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Intra Cranial EEG Activity During Dexmedetomidine Sedation

Intra Cranial EEG Activity During Dexmedetomidine Sedation.Comparing the Effects of Dexmedetomidine on the Cortical and the Sub Cortical(Hippocampus) Structures.

Status
Terminated
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT01648959
Enrollment
5
Registered
2012-07-25
Start date
2012-07-31
Completion date
2014-03-31
Last updated
2022-12-22

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Complex Partial Seizures

Brief summary

Various parts of the brain are sensitive to various anesthetics.We like to study the effect of dexmedetomidine on the different parts of the brain in patients who are coming for DBS electrode removal under sedation.

Detailed description

Cortical and sub cortical structures will have different sensitivities to various anesthetics.The objective of this study is to look at the changes in the intracranial electroencephalographic (EEG) characteristics during dexmedetomidine sedation and to determine the differences in the EEG characteristics between cortical and subcortical structures.

Interventions

Sponsors

University Health Network, Toronto
Lead SponsorOTHER

Study design

Observational model
COHORT
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
18 Years to 80 Years
Healthy volunteers
No

Inclusion criteria

* Adults between 18 to 80 years of age, who are scheduled for elective removal of intracranial (surface and depth) electrodes under conscious sedation

Exclusion criteria

* Lack of informed consent * Hypersensitivity to dexmedetomidine * Language barrier * Emergency surgery

Design outcomes

Primary

MeasureTime frameDescription
iEEG Recording1 dayiEEG data from each patient was analyzed using MATLAB (Natick, MA, USA). Data were presented as power spectral density, also referred to as the power spectrum or spectrum which quantifies the frequency distribution of energy or power within a signal. The spectrogram is a time-varying version of the spectrum. In these spectrograms, frequencies are arranged along the y-axis, and time along the x-axis, and power is indicated by color on a decibel (dB) scale. The power spectrum was computed for each channel using The Fast Fourier Transform (FFT). A window length of 20,000 data points was chosen in order to incorporate 4 cycles of a 1 Hz signal. The length of each window was therefore 4 seconds. A Hanning window was used to avoid edge effects of the windowing procedure. The length of the FFT was chosen to be 32768, which is the next power of 2 of the window length. The window overlap was set to zero.

Countries

Canada

Participant flow

Participants by arm

ArmCount
Dexmedetomidine Infusion and iEEG Activity
5 patients included in this study underwent bi-temporal implantation, and were shown to have unilateral hippocampal seizure onsets. iEEG data acquires every minute from the start of dexmedetomidine infusion to 5 minutes after the bolus dose.
5
Total5

Baseline characteristics

CharacteristicDexmedetomidine Infusion and iEEG Activity
Age, Customized
Age
37.3 years
STANDARD_DEVIATION 7
Race and Ethnicity Not Collected— Participants
Sex: Female, Male
Female
2 Participants
Sex: Female, Male
Male
3 Participants

Adverse events

Event typeEG000
affected / at risk
deaths
Total, all-cause mortality
0 / 5
other
Total, other adverse events
0 / 5
serious
Total, serious adverse events
0 / 5

Outcome results

Primary

iEEG Recording

iEEG data from each patient was analyzed using MATLAB (Natick, MA, USA). Data were presented as power spectral density, also referred to as the power spectrum or spectrum which quantifies the frequency distribution of energy or power within a signal. The spectrogram is a time-varying version of the spectrum. In these spectrograms, frequencies are arranged along the y-axis, and time along the x-axis, and power is indicated by color on a decibel (dB) scale. The power spectrum was computed for each channel using The Fast Fourier Transform (FFT). A window length of 20,000 data points was chosen in order to incorporate 4 cycles of a 1 Hz signal. The length of each window was therefore 4 seconds. A Hanning window was used to avoid edge effects of the windowing procedure. The length of the FFT was chosen to be 32768, which is the next power of 2 of the window length. The window overlap was set to zero.

Time frame: 1 day

ArmMeasureValue (MEAN)
iEEG ActivityiEEG Recording8 (Hz)

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026