Decrease of vigilance assessed by EEG-mapping in type I diabetic patients with history of recurrent severe hypoglycaemia

Diabetes and associated cognitive disorders: Role of the Hypothalamic-Pituitary Adrenal axis

Both diabetes types, types 1 and 2, are associated with cognitive impairments. Each period of life is concerned, and this is an increasing public health problem. Animal models have been developed to investigate the biological actors involved in such impairments. Many levels of the brain function (structure, volume, neurogenesis, neurotransmission, behavior) are involved. In this review, we detailed the part potentially played by the Hypothalamic-Pituitary Adrenal axis in these dysfunctions. Notably, regulating glucocorticoid levels, their receptors and their bioavailability appear to be relevant for future research studies, and treatment development.

Central neuronal transmission in response to tonic cold pain is modulated in people with type 1 diabetes and severe polyneuropathy

AIMS

This study aimed to investigate cortical source activity and identify source generators in people with type 1 diabetes during rest and tonic cold pain.

METHODS

Forty-eight participants with type 1 diabetes and neuropathy, and 21 healthy controls were investigated with electroencephalography (EEG) during 5-minutes resting and 2-minutes tonic cold pain (immersing the hand into water at 2 °C). EEG power was assessed in eight frequency bands, and EEG source generators were analyzed using standardized low-resolution electromagnetic tomography (sLORETA).

RESULTS

Compared to resting EEG, cold pain EEG power differed in all bands in the diabetes group (all p < 0.001) and six bands in the controls (all p < 0.05). Source generator activity in the diabetes group was increased in delta, beta2, beta3, and gamma bands and decreased in alpha1 (all p < 0.006) with changes mainly seen in the frontal and limbic lobe. Compared to controls, people with diabetes had decreased source generator activity during cold pain in the beta2 and beta3 bands (all p < 0.05), mainly in the frontal lobe.

CONCLUSIONS

Participants with type 1 diabetes had altered EEG power and source generator activity predominantly in the frontal and limbic lobe during tonic cold pain. The results may indicate modulated central transmission and neuronal impairment.

The Effect of Hypoglycemia on Spectral Moments in EEG Epochs of Different Durations in Type 1 Diabetes Patients

The potential of using an electroencephalogram (EEG) to detect hypoglycemia in patients with type 1 diabetes (T1D) has been investigated in both time and frequency domains. Under hyperinsulinemic hypoglycemic clamp conditions, we have shown that the brain's response to hypoglycemic episodes could be described by the centroid frequency and spectral gyration radius evaluated from spectral moments of EEG signals. The aim of this paper is to investigate the effect of hypoglycemia on spectral moments in EEG epochs of different durations and to propose the optimal time window for hypoglycemia detection without using clamp protocols. The incidence of hypoglycemic episodes at night time in five T1D adolescents was analyzed from selected data of ten days of observations in this study. We found that hypoglycemia is associated with significant changes (P < 0.05) in spectral moments of EEG segments in different lengths. Specifically, the changes were more pronounced on the occipital lobe. We used effect size as a measure to determine the best EEG epoch duration for the detection of hypoglycemic episodes. Using Bayesian neural networks, this study showed that 30 second segments provide the best detection rate of hypoglycemia. In addition, Clarke's error grid analysis confirms the correlation between hypoglycemia and EEG spectral moments of this optimal time window, with 86% of clinically acceptable estimated blood glucose values. These results confirm the potential of using EEG spectral moments to detect the occurrence of hypoglycemia.

On the physiology of cognitive decline in type 1 diabetes

OBJECTIVES

Type 1 diabetes mellitus (T1DM) may be associated with cognitive impairment and notably a decline in psychomotor speed, information processing speed and attention. The mechanism for this decline is uncertain. Previous studies by our group and others have demonstrated a decline in EEG-power and event-related potential amplitude in T1DM. The objectives of the present study were to explore whether 1) the association between event-related potential (N100) amplitude and psychomotor speed is different between T1DM and healthy subjects, and 2) the decline in N100 amplitude depends on duration of diabetes.

