Burst SuppressionNCT05508386
Interrater Variability for the Identification of Anesthetic-induced Burst Suppression EEG
A study testing MATLAB-based interface, showing 50 EEG traces, classification of the EEG-pattern as Burst Suppression possible, yes, no. in people with Burst Suppression and General Anesthesia, run by Technical University of Munich at 1 site in Germany.
Trial summary
Burst suppression describes a specific EEG pattern that can generally indicate a too deep general anesthesia. The pathophysiology of anesthetic-induced Burst Suppression may be distinctly different from the pathophysiology of Burst Suppression from other medical causes (e.g., coma, hypothermia, intoxication). Read more about this study
- Who is it for?
- Any ageHealthy volunteers can take part
- Conditions the study is for
- Burst Suppression, General Anesthesia, Electroencephalogram
- What is being tested?
- MATLAB-based interface, showing 50 EEG traces, classification of the EEG-pattern as Burst Suppression possible, yes, no.
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 40 participants
- Where
- 1 siteGermany
- Study dates
- 10 Aug 2022to 1 Apr 2023
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages Any age
- All sexes
- Healthy volunteers accepted
- Child, Adult, Older adult
Who may be able to join
- leading international experts in the field of intraoperative EEG analysis
Who cannot join
- members of study group
Trial locations and contacts
1 site in 1 country.
Germany1 site
Klinikum rechts der Isar - Klinik für Anästhesiologie und Intensivmedizin
Munich, Bavaria, 81675
About this study
Burst suppression describes a specific EEG pattern that can generally indicate a too deep general anesthesia. The pathophysiology of anesthetic-induced Burst Suppression may be distinctly different from the pathophysiology of Burst Suppression from other medical causes (e.g., coma, hypothermia, intoxication). Definition criteria of neurologic societies cannot be applied to the classification of Burst Suppression during general anesthesia without adaptation. The lack of a clear definition complicates structured research on anesthetic-induced Burst Suppression EEG in the perioperative setting because of subjective bias. Therefore, a unified agreement on what anesthesia-induced Burst Suppression looks like is crucial to conduct the best possible research. The aim of this study is to formulate the basis for a clear definition of burst suppression EEG that may help to truly understand the significance of this EEG pattern and its relationship to proposed postoperative outcomes such as postoperative delirium, longterm postoperative neurocognitive disorders (PNDs) or increased mortality.
Read the detailed description
Intraoperative neuromonitoring is recommended to assess the level of general anesthesia. Additionally, specific intraoperative EEG patterns seem to be associated with PNDs. One of these EEG patterns is the burst suppression EEG. The pattern of waxing and waning activity has been associated with a higher risk factor for postoperative delirium.
Commercial patient monitoring systems seem to underestimate the occurrence of Burst Suppression because the detection algorithms may not capture every suppression episode. A visual identification of this pattern is possible, but in the context of anesthesia monitoring, there is no standard definition of a Burst Suppression-EEG in the perioperative setting. Further, it displays unique clinical morphological characteristics. In particular, parameters of the EEG frequency spectrum are remarkably influenced by patients age and anesthetic agents. In order to agree on a definition for Burst Suppression during general anesthesia that will help to standardize Burst Suppression research and to optimize Burst Suppression monitoring, an expert consensus is essential. The planned project aims to pave the way to such a consensus of international expert societies in anesthesiology. Based on EEG data recorded within the framework of previous studies (approved Ethics application dated 20.08.2018 with number 246/18 S \& 213/17S, dated 24.05.2017), the investigators will compose a representative data set (overall 50 EEG patterns) consisting of definitive Burst Suppression patterns (positive control), intraoperative EEG without Burst Suppression (negative control) and patterns that indicate different manifestations of a possible Burst Suppression-like pattern.
The EEG recordings of this data set will be evaluated by selected international leading experts in EEG-based anesthesia monitoring.
Therefore, a software environment (MATLAB) was developed, that allows the international experts to access the data set and score the traces pseudonymously. After the data sets have been scored, the interrater agreement for the single EEG episodes will be statistically analyzed.
- Conditions
- Burst Suppression, General Anesthesia, Electroencephalogram
- Being tested
- MATLAB-based interface, showing 50 EEG traces, classification of the EEG-pattern as Burst Suppression possible, yes, no.
