Hypoglycemia-associated changes in the electroencephalogram in patients with type 1 diabetes and normal hypoglycemia awareness or unawareness

Rhythmic high-amplitude delta with superimposed spikes (RHADS): a treatment dilemma

Pathognomonic EEG patterns have been described in genetic conditions such as Angelman and Rett syndromes. EEG patterns along the ictal-interictal continuum have been increasingly recognized with the greater availability of continuous EEG monitoring; however, treatment decisions may be difficult with unpredictable clinical implications. Rhythmic High-Amplitude Delta Activity with Superimposed (Poly) Spikes (RHADS) has been described as a particular EEG pattern in POLG1 Alpers Syndrome. The balance between treating subclinical seizures and managing encephalopathy in these patients is challenging.

Electroencephalographic Measures of Delirium in the Perioperative Setting: A Systematic Review

Postoperative delirium (POD) is frequent in older adults and is associated with adverse cognitive and functional outcomes. In the last several decades, there has been an increased interest in exploring tools that easily allow the early recognition of patients at risk of developing POD. The electroencephalogram (EEG) is a widely available tool used to understand delirium pathophysiology, and its use in the perioperative setting has grown exponentially, particularly to predict and detect POD. We performed a systematic review to investigate the use of EEG in the pre-, intra-, and postoperative settings. We identified 371 studies, and 56 met the inclusion criteria. A range of techniques was used to obtain EEG data, from limited 1-4 channel setups to complex 256-channel systems. Power spectra were often measured preoperatively, yet the outcomes were inconsistent. During surgery, the emphasis was primarily on burst suppression (BS) metrics and power spectra, with a link between the frequency and timing of BS, and POD. The EEG patterns observed in POD aligned with those noted in delirium in different contexts, suggesting a reduction in EEG activity. Further research is required to investigate preoperative EEG indicators that may predict susceptibility to delirium.

Metabolic effect of adrenaline infusion in people with type 1 diabetes and healthy individuals

AIMS/HYPOTHESIS

As a result of early loss of the glucagon response, adrenaline is the primary counter-regulatory hormone in type 1 diabetes. Diminished adrenaline responses to hypoglycaemia due to counter-regulatory failure are common in type 1 diabetes, and are probably induced by exposure to recurrent hypoglycaemia, however, the metabolic effects of adrenaline have received less research attention, and also there is conflicting evidence regarding adrenaline sensitivity in type 1 diabetes. Thus, we aimed to investigate the metabolic response to adrenaline and explore whether it is modified by prior exposure to hypoglycaemia.

METHODS

Eighteen participants with type 1 diabetes and nine healthy participants underwent a three-step ascending adrenaline infusion during a hyperinsulinaemic-euglycaemic clamp. Continuous glucose monitoring data obtained during the week before the study day were used to assess the extent of hypoglycaemia exposure.

RESULTS

While glucose responses during the clamp were similar between people with type 1 diabetes and healthy participants, plasma concentrations of NEFAs and glycerol only increased in the group with type 1 diabetes (p<0.001). Metabolomics revealed an increase in the most common NEFAs (p<0.01). Other metabolic responses were generally similar between participants with type 1 diabetes and healthy participants. Exposure to hypoglycaemia was negatively associated with the NEFA response; however, this was not statistically significant.

CONCLUSIONS/INTERPRETATION

In conclusion, individuals with type 1 diabetes respond with increased lipolysis to adrenaline compared with healthy participants by mobilising the abundant NEFAs in plasma, whereas other metabolic responses were similar. This may suggest that the metabolic sensitivity to adrenaline is altered in a pathway-specific manner in type 1 diabetes.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05095259.

Counterregulatory hormone and symptom responses to hypoglycaemia in people with type 1 diabetes, insulin-treated type 2 diabetes or without diabetes: the Hypo-RESOLVE hypoglycaemic clamp study

AIM

The sympathetic nervous and hormonal counterregulatory responses to hypoglycaemia differ between people with type 1 and type 2 diabetes and may change along the course of diabetes, but have not been directly compared. We aimed to compare counterregulatory hormone and symptom responses to hypoglycaemia between people with type 1 diabetes, insulin-treated type 2 diabetes and controls without diabetes, using a standardised hyperinsulinaemic-hypoglycaemic clamp.

MATERIALS

We included 47 people with type 1 diabetes, 15 with insulin-treated type 2 diabetes, and 32 controls without diabetes. Controls were matched according to age and sex to the people with type 1 diabetes or with type 2 diabetes. All participants underwent a hyperinsulinaemic-euglycaemic-(5.2 ± 0.4 mmol/L)-hypoglycaemic-(2.8 ± 0.13 mmol/L)-clamp.

