Hypoglycemia-Induced Changes in the Electroencephalogram: An Overview

Mind the Metabolic Gap: Bridging Migraine and Alzheimer's disease through Brain Insulin Resistance

Brain insulin resistance has recently been described as a metabolic abnormality of brain glucose homeostasis that has been proven to downregulate insulin receptors, both in astrocytes and neurons, triggering a reduction in glucose uptake and glycogen synthesis. This condition may generate a mismatch between brain's energy reserve and expenditure, ??mainly during high metabolic demand, which could be involved in the chronification of migraine and, in the long run, at least in certain subsets of patients, in the prodromic phase of Alzheimer's disease, along a putative metabolic physiopathological continuum. Indeed, the persistent disruption of glucose homeostasis and energy supply to neurons may eventually impair protein folding, an energy-requiring process, promoting pathological changes in Alzheimer's disease, such as amyloid-β deposition and tau hyperphosphorylation. Hopefully, the "neuroenergetic hypothesis" presented herein will provide further insight on there being a conceivable metabolic bridge between chronic migraine and Alzheimer's disease, elucidating novel potential targets for the prophylactic treatment of both diseases.

Exploring recurrence quantification analysis and fractal dimension algorithms for diagnosis of encephalopathy

Electroencephalography (EEG) is a crucial non-invasive medical tool for diagnosing neurological disorder called encephalopathy. There is a requirement for powerful signal processing algorithms as EEG patterns in encephalopathies are not specific to a particular etiology. As visual examination and linear methods of EEG analysis are not sufficient to get the subtle information regarding various neuro pathologies, non-linear analysis methods can be employed for exploring the dynamic, complex and chaotic nature of EEG signals. This work aims identifying and differentiating the patterns specific to cerebral dysfunctions associated with Encephalopathy using Recurrence Quantification Analysis and Fractal Dimension algorithms. This study analysed six RQA features, namely, recurrence rate, determinism, laminarity, diagonal length, diagonal entropy and trapping time and comparing them with fractal dimensions, namely, Higuchi's and Katz's fractal dimension. Fractal dimensions were found to be lower for encephalopathy cases showing decreased complexity when compared to that of normal healthy subjects. On the other hand, RQA features were found to be higher for encephalopathy cases indicating higher recurrence and more periodic patterns in EEGs of encephalopathy compared to that of normal healthy controls. The feature reduction was then performed using Principal Component Analysis and fed to three promising classifiers: SVM, Random Forest and Multi-layer Perceptron. The resultant system provides a practically realizable pipeline for the diagnosis of encephalopathy.

Pancreatic insulinoma: Diagnosis and treatment of a rare tumour with misleading symptoms - A case report

INTRODUCTION

Insulinomas are an uncommon occurrence, with an annual incidence of approximately 4 per million. These functional pancreatic neuroendocrine tumours can present with a myriad of nonspecific symptoms leading to frequent misdiagnoses.

PRESENTATION OF CASE

In this case report is presented a 55-year-old man who was misdiagnosed and managed for a seizure disorder with escalating antiepileptic treatments for 11 months. A thorough history after an attack was the main tool in solving the mystery of his refractory seizures, leading to the discovery of a pancreatic insulinoma. Biochemical tests revealed fasting hypoglycaemia and a relative hyperinsulinemia, and a distal pancreatic lesion measuring approximately 1.8 cm × 1.3 cm was detected on CT, MRI and endoscopic ultrasound. Successful laparoscopic pancreatic left resection led to complete resolution of symptoms and restoration of quality of life to pre-illness levels.

DISCUSSION AND CONCLUSION

Insulinomas have historically been difficult to diagnose because their symptoms mimic neurologic and psychiatric conditions. Patterns of symptom occurrence obtained from a carefully-taken history is the single most important tool in assessing patients with insulinomas, who usually present with unusual and refractory neuropsychiatric conditions.

Description and Outcome of Severe Hypoglycemic Encephalopathy in the Intensive Care Unit

BACKGROUND

Disorders of consciousness due to severe hypoglycemia are rare but challenging to treat. The aim of this retrospective cohort study was to describe our multimodal neurological assessment of patients with hypoglycemic encephalopathy hospitalized in the intensive care unit and their neurological outcomes.

