Failure of nocturnal hypoglycemia to cause daytime hyperglycemia in patients with IDDM

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.

Enlarged glycemic variability in sulfonylurea-treated well-controlled type 2 diabetics identified using continuous glucose monitoring

Time in range (TIR) is an index of glycemic control obtained from continuous glucose monitoring (CGM). The aim was to compare the glycemic variability of treatment with sulfonylureas (SUs) in type 2 diabetes mellitus (T2DM) with well-controlled glucose level (TIR > 70%). The study subjects were 123 patients selected T2DM who underwent CGM more than 24 h on admission without changing treatment. The primary endpoint was the difference in glycemic variability, while the secondary endpoint was the difference in time below range < 54 mg/dL; TBR < 54, between the SU (n = 63) and non-SU (n = 60) groups. The standard deviation, percentage coefficient of variation (%CV), and maximum glucose level were higher in the SU group than in the non-SU group, and TBR < 54 was longer in the high-dose SU patients. SU treatment was identified as a significant factor that affected %CV (β: 2.678, p = 0.034). High-dose SU use contributed to prolonged TBR < 54 (β: 0.487, p = 0.028). Our study identified enlarged glycemic variability in sulfonylurea-treated well-controlled T2DM patients and high-dose SU use was associated with TBR < 54. The results highlight the need for careful adjustment of the SU dose, irrespective of glycated hemoglobin level or TIR value.

Investigating the Relationship between Morning Glycemic Variability and Patient Characteristics Using Continuous Glucose Monitoring Data in Patients with Type 2 Diabetes

Objective To investigate the relationship between patient characteristics and morning glycemic variability. Methods We retrospectively evaluated 106 patients with type 2 diabetes who underwent continuous glucose monitoring during admission. The highest postprandial glucose level (within 3 hours after breakfast; 'highest level'), the time from the start of breakfast to the highest postprandial glucose level ('highest time'), the difference between the pre-breakfast and highest postprandial breakfast glucose level ('increase'), the area under the curve (AUC; ≥180 mg/dL) for the glycemic variability within 3 hours after breakfast ('morning AUC'), and the post-breakfast glucose gradient ('gradient') were calculated. We analyzed the associations between these factors and nocturnal hypoglycemia and the patients' characteristics by using a regression analysis. Results After stepwise multivariate adjustment, significant independent associations were found between 'highest level' and high age, low BMI, and high HbA1c; 'highest time' and high HbA1c, low C-peptide immunoreactivity (CPR), and low fasting plasma glucose (FPG); the 'increase' and high age, low BMI, high HbA1c, low FPG and hypoglycemia; 'morning AUC' and high age, high HbA1c and hypoglycemia; and 'gradient' and long duration of diabetes and low BMI. Conclusion Higher age and lower BMI are associated with higher 'highest' and 'increase' levels. Higher HbA1c levels were linked to a longer 'highest time', and longer durations of the diabetes, while lower BMI values were related to a higher 'gradient'.

Major Increases between Pre- and Post-breakfast Glucose Levels May Predict Nocturnal Hypoglycemia in Type 2 Diabetes

Objective The aim of this study was to determine whether nocturnal hypoglycemia may be predicted according to morning glucose levels. Methods We retrospectively evaluated 106 patients with type 2 diabetes who underwent continuous glucose monitoring during admission. The pre-breakfast glucose level (Pre-breakfast level), highest postprandial glucose level within 3 hours after breakfast (Highest level), time from the start of breakfast to the highest postprandial glucose level (Highest time), difference between the pre-breakfast and highest postprandial breakfast glucose levels (Increase), area under the glucose curve (≥180 mg/dL) within 3 hours after breakfast (Morning AUC), post-breakfast glucose gradient (Gradient), and the increase-to-pre-breakfast ratio (Increase/Pre-breakfast) were calculated. The subjects were divided into hypoglycemic and non-hypoglycemic patients and compared for the above parameters using the t-test. A receiver operating characteristic analysis was used to determine the optimal cut-off values to predict nocturnal hypoglycemia (Hypoglycemia). Results Twenty-eight patients (26.4%) had hypoglycemia. The Pre-breakfast levels were significantly lower in patients with hypoglycemia than those without (p=0.03). The Increases were significantly higher in patients with hypoglycemia than those without (p=0.047). The Increase/Pre-breakfast ratio were significantly larger in patients with hypoglycemia than those without (p=0.0002). Their cut-off values were as follows (level, sensitivity, specificity, and area under the curve): 123 mg/dL, 0.89, 0.55, and 0.78 (p<0.0001); 90.5 mg/dL, 0.75, 0.64, and 0.76 (p<0.0001); and 90.2%, 0.75, 0.76, and 0.78 (p<0.0001), respectively. Conclusion Major increases between the pre- and post-breakfast glucose levels may predict nocturnal hypoglycemia in patients with type 2 diabetes.