RESULTS

The glucagon response was lower in people with type 1 diabetes (9.4 ± 0.8 pmol/L, 8.0 [7.0-10.0]) compared to type 2 diabetes (23.7 ± 3.7 pmol/L, 18.0 [12.0-28.0], p < 0.001) and controls (30.6 ± 4.7, 25.5 [17.8-35.8] pmol/L, p < 0.001). The adrenaline response was lower in type 1 diabetes (1.7 ± 0.2, 1.6 [1.3-5.2] nmol/L) compared to type 2 diabetes (3.4 ± 0.7, 2.6 [1.3-5.2] nmol/L, p = 0.001) and controls (2.7 ± 0.4, 2.8 [1.4-3.9] nmol/L, p = 0.012). Growth hormone was lower in people with type 2 diabetes than in type 1 diabetes, at baseline (3.4 ± 1.6 vs 7.7 ± 1.3 mU/L, p = 0.042) and during hypoglycaemia (24.7 ± 7.1 vs 62.4 ± 5.8 mU/L, p = 0.001). People with 1 diabetes had lower overall symptom responses than people with type 2 diabetes (45.3 ± 2.7 vs 58.7 ± 6.4, p = 0.018), driven by a lower neuroglycopenic score (27.4 ± 1.8 vs 36.7 ± 4.2, p = 0.012).

CONCLUSION

Acute counterregulatory hormone and symptom responses to experimental hypoglycaemia are lower in people with type 1 diabetes than in those with long-standing insulin-treated type 2 diabetes and controls.

Association between Preoperative Glucose Dysregulation and Delirium after Non-Cardiac Surgery

This study aimed to investigate the association between glucose dysregulation and delirium after non-cardiac surgery. Among a total of 203,787 patients who underwent non-cardiac surgery between January 2011 and June 2019 at our institution, we selected 61,805 with available preoperative blood glucose levels within 24 h before surgery. Patients experiencing glucose dysregulation were divided into three groups: hyperglycemia, hypoglycemia, and both. We compared the incidence of postoperative delirium within 30 days after surgery between exposed and unexposed patients according to the type of glucose dysregulation. The overall incidence of hyperglycemia, hypoglycemia, and both was 5851 (9.5%), 1452 (2.3%), and 145 (0.2%), respectively. The rate of delirium per 100 person-months of the exposed group was higher than that of the unexposed group in all types of glucose dysregulation. After adjustment, the hazard ratios of glucose dysregulation in the development of delirium were 1.35 (95% CI, 1.18-1.56) in hyperglycemia, 1.36 (95% CI, 1.06-1.75) in hypoglycemia, and 3.14 (95% CI, 1.27-7.77) in both. The subgroup analysis showed that exposure to hypoglycemia or both to hypo- and hyperglycemia was not associated with delirium in diabetic patients, but hyperglycemia was consistently associated with postoperative delirium regardless of the presence of diabetes. Preoperative glucose dysregulation was associated with increased risk of delirium after non-cardiac surgery. Our findings may be helpful for preventing postoperative delirium, and further investigations are required to verify the association and mechanisms for the effect we observed.

Hypoglycaemia symptom frequency, severity, burden, and utility among adults with type 1 diabetes and impaired awareness of hypoglycaemia: Baseline and 24-week findings from the HypoCOMPaSS study

AIMS

To determine the frequency, severity, burden, and utility of hypoglycaemia symptoms among adults with type 1 diabetes (T1D) and impaired awareness of hypoglycaemia (IAH) at baseline and week 24 following the HypoCOMPaSS awareness restoration intervention.

METHODS

Adults (N = 96) with T1D (duration: 29 ± 12 years; 64% women) and IAH completed the Hypoglycaemia Burden Questionnaire (HypoB-Q), assessing experience of 20 pre-specified hypoglycaemia symptoms, at baseline and week 24.

RESULTS

At baseline, 93 (97%) participants experienced at least one symptom (mean ± SD 10.6 ± 4.6 symptoms). The proportion recognising each specific symptom ranged from 15% to 83%. At 24 weeks, symptom severity and burden appear reduced, and utility increased.

CONCLUSIONS

Adults with T1D and IAH experience a range of hypoglycaemia symptoms. Perceptions of symptom burden or utility are malleable. Although larger scale studies are needed to confirm, these findings suggest that changing the salience of the symptomatic response may be more important in recovering protection from hypoglycaemia through regained awareness than intensifying symptom frequency or severity.

