EEG-Changes During Insulininduced Hypoglycemia in Type 1 Diabetes
Condition: Hypoglycemia; Type 1 Diabetes
MeSH terms: Diabetes Mellitus; Diabetes Mellitus, Type 1; Hypoglycemia
Study type: Observational

Summary: 
      The aim of this study is based on recent pilot studies carried out at Odense University
      Hospital showing that the acute changes in electroencephalographic (EEG) signals (i.e.
      electrical activity inthe brain) elicited by insulin-induced hypoglycemia in patients with
      type 1 diabetes can be reliable detected by real-time processing of these EEG signals using
      mathematical algorithms and state of the art noise and artifact reduction. These preliminary
      results also showed that the hypoglycemia-induced EEG changes are detectable 15-30 min before
      deterioration in cognitive function impedes an adequate response to warning. We hypothesize
      that these observations apply to the majority of patients with type 1 diabetes, and
      therefore, that it is possible to develop an automated device to detect hypoglycemic episodes
      by continuous real-time monitoring and processing of EEG signals. To test our hypothesis, the
      specific aims of the present proposal are:

        1. Detection of hypoglycemia-induced EEG changes using subcutaneous electrodes

        2. Ambulatory EEG monitoring using subcutaneous electrodes
    

Detailed description: 
      The near-normalization of glycemic control has become an established treatment goal in
      diabetes in order to reduce late complications such as nephropathy, neuropathy, retinopathy
      and cardiovascular disease (1,2). However, the frequency of insulin-induced hypoglycemia
      increases several-fold during intensified insulin therapy (2,3). Thus, hypoglycemia is the
      most common acute complication in the treatment of diabetes with insulin. During hypoglycemia
      the cognitive function is disturbed, and may progress to unconsciousness and seizures. This
      can lead to high-risk situations, e.g. while driving or operating a machine. Estimates of
      deaths in patients with type 1 diabetes attributed to hypoglycemia vary between 2% and 6%
      (4,5). Moreover, the risk of hypoglycemia limits everyday activities of diabetic patients
      decreasing their quality of life. It is therefore not surprising that hypoglycemia is the
      most feared acute complication of insulin therapy in diabetic patients. This fear of
      hypoglycemia discourages diabetic subjects from attempting to maintain tight glycemic
      control, which in turn leads to a higher incidence of late complications and consequently
      increased mortality rate (1,6,7) In the first years of type 1 diabetes, most patients are
      able to sense the characteristic symptoms of hypoglycemia, which can then be relieved by
      consuming appropriate food. The symptoms of hypoglycemia can roughly be classified as
      autonomic (warning) symptoms caused by the release of catecholamines, and neuroglycopenic
      symptoms caused by the lack of glucose in the brain. In many patients symptoms are often
      compromised at night (nocturnal asymptomatic hypoglycemia) due to impaired glucose
      counterregulatory response by adrenaline and glucagon. The chronic form of hypoglycemia
      unawareness is very common. A quarter of all insulin-treated diabetic patients have some
      degree of diminished symptomatic awareness, but this proportion increases to almost 50% in
      patients who have had diabetes for more than 20 years (8). Strict control of diabetes by
      intensive insulin therapy is associated with increased risk of the hypoglycemia unawareness
      syndrome with loss of autonomic warning symptoms (2,6,9). This seems to involve diminished
      hormonal glucose counterregulation due to recurrent hypoglycemic episodes (6,9).

      For these reasons, a number of studies have been carried out with the aim of developing
      automatic detection systems, which can warn the diabetic patients before blood glucose levels
      are reduced to the level at which severe neuroglycopenia develops, typically about 2.0-2.5
      mmol/l. Most studies have evaluated the potential of continuous glucose monitoring (CMG) to
      decrease the frequency of hypoglycemia. Although, smaller studies have reported a lower risk
      of hypoglycemia using CMG compared with conventional glucose measurements (10,11), larger
      multi-center studies have failed to reproduce these findings (11-14). This could be explained
      by a low accuracy in the low range of glucose values and delay in detection time during rapid
      changes using CMG (11,13,14). In fact, CMG only recognizes less than 50% of hypoglycemic
      events (15). Thus, even with a marginal improvement compared with conventional glucose
      measurements, CMG is far from the goal of completely avoiding severe hypoglycemic episodes.

      The EEG signal reflects the functional state and metabolism of the brain. The brain is almost
      totally dependent on a continuous supply of glucose, and when this is lower than the
      metabolic requirements of the brain, its function deteriorates. Indeed, neuroglycopenic
      hypoglycemia in insulin-treated diabetic patients is associated with characteristic changes
      in EEG with a decrease in alpha activity, an increase in delta activity, and in particular an
      increase in theta activity (16-19). These changes are clearly seen at ~2.0 mmol/l (16,17),
      but may be present already at higher glucose levels (~3.0 mmol/l), in particular in type 1
      diabetic patients with hypoglycemic unawareness (19,20). It has been shown that the most
      characteristic changes, the increase in theta activity, appears 19 min before severe
      cognitive impairment (20). This suggests a "window" between hypoglycemia-induced EEG changes
      and severe neuroglycepenia, which is an important prerequisite in developing an automatic
      detection system capable of warning the patient.

      A number of studies have characterized the changes in the EEG that results from hypoglycemia
      (16-20), but none have proposed a method of processing and testing in real-time. With a
      device, which can perform real-time monitoring and processing of EEG signals and
      automatically detect and warn the patient of hypoglycemia-induced EEG changes, it would be
      possible for the patient to avoid severe neuroglypenic symptoms e.g. by ingestion of
      carbohydrates. The construction of an EEG-based hypoglycemia alarm system must fulfill the
      following criteria. First, the device should be able to distinguish hypoglycemia-induced EEG
      changes from normal changes in EEG, noise and artifacts with high sensitivity and specificity
      using a mathematical algorithm that classifies the EEG in real-time. Second, these EEG
      changes should be observed in the majority of insulin-treated diabetic patients during
      hypoglycemia. Third, there should be a "window" between hypoglycemia-induced EEG changes and
      severe cognitive impairment. Moreover, the device should be fully compatible with normal
      everyday activities. Thus, the electrodes should be thin and implanted subcutaneously, and
      the monitoring and processing unit should be small, have sufficient battery power, and
      capable of communicating with a PDA or cell phone.
    

Study population: 
        Twenty adult patients with type 1 diabetes will be participating in the study.
      
Keywords: Hypoglycemia; EEG; type 1 diabetes; neuroglycopenia; Hypoglycemia is a potential dangerous condition; EEG is changed during hypoglycemia; A hypoglycemia alarm based on EEG-measures may prevent development of severe hypoglycemia