METHODS

Consecutive patients with disorders of consciousness related to hypoglycemia admitted for neuroprognostication from 2010 to 2020 were included. Multimodal neurological assessment included electroencephalography, somatosensory and cognitive event-related potentials, and morphological and quantitative magnetic resonance imaging (MRI) with quantification of fractional anisotropy. Neurological outcomes at 28 days, 3 months, 6 months, 1 year, and 2 years after hypoglycemia were retrieved.

RESULTS

Twenty patients were included. After 2 years, 75% of patients had died, 5% remained in a permanent vegetative state, 10% were in a minimally conscious state, and 10% were conscious but with severe disabilities (Glasgow Outcome Scale-Extended scores 3 and 4). All patients showed pathologic electroencephalography findings with heterogenous patterns. Morphological brain MRI revealed abnormalities in 95% of patients, with various localizations including cortical atrophy in 65% of patients. When performed, quantitative MRI showed decreased fractional anisotropy affecting widespread white matter tracts in all patients.

CONCLUSIONS

The overall prognosis of patients with severe hypoglycemic encephalopathy was poor, with only a small fraction of patients who slowly improved after intensive care unit discharge. Of note, patients who did not improve during the first 6 months did not recover consciousness. This study suggests that a multimodal approach capitalizing on advanced brain imaging and bedside electrophysiology techniques could improve diagnostic and prognostic performance in severe hypoglycemic encephalopathy.

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.

Mitigation of Ionizing Radiation-Induced Gastrointestinal Damage by Insulin-Like Growth Factor-1 in Mice

Purpose: Insulin-like growth factor-1 (IGF-1) stimulates epithelial regeneration but may also induce life-threatening hypoglycemia. In our study, we first assessed its safety. Subsequently, we examined the effect of IGF-1 administered in different dose regimens on gastrointestinal damage induced by high doses of gamma radiation.

Material and methods: First, fasting C57BL/6 mice were injected subcutaneously with IGF-1 at a single dose of 0, 0.2, 1, and 2 mg/kg to determine the maximum tolerated dose (MTD). The glycemic effect of MTD (1 mg/kg) was additionally tested in non-fasting animals. Subsequently, a survival experiment was performed. Animals were irradiated (⁶⁰Co; 14, 14.5, or 15 Gy; shielded head), and IGF-1 was administered subcutaneously at 1 mg/kg 1, 24, and 48 h after irradiation. Simultaneously, mice were irradiated (⁶⁰Co; 12, 14, or 15 Gy; shielded head), and IGF-1 was administered subcutaneously under the same regimen. Jejunum and lung damage were assessed 84 h after irradiation. Finally, we evaluated the effect of six different IGF-1 dosage regimens administered subcutaneously on gastrointestinal damage and peripheral blood changes in mice 6 days after irradiation (⁶⁰Co; 12 and 14 Gy; shielded head). The regimens differed in the number of doses (one to five doses) and the onset of administration (starting at 1 [five regimens] or 24 h [one regimen] after irradiation).

Results: MTD was established at 1 mg/kg. MTD mitigated lethality induced by 14 Gy and reduced jejunum and lung damage caused by 12 and 14 Gy. However, different dosing regimens showed different efficacy, with three and four doses (administered 1, 24, and 48 h and 1, 24, 48, and 72 h after irradiation, respectively) being the most effective. The three-dose regimens supported intestinal regeneration even if the administration started at 24 h after irradiation, but its potency decreased.

Conclusion: IGF-1 seems promising in the mitigation of high-dose irradiation damage. However, the selected dosage regimen affects its efficacy.

Ability of Current Machine Learning Algorithms to Predict and Detect Hypoglycemia in Patients With Diabetes Mellitus: Meta-analysis

Background

Machine learning (ML) algorithms have been widely introduced to diabetes research including those for the identification of hypoglycemia.