The possible role of gut microbiota dysbiosis in the pathophysiology of delirium in older persons

Delirium is a clinical syndrome characterized by an acute change in attention, awareness and cognition with fluctuating course, frequently observed in older patients during hospitalization for acute medical illness or after surgery. Its pathogenesis is multifactorial and still not completely understood, but there is general consensus on the fact that it results from the interaction between an underlying predisposition, such as neurodegenerative diseases, and an acute stressor acting as a trigger, such as infection or anesthesia. Alterations in brain insulin sensitivity and metabolic function, increased blood-brain barrier permeability, neurotransmitter imbalances, abnormal microglial activation and neuroinflammation have all been involved in the pathophysiology of delirium. Interestingly, all these mechanisms can be regulated by the gut microbiota, as demonstrated in experimental studies investigating the microbiota-gut-brain axis in dementia. Aging is also associated with profound changes in gut microbiota composition and functions, which can influence several aspects of disease pathophysiology in the host. This review provides an overview of the emerging evidence linking age-related gut microbiota dysbiosis with delirium, opening new perspectives for the microbiota as a possible target of interventions aimed at delirium prevention and treatment.

Pharmacologic Management of Delirium in the Intensive Care Unit

Delirium, often underdiagnosed in the intensive care unit, is a common complication of critical illness that contributes to significant morbidity and mortality. Clinicians should be aware of common risk factors and triggers and should work to mitigate these as much as possible to reduce the occurrence of delirium. This review first provides an overview of the epidemiology, pathophysiology, evaluation, and consequences of delirium in critically ill patients. Presented next is the current evidence for the pharmacologic management of delirium, focusing on prevention and treatment of delirium in the intensive care unit. It concludes by outlining some emerging treatments of delirium.

Impact of Polymorphism in the β2-Receptor Gene on Metabolic Responses to Repeated Hypoglycemia in Healthy Humans

CONTEXT

The Arg16 variant in the β2-receptor gene is associated with increased risk of severe hypoglycemia in subjects with type 1 diabetes mellitus.

OBJECTIVE

We hypothesized that the Arg16 variant is associated with decreased metabolic and symptomatic responses to recurrent hypoglycemia.

METHODS

Twenty-five healthy male subjects selected according to ADRB2 genotype and being homozygous for either Arg16 (AA; n = 13) or Gly16 (GG; n = 12) participated in 2 consecutive trial days with 3 periods of hypoglycemia (H1-H3) induced by a hyperinsulinemic hypoglycemic clamp. The main outcome measure was mean glucose infusion rate (GIR) during H1-H3.

RESULTS

During H1-H3, there was no difference between AA or GG subjects in GIR, counter-regulatory hormones (glucagon, epinephrine, cortisol, growth hormone), or substrate levels of lactate, glycerol, and free fatty acids (FFAs), and no differences in symptom response score or cognitive performance (trail making test, Stroop test). At H3, lactate response was reduced in both genotype groups, but AA subjects had decreased response (mean ± standard error of the mean of area under the curve) of glycerol (-13.1 ± 3.8 μmol L-1 hours; P = .0052), FFA (-30.2 ± 11.1 μmol L-1 hours; P = .021), and β-hydroxybutyrate (-0.008 ± 0.003 mmol L-1 hour; P = .027), while in GG subjects alanine response was increased (negative response values) (-53.9 ± 20.6 μmol L-1 hour; P = .024).

CONCLUSION

There was no difference in GIR between genotype groups, but secondary outcomes suggest a downregulation of the lipolytic and β-hydroxybutyrate responses to recurrent hypoglycemia in AA subjects, in contrast to the responses in GG subjects.

Association between stress hyperglycemia ratio and delirium in older hospitalized patients: a cohort study

Background

It remains unclear whether stress hyperglycemia is associated with delirium. We performed this cohort study to determine the association between stress hyperglycemia and delirium.

Methods

We consecutively enrolled patients aged ≥70 years who were admitted to the Geriatric Department of West China Hospital between March 2016 and July 2017. Stress hyperglycemia ratio (SHR) was calculated as fasting blood glucose divided by estimated average glucose derived from glycosylated hemoglobin (HbA1c) and was classified into three tertiles. Delirium was screened within 24 h of admission and three times daily thereafter, using the confusion assessment method. The Cox proportional hazards models were used to assess the association of SHR with delirium.

Results

Among 487 included patients (mean age 83.0 years, 72.0% male), 50 (10.3%) patients experienced delirium during hospitalization. Compared to the second tertile, both the lowest and the highest SHR tertiles were independently associated with delirium (hazard ratio [HR] 3.71, 95% confidence interval [CI] 1.45-9.51; and HR 2.97, 95% CI 1.29-6.81, respectively). Similar results were found after further adjusting for statin comedication. Multiple-adjusted restricted cubic splines revealed a nonlinear relationship between SHR and delirium (P_nonlinearity=0.04). Adding SHR to conventional risk factors improved the risk prediction of delirium (net reclassification index 0.39, P=0.01; integrated discrimination improvement 0.07, P=0.03). Subgroup analyses indicated that the relationship between SHR and delirium was more apparent in patients with HbA1c <6.5%, with significantly higher HR in the first (3.65, 95% CI 1.11-11.97) and third (3.13, 95% CI 1.13-8.72) SHR tertiles compared to the second tertile, while there was no significant association between SHR and delirium in those with HbA1c ≥6.5%.