- Keywords
- Intraoperative EEG based monitoring, Burst Suppression, EEG-signal characteristics, intraoperative monitoring, general anesthesia
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
MATLAB-based interface, showing 50 EEG traces, classification of the EEG-pattern as Burst Suppression possible, yes, no.Other
A software environment (MATLAB) was developed, that allows the international experts to access the data set and score the traces pseudonymously. This MATLAB-based interface shows 50 EEG traces. A representative dataset was composed, consisting of definite Burst Suppression patterns (positive control), intraoperative EEG without Burst Suppression patterns (negative control), and patterns indicating different manifestations of a possible Burst Suppression-like pattern.
| Study group | Role | What they receive |
|---|---|---|
| MATLAB-based interface, showing 50 EEG traces | Other | A software environment (MATLAB) was developed, that allows the international experts to access the data set and score the traces pseudonymously. This MATLAB-based interface shows 50 EEG traces. A representative dataset was composed, consisting of definite Burst Suppression patterns (positive control), intraoperative EEG without Burst Suppression patterns (negative control), and patterns indicating different manifestations of a possible Burst Suppression-like pattern. Receives: Other: MATLAB-based interface, showing 50 EEG traces, classification of the EEG-pattern as Burst Suppression possible, yes, no. |
What is being measured
The primary outcome is the main question the study is designed to answer.
To obtain expert knowledge that can help to introduce a clear definition of EEG features to identify anesthetic-induced Burst Suppression.
Interrater variability for identification of Burst Suppression during general anesthesia.
Measured: 2 months
Investigation of spectral and time domain EEG features to assess objectively the individual raters scoring criteria.
Spectral and time domain EEG features of the scored EEG sequences.
Measured: 2 months
Secondary outcomes (2)
Establishment of structures and working groups for the development of international definition criteria for Burst Suppression during general anesthesia.
International, validated definition criteria for Burst Suppression during general anesthesia (as a result of international expert knowledge).
Measured: 5 years
Verification of the clinical applicability of the new definition criteria
Multi-stage coordination process; testing of the applicability in the subject-specific context and clinical routine.
Measured: 5 years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted19 Aug 2022
- Study start10 Aug 2022
- Primary completion15 Nov 2022 (estimated)
- Study completion1 Apr 2023 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Burst SuppressionStudies of the same condition, open and under way.
- More trials run by Technical University of MunichThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 40 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Technical University of Munich
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Stefanie Pilge, PD Dr., Study chair, Senior Physician - Department of anesthesiology and intensive careGerhard Schneider, Prof. Dr., Study chair, Clinic director - Department of anesthesiology and intensive care
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05508386
- Sponsor's protocol ID
- Burst Supp Identification
- Status last verified
- Aug 2022
- First submitted
- 10 Aug 2022
- Last updated
- 3 Oct 2022
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 3 Oct 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Interrater Variability for the Identification of Anesthetic-induced Burst Suppression EEG
- ClinicalTrials.gov ID
- NCT05508386
- Acronym / sponsor ID
- Burst Supp Identification
- Conditions
- Burst Suppression, General Anesthesia, Electroencephalogram
- Keywords
- Intraoperative EEG based monitoring, Burst Suppression, EEG-signal characteristics, intraoperative monitoring, general anesthesia
- Study type
- Interventional
- Recruitment status
- Unknown status
- Enrolment
- 40 participants (estimated)
- Lead sponsor
- Technical University of MunichUniversity, hospital or other
- Study start
- 10 Aug 2022 (actual)
- Primary completion
- 15 Nov 2022 (estimated)
- Study completion
- 1 Apr 2023 (estimated)
- First posted
- 19 Aug 2022 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Burst suppression describes a specific EEG pattern that can generally indicate a too deep general anesthesia. The pathophysiology of anesthetic-induced Burst Suppression may be distinctly different from the pathophysiology of Burst Suppression from other medical causes (e.g., coma, hypothermia, intoxication). Definition criteria of neurologic societies cannot be applied to the classification of Burst Suppression during general anesthesia without adaptation. The lack of a clear definition complicates structured research on anesthetic-induced Burst Suppression EEG in the perioperative setting because of subjective bias. Therefore, a unified agreement on what anesthesia-induced Burst Suppression looks like is crucial to conduct the best possible research. The aim of this study is to formulate the basis for a clear definition of burst suppression EEG that may help to truly understand the significance of this EEG pattern and its relationship to proposed postoperative outcomes such as postoperative delirium, longterm postoperative neurocognitive disorders (PNDs) or increased mortality.