Objective

The objective of this meta-analysis is to assess the current ability of ML algorithms to detect hypoglycemia (ie, alert to hypoglycemia coinciding with its symptoms) or predict hypoglycemia (ie, alert to hypoglycemia before its symptoms have occurred).

Methods

Electronic literature searches (from January 1, 1950, to September 14, 2020) were conducted using the Dialog platform that covers 96 databases of peer-reviewed literature. Included studies had to train the ML algorithm in order to build a model to detect or predict hypoglycemia and test its performance. The set of 2 × 2 data (ie, number of true positives, false positives, true negatives, and false negatives) was pooled with a hierarchical summary receiver operating characteristic model.

Results

A total of 33 studies (14 studies for detecting hypoglycemia and 19 studies for predicting hypoglycemia) were eligible. For detection of hypoglycemia, pooled estimates (95% CI) of sensitivity, specificity, positive likelihood ratio (PLR), and negative likelihood ratio (NLR) were 0.79 (0.75-0.83), 0.80 (0.64-0.91), 8.05 (4.79-13.51), and 0.18 (0.12-0.27), respectively. For prediction of hypoglycemia, pooled estimates (95% CI) were 0.80 (0.72-0.86) for sensitivity, 0.92 (0.87-0.96) for specificity, 10.42 (5.82-18.65) for PLR, and 0.22 (0.15-0.31) for NLR.

Conclusions

Current ML algorithms have insufficient ability to detect ongoing hypoglycemia and considerate ability to predict impeding hypoglycemia in patients with diabetes mellitus using hypoglycemic drugs with regard to diagnostic tests in accordance with the Users’ Guide to Medical Literature (PLR should be ≥5 and NLR should be ≤0.2 for moderate reliability). However, it should be emphasized that the clinical applicability of these ML algorithms should be evaluated according to patients’ risk profiles such as for hypoglycemia and its associated complications (eg, arrhythmia, neuroglycopenia) as well as the average ability of the ML algorithms. Continued research is required to develop more accurate ML algorithms than those that currently exist and to enhance the feasibility of applying ML in clinical settings.

Trial Registration

PROSPERO International Prospective Register of Systematic Reviews CRD42020163682; http://www.crd.york.ac.uk/PROSPERO/display_record.php?ID=CRD42020163682

Excitatory-inhibitory balance within EEG microstates and resting-state fMRI networks: assessed via simultaneous trimodal PET-MR-EEG imaging

The symbiosis of neuronal activities and glucose energy metabolism is reflected in the generation of functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) signals. However, their association with the balance between neuronal excitation and inhibition (E/I-B), which is closely related to the activities of glutamate and γ-aminobutyric acid (GABA) and the receptor availability (RA) of GABAA and mGluR5, remains unexplored. This research investigates these associations during the resting state (RS) condition using simultaneously recorded PET/MR/EEG (trimodal) data. The trimodal data were acquired from three studies using different radio-tracers such as, [11C]ABP688 (ABP) (N = 9), [11C]Flumazenil (FMZ) (N = 10) and 2-[18F]fluoro-2-deoxy-D-glucose (FDG) (N = 10) targeted to study the mGluR5, GABAA receptors and glucose metabolism respectively. Glucose metabolism and neuroreceptor binding availability (non-displaceable binding potential (BPND)) of GABAA and mGluR5 were found to be significantly higher and closely linked within core resting-state networks (RSNs). The neuronal generators of EEG microstates and the fMRI measures were most tightly associated with the BPND of GABAA relative to mGluR5 BPND and the glucose metabolism, emphasising a predominance of inhibitory processes within in the core RSNs at rest. Changes in the neuroreceptors leading to an altered coupling with glucose metabolism may render the RSNs vulnerable to psychiatric conditions. The paradigm employed here will likely help identify the precise neurobiological mechanisms behind these alterations in fMRI functional connectivity and EEG oscillations, potentially benefitting individualised healthcare treatment measures.