Rebound hyperglycaemia in diabetic cats

OBJECTIVES

Rebound hyperglycaemia (also termed Somogyi effect) is defined as hyperglycaemia caused by the release of counter-regulatory hormones in response to insulin-induced hypoglycaemia, and is widely believed to be common in diabetic cats. However, studies in human diabetic patients over the past quarter century have rejected the common occurrence of this phenomenon. Therefore, we evaluated the occurrence and prevalence of rebound hyperglycaemia in diabetic cats.

METHODS

In a retrospective study, 10,767 blood glucose curves of 55 cats treated with glargine using an intensive blood glucose regulation protocol with a median of five blood glucose measurements per day were evaluated for evidence of rebound hyperglycaemic events, defined in two different ways (with and without an insulin resistance component).

RESULTS

While biochemical hypoglycaemia occurred frequently, blood glucose curves consistent with rebound hyperglycaemia with insulin resistance was confined to four single events in four different cats. In 14/55 cats (25%), a median of 1.5% (range 0.32-7.7%) of blood glucose curves were consistent with rebound hyperglycaemia without an insulin resistance component; this represented 0.42% of blood glucose curves in both affected and unaffected cats.

CONCLUSIONS AND RELEVANCE

We conclude that despite the frequent occurrence of biochemical hypoglycaemia, rebound hyperglycaemia is rare in cats treated with glargine on a protocol aimed at tight glycaemic control. For glargine-treated cats, insulin dose should not be reduced when there is hyperglycaemia in the absence of biochemical or clinical evidence of hypoglycaemia.

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.

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.

[Hypoglycemia as a limiting factor in the management of type 1 diabetes]

Type 1 diabetic patients frequently present hypoglycemic episodes during their insulinotherapy, which, besides the discomfort and constrains does not allow the ideal glycemic control. Further, hypoglycemic events lead to the deficiency of the counter-regulation mechanisms in the subsequent episode, with a decrease in the release of epinephrine and the symptoms of warming, with great risk of severe hypoglycemia. The occurrence of hypoglycemia during some risky activities, specially driving, could result in accidents with the patient and /or third parts including property damage, stressing here the need to advise diabetics against having the necessary caution while driving. Generally the connective recovery is total after correcting a hypoglycemic coma. However when these episodes are repetitive, particularly in children, they could result in definitive cognitive disturbances. Hypoglycemic events without a warning signal (hypoglycemic unawareness) are difficult to reverse, thus it is necessary to prevent their occurrence, adjusting the treatment with glycemic targets, using continuous glucose monitoring at home and teaching them how to have an early recognition of hypoglycemia.

Nocturnal hypoglycaemias in type 1 diabetic patients: what can we learn with continuous glucose monitoring?

AIM

In type 1 diabetic patients (T1DM), nocturnal hypoglycaemias (NH) are a serious complication of T1DM treatment; self-monitoring of blood glucose (SMBG) is recommended to detect them. However, the majority of NH remains undetected on an occasional SMBG done during the night. An alternative strategy is the Continuous glucose monitoring (CGMS), which retrospectively shows the glycaemic profile. The aims of this retrospective study were to evaluate the true incidence of NH in T1DM, the best SMBG time to predict NH, the relationship between morning hyperglycaemia and NH (Somogyi phenomenon) and the utility of CGMS to reduce NH.

METHODS

Eighty-eight T1DM who underwent a CGMS exam were included. Indications for CGMS evaluation, hypoglycaemias and correlation with morning hyperglycaemias were recorded. The efficiency of CGMS to reduce the suspected NH was evaluated after 6-9 months.