Conclusions

Both lower and higher SHR were associated with increased risk of delirium but only in patients with HbA1c <6.5%. Admission SHR may serve as a promising predictor of delirium, and incorporating this biomarker into prediction algorithms might have potential clinical utility in aiding delirium risk stratification, especially in those with HbA1c <6.5%.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-022-02935-6.

Treatment of Delirium During Critical Illness

Delirium, an acute disturbance in mental status due to another medical condition, is common and morbid in the intensive care unit. Despite its clear association with multiple common risk factors and important outcomes, including mortality and long-term cognitive impairment, both the ultimate causes of and ideal treatments for delirium remain unclear. Studies suggest that neuroinflammation, hypoxia, alterations in energy metabolism, and imbalances in multiple neurotransmitter pathways contribute to delirium, but commonly used treatments (e.g., antipsychotic medications) target only one or a few of these potential mechanisms and are not supported by evidence of efficacy. At this time, the optimal treatment for delirium during critical illness remains avoidance of risk factors, though ongoing trials may expand on the promise shown by agents such as melatonin and dexmedetomidine. Expected final online publication date for the Annual Review of Medicine, Volume 73 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Delirium

Delirium, a syndrome characterized by an acute change in attention, awareness and cognition, is caused by a medical condition that cannot be better explained by a pre-existing neurocognitive disorder. Multiple predisposing factors (for example, pre-existing cognitive impairment) and precipitating factors (for example, urinary tract infection) for delirium have been described, with most patients having both types. Because multiple factors are implicated in the aetiology of delirium, there are likely several neurobiological processes that contribute to delirium pathogenesis, including neuroinflammation, brain vascular dysfunction, altered brain metabolism, neurotransmitter imbalance and impaired neuronal network connectivity. The Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM-5) is the most commonly used diagnostic system upon which a reference standard diagnosis is made, although many other delirium screening tools have been developed given the impracticality of using the DSM-5 in many settings. Pharmacological treatments for delirium (such as antipsychotic drugs) are not effective, reflecting substantial gaps in our understanding of its pathophysiology. Currently, the best management strategies are multidomain interventions that focus on treating precipitating conditions, medication review, managing distress, mitigating complications and maintaining engagement to environmental issues. The effective implementation of delirium detection, treatment and prevention strategies remains a major challenge for health-care organizations globally.

Glucagon for hypoglycaemia treatment in type 1 diabetes

To achieve strict glycaemic control and avoid chronic diabetes complications, individuals with type 1 diabetes (T1D) are recommended to follow an intensive insulin regimen. However, the risk and fear of hypoglycaemia often prevent individuals from achieving the treatment goals. Apart from early insulin suspension in insulin pump users, carbohydrate ingestion is the only option for preventing and treating non-severe hypoglycaemic events. These rescue treatments may give extra calories and cause overweight. As an alternative, the use of low-dose glucagon to counter hypoglycaemia has been proposed as a tool to raise glucose concentrations without adding extra calories. Previously, the commercially available glucagon formulations required reconstitution from powder to a solution before being injected subcutaneously or intramuscularly-making it practical only for treating severe hypoglycaemia. Several companies have developed more stable formulations that do not require the time-consuming reconstitution process before use. As well as treating severe hypoglycaemia, non-severe and impending hypoglycaemia can also be treated with lower doses of glucagon. Once available, low-dose glucagon can be either delivered manually, as an injection, or automatically, by an infusion pump. This review focuses on the role and perspectives of using glucagon to treat and prevent hypoglycaemia in T1D.

Detection of Hypoglycemia Using Measures of EEG Complexity in Type 1 Diabetes Patients

Previous literature has demonstrated that hypoglycemic events in patients with type 1 diabetes (T1D) are associated with measurable scalp electroencephalography (EEG) changes in power spectral density. In the present study, we used a dataset of 19-channel scalp EEG recordings in 34 patients with T1D who underwent a hyperinsulinemic-hypoglycemic clamp study. We found that hypoglycemic events are also characterized by EEG complexity changes that are quantifiable at the single-channel level through empirical conditional and permutation entropy and fractal dimension indices, i.e., the Higuchi index, residuals, and tortuosity. Moreover, we demonstrated that the EEG complexity indices computed in parallel in more than one channel can be used as the input for a neural network aimed at identifying hypoglycemia and euglycemia. The accuracy was about 90%, suggesting that nonlinear indices applied to EEG signals might be useful in revealing hypoglycemic events from EEG recordings in patients with T1D.