METHODS

Patients with T1DM (N = 204) and healthy control subjects (N = 358) were included in a cross-sectional study. Event-related brain potentials were recorded with auditory reaction tasks. Psychomotor speed was evaluated with the Grooved Pegboard test in a subset of the patients (N = 70) and the healthy control subjects (N = 89).

RESULTS

Patients with T1DM had a decrease in the N100 amplitude that correlated with a decline in psychomotor speed, longer duration of diabetes and increasing age. In healthy controls, the N100 amplitude did not decrease with age and the association between psychomotor speed and N100 amplitude was absent.

CONCLUSION

The association between psychomotor speed and N100 amplitude is likely to be a specific trait for T1DM since it was not found in healthy controls and was dependent on diabetes duration. Our findings indicate that the pathogenesis of cognitive decline in T1DM may involve a disease-related factor with a long-term influence on the N100 amplitude.

Type-1 diabetes shapes working memory processing strategies

BACKGROUND

Type 1 diabetes (T1D) is a metabolic disorder characterized by recurrent hypo- and hyperglycemic episodes, whose clinical development has been associated with cognitive and working memory (WM) deficits.

OBJECTIVE

To contrast quantitative electroencephalography (qEEG) measures between young patients with T1D and healthy controls while performing a visuospatial WM task with two memory load levels and facial emotional stimuli.

METHODS

Four or five neutral or happy faces were sequentially and pseudo-randomly presented in different spatial locations, followed by subsequent sequences displaying the reversed spatial order or any other. Participants were instructed to discriminate between these two alternatives during EEG recording.

RESULTS

A significant increase in the absolute power of the delta and theta bands, distributed mainly over the frontal region was found during task execution, with a slight decrease of alpha band power in both groups but mainly in control individuals. However, these changes were more pronounced in the T1D patients, and reached their maximum level during the WM encoding phase, even on trials with the lower memory load. In contrast, changes seemed to occur more gradually in controls and results differed significantly only on the trials with the higher WM load.

CONCLUSIONS

These results reflect adaptive WM-processing mechanisms in which cognitive strategies have evolved in T1D patients in order to meet task demands.

Cognitive, neurophysiologic and metabolic sequelae of previous hypoglycemic coma revealed by hyperinsulinemic-hypoglycemic clamp in type 1 diabetic patients

To examine the relationship between electroencephalographic (EEG) activity and hypoglycemia unawareness, we investigated early parameters of vigilance and awareness of various symptom categories in response to hypoglycemia in intensively treated type 1 diabetic (T1DM) patients with different degrees of hypoglycemia unawareness. Hypoglycemia was induced with a hyperinsulinemic-hypoglycemic clamp in six T1DM patients with a history of hypoglycemia unawareness previous severe hypoglycemic coma (SH) and in six T1DM patients without (C) history of hypoglycemia unawareness previous severe hypoglycemic coma. Cognitive function tests (four choice reaction time), counterregulatory responses (adrenaline), and symptomatic responses were evaluated at euglycemia (90 mg/dl) and during step-wise plasma glucose reduction (68, 58 and 49 mg/dl). EEG activity was recorded continuously throughout the study and analyzed by spectral analysis. Cognitive function deteriorated significantly at a glucose threshold of 55 ± 1 mg/dl in both groups (p = ns) during hypoglycemia, while the glucose threshold for autonomic symptoms was significantly lower in SH patients than in C patients (49 ± 1 vs. 54 ± 1 mg/dl, p < 0.05, respectively). In SH patients, eye-closed resting EEG showed a correlation between the mean dominance frequency and plasma glucose (r = 0.62, p < 0.001). Theta relative power increased during controlled hypoglycemia compared to euglycemia (21.6 ± 6 vs. 15.5 ± 3% Hz p < 0.05) and was higher than in the C group (21.6 ± 6 vs. 13.8 ± 3%, p < 0.03). The cognitive task beta activity was lower in the SH group than in the C group (14.8 ± 3 Hz, vs. 22.6 ± 4 vs. p < 0.03). Controlled hypoglycemia elicits cognitive dysfunction in both C and SH patients; however, significant EEG alterations during hypoglycemia were detected mainly in patients with a history of hypoglycemia unawareness and previous severe hypoglycemic coma. These data suggest that prior episodes of hypoglycemic coma modulate brain electric activity.