RESULTS

The prevalence of NH was 67% (32% of them unsuspected). A measured hypoglycaemia at bedtime (22-24 h) had a sensitivity of 37% to detect NH (OR=2.37, P=0.001), while a single measure < or =4 mmol/l at 3-hour had a sensitivity of 43% (OR=4.60, P<0.001). NH were not associated with morning hyperglycaemias but with morning hypoglycaemias (OR=3.95, P<0.001). After 6-9 months, suspicions of NH decreased from 60 to 14% (P<0.001).

CONCLUSION

NH were highly prevalent and often undetected. SMBG at bedtime, which detected hypoglycaemia had sensitivity almost equal to that of 3-hour and should be preferred because it is easier to perform. Somogyi phenomenon was not observed. CGMS is useful to reduce the risk of NH in 75% of patients.

Unrecognised hypoglycaemia in children and adolescents with type 1 diabetes using the continuous glucose monitoring system: prevalence and contributors

AIM

To determine prevalence of hypoglycaemia, and contributing factors, in children with type 1 diabetes, using the Medtronic MiniMed continuous glucose monitoring system (CGMS).

METHODS

Fifty-one children and adolescents with diabetes were studied with the CGMS. The studies were analysed for frequency and duration of hypoglycaemia (below 3.5 and 2.5 mmol/L). Contributing clinical factors were determined. Occurrence of nocturnal hypoglycaemia was related to bedtime and fasting home glucose recording.

RESULTS

Hypoglycaemia was common, with 1 (0-4.2) (median (range)) episode per patient per 24 hours, and 0.33 (0-2) episodes per patient per night. Nocturnal episodes were longer than daytime episodes [97.5 (5-720) versus 35 (5-295) minutes for episodes below 3.5 mmol/L, P < 0.001; and 75 (10-640) versus 25 (5-200) minutes for episodes below 2.5 mmol/L, P < 0.001], and less likely to be recognised by the subject (P < 0.001 for episodes below both 3.5 and 2.5 mmol/L). Nocturnal hypoglycaemia was more common with a bedtime glucose recording <6 mmol/L, but also occurred frequently in subjects with glucose recordings >10 mmol/L. No bedtime glucose value reduced the risk of nocturnal hypoglycaemia to <10%.

CONCLUSION

Hypoglycaemia, assessed using the CGMS, is common in children with type 1 diabetes and can be prolonged (although is predominantly mild). Bedtime home glucose recordings are poorly predictive of hypoglycaemia during the following night. Continuous glucose monitoring has proven very useful in management of individual patients, particularly adolescents experiencing difficulties with adherence to diabetes management.

The Dawn Phenomenon Revisited: Implications for Diabetes Therapy

OBJECTIVE

To summarize current data on the magnitude, prevalence, variability, pathogenesis, and management of the dawn phenomenon in patients with diabetes mellitus.

METHODS

On the basis of the pertinent available literature and clinical experience, we propose a quantitative definition of the dawn phenomenon, discuss potential pathogenic mechanisms, and suggest management options.

RESULTS

The "dawn phenomenon" is a term used to describe hyperglycemia or an increase in the amount of insulin needed to maintain normoglycemia, occurring in the absence of antecedent hypoglycemia or waning insulin levels, during the early morning hours. To be clinically relevant, the magnitude of the dawn increase in blood glucose level should be more than 10 mg/dL or the increase in insulin requirement should be at least 20% from the overnight nadir. Controversy exists regarding the frequency, reproducibility, and pathogenesis of the dawn phenomenon. Approximately 54% of patients with type 1 diabetes and 55% of patients with type 2 diabetes experience the dawn phenomenon when the foregoing quantitative definition is used. The most likely pathogenic mechanism underlying the dawn phenomenon is growth hormone-mediated impairment of insulin sensitivity at the liver and muscles. The exact biochemical pathways involved are unknown. Therapeutic decisions aimed at correcting fasting hyperglycemia should take into account the variability and magnitude of the dawn phenomenon within individual patients. Successful insulinization appears to minimize the effects of the dawn phenomenon. Currently, no subcutaneous depot preparation of insulin exists that is capable of mimicking the basal insulinsecretion of the healthy pancreas.

CONCLUSION

Increases in the bedtime doses of hypoglycemic agents with nighttime peaks in action may correct early morning hyperglycemia but be associated with undesirable nocturnal hypoglycemia. Targeted continuous subcutaneous insulin infusion programming can facilitate the prevention of early morning hyperglycemia in selected patients.