A multiparameter model for non-invasive detection of hypoglycemia

OBJECTIVE

Severe hypoglycemia is the most serious acute complication for people with type 1 diabetes (T1D). Approximately 25% of people with T1D have impaired ability to recognize impending hypoglycemia, and nocturnal episodes are feared.

APPROACH

We have investigated the use of non-invasive sensors for detection of hypoglycemia based on a mathematical model which combines several sensor measurements to identify physiological responses to hypoglycemia. Data from randomized single-blinded euglycemic and hypoglycemic glucose clamps in 20 participants with T1D and impaired awareness of hypoglycemia was used in the analyses.

MAIN RESULTS

Using a sensor combination of sudomotor activity at three skin sites, ECG-derived heart rate and heart rate corrected QT interval, near-infrared and bioimpedance spectroscopy; physiological responses associated with hypoglycemia could be identified with an F1 score accuracy up to 88%.

SIGNIFICANCE

We present a novel model for identification of non-invasively measurable physiological responses related to hypoglycemia, showing potential for detection of moderate hypoglycemia using a wearable sensor system.

Different patterns of electroencephalography during hypoglycemia in type 1 diabetes mellitus: A case report

RATIONALE

Electroencephalographic (EEG) changes are frequently observed not only by epileptic seizures but also by metabolic encephalopathies. The EEG changes during hypoglycemia are known as mixed frequency theta to delta activity with higher amplitude than the initial background rhythm. Although there are many reports about hypoglycemia induced EEG changes, few studies of hypoglycemic EEG patterns have been evaluated between arousal and sleep stage.

PATIENT CONCERNS

A 45-year-old man who had been diagnosed as type 1 diabetes mellitus for 15 years admitted to the emergency room due to seizure attack. The EEG findings of the patient showed increased amplitude of theta slowing on both hemispheres. The abnormal EEG finding had recovered and the background frequency remarkably increased as the patient fell asleep, but reappeared when he woke up.

DIAGNOSIS

The patient was diagnosed as hypoglycemia with altered mentality.

INTERVENTIONS

Fifty percent dextrose fluid 50 mL was loaded and maintained with 10% dextrose water afterwards.

OUTCOMES

The patient improved after medical treatment.

LESSONS

The EEG presentation of hypoglycemia involves low frequency and increased amplitude of delta-theta activity. As the previous studies, we observed medium amplitude semi-rhythmic theta slowing EEG findings on both hemispheres during arousal, indicating hypoglycemia. However, it was stabilized during sleep as background frequency increased and medium amplitude of slowing disappeared. Although there are many reports about hypoglycemia induced EEG changes, few studies of hypoglycemic EEG patterns have been evaluated between arousal and sleep stage. We report a case of different EEG patterns between arousal and sleep stage during hypoglycemia.

Evaluation of Hypoglycaemia with Non-Invasive Sensors in People with Type 1 Diabetes and Impaired Awareness of Hypoglycaemia

People with type 1 diabetes and impaired awareness of hypoglycaemia (IAH) are prone to severe hypoglycaemia. Previous attempts to develop non-invasive hypoglycaemia alarm systems have shown promising results, but it is not known if such alarms can detect severe hypoglycaemia in people with IAH. We aimed to explore whether a combination of non-invasive sensors could reliably evaluate hypoglycaemia (plasma glucose (PG) minimum 2.5 mmol/L) in people with IAH. Twenty participants with type 1 diabetes and IAH underwent randomly ordered, single blinded hyperinsulinemic euglycaemic and hyperinsulinemic hypoglycaemic clamps. Sweating, skin temperature, ECG, counterregulatory hormones and symptoms of hypoglycaemia were assessed. Overall, we were not able to detect clamp-induced hypoglycaemia with sufficient sensitivity and specificity for further clinical use. As a post-hoc analysis, we stratified participants according to their ability to identify hypoglycaemic symptoms during hypoglycaemic clamps. Five out of 20 participants could identify such symptoms. These participants had a significantly higher adrenaline response to hypoglycaemia (p < 0.001) and were reliably identified by sensors. Based on our observations, a non-invasive alarm system based on measurement of sweating responses and ECG changes during hypoglycaemia might provide an alert at a plasma glucose concentration around 2.5 mmol/L if an adequate sympatho-adrenal reaction is elicited.

Presumed Neuroglycopenia Caused by Severe Hypoglycemia in Horses

BACKGROUND

Neuroglycopenia refers to a shortage of glucose in the brain resulting in neuronal dysfunction and death if left untreated. Presumed neuroglycopenia has not been described in horses.