Hyperglycemia is associated with simultaneous alterations in electrical brain activity in youths with type 1 diabetes mellitus

OBJECTIVE

To assess the association between hyperglycemia and electrical brain activity in type 1 diabetes mellitus (T1DM).

METHODS

Nine youths with T1DM were monitored simultaneously and continuously by EEG and continuous glucose monitor system, for 40 h. EEG powers of 0.5-80 Hz frequency bands in all the different brain regions were analyzed according to interstitial glucose concentration (IGC) ranges of 4-11 mmol/l, 11-15.5 mmol/l and >15.5 mmol/l. Analysis of variance was used to examine the differences in EEG power of each frequency band between the subgroups of IGC. Analysis was performed separately during wakefulness and sleep, controlling for age, gender and HbA1c.

RESULTS

Mean IGC was 11.49 ± 5.26 mmol/l in 1253 combined measurements. IGC>15.5 mmol/l compared to 4-11 mmol/l was associated during wakefulness with increased EEG power of low frequencies and with decreased EEG power of high frequencies. During sleep, it was associated with increased EEG power of low frequencies in all brain areas and of high frequencies in frontal and central areas.

CONCLUSIONS

Asymptomatic transient hyperglycemia in youth with T1DM is associated with simultaneous alterations in electrical brain activity during wakefulness and sleep.

SIGNIFICANCE

The clinical implications of immediate electrical brain alterations under hyperglycemia need to be studied and may lead to adaptations of management.

Type 1 diabetes-associated cognitive decline: a meta-analysis and update of the current literature

BACKGROUND

Type 1 diabetes (T1D) can have a significant impact on brain structure and function, which is referred to as T1D-associated cognitive decline (T1DACD). Diabetes duration, early onset disease, and diabetes-associated complications are all proposed as factors contributing to T1DACD. However, there have been no comparisons in T1DACD between children and adults with T1D. To obtain a better insight into the occurrence and effects of T1DACD in T1D, the aim of the present meta-analysis was to investigate differences between children and adults and to analyse factors contributing T1DACD.

METHODS

Two electronic databases were consulted: PubMed and ISI Web of Knowledge. Literature published up until the end of 2013 was included in the analysis. Effect sizes (Cohen's d), which are standardized differences between experimental and control groups, were calculated.

RESULTS

There was a small to modest decrease in cognitive performance in T1D patients compared with non-diabetic controls. Children with T1D performed worse while testing for executive function, full intelligence quotient (IQ), and motor speed, whereas adults with T1D performed worse while testing the full, verbal and performance IQ, part of the executive function, memory, spatial memory, and motor speed. Episodes of severe hypoglycemia, chronic hyperglycemia, and age of onset can be significant factors influencing cognitive function in T1D.

CONCLUSIONS

The findings in the literature suggest that T1DACD is more severe in adults than children, indicating that age and diabetes duration contribute to this T1DACD.

Severe hypoglycemia in a juvenile diabetic rat model: presence and severity of seizures are associated with mortality

