Ischemic StrokeCIDAIBASSAHNCT06069973
Using Machine Learning and Biomarkers for Early Detection of Delayed Cerebral Ischemia
An observational study of Ischemic Stroke and Hemorrhagic Stroke, run by Sahlgrenska University Hospital at 1 site in Sweden.
Trial summary
The overall goal of this project is to determine if machine learning and analysis of neurospecific biomarkers can enable early detection of upcoming or ongoing cerebral ischaemia in patients suffering from subarachnoid haemorrhage with altered consciousness due to cerebral injury or sedation. Read more about this study
- Who is it for?
- Ages 18 to 110 years
- Conditions the study is for
- Ischemic Stroke, Hemorrhagic Stroke
- How many people
- 1,500 participants
- Where
- 1 siteSweden
- Study dates
- 1 Jan 2024to 31 Dec 2033
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
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 18 to 110 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Adult people with aneurysmal subarachnoid hemorrhage
Who may be able to join
- Patients over the age of 18 with aneurysmal subarachnoid hemorrhage admitted to intensive care units at Sahlgrenska University hospital.
Who cannot join
- Unable to consent,
- Cardiac arrythmia,
- Previous brain damage
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Sweden1 site, 1 recruiting
- Recruiting
Sahlgrenska University Hospital
Gothenburg, 41345
Block, PI, Associate professor, +46313428173, linda.block@vgregion.se
About this study
Official title: Machine Learning and Biomarkers for Early Detection of Delayed Cerebral Ischemia
The overall goal of this project is to determine if machine learning and analysis of neurospecific biomarkers can enable early detection of upcoming or ongoing cerebral ischaemia in patients suffering from subarachnoid haemorrhage with altered consciousness due to cerebral injury or sedation. Analyses of heart rate variability, electroencephalgraphy,nearinfrared spectroscopy, cerebral autoregulation, and brain injury specific biomarkers in blood and cerebrospinal fluid will be performed.
Read the detailed description
A new and promising approach to detect ongoing cerebral ischemia might be the detection of neurospecific biomarkers in blood. A biomarker for cerebral ischaemia, similar to troponin T and troponin I for detecting cardiac ischaemia, would be precious; however, such a biomarker for cerebral ischaemia is currently lacking. (9) There are several interesting neurospecific biomarkers for this purpose, such as Glial fibrillary acidic protein (GFAP), neuron-specific enolase (NSE), total tau, S-100, and neurofilament light chains (NFL). At this point, we do not have enough knowledge about levels of neurospecific biomarkers in blood and cerebrospinal fluid during delayed cerebral ischemia after subarachnoid hemorrhage. The sampling of neurospecific biomarkers have a dual purpose, the first is to investigate if we can detect ongoing cerebral ischemia with these biomarkers, and the second purpose is to compare levels of biomarkers to outcome in mortality and morbidity determined by the Glasgow Coma Scale Extended at 1-year, 3-years and 5-years after admission.
Machine learning algorithms for predicting outcomes after delayed cerebral ischemia using a combination of clinical and imaging data have emerged. Nevertheless, prediction of delayed cerebral ischemia does not prevent it; to prevent delayed cerebral ischemia, an easily applied, cheap and reliable monitoring system that can warn physicians of the imminent risk of cerebral ischemia needs to be developed, making it possible to intervene.
The overall goal of this project is to develop methods that enable the detection of upcoming or ongoing cerebral ischaemia in patients with subarachnoid haemorrhage
Our primary aims are:
- To develop a machine learning-based model that can identify patterns in signals obtained from HRV, NIRS, and EEG monitoring, which are consistent with upcoming cerebral ischemia and provide a warning about this to attending physicians.
- To define the specificity and time relation of neurospecific biomarkers in blood and cerebrospinal fluid in patients with subarachnoid haemorrhage with and without delayed cerebral ischemia to evaluate if any of these biomarkers can be used as an indicator for ongoing cerebral ischemia.
- To assess the prognostic value of changes in physiological and neurospecific biomarkers changes during the acute phase after subarachnoid hemorrhage on long-term outcome.
- Conditions
- Ischemic Stroke, Hemorrhagic Stroke
- Being tested
- No intervention, observational study
- Medical subject headings
- Ischemic Stroke, Hemorrhagic Stroke
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
No intervention, observational studyOther
No intervention
| Study group | Role | What they receive |
|---|---|---|
| Delayed cerebral ischemia | Definition by Vergouwen et al. Verified by computed tomography Receives: Other: No intervention, observational study | |
| Non-delayed cerebral ischemia | No signs of cerebral ischemia clinically or by computed tomography. Receives: Other: No intervention, observational study |
What is being measured
The primary outcome is the main question the study is designed to answer.
Early warning system
To develop a machine learning-based model that can identify patterns in signals obtained from HRV, NIRS, and EEG monitoring, which are consistent with upcoming cerebral ischemia and provide a warning about this to attending physicians.
To define the specificity and time relation of neurospecific biomarkers in blood and cerebrospinal fluid in patients with subarachnoid haemorrhage with and without delayed cerebral ischemia to evaluate if any of these biomarkers can be used as an indicator for ongoing cerebral ischemia.
To assess the prognostic value of changes in physiological and neurospecific biomarkers changes during the acute phase after subarachnoid hemorrhage on long-term outcome.
Measured: 2023-2033
Autoregulation
xyz
Measured: 2023-2033
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted6 Oct 2023
- Study start1 Jan 2024
- Primary completion31 Dec 2033 (estimated)
- Study completion31 Dec 2033 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Ischemic StrokeStudies of the same condition, open and under way.