OBJECTIVE

To report neurological signs in horses with presumed neuroglycopenia as the result of severe hypoglycemia.

ANIMALS

Ninety horses (hours to 28 years of age) diagnosed with hypoglycemia (blood glucose concentration < 75 mg/dL [< 4.2 mmol/L]).

METHODS

Retrospective study. Electronic medical records were searched. Signalment, history, complaint, clinical signs, laboratory findings including CSF analysis, electroencephalogram, clinical or definitive diagnosis, and outcome were recorded. Kruskal-Wallis analysis of variance and logistic regression were used to investigate association between blood glucose concentration and data extracted. Statistical significance was set at P < 0.05.

RESULTS

Thirty-eight and 52 horses had mild (50-74 mg/dL [2.8-4.1 mmol/L]), and severe hypoglycemia (< 50 mg/dL [< 2.8 mmol/L]), respectively. Most common causes of hypoglycemia included liver and gastrointestinal (40%) disease, sepsis (33%), neoplasia (7%), and insulin-induced (4%). Most common neurologic deficits included obtundation (100%), seizures (42%), and disorientation (22%). CSF-glucose was severely low (mean 2.5 mg/dL [0.1 mmol/L], median 0 mg/dL). Paroxysmal discharges in support of seizures were identified in the occipital (visual) and parietal (closest to temporal-auditory) cortical regions upon EEG examination (8/8 horses).

CONCLUSIONS AND CLINICAL IMPORTANCE

Neuroglycopenia is presumed to occur in horses as the result of severe hypoglycemia. Subclinical seizures, and intermittent blindness and deafness of cortical origin can occur. Severe altered state of consciousness and seizures can be observed at a blood glucose cut-off value of < 42 mg/dL (< 2.3 mmol/L).

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.

Glycemic Variability in Type 1 Diabetes Compared with Degludec and Glargine on the Morning Injection: An Open-label Randomized Controlled Trial

INTRODUCTION

Optimal adjustment of basal insulin to overcome hypoglycemia and glycemic variability (GV) depends on its duration of action and peak-less profile. Owing to the ability of long-acting basal insulin to avoid hypoglycemia, we titrated pre-meal glucose to normal fasting blood glucose, 80-110 mg/dL (4.5-6.1 mmol/L), and post-meal glucose to 80-140 mg/dL (4.5-7.8 mmol/L). The purpose of this study was to evaluate two basal insulin analogues degludec (IDeg) and glargine (IGlar), injected in the morning, for GV using continuous glucose monitoring (CGM) in type 1 diabetes (T1DM).

METHODS

In this crossover study, 20 Japanese patients with T1DM (age 54 ± 16 years, disease duration 16 ± 8 years, BMI 24 ± 4 kg/m², HbA1c 7.4 ± 0.8%) were randomized into one of two different starting regimens, and CGM was conducted on three consecutive days during the last week of each 12-week titration period. Treatment satisfaction was assessed at the end of each treatment period using the Diabetes Therapy-Related Quality of Life Questionnaire (DTR-QOL).

RESULTS

There were no differences in HbA1c, total insulin dosage, body weight changes, and basal to bolus ratio between the IDeg and IGlar arms. The day-to-day variability in fasting interstitial GV on the CGM curves was significantly less in the IDeg than IGlar treatment period (25.9 ± 22.0 vs. 43.8 ± 30.1 mg/dl, p = 0.04). Other markers of GV, calculated by the EasyGV software, including mean amplitude of glycemic excursions (MAGE), J-index, total and nocturnal hypoglycemia were not different between the two treatment periods. The score of "satisfaction with treatment", a subdomain of the DTR-QOL system, was higher in the IDeg period.

CONCLUSION

Thus, the morning injection of the two long-acting insulin analogues seemed similar with regard to the magnitude of hypoglycemia in T1DM, but treatment with IDeg was associated with lower day-to-day variation in glucose level. These results suggest that IDeg is safe with minimal morning GV in patients with T1DM.

CLINICAL TRIAL REGISTRATION

Japanese Clinical Trials Registry, UMIN000012358.

Hypoglycemia-Associated EEG Changes Following Antecedent Hypoglycemia in Type 1 Diabetes Mellitus

BACKGROUND

Recurrent hypoglycemia has been shown to blunt hypoglycemia symptom scores and counterregulatory hormonal responses during subsequent hypoglycemia. We therefore studied whether hypoglycemia-associated electroencephalogram (EEG) changes are affected by an antecedent episode of hypoglycemia.

