The near-normalization of glycemic control has become an established treatment goal in diabetes in order to reduce the risk of late complications such as nephropathy, neuropathy, retinopathy and cardiovascular disease (1). However, the frequency of insulin-induced hypoglycaemia increases several-fold during intensified insulin therapy (2;3) and hypoglycaemia is the most common acute complication in insulin-treated diabetes. The fear of hypoglycaemia discourages diabetic subjects from the attempt to maintain tight glycemic control, which in turn leads to increased diabetes related morbidity and mortality (4;5). Symptoms of hypoglycaemia can be classified as autonomic (warning) symptoms caused by the release of catecholamines and neuroglycopenic symptoms caused by the lack of glucose supply to the brain. Symptoms of hypoglycaemia may be compromised at night-time (nocturnal asymptomatic hypoglycaemia) due to impaired glucose counterregulatory response by adrenaline and glucagon. Some 25% of patients with type 1 diabetes suffer from unawareness in various degrees increasing with long diabetes duration and tight glycemic control (4;6;7).~Several studies have evaluated the potential use of continuous glucose monitoring system (CGMS) as hypoglycaemia alarms but so far failed to show reduction in the frequency of severe hypoglycaemia (8;9). Although the technology is continuously being improved it is still associated with a number of problems (10). The technique is rather imprecise, particularly in the lower range of glucose measurements, and only about 33% of hypoglycemic events were detected in a larger clinical trial (11). The accuracy of the reading is reduced when rapid changes in blood glucose occur (12). There is a significant and variable delay from the change in blood glucose to the change in the interstitial compartment ranging from 4 - 10 minutes (13) and the catheters are rather costly and must be replaced every 72 hours.~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 the glucose level is lower than the metabolic requirements of the brain, its function deteriorates. Neuroglycopenic hypoglycaemia in insulin-treated diabetic patients is associated with characteristic changes in EEG with a decrease in alpha activity and an increase in delta and theta activity (14-17). These changes are clearly seen at blood glucose ~2.0mmol/l (14;15) preceding the development of severe cognitive dysfunction (18). We have recently demonstrated that hypoglycaemia-associated EEG-changes can be recorded from subcutaneously placed electrodes using an automated mathematical algorithm based on non-linear spectral analysis and that EEG-changes above a predefined threshold can be demonstrated more than 10 minutes before development of severe hypoglycaemia in the majority of the patients (19). We found a very low rate of false alarms and no adverse reactions related to implantation of the electrodes. We have subsequently performed a number of studies with real-time alarms type 1 diabetes patients exposed to insulin induced hypoglycaemia. In these studies the patients were instructed to ingest carbohydrates when he/she heard the alarm sound. In three out of four cases the patients were able to do so, while a fourth patient did not spontaneously ingest the meal although, he was fully conscious and not clinically affect by the hypoglycaemia. These findings hold promises that an alarm, given at the time of EEG-changes, can help the patients to avoid severe hypoglycaemia by ingestion of carbohydrate.~For clinical applicability the device should be able to distinguish hypoglycaemia-induced EEG changes from noise, artefacts and physiological variations in the EEG including the low-frequency waves seen during sleep, with high sensitivity and specificity using a mathematical algorithm that classifies the EEG in real-time. There should be a time-window between hypoglycaemia-induced EEG changes and severe cognitive impairment. The device should be fully compatible with normal everyday activities. Thus, the device should be small, fully biocompatible and implantable, and the monitoring and processing unit should be small and have sufficient battery power.~This is the first larger scale trial testing the clinical applicability of a hypoglycaemia-alarm based on real-time analysis of EEG-signals.
Hypoglycaemia is the most common acute complication in insulin-treated diabetes. The fear of hypoglycaemia discourages diabetic subjects from the attempt to maintain tight glycemic control, which in turn leads to increased diabetes related morbidity and mortality.~Neuroglycopenic hypoglycaemia in insulin-treated diabetic patients is associated with characteristic changes in EEG with a decrease in alpha activity and an increase in delta and theta activity. We have recently demonstrated that hypoglycaemia-associated EEG-changes can be recorded from subcutaneously placed electrodes using an automated mathematical algorithm based on non-linear spectral analysis. Experimental findings hold promises that an alarm, given at the time of EEG-changes, can help the patients to avoid severe hypoglycaemia by ingestion of carbohydrate.~This is the first larger scale trial testing the clinical applicability of a hypoglycaemia-alarm based on real-time analysis of EEG-signals.