It is well accepted that insulin-induced hypoglycemia can result in seizures. However, the effects of the seizures, as well as possible treatment strategies, have yet to be elucidated, particularly in juvenile or insulin-dependent diabetes mellitus (IDDM). Here we establish a model of diabetes in young rats, to examine the consequences of severe hypoglycemia in this age group; particularly seizures and mortality. Diabetes was induced in post-weaned 22-day-old Sprague-Dawley rats by streptozotocin (STZ) administered intraperitoneally (IP). Insulin IP (15 U/kg), in rats fasted (14-16 hours), induced hypoglycemia, defined as <3.5 mM blood glucose (BG), in 68% of diabetic (STZ) and 86% of control rats (CON). Seizures occurred in 86% of STZ and all CON rats that reached hypoglycemic levels with mortality only occurring post-seizure. The fasting BG levels were significantly higher in STZ (12.4 ± 1.3 mM) than in CON rodents (6.3 ± 0.3 mM), resulting in earlier onset of hypoglycemia and seizures in the CON group. However, the BG at seizure onset was statistically similar between STZ (1.8 ± 0.2 mM) and CON animals (1.6 ± 0.1 mM) as well as between those that survived (S+S) and those that died (S+M) post-seizure. Despite this, the S+M group underwent a significantly greater number of seizure events than the S+S group. 25% glucose administered at seizure onset and repeated with recurrent seizures was not sufficient to mitigate these continued convulsions. Combining glucose with diazepam and phenytoin significantly decreased post-treatment seizures, but not mortality. Intracranial electroencephalograms (EEGs) were recorded in 10 CON and 9 STZ animals. Predictive EEG changes were not observed in these animals that underwent seizures. Fluorojade staining revealed damaged cells in non-seizing STZ animals and in STZ and CON animals post-seizure. In summary, this model of hypoglycemia and seizures in juvenile diabetic rats provides a paradigm for further study of underlying mechanisms. Our data demonstrate that severe hypoglycemia (<2.0 mM) is a necessary precondition for seizures, and the increased frequency of these seizures is associated with mortality.

Analyzing EEG signals under insulin-induced hypoglycemia in type 1 diabetes patients

Hypoglycemia is dangerous and considered as a limiting factor of the glycemic control therapy for patients with type 1 diabetes mellitus (T1DM). Nocturnal hypoglycemia is especially feared because early warning symptoms are unclear during sleep so an episode of hypoglycemia may lead to a fatal effect on patients. The main objective of this paper is to explore the correlation between hypoglycemia and electroencephalography (EEG) signals. To do this, the EEG of five T1DM adolescents from an overnight insulin-induced study is analyzed by spectral analysis to extract four different parameters. We aim to explore the response of these parameters during the clamp study which includes three main phases of normal, hypoglycemia and recovery. We also look at data at the blood glucose level (BGL) of 3.3-3.9 mmol/l to find a threshold to distinguish between non-hypoglycemia and hypoglycemia states. The results show that extracted EEG parameters are highly correlated with patients' conditions during the study. It is also shown that at the BGL of 3.3 mmol/l, responses to hypoglycemia in EEG signals start to significantly occur.

A review of electroencephalographic changes in diabetes mellitus in relation to major depressive disorder

A bidirectional relationship exists between diabetes mellitus (DM) and major depressive disorder (MDD), with depression commonly reported in both type 1 DM (T1DM) and type 2 DM (T2DM), and depressive symptoms associated with a higher incidence of diabetes. However, how the two conditions are pathologically connected is not completely understood. Similar neurophysiological abnormalities have been reported in both DM and MDD, including elevated electroencephalographic (EEG) activity in low-frequency slow waves and increased latency and/or reduced amplitude of event-related potentials. It is possible that this association reflects some common underlying pathology, and it has been proposed that diabetes may place patients at risk for depression through a biological mechanism linking the metabolic changes of DM to changes in the central nervous system. In this review we will discuss EEG abnormalities in DM, as well as the biological mechanisms underlying various EEG parameters, in order to evaluate whether or not a common EEG biosignature exists between DM and MDD. Identifying such commonalities could significantly inform the current understanding of the mechanisms that subserve the development of the two conditions. Moreover, this new insight may provide the basis for informing new drug discovery capable of mitigating and possibly even preventing both conditions.

Quantitative EEG in type 1 diabetic adults with childhood exposure to severe hypoglycaemia: a 16 year follow-up study

AIMS/HYPOTHESIS

In diabetic children and adolescents, a history of severe hypoglycaemia (SH) has been associated with increased slow EEG activity and reduced cognition, possibly due to harmful effects of SH on the developing brain. In a group of type 1 diabetic patients with early exposure to SH, who had EEG abnormalities and reduced cognition in childhood, we have recently demonstrated that the reduced cognition may persist into adulthood. We have now assessed whether the reduced cognition was accompanied by lasting EEG abnormalities.