Nocturnal hypoglycemia: clinical manifestations and therapeutic strategies toward prevention

OBJECTIVE

To review the features of nocturnal hypoglycemia and various preventive strategies.

METHODS

We discuss the physiologic changes, the potential precipitating factors, the immediate and long-term effects, and the currently available options for treatment of nocturnal hypoglycemia in patients with diabetes.

RESULTS

Nocturnal hypoglycemia is common in patients with type 1 diabetes and is usually asymptomatic. Nocturnal hyperinsulinemia frequently occurs with insulin therapy, and although blood glucose levels are often low during sleep, they are seldom measured routinely. Almost 50% of all episodes of severe hypoglycemia occur at night during sleep. Such episodes can cause convulsions and coma and have been implicated as a precipitating factor in cardiac arrhythmias resulting in sudden death--the "dead-in-bed syndrome." Nocturnal hypoglycemia seems to have no immediate detrimental effect on cognitive function; however, on the following day, mood and well-being may be adversely affected. Recurrent exposure to nocturnal hypoglycemia may impair cognitive function; other substantial long-term morbidity includes the development of acquired hypoglycemia syndromes, such as impaired awareness of hypoglycemia, through the putative effect of unsuspected recurrent episodes of nocturnal hypoglycemia.

CONCLUSION

In efforts to decrease the risk of nocturnal hypoglycemic episodes, various strategies can be used to minimize the nocturnal hyperinsulinemia that is associated with many insulin replacement regimens. Regular blood glucose monitoring (particularly at bedtime), the ingestion of appropriate bedtime snacks, and the utilization of short- and long-acting insulin analogues may all help to prevent or minimize the frequency of nocturnal hypoglycemia.

Frequency of the dawn phenomenon in type 2 diabetes: implications for diabetes therapy

This study was designed to assess the frequency of the dawn phenomenon in patients with type 2 diabetes. A secondary aim was to examine the influence of varying treatment regimens on the frequency of the dawn phenomenon. The dawn phenomenon was defined as a rise in plasma glucose levels of > or = 0.5 mmol/L (10 mg/dL) between 0500 and 0900 h occurring after a growth hormone surge of > or = 5 microg/L. Sixteen subjects (six men, 10 women) with type 2 diabetes were studied overnight on their current mode of therapy in the General Clinical Research Center. Additionally, six of these subjects were restudied in random order after each of the following three therapeutic regimens: (1) 6 weeks of glipizide, (2) 6 weeks of bedtime NPH insulin, and (3) 3 days of intensive insulin therapy with multiple injections of regular insulin followed by assessment during overnight intravenous infusion of insulin. Thus, a total of 34 overnight studies were performed under various treatment conditions to provide an approximate frequency of the dawn phenomenon in type 2 diabetes. Blood was drawn every 30 min between midnight and 0800 h for measurement of glucose, insulin, C-peptide, and growth hormone levels. Additional counterregulatory hormone levels were determined during 24 of the studies, and the integrity of growth hormone secretion in response to insulin-induced hypoglycemia was assessed in 12 of the 16 patients. The subjects were aged 51 +/- 15 years with a body mass index of 31 +/- 5 kg/m(2) and a mean glycosylated hemoglobin of 8.1 +/- 1.2%. The dawn phenomenon occurred in only one of 34 (3%) studies. Moreover, the four different treatment regimens did not affect the frequency of occurrence of the dawn phenomenon. Ten of the 12 patients tested failed to secrete growth hormone in response to insulin-induced hypoglycemia. These data suggest that the dawn phenomenon is unusual in type 2 diabetes. Previously reported high prevalence rates in studies using similar sample size may be attributable to a Biostator-induced artifact. Decisions regarding therapies for type 2 diabetes should not be based on the assumption that the dawn phenomenon routinely causes early morning hyperglycemia.

Analysing the hypoglycaemic counter-regulation: a clinically relevant phenomenon?

This paper describes an analysis of the temporal relation between episodes of low blood glucose (hypoglycaemia) and counter-regulations, i.e., episodes of elevated blood glucose (hyperglycaemia), in patients with insulin dependent diabetes. The relation was assessed by statistical methods based on a metabolic computer model of the human glucose metabolism. The study material was standard collected clinical data on meals, insulin injections, and measured blood glucose from hospitalised patients. We have found that a typical hypoglycaemic counter-regulation begins 6-8 h after the hypoglycaemia, that it lasts 16-18 h, giving a total duration of 24 h, and that it elevates the blood glucose by 4-10 mmol/l. The phenomenon was demonstrated in the data from more than half of the patients with hypoglycaemic episodes.