METHODS

Twenty-four patients with type 1 diabetes mellitus (10 with normal hypoglycemia awareness, 14 with hypoglycemia unawareness) were studied on 2 consecutive days by hyperinsulinemic glucose clamp at hypoglycemia (2.0-2.5 mmol/L) during a 1-h period. EEG was recorded, cognitive function assessed, and hypoglycemia symptom scores and counterregulatory hormonal responses were obtained.

RESULTS

Twenty-one patients completed the study. Hypoglycemia-associated EEG changes were identified on both days with no differences in power or frequency distribution in the theta, alpha, or the combined theta-alpha band during hypoglycemia on the 2 days. Similar degree of cognitive dysfunction was also present during hypoglycemia on both days. When comparing the aware and unaware group, there were no differences in the hypoglycemia-associated EEG changes. There were very subtle differences in cognitive function between the two groups on day 2. The symptom response was higher in the aware group on both days, while only subtle differences were seen in the counterregulatory hormonal response.

CONCLUSION

Antecedent hypoglycemia does not affect hypoglycemia-associated EEG changes in patients with type 1 diabetes mellitus.

Hypoglycemia-Induced Changes in the Electroencephalogram: An Overview

Hypoglycemia is defined by an abnormally low blood glucose level. The condition develops when rates of glucose entry into the systematic circulation are reduced relative to the glucose uptake by the tissues. A cardinal manifestation of hypoglycemia arises from inadequate supply of glucose to the brain, where glucose is the primary metabolic fuel. The brain is one of the first organs to be affected by hypoglycemia. Shortage of glucose in the brain, or neuroglycopenia, results in a gradual loss of cognitive functions causing slower reaction time, blurred speech, loss of consciousness, seizures, and ultimately death, as the hypoglycemia progresses. The electrical activity in the brain represents the metabolic state of the brain cells and can be measured by electroencephalography (EEG). An association between hypoglycemia and changes in the EEG has been demonstrated, although blood glucose levels alone do not seem to predict neuroglycopenia. This review provides an overview of the current literature regarding changes in the EEG during episodes of low blood glucose.

Hypoglycemia-Associated EEG Changes in Prepubertal Children With Type 1 Diabetes

BACKGROUND

The purpose of this study was to explore the possible difference in the electroencephalogram (EEG) pattern between euglycemia and hypoglycemia in children with type 1 diabetes (T1D) during daytime and during sleep. The aim is to develop a hypoglycemia alarm based on continuous EEG measurement and real-time signal processing.

METHOD

Eight T1D patients aged 6-12 years were included. A hyperinsulinemic hypoglycemic clamp was performed to induce hypoglycemia both during daytime and during sleep. Continuous EEG monitoring was performed. For each patient, quantitative EEG (qEEG) measures were calculated. A within-patient analysis was conducted comparing hypoglycemia versus euglycemia changes in the qEEG. The nonparametric Wilcoxon signed rank test was performed. A real-time analyzing algorithm developed for adults was applied.

RESULTS

The qEEG showed significant differences in specific bands comparing hypoglycemia to euglycemia both during daytime and during sleep. In daytime the EEG-based algorithm identified hypoglycemia in all children on average at a blood glucose (BG) level of 2.5 ± 0.5 mmol/l and 18.4 (ranging from 0 to 55) minutes prior to blood glucose nadir. During sleep the nighttime algorithm did not perform.

CONCLUSIONS

We found significant differences in the qEEG in euglycemia and hypoglycemia both during daytime and during sleep. The algorithm developed for adults detected hypoglycemia in all children during daytime. The algorithm had too many false alarms during the night because it was more sensitive to deep sleep EEG patterns than hypoglycemia-related EEG changes. An algorithm for nighttime EEG is needed for accurate detection of nocturnal hypoglycemic episodes in children. This study indicates that a hypoglycemia alarm may be developed using real-time continuous EEG monitoring.

Generalized Anxiety Disorder and Hypoglycemia Symptoms Improved with Diet Modification

Observational evidence suggests that a relationship may exist between high glycemic index diets and the development of anxiety and depression symptoms; however, as no interventional studies assessing this relationship in a psychiatric population have been completed, the possibility of a causal link is unclear. AB is a 15-year-old female who presented with concerns of generalized anxiety disorder and hypoglycemia symptoms. Her diet consisted primarily of refined carbohydrates. The addition of protein, fat, and fiber to her diet resulted in a substantial decrease in anxiety symptoms as well as a decrease in the frequency and severity of hypoglycemia symptoms. A brief return to her previous diet caused a return of her anxiety symptoms, followed by improvement when she restarted the prescribed diet. This case strengthens the hypothesis that dietary glycemic index may play a role in the pathogenesis or progression of mental illnesses such as generalized anxiety disorder and subsequently that dietary modification as a therapeutic intervention in the treatment of mental illness warrants further study.