METHODS

In 1992-1993, we studied EEG and cognition in 28 diabetic children and 28 matched controls. 16 years later, we re-investigated the same participants, with 96% participation rate. Diabetic participants were classified as with (n = 9) or without (n = 18) early SH, defined as episodes with convulsions or loss of consciousness by 10 years of age. For each EEG band (delta, theta, alpha and beta) and cerebral region (frontocentral, temporal, and parietooccipital), we calculated relative amplitudes and amplitude asymmetry. We also calculated occipital alpha mean frequency, alpha peak frequency at maximum amplitude, alpha peak width, and theta regional mean frequencies. We examined whether these EEG measures, relative to age- and sex-matched controls, differed between diabetic participants with and without early SH.

RESULTS

We found no association of early SH with any of the EEG measures.

CONCLUSIONS/INTERPRETATION

Childhood SH was not associated with EEG abnormalities in young type 1 diabetic adults. Our findings suggest that the reduced adulthood cognition associated with childhood exposure to SH is not accompanied by lasting EEG abnormalities.

Decreased cortical connectivity and information flow in type 1 diabetes

OBJECTIVE

To investigate the effect of type 1 diabetes on EEG connectivity and information flow and study the relationship between these parameters and electrophysiological, neuropsychological and clinical variables.

METHODS

Connectivity was assessed using several measures (phase coherence, phase lag index, synchronization likelihood and phase slope index) on 119 patients and 61 healthy controls over several frequency bands (between 0.5 and 45 Hz). Data was further correlated to EEG power, event related potentials, neuropsychological function and demographic variables.

RESULTS

Multivariate test on the connectivity data showed a difference between patients and controls both with mastoid reference (p<0.01) and current source density estimates (p<0.04). Connectivity and information flow correlated with EEG power but not with event related potentials or neuropsychological function.

CONCLUSIONS

Connectivity and information flow are decreased in diabetes. These variables assess other functions of the brain than captured by the present cognitive tests. Several tests need to be performed in order to monitor the effect of diabetes on brain function.

SIGNIFICANCE

The decrease in connectivity and cortical information flow are EEG abnormalities that add to the previously described EEG and ERP abnormalities described for type 1 diabetes.

Detection of nocturnal hypoglycemic episodes using EEG signals

Hypoglycemia (low blood glucose) or the fear of hypoglycemia constitutes a significant barrier to the achievement of good glycemic control in the insulin treated diabetic patients. By measuring physiological responses derived from EEG and analyzing these, we establish that hypoglycemia can be detected non-invasively. From a clinical study of six children with type 1 diabetes (T1D), associated with hypoglycemic episodes at night, their centroid (centre of gravity) alpha frequency reduced significantly (P〈0.001) and their centroid theta frequency increased significantly (P〈0.02). The overall data were organized into a training set (3 patients) and a test set (another 3 patients) randomly selected. Using the optimal Bayesian neural network which was derived from the training set with the highest log evidence, the estimated blood glucose profiles produced a significant correlation (P〈0.005) against measured values in the test set.

High connectivity between reduced cortical thickness and disrupted white matter tracts in long-standing type 1 diabetes

OBJECTIVE

Previous studies have observed disruptions in brain white and gray matter structure in individuals with type 1 diabetes, and these structural differences have been associated with neurocognitive testing deficiencies. This study investigated the relationship between cerebral cortical thickness reductions and white matter microstructural integrity loss in a group of patients with type 1 diabetes and in healthy control subjects using diffusion tensor imaging (DTI).

RESEARCH DESIGN AND METHODS

Twenty-five subjects with type 1 diabetes for at least 15 years and 25 age- and sex-matched control subjects underwent structural T1 and proton-density and DTI on a 3.0 Tesla scanner. Fractional anisotropy measurements were made on major cerebral white matter tracts, and DTI tractography was performed to identify cortical regions with high connectivity to these tracts.