Nocturnal electroencephalogram registrations in type 1 (insulin-dependent) diabetic patients with hypoglycaemia

Eight Type 1 (insulin-dependent) diabetic patients with no diabetic complications were studied overnight for two consecutive and one subsequent night with continuous monitoring of electroencephalogram and serial hormone measurements. The aims were: 1) to evaluate the influence of spontaneous and insulin-induced hypoglycaemia on nocturnal electroencephalogram sleep-patterns and, 2) to evaluate counter-regulatory hormone responses. Spontaneous hypoglycaemia occurred on six nights (38%) with blood glucose concentrations less than 3.0 mmol/l and on four nights less than 2.0 mmol/l. All the patients experienced insulin-induced hypoglycaemia with a blood glucose nadir of 1.6 (range 1.4-1.9) mmol/l. The electroencephalogram was analysed by a new method developed for this purpose in contrast to the traditional definition of delta-, theta-, alpha- and beta-activity. The blood glucose concentration could be correlated to the rank of individual electroencephalogram-patterns during the whole night, and specific hypoglycaemic amplitude-frequency patterns could be assigned. Three of the eight patients showed electroencephalogram changes at blood glucose levels below 2.0 (1.6-2.0) mmol/l. The electroencephalogram classes representing hypoglycaemic activity had peak frequencies at 4 and 6 Hz, respectively, clearly different from the patients' delta- and theta-activity. The changes were not identical in each patient, however, they were reproducible in each patient. The changes were found equally in all regions of the brain. The three patients with electroencephalogram changes during nocturnal hypoglycaemia could only be separated from the other five patients by their impaired glucagon responses. Against this background the possibility of protection by glucagon, against neurophysiologic changes in the brain during hypoglycaemia may be considered.

Prevalence and consequences of nocturnal hypoglycemia among conventionally treated children with diabetes mellitus

To determine the prevalence and predictors of, and the glucose responses after, nocturnal hypoglycemia, we studied 135 pediatric patients with insulin-dependent diabetes mellitus on 388 nights. The frequencies of blood glucose values less than 60, 50, and 40 mg/dl (3.3, 2.8, and 2.2 mmol/L) at 2 AM were 14.4%, 7.0%, and 2.1%, and at 6 AM were 6.7%, 2.6%, and 0.5%, respectively. Longer duration of diabetes, higher daily insulin doses, and lower glycosylated hemoglobin values were all significant but weak predictors of 2 AM hypoglycemia (glucose less than or equal to 60 mg/dl (less than or equal to 3.3 mmol/L). A 10 PM glucose concentration less than or equal to 100 mg/dl (less than or equal to 5.6 mmol/L) was present on 48% of nights with 2 AM glucose values less than or equal to 60 mg/dl (less than or equal to 3.3 mmol/L), but only 24% of nights with 10 PM blood glucose values less than or equal to 100 mg/dl (less than or equal to 5.6 mmol/L) were followed by 2 AM hypoglycemia. After treatment of 70 episodes of 2 AM glucose concentrations less than or equal to 60 mg/dl (less than or equal to 3.3 mmol/L), mean 6 AM glucose concentration was 95 +/- 6 mg/dl (5.7 +/- 0.3 mmol/L) and less than or equal to 100 mg/dl in 68.6%. In only 4.3% of these cases was the 6 AM glucose concentration greater than 200 mg/dl (greater than 11.1 mmol/L). Among patients who experienced 2 AM hypoglycemia, after-breakfast glucose values were not greater on days with 2 AM hypoglycemia than on days without it. These data indicate that 2 AM hypoglycemia is relatively common in patients with insulin-dependent diabetes mellitus, is frequently preceded by a 10 PM glucose value less than or equal to 5.6 mmol/L, and is less well predicted by other factors. Appropriate treatment of 2 AM hypoglycemia seldom results in either before-breakfast or after-breakfast blood glucose values greater than 200 mg/dl (greater than 11.1 mmol/L). Early-morning hypoglycemia is an uncommon cause of otherwise unexplained, prebreakfast hyperglycemia in children with insulin-dependent diabetes mellitus.