Using Machine Learning and Biomarkers for Early Detection of Delayed Cerebral Ischemia
Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18-110
SponsorSahlgrenska University Hospital
About this trial
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.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
None
Disqualifiers
Unable to consent,
Cardiac arrythmia,
Previous brain damage
Trial population
Adult people with aneurysmal subarachnoid hemorrhage
Trial design
Design model
Cohort
Time perspective
Prospective
Treatments tested in this trial
No intervention, observational study
Other interventionNo intervention
Treatment groups
1,500 Participants
are divided into 2 treatment groupsGroup A: Delayed cerebral ischemia1 intervention
Group B: Non-delayed cerebral ischemia1 intervention
Trial outcomes
Primary outcomes
1
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.
Time frame
2023-20332
Autoregulation
xyz
Time frame
2023-2033Sponsors and contacts
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Source ClinicalTrials.gov