RESULTS

Posterior white matter tracts with reduced fractional anisotropy (optic radiations, posterior corona radiata, and the splenium region of the corpus callosum) were found to have high connectivity with a number of posterior cortical regions, including the cuneus, precuneus, fusiform, and posterior parietal cortical regions. A significant reduction in cortical thickness in the diabetic group was observed in the regions with high connectivity to the optic radiations and posterior corona radiata tracts (P < 0.05).

CONCLUSIONS

The direct relationship between white and gray matter structural pathology has not been previously demonstrated in subjects with long-standing type 1 diabetes. The relationship between posterior white matter microstructural integrity disruption and lower cortical thickness demonstrated using a novel DTI connectivity technique suggests a common or interrelated pathophysiological mechanism in type 1 diabetes.

Automated detection of hypoglycemia-induced EEG changes recorded by subcutaneous electrodes in subjects with type 1 diabetes--the brain as a biosensor

AIMS

Hypoglycemia unawareness is a common condition associated with increased risk of severe hypoglycemia. We test the hypothesis that specific changes in the electroencephalogram (EEG) during hypoglycemia can be recorded by subcutaneous electrodes and processed by a general mathematical algorithm, and that hypoglycemia associated EEG changes appear before the development of severe hypoglycemia.

METHODS

Fifteen patients with type 1 diabetes were exposed to insulin-induced hypoglycemia and EEG was recorded. The cognitive function was evaluated by repeated cognitive testing. Insulin infusion was terminated when plasma glucose reached 1.8mmol/l or when the subjects showed obvious signs of cognitive dysfunction. EEG was analyzed by an automated mathematical algorithm with a predefined threshold of hypoglycemia.

RESULTS

Hypoglycemia associated EEG changes were detected by the mathematical algorithm in all subjects. Plasma glucose at the time of EEG changes above the threshold value ranged from 2.0 to 3.4mmol/l and occurred 29+/-28min (range 3-113min) before termination of insulin infusion.

CONCLUSIONS

Hypoglycemia associated EEG changes could be detected by an automated mathematical algorithm in all subjects exposed to insulin-induced hypoglycemia. In 12 of 15 patients, EEG changes occurred before severe hypoglycemia as evaluated by the cognitive testing.

Cognitive dysfunction and diabetes mellitus

The deleterious effects of diabetes mellitus on the retinal, renal, cardiovascular, and peripheral nervous systems are widely acknowledged. Less attention has been given to the effect of diabetes on cognitive function. Both type 1 and type 2 diabetes mellitus have been associated with reduced performance on numerous domains of cognitive function. The exact pathophysiology of cognitive dysfunction in diabetes is not completely understood, but it is likely that hyperglycemia, vascular disease, hypoglycemia, and insulin resistance play significant roles. Modalities to study the effect of diabetes on the brain have evolved over the years, including neurocognitive testing, evoked response potentials, and magnetic resonance imaging. Although much insightful research has examined cognitive dysfunction in patients with diabetes, more needs to be understood about the mechanisms and natural history of this complication in order to develop strategies for prevention and treatment.

Cognitive dysfunction and diabetes mellitus

The deleterious effects of diabetes mellitus on the retinal, renal, cardiovascular, and peripheral nervous systems are widely acknowledged. Less attention has been given to the effect of diabetes on cognitive function. Both type 1 and type 2 diabetes mellitus have been associated with reduced performance on numerous domains of cognitive function. The exact pathophysiology of cognitive dysfunction in diabetes is not completely understood, but it is likely that hyperglycemia, vascular disease, hypoglycemia, and insulin resistance play significant roles. Modalities to study the effect of diabetes on the brain have evolved over the years, including neurocognitive testing, evoked response potentials, and magnetic resonance imaging. Although much insightful research has examined cognitive dysfunction in patients with diabetes, more needs to be understood about the mechanisms and natural history of this complication in order to develop strategies for prevention and treatment.