Non-invasive, home-based electroencephalography hypoglycaemia warning system for personal monitoring using skin surface electrodes: a single-case feasibility study

AIMS

Hypoglycaemia unawareness is a common condition associated with increased risk of severe hypoglycaemia. The purpose of the authors' study was to develop a simple to use, home-based and non-invasive hypoglycaemia warning system based on electroencephalography (EEG), and to demonstrate its use in a single-case feasibility study.

METHODS

A participant with type 1 diabetes forms a single-person case study where blood sugar levels and EEG were recorded. EEG was recorded using skin surface electrodes placed behind the ear located within the T3 region by the participant in the home. EEG was analysed retrospectively to develop an algorithm which would trigger a warning if EEG changes associated with hypoglycaemia onset were detected.

RESULTS

All hypoglycaemia events were detected by the EEG hypoglycaemia warning algorithm. Warnings were triggered with blood glucose concentration levels at or below 4.2 mmol/l in this participant and no warnings were issued when in euglycaemia.

CONCLUSION

The feasibility of a non-invasive EEG-based hypoglycaemia warning system for personal monitoring in the home has been demonstrated in a single case study. The results suggest that further studies are warranted to evaluate the system prospectively in a larger group of participants.

Hypoglycemia-Induced Decrease of EEG Coherence in Patients with Type 1 Diabetes

BACKGROUND

Hypoglycemic events in patients with type 1 diabetes (T1D) are associated with measurable electroencephalography (EEG) changes. Previous studies have, however, evaluated these changes on a single EEG channel level, whereas multivariate analysis of several EEG channels has been scarcely investigated. The aim of the present work is to use a coherence approach to quantitatively assess how hypoglycemia affects mutual connectivity of different brain areas.

MATERIALS AND METHODS

EEG multichannel data were obtained from 19 patients with T1D (58% males; mean age, 55 ± 2.4 years; diabetes duration, 28.5 ± 2.6 years; glycated hemoglobin, 8.0 ± 0.2%) who underwent a hyperinsulinemic-hypoglycemic clamp study. The information partial directed coherence (iPDC) function was computed through multivariate autoregressive models during eu- and hypoglycemia in the theta and alpha bands.

RESULTS

In passing from eu- to hypoglycemia, absolute values of the iPDC function tend to decrease in both bands in all combinations of the considered channels. In particular, the scalar indicator [Formula: see text], which summarizes iPDC information, significantly decreased (P < 0.01) in 17 of 19 subjects: from T5-A1A2 to C3-A1A2 from O1-A1A2 to C4-A1A2 and from O2-A1A2 to Cz-A1A2 in the theta band and from O1-A1A2 to T4-A1A2 and from O1-A1A2 to C4-A1A2 in the alpha band.

CONCLUSIONS

The coherence decrease measured by iPDC in passing from eu- to hypoglycemia is likely related to the progressive loss of cognitive function and altered cerebral activity in hypoglycemia. This result encourages further quantitative investigation of EEG changes in hypoglycemia and of how EEG acquisition and real-time processing can support hypoglycemia alert systems.

Infrared thermographic assessment of changes in skin temperature during hypoglycaemia in patients with type 1 diabetes

AIMS/HYPOTHESIS

Hypoglycaemia is associated with reduced skin temperature (Ts). We studied whether infrared thermography can detect Ts changes during hypoglycaemia in patients with type 1 diabetes and how the Ts response differs between patients with normal hypoglycaemia awareness and hypoglycaemia unawareness.

METHODS

Twenty-four patients with type 1 diabetes (ten aware, 14 unaware) were studied during normoglycaemia (5.0-6.0 mmol/l), hypoglycaemia (2.0-2.5 mmol/l) and during recovery from hypoglycaemia (5.0-6.0 mmol/l) using hyperinsulinaemic glucose clamping. During each 1 h phase, Ts was measured twice by infrared thermography imaging in pre-defined areas (nose, glabella and the five left fingertips), symptoms of hypoglycaemia were scored and blood was sampled.

RESULTS

Ts decreased during hypoglycaemia on the nose and glabella. The highest decrements were recorded on the nose (aware: -2.6 °C, unaware: -1.1 °C). In aware patients, the differences in temperature were statistically significant on both nose and glabella, whereas there was only a trend in the unaware group. There was a significant difference in hypoglycaemia-induced temperature changes between the groups. Patients in the aware group had higher hypoglycaemia symptom scores and higher adrenaline (epinephrine) levels during hypoglycaemia.

CONCLUSIONS/INTERPRETATION

The hypoglycaemia-associated decrement in Ts can be assessed by infrared thermography and is larger in patients with normal hypoglycaemia awareness compared with unaware patients.