Detailed description
Intraoperative neuromonitoring is recommended to assess the level of general anesthesia. Additionally, specific intraoperative EEG patterns seem to be associated with PNDs. One of these EEG patterns is the burst suppression EEG. The pattern of waxing and waning activity has been associated with a higher risk factor for postoperative delirium.
Commercial patient monitoring systems seem to underestimate the occurrence of Burst Suppression because the detection algorithms may not capture every suppression episode. A visual identification of this pattern is possible, but in the context of anesthesia monitoring, there is no standard definition of a Burst Suppression-EEG in the perioperative setting. Further, it displays unique clinical morphological characteristics. In particular, parameters of the EEG frequency spectrum are remarkably influenced by patients age and anesthetic agents. In order to agree on a definition for Burst Suppression during general anesthesia that will help to standardize Burst Suppression research and to optimize Burst Suppression monitoring, an expert consensus is essential. The planned project aims to pave the way to such a consensus of international expert societies in anesthesiology. Based on EEG data recorded within the framework of previous studies (approved Ethics application dated 20.08.2018 with number 246/18 S \& 213/17S, dated 24.05.2017), the investigators will compose a representative data set (overall 50 EEG patterns) consisting of definitive Burst Suppression patterns (positive control), intraoperative EEG without Burst Suppression (negative control) and patterns that indicate different manifestations of a possible Burst Suppression-like pattern.
The EEG recordings of this data set will be evaluated by selected international leading experts in EEG-based anesthesia monitoring.
Therefore, a software environment (MATLAB) was developed, that allows the international experts to access the data set and score the traces pseudonymously. After the data sets have been scored, the interrater agreement for the single EEG episodes will be statistically analyzed.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| MATLAB-based interface, showing 50 EEG traces | Other | Other: MATLAB-based interface, showing 50 EEG traces, classification of the EEG-pattern as Burst Suppression possible, yes, no.A software environment (MATLAB) was developed, that allows the international experts to access the data set and score the traces pseudonymously. This MATLAB-based interface shows 50 EEG traces. A representative dataset was composed, consisting of definite Burst Suppression patterns (positive control), intraoperative EEG without Burst Suppression patterns (negative control), and patterns indicating different manifestations of a possible Burst Suppression-like pattern. |
Who may qualify
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child, Adult, Older adult
Key inclusion criteria (1 listed)
- leading international experts in the field of intraoperative EEG analysis
Key exclusion criteria (1 listed)
- members of study group
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| MATLAB-based interface, showing 50 EEG traces, classification of the EEG-pattern as Burst Suppression possible, yes, no.A software environment (MATLAB) was developed, that allows the international experts to access the data set and score the traces pseudonymously. This MATLAB-based interface shows 50 EEG traces. A representative dataset was composed, consisting of definite Burst Suppression patterns (positive control), intraoperative EEG without Burst Suppression patterns (negative control), and patterns indicating different manifestations of a possible Burst Suppression-like pattern. | Other | MATLAB-based interface, showing 50 EEG traces |
Primary outcome
To obtain expert knowledge that can help to introduce a clear definition of EEG features to identify anesthetic-induced Burst Suppression.
Time frame: 2 months
Interrater variability for identification of Burst Suppression during general anesthesia.
Investigation of spectral and time domain EEG features to assess objectively the individual raters scoring criteria.
Time frame: 2 months
Spectral and time domain EEG features of the scored EEG sequences.
2 secondary outcomes
Establishment of structures and working groups for the development of international definition criteria for Burst Suppression during general anesthesia.
Time frame: 5 years
Verification of the clinical applicability of the new definition criteria
Time frame: 5 years
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 3 Oct 2022.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Stefanie Pilge, PD Dr. study chair
Senior Physician - Department of anesthesiology and intensive care
Gerhard Schneider, Prof. Dr. study chair
Clinic director - Department of anesthesiology and intensive care
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing MATLAB-based interface, showing 50 EEG traces, classification of the EEG-pattern as Burst Suppression possible, yes, no. in people with Burst Suppression and General Anesthesia, run by Technical University of Munich at 1 site in Germany.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 3 Oct 2022. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Germany. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
To obtain expert knowledge that can help to introduce a clear definition of EEG features to identify anesthetic-induced Burst Suppression. (time frame: 2 months). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 3 Oct 2022.