The human EEG--physiological and clinical studies

The present review summarizes the research in EEG performed by our group during the last 5 years. Our studies have been focussed on two areas: studies of variability and correlations in the oscillations during resting conditions of normal subjects, and the abnormalities related to type 1 diabetes. Recordings in normal subjects showed that also under standardized conditions with regular cycles of closed and open eyes, there is a temporal variability of the spectral components in EEG that necessitates samples>124 s in order to achieve estimates of alpha power with a coefficient of variation<0.1 in all recording channels (brain regions). The temporal variability in alpha and beta power demonstrates long-range temporal correlations, i.e., periods of large power (alpha or beta) are more likely to be followed by large power, and vice versa. The long-range temporal correlations were reproducible, especially during the closed-eyes condition, stronger in males than females, and not age dependent. In patients with type 1 diabetes, the alpha and beta power components were both decreased with similar nadirs in the posterior temporal regions, and the slow spectral components were increased in the frontal regions. The cognitive function was presently not studied but in a group of adolescents with diabetes we found a correlation between the presence of slow activity and the number of hypoglycaemic episodes. The loss of alpha and beta power was highly correlated which initiated a study of the normal alpha-beta correlation. A significant 1:2 phase synchronization was present between alpha and beta oscillations with a phase lag of about pi/2 in all electrode derivations. The strong frequency relationship between the resting beta and alpha oscillations suggested that they are generated by a common mechanism.

EEG abnormalities with and without relation to severe hypoglycaemia in adolescents with type 1 diabetes

AIMS/HYPOTHESIS

The aim of the present study was to identify whether adolescents with type 1 diabetes receiving modern multiple insulin injection therapy (MIT) have abnormal EEGs, and to elucidate possible correlations with a history of severe hypoglycaemia, poor metabolic control and nerve conduction defects.

METHODS

We investigated 35 patients (age 14-19 years) with disease duration 7.6+/-4.6 years, and 45 healthy control subjects. EEG spectral components were obtained from 15-min recordings in resting, awake subjects. Nerve conduction was measured bilaterally in motor and sensory fibres in the median, peroneal and sural nerves.

RESULTS

The EEGs of patients showed an increase in slow activity (delta and theta) and a reduction in alpha peak frequency, both of which were most pronounced in the frontal regions (p<0.001). They also showed a decrease in fast activity, which was most pronounced bilaterally in the posterior temporal regions (alpha p<0.001, beta p<0.01, gamma p<0.001). A history of severe hypoglycaemia was correlated with a global increase in theta activity (p<0.01-0.05). Poor metabolic control, measured as acute and long-term HbA1c levels, was correlated with an increase in delta activity and a decrease in alpha peak frequency. The decrease in fast activity in the temporal regions was a separate type of abnormality because it had a different distribution, and was not correlated with the increase in delta/theta power, poor metabolic control or with hypoglycaemia.

CONCLUSIONS/INTERPRETATION

Recurrent severe hypoglycaemia and poor metabolic control are risk factors for EEG abnormalities in adolescents with type 1 diabetes receiving MIT treatment. In addition, we found pronounced abnormalities in the temporal regions that were not related to these risk factors.

The effects of type 1 diabetes on cognitive performance: a meta-analysis

OBJECTIVE

To investigate the exact nature and magnitude of cognitive impairments in patients with type 1 diabetes and the possible association with other disease variables, such as recurrent episodes of hypoglycemia and metabolic control.

RESEARCH DESIGN AND METHODS

MedLine and PsycLit search engines were used to identify studies on cognitive performance in patients with type 1 diabetes. Effect sizes (Cohen's d), which are the standardized differences between the experimental and the control group, were calculated. In the meta-analysis, a combined d value was calculated, expressing the magnitude of associations across studies.

RESULTS

A total of 33 studies were identified that met the inclusion criteria. Compared with nondiabetic control subjects, the type 1 diabetic group demonstrated a significantly lowered performance on the following cognitive domains: intelligence (d = -0.7), speed of information processing (d = -0.3), psychomotor efficiency (d = -0.6), visual (d = -0.4) and sustained attention (d = -0.3), cognitive flexibility (d = -0.5), and visual perception (d = -0.4). Lowered cognitive performance in diabetic patients appeared to be associated with the presence of microvascular complications but not with the occurrence of severe hypoglycemic episodes or with poor metabolic control.