Evaluation of Brain Death in Laying Hens During On-Farm Killing by Cervical Dislocation Methods or Pentobarbital Sodium Injection

This study investigated changes in the electroencephalograph (EEG) power spectrum as well as physiological and behavioral responses to on-farm killing via mechanical cervical dislocation (MCD), manual cervical dislocation (CD) or intravenous pentobarbital sodium administration in lightly anesthetized laying hens, to evaluate the welfare impact of each method. A mixed group of 44 white Leghorn and Smoky Joe laying hens (60 weeks-old) were anesthetized with isoflurane in oxygen and maintained at 1.5–2% isoflurane/O₂ until the killing method was applied. Birds were randomly assigned to one of three experimental groups on each trial day. The EEG was recorded bilaterally in a four-electrode montage. After recording a 5-min baseline, the killing method was applied and EEGs and other behavioral and physiological responses, including convulsions, gasping, cessation of body movements and feather erection were recorded for 5 min. Changes in EEG frequency bands (alpha, beta, delta, theta), median frequency (F50), 95% spectral edge frequency (F95), and total power (Ptot) were used to assess the quality of the on-farm killing event. Within 15 s after administration of pentobarbital sodium, there were significant decreases in mean frequency bands, increases in mean F50 and F95, and decreases in Ptot, suggesting brain death. In addition, birds presented a shorter latency to cessation of movement after pentobarbital sodium injection compared to MCD and CD (22 vs. 115 s and 136 s, respectively). There were significant increases in F95 and decreases in Ptot at 120 s after application of CD; and a concomitant decrease in the frequency bands at 135 s and isoelectric EEG at 171 ± 15 s. Changes consistent with brain death after MCD included isoelectric EEG at 207 ± 23 s and a significant decreases in some frequency bands at 300 s post-application. No other significant spectrum frequency changes were observed in the MCD group, suggesting brain death likely occurred near the 5-min endpoint. There was no clear association between behavioral, physiological, and EEG responses within CD and MCD treatments. The data demonstrate that pentobarbital sodium induced a rapid death with minimal behavioral and physiological responses regardless of strain of hens. In comparison, use of CD and MCD resulted in a slow onset of brain death in hens.

Electroencephalogram Spectral Moments for the Detection of Nocturnal Hypoglycemia

Hypoglycemia or low blood glucose is the most feared complication of insulin treatment of diabetes. For people with diabetes, the mismatch between the insulin therapy and the body's physiology could increase the risk of hypoglycemia. Nocturnal hypoglycemia is particularly dangerous for type-1 diabetes patients because its symptoms may obscure during sleep. The early onset detection of hypoglycemia at night time is necessary because it can result in unconsciousness and even death. This paper presents new electroencephalogram spectral features for nocturnal hypoglycemia detection. The system uses high-order spectral moments for feature extraction and Bayesian neural network for classification. From a clinical study of hypoglycemia of eight patients with type-1 diabetes at night, we find that these spectral moments of theta band and alpha band changed significantly. During hypoglycemia episodes, the theta moments increased significantly (P < 0.001) while the features of alpha band reduced significantly (P < 0.001). Using the optimal Bayesian neural network, the classification results were 85% and 52% in sensitivity and specificity, respectively. The significant correlation (P < 0.001) with real blood glucose profiles shows the effectiveness of the proposed features for the detection of nocturnal hypoglycemia.

Electroencephalographic, physiologic and behavioural responses during cervical dislocation euthanasia in turkeys

Background

There is a critical need to develop appropriate on-farm euthanasia methods for poultry species. Euthanasia methods should affect the brain first causing insensibility, followed by cardiorespiratory arrest. Neck or cervical dislocation methods, either manual (CD) or mechanical (MCD), are reported to cause a prolonged time to loss of sensibility and death with inconsistent results upon application, especially MCD methods. However, there is limited information on cervical dislocation in turkeys. The overall objective of this study was to assess the welfare implications of CD and a newly developed MCD device for euthanasia of cull turkeys in comparison with intravenous (IV) pentobarbital sodium (1 mL/4.5 kg), the gold standard euthanasia method. Time to death using electroencephalographic (EEG) and behavioural responses were monitored in eight and eighteen week-old turkeys for five minutes after each euthanasia method application. Spectral analyses of EEG responses and onset of isoelectric EEGs were compared to baseline EEG recordings of birds under anesthesia and behavioural responses were studied among euthanasia treatments. A significant decrease in brain activity frequencies analysis and isoelectric EEG were recorded as time of brain death.

Results

All turkeys euthanized with IV pentobarbital sodium presented a rapid and irreversible decrease in the EEG activity at approximately 30s post-injection with minimal behavioural responses. CD and MCD methods caused EEG responses consistent with brain death at approximately 120 s and 300 s, respectively. Additionally, isoelectric EEGs resulted in all pentobarbital sodium and CD groups, but only in 54 and 88% of the eight and eighteen week-old turkeys in the MCD groups, respectively. There were few clear patterns of behavioural responses after CD and MCD application. However, cessation of body movement and time to isoelectric EEG after CD application were positively correlated.

Conclusions

Use of CD and MCD resulted in a prolonged time to death in both age groups of turkeys. MCD application presents a number of welfare risks based on electroencephalographic and behavioural findings. Intravenous pentobarbital sodium induced rapid brain death, but possesses several on-farm limitations. To develop improvements in cervical dislocation methods, further investigations into combined or alternative methods are required to reduce the prolonged time to insensibility and death.

Electronic supplementary material

The online version of this article (10.1186/s12917-019-1885-x) contains supplementary material, which is available to authorized users.

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).

Higher HbA1c and/or glucose levels alter the association patterns between glycated hemoglobin and fasting glucose levels

AIMS

To verify the correlations between HbA1c and fasting glucose levels.

METHODS

A cross-sectional study with 14,249 Chinese subjects. Objective was evaluated in pooled, age-stratified, HbA1c and fasting glucose-stratified populations.

RESULTS

In pooled populations, the Pearson correlation coefficients (PCCs) of males and females were 0.684 (P < 0.001) and 0.800 (P < 0.001), respectively. HbA1c and fasting glucose maintained significant correlations within the group with HbA1c < 6.5% and glucose <7.0 mmol/L and the group with HbA1c ≥ 6.5% and glucose ≥7.0 mmol/L in both males (PCC: 0.342, P < 0.001; and PCC: 0.765, P < 0.001, respectively) and females (PCC: 0.318, P < 0.001 and PCC: 0.788, P < 0.001, respectively). The slopes increased from the group with HbA1c < 6.5% and glucose <7.0 mmol/L to the group with HbA1c ≥ 6.5% and glucose ≥7.0 mmol/L in both males (0.26-0.44) and females (0.31-0.46). Linear regression analysis showed that fasting glucose and age were two common factors positively associated with HbA1C, and red blood cell count and red cell distribution width were two common factors negatively associated with HbA1c in both males and females with HbA1c < 6.5% and glucose <7.0 mmol/L. The correlations changed dramatically in the groups with HbA1c ≥ 6.5% and glucose <7.0 mmol/L and HbA1c < 6.5% and glucose ≥7.0 mmol/L.

CONCLUSIONS

High HbA1c and fasting glucose levels greatly altered the associations between HbA1c, glucose and age.

Abnormally low Bispectral index and severe hypoglycemia during maintenance of and recovery from general anesthesia in diabetic retinopathy surgery: two case reports

Background

Hypoglycemia is one of the most fatal complications during the perioperative period. General anesthesia or sedation can mask a hypoglycemia-altered mental status. Acute hypoglycemia might result in permanent brain injury. There is no way to detect hypoglycemia during general anesthesia, except for intermittent blood glucose monitoring.

Case presentation

Hypoglycemia is associated with changes in electroencephalogram readings. Here, we report two cases of patients with an abnormally low Bispectral Index (BIS) associated with diabetic retinopathy surgery, one in the recovery stage of general anesthesia and the other in the maintenance of general anesthesia. Hemodynamics were stable. Severe hypoglycemia (1.6 mmol/L and 2.2 mmol/L) was then detected. BIS increased with the correction of severe hypoglycemia.

Conclusions

For diabetic patients, when the intraoperative BIS value is abnormally low, hypoglycemia should be considered. Severe hypoglycemia may be presented in BIS monitoring during general anesthesia.