- 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
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 1,500 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Sahlgrenska University Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Linda Block, Sahlgrenska University Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06069973
- Sponsor's protocol ID
- CIDAI-BAS-SAH
- Acronym
- CIDAIBASSAH
- Status last verified
- Jan 2026
- First submitted
- 26 Sep 2023
- Last updated
- 12 Jan 2026
- 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 12 Jan 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Machine Learning and Biomarkers for Early Detection of Delayed Cerebral Ischemia
- ClinicalTrials.gov ID
- NCT06069973
- Acronym / sponsor ID
- CIDAIBASSAH / CIDAI-BAS-SAH
- Conditions
- Ischemic Stroke, Hemorrhagic Stroke
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 1,500 participants (estimated)
- Lead sponsor
- Sahlgrenska University HospitalUniversity, hospital or other
- Study start
- 1 Jan 2024 (actual)
- Primary completion
- 31 Dec 2033 (estimated)
- Study completion
- 31 Dec 2033 (estimated)
- First posted
- 6 Oct 2023 (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.
The overall goal of this project is to determine if machine learning and analysis of neurospecific biomarkers can enable early detection of upcoming or ongoing cerebral ischaemia in patients suffering from subarachnoid haemorrhage with altered consciousness due to cerebral injury or sedation. Analyses of heart rate variability, electroencephalgraphy,nearinfrared spectroscopy, cerebral autoregulation, and brain injury specific biomarkers in blood and cerebrospinal fluid will be performed.
Detailed description
A new and promising approach to detect ongoing cerebral ischemia might be the detection of neurospecific biomarkers in blood. A biomarker for cerebral ischaemia, similar to troponin T and troponin I for detecting cardiac ischaemia, would be precious; however, such a biomarker for cerebral ischaemia is currently lacking. (9) There are several interesting neurospecific biomarkers for this purpose, such as Glial fibrillary acidic protein (GFAP), neuron-specific enolase (NSE), total tau, S-100, and neurofilament light chains (NFL). At this point, we do not have enough knowledge about levels of neurospecific biomarkers in blood and cerebrospinal fluid during delayed cerebral ischemia after subarachnoid hemorrhage. The sampling of neurospecific biomarkers have a dual purpose, the first is to investigate if we can detect ongoing cerebral ischemia with these biomarkers, and the second purpose is to compare levels of biomarkers to outcome in mortality and morbidity determined by the Glasgow Coma Scale Extended at 1-year, 3-years and 5-years after admission.
Machine learning algorithms for predicting outcomes after delayed cerebral ischemia using a combination of clinical and imaging data have emerged. Nevertheless, prediction of delayed cerebral ischemia does not prevent it; to prevent delayed cerebral ischemia, an easily applied, cheap and reliable monitoring system that can warn physicians of the imminent risk of cerebral ischemia needs to be developed, making it possible to intervene.
The overall goal of this project is to develop methods that enable the detection of upcoming or ongoing cerebral ischaemia in patients with subarachnoid haemorrhage
Our primary aims are:
- To develop a machine learning-based model that can identify patterns in signals obtained from HRV, NIRS, and EEG monitoring, which are consistent with upcoming cerebral ischemia and provide a warning about this to attending physicians.
- To define the specificity and time relation of neurospecific biomarkers in blood and cerebrospinal fluid in patients with subarachnoid haemorrhage with and without delayed cerebral ischemia to evaluate if any of these biomarkers can be used as an indicator for ongoing cerebral ischemia.
- To assess the prognostic value of changes in physiological and neurospecific biomarkers changes during the acute phase after subarachnoid hemorrhage on long-term outcome.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Delayed cerebral ischemia | – | Other: No intervention, observational studyDefinition by Vergouwen et al. Verified by computed tomography |
| Non-delayed cerebral ischemia | – | Other: No intervention, observational studyNo signs of cerebral ischemia clinically or by computed tomography. |
Who may qualify
- Ages
- 18 to 110 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Adult people with aneurysmal subarachnoid hemorrhage
Key inclusion criteria (1 listed)
- Patients over the age of 18 with aneurysmal subarachnoid hemorrhage admitted to intensive care units at Sahlgrenska University hospital.
Key exclusion criteria (3 listed)
- Unable to consent,
- Cardiac arrythmia,
- Previous brain damage
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 |
|---|---|---|
| No intervention, observational studyNo intervention | Other | Delayed cerebral ischemia, Non-delayed cerebral ischemia |
Primary outcome
Early warning system
Time frame: 2023-2033
To develop a machine learning-based model that can identify patterns in signals obtained from HRV, NIRS, and EEG monitoring, which are consistent with upcoming cerebral ischemia and provide a warning about this to attending physicians. To define the specificity and time relation of neurospecific biomarkers in blood and cerebrospinal fluid in patients with subarachnoid haemorrhage with and without delayed cerebral ischemia to evaluate if any of these biomarkers can be used as an indicator for ongoing cerebral ischemia. To assess the prognostic value of changes in physiological and neurospecific biomarkers changes during the acute phase after subarachnoid hemorrhage on long-term outcome.
Autoregulation
Time frame: 2023-2033
xyz
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 12 Jan 2026.
- 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.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Ischemic Stroke and Hemorrhagic Stroke, run by Sahlgrenska University Hospital at 1 site in Sweden.
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 3 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: looking for participants now, as of the sponsor's last update on 12 Jan 2026. 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 Sweden. 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?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Each site lists its own contact: choose the nearest one under Trial locations. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Early warning system (time frame: 2023-2033). 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 12 Jan 2026.