Hypoglycemia-related electroencephalogram changes are independent of gender, age, duration of diabetes, and awareness status in type 1 diabetes

Line Sofie Remvig, Rasmus Elsborg, Anne-Sophie Sejling, Jens Ahm Sørensen, Lena Sønder Snogdal, Lars Folkestad, Claus B Juhl

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

Resumé

Introduction: Neuroglycopenia in type 1 diabetes mellitus (T1DM) results in reduced cognition, unconsciousness, seizures, and possible death. Characteristic changes in the electroencephalogram (EEG) can be detected even in the initial stages. This may constitute a basis for a hypoglycemia alarm device. The aim of the present study was to explore the characteristics of the EEG differentiating normoglycemia and hypoglycemia and to elucidate potential group differences. Methods: We pooled data from experiments in T1DM where EEG was available during both normoglycemia and hypo-glycemia for each subject. Temporal EEG was analyzed by quantitative electroencephalogram (qEEG) analysis with respect to absolute amplitude and centroid frequency of the delta, theta, alpha, and beta bands, and the peak frequency of the unified theta-alpha band. To elucidate possible group differences, data were subsequently stratified by age group (± 50 years), gender, duration of diabetes (± 20 years), and hypoglycemia awareness status (normal/impaired awareness of hypoglycemia). Results: An increase in the log amplitude of the delta, theta, and alpha band and a decrease in the alpha band centroid frequency and the peak frequency of the unified theta-alpha band constituted the most significant hypoglycemia indicators (all p <.0001). The size of these qEEG changes remained stable across all strata. Conclusions: Hypoglycemia-associated EEG changes remain stable across age group, gender, duration of diabetes, and hypoglycemia awareness status. This indicates that it may be possible to establish a general algorithm for hypoglycemia detection based on EEG measures.
OriginalsprogEngelsk
TidsskriftJournal of Diabetes Science and Technology
Vol/bind6
Udgave nummer6
Sider (fra-til)1337-44
Antal sider8
ISSN1932-2968
StatusUdgivet - 2012

Fingeraftryk

Medical problems
Electroencephalography
Hypoglycemia
Age Groups
Bioelectric potentials
Cognition
Frequency bands
Equipment and Supplies

Citer dette

Remvig, Line Sofie ; Elsborg, Rasmus ; Sejling, Anne-Sophie ; Sørensen, Jens Ahm ; Sønder Snogdal, Lena ; Folkestad, Lars ; Juhl, Claus B. / Hypoglycemia-related electroencephalogram changes are independent of gender, age, duration of diabetes, and awareness status in type 1 diabetes. I: Journal of Diabetes Science and Technology. 2012 ; Bind 6, Nr. 6. s. 1337-44.
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title = "Hypoglycemia-related electroencephalogram changes are independent of gender, age, duration of diabetes, and awareness status in type 1 diabetes",
abstract = "Introduction: Neuroglycopenia in type 1 diabetes mellitus (T1DM) results in reduced cognition, unconsciousness, seizures, and possible death. Characteristic changes in the electroencephalogram (EEG) can be detected even in the initial stages. This may constitute a basis for a hypoglycemia alarm device. The aim of the present study was to explore the characteristics of the EEG differentiating normoglycemia and hypoglycemia and to elucidate potential group differences. Methods: We pooled data from experiments in T1DM where EEG was available during both normoglycemia and hypo-glycemia for each subject. Temporal EEG was analyzed by quantitative electroencephalogram (qEEG) analysis with respect to absolute amplitude and centroid frequency of the delta, theta, alpha, and beta bands, and the peak frequency of the unified theta-alpha band. To elucidate possible group differences, data were subsequently stratified by age group (± 50 years), gender, duration of diabetes (± 20 years), and hypoglycemia awareness status (normal/impaired awareness of hypoglycemia). Results: An increase in the log amplitude of the delta, theta, and alpha band and a decrease in the alpha band centroid frequency and the peak frequency of the unified theta-alpha band constituted the most significant hypoglycemia indicators (all p <.0001). The size of these qEEG changes remained stable across all strata. Conclusions: Hypoglycemia-associated EEG changes remain stable across age group, gender, duration of diabetes, and hypoglycemia awareness status. This indicates that it may be possible to establish a general algorithm for hypoglycemia detection based on EEG measures.",
author = "Remvig, {Line Sofie} and Rasmus Elsborg and Anne-Sophie Sejling and S{\o}rensen, {Jens Ahm} and {S{\o}nder Snogdal}, Lena and Lars Folkestad and Juhl, {Claus B}",
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volume = "6",
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Hypoglycemia-related electroencephalogram changes are independent of gender, age, duration of diabetes, and awareness status in type 1 diabetes. / Remvig, Line Sofie; Elsborg, Rasmus; Sejling, Anne-Sophie; Sørensen, Jens Ahm; Sønder Snogdal, Lena; Folkestad, Lars; Juhl, Claus B.