CONCLUSIONS

In patients with type 1 diabetes, cognitive dysfunction is characterized by a slowing of mental speed and a diminished mental flexibility, whereas learning and memory are spared.The magnitude of the cognitive deficits is mild to moderate, but even mild forms of cognitive dysfunction might hamper everyday activities since they can be expected to present problems in more demanding situations.

Cerebral dysfunction in type 1 diabetes: effects of insulin, vascular risk factors and blood-glucose levels

Type 1 diabetes can lead to several well-described complications such as retinopathy, nephropathy and peripheral neuropathy. Evidence is accumulating that it is also associated with gradually developing end-organ damage in the central nervous system. This relatively unknown complication can be referred to as "diabetic encephalopathy" and is characterised by electrophysiological and neuroradiological changes, such as delayed latencies of evoked potentials, modest cerebral atrophy and (periventricular) white matter lesions. Furthermore, individuals with type 1 diabetes may show performance deficits in a wide range of cognitive domains. The exact mechanisms underlying this diabetic encephalopathy are only partially known. Chronic metabolic and vascular changes appear to play an important role. Interestingly, the differences in the "cognitive profile" between type 1 and type 2 diabetes also suggest a critical role for disturbances of insulin action in the central nervous system.

Loss of temporal lobe beta power in young adults with type 1 diabetes mellitus

Cognitive defects have been reported in type 1 diabetes mellitus with possible correlation to recurrent episodes of hypoglycemia. The purpose of the present study was to identify signs of brain dysfunction with quantitative EEG in adults with insulin-dependent (type 1) diabetes. Patients (n = 49) with type 1 diabetes and controls (n = 51) were recruited. All patients had good glycemic control, no diabetic polyneuropathy and a minor history of severe hypoglycaemia. EEG was recorded for 15 min following a standardized protocol, power spectra were obtained from 236-584 s of artefact-free EEG from each subject and EEG was repeated in diabetic patients after 3 and 9 months. The most pronounced finding was a loss of fast oscillations (alpha, beta and gamma activity) in both posterior temporal regions, with p< 0.001 for beta and p< 0.05 or 0.01 for alpha and gamma activity in the diabetes patients. A decrease in beta activity was also present bilaterally in the anterior temporal and occipital regions (p< 0.05 or 0.01). The alpha peak frequency was lower in patients than in controls, with reductions bilaterally in the temporo-central regions (p< 0.01). These changes were not found to correlate to a previous history of hypoglycaemia. The alpha and beta power showed a high test-retest reliability at both 3 and 9 months (0.88-0.92). The focal decrease in temporal lobe fast activity suggests that these brain regions are preferentially affected by type 1 diabetes. This abnormality may be related to the mechanism underlying the cognitive dysfunction described in diabetes.

Neuropsychological functioning in older people with type 2 diabetes: the effect of controlling for confounding factors

AIMS AND METHODS

Neuropsychological functioning was examined in a group of 33 older (mean age 62.40 +/- 9.62 years) people with Type 2 diabetes (Group 1) and 33 non-diabetic participants matched with Group 1 on age, sex, premorbid intelligence and presence of hypertension and cardio/cerebrovascular conditions (Group 2).

RESULTS

Data statistically corrected for confounding factors obtained from the diabetic group were compared with the matched control group. The results suggested small cognitive deficits in diabetic people's verbal memory and mental flexibility (Logical Memory A and SS7). No differences were seen between the two samples in simple and complex visuomotor attention, sustained complex visual attention, attention efficiency, mental double tracking, implicit memory, and self-reported memory problems.

CONCLUSIONS

These findings indicate minimal cognitive impairment in relatively uncomplicated Type 2 diabetes and demonstrate the importance of control and matching for confounding factors.