocturnal hypoglycemia (ANH) has so far proven successful. The aim of the present study was to evaluate quantitative changes of motor activity by actigraphy during episodes of ANH in adolescents with type 1 diabetes mellitus. A total of 18 patients aged 10-16 years with a history of ANH were investigated. Blood was sampled at half-hourly intervals between 22.30 and 06.00 hours with a micropump, and an actigraph was fastened to the right wrist. Blood glucose concentrations were measured and compared to motor activity. Nocturnal hypoglycemia was recorded in 10 patients (55%), with blood glucose during periods of hypoglycemia of 3.00+0.17 mmol/l (range, 1.2-3.4 mmol/l), and duration of hypoglycemia of 1.95+1.34 hours (range, 0.5-5.0 hours). All periods of hypoglycemia were clinically asymptomatic. Regression analysis revealed a statistically significant linear correlation ( p=0.03) between blood glucose concentration and the respective 30-min activity counts. Activity counts in patients with nocturnal hypoglycemia were significantly (ANOVA, p<0.02) higher than in patients with normoglycemia. We conclude that low blood glucose was significantly correlated with an increase in motor activity as detected by actigraphy. This implies the possibility of noninvasive screening of asymptomatic nocturnal hypoglycemia.