I: Journal of Diabetes Science and Technology, Bind 6, Nr. 6, 2012, s. 1337-44.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

TY - JOUR

T1 - Hypoglycemia-related electroencephalogram changes are independent of gender, age, duration of diabetes, and awareness status in type 1 diabetes

AU - Remvig, Line Sofie

AU - Elsborg, Rasmus

AU - Sejling, Anne-Sophie

AU - Sørensen, Jens Ahm

AU - Sønder Snogdal, Lena

AU - Folkestad, Lars

AU - Juhl, Claus B

N1 - © 2012 Diabetes Technology Society.

PY - 2012

Y1 - 2012

N2 - Introduction: Neuroglycopenia in type 1 diabetes mellitus (T1DM) results in reduced cognition, unconsciousness, seizures, and possible death. Characteristic changes in the electroencephalogram (EEG) can be detected even in the initial stages. This may constitute a basis for a hypoglycemia alarm device. The aim of the present study was to explore the characteristics of the EEG differentiating normoglycemia and hypoglycemia and to elucidate potential group differences. Methods: We pooled data from experiments in T1DM where EEG was available during both normoglycemia and hypo-glycemia for each subject. Temporal EEG was analyzed by quantitative electroencephalogram (qEEG) analysis with respect to absolute amplitude and centroid frequency of the delta, theta, alpha, and beta bands, and the peak frequency of the unified theta-alpha band. To elucidate possible group differences, data were subsequently stratified by age group (± 50 years), gender, duration of diabetes (± 20 years), and hypoglycemia awareness status (normal/impaired awareness of hypoglycemia). Results: An increase in the log amplitude of the delta, theta, and alpha band and a decrease in the alpha band centroid frequency and the peak frequency of the unified theta-alpha band constituted the most significant hypoglycemia indicators (all p <.0001). The size of these qEEG changes remained stable across all strata. Conclusions: Hypoglycemia-associated EEG changes remain stable across age group, gender, duration of diabetes, and hypoglycemia awareness status. This indicates that it may be possible to establish a general algorithm for hypoglycemia detection based on EEG measures.

AB - Introduction: Neuroglycopenia in type 1 diabetes mellitus (T1DM) results in reduced cognition, unconsciousness, seizures, and possible death. Characteristic changes in the electroencephalogram (EEG) can be detected even in the initial stages. This may constitute a basis for a hypoglycemia alarm device. The aim of the present study was to explore the characteristics of the EEG differentiating normoglycemia and hypoglycemia and to elucidate potential group differences. Methods: We pooled data from experiments in T1DM where EEG was available during both normoglycemia and hypo-glycemia for each subject. Temporal EEG was analyzed by quantitative electroencephalogram (qEEG) analysis with respect to absolute amplitude and centroid frequency of the delta, theta, alpha, and beta bands, and the peak frequency of the unified theta-alpha band. To elucidate possible group differences, data were subsequently stratified by age group (± 50 years), gender, duration of diabetes (± 20 years), and hypoglycemia awareness status (normal/impaired awareness of hypoglycemia). Results: An increase in the log amplitude of the delta, theta, and alpha band and a decrease in the alpha band centroid frequency and the peak frequency of the unified theta-alpha band constituted the most significant hypoglycemia indicators (all p <.0001). The size of these qEEG changes remained stable across all strata. Conclusions: Hypoglycemia-associated EEG changes remain stable across age group, gender, duration of diabetes, and hypoglycemia awareness status. This indicates that it may be possible to establish a general algorithm for hypoglycemia detection based on EEG measures.

M3 - Journal article

C2 - 23294778

VL - 6

SP - 1337

EP - 1344

JO - Journal of Diabetes Science and Technology

JF - Journal of Diabetes Science and Technology

SN - 1932-2968

IS